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Semi-Structured Interview | Definition, Guide & Examples

Published on January 27, 2022 by Tegan George . Revised on June 22, 2023.

A semi-structured interview is a data collection method that relies on asking questions within a predetermined thematic framework. However, the questions are not set in order or in phrasing.

In research, semi-structured interviews are often qualitative in nature. They are generally used as an exploratory tool in marketing, social science, survey methodology, and other research fields.

They are also common in field research with many interviewers, giving everyone the same theoretical framework, but allowing them to investigate different facets of the research question .

• Structured interviews : The questions are predetermined in both topic and order.
• Unstructured interviews : None of the questions are predetermined.
• Focus group interviews : The questions are presented to a group instead of one individual.

Table of contents

What is a semi-structured interview, when to use a semi-structured interview, advantages of semi-structured interviews, disadvantages of semi-structured interviews, semi-structured interview questions, how to conduct a semi-structured interview, how to analyze a semi-structured interview, presenting your results (with example), other interesting articles, frequently asked questions about semi-structured interviews.

Semi-structured interviews are a blend of structured and unstructured types of interviews.

• Unlike in an unstructured interview, the interviewer has an idea of what questions they will ask.
• Unlike in a structured interview, the phrasing and order of the questions is not set.

Semi-structured interviews are often open-ended, allowing for flexibility. Asking set questions in a set order allows for easy comparison between respondents, but it can be limiting. Having less structure can help you see patterns, while still allowing for comparisons between respondents.

Semi-structured interviews are best used when:

• You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uneasy.
• Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

Just like in structured interviews, it is critical that you remain organized and develop a system for keeping track of participant responses. However, since the questions are less set than in a structured interview, the data collection and analysis become a bit more complex.

Differences between different types of interviews

Make sure to choose the type of interview that suits your research best. This table shows the most important differences between the four types.

Semi-structured interviews come with many advantages.

Best of both worlds

No distractions, detail and richness.

However, semi-structured interviews also have their downsides.

Low validity

High risk of research bias, difficult to develop good semi-structured interview questions.

Since they are often open-ended in style, it can be challenging to write semi-structured interview questions that get you the information you’re looking for without biasing your responses. Here are a few tips:

• Define what areas or topics you will be focusing on prior to the interview. This will help you write a framework of questions that zero in on the information you seek.
• Write yourself a guide to refer to during the interview, so you stay focused. It can help to start with the simpler questions first, moving into the more complex ones after you have established a comfortable rapport.
• Be as clear and concise as possible, avoiding jargon and compound sentences.
• How often per week do you go to the gym? a) 1 time; b) 2 times; c) 3 times; d) 4 or more times
• If yes: What feelings does going to the gym bring out in you?
• If no: What do you prefer to do instead?
• If yes: How did this membership affect your job performance? Did you stay longer in the role than you would have if there were no membership?

Once you’ve determined that a semi-structured interview is the right fit for your research topic , you can proceed with the following steps.

Step 1: Set your goals and objectives

You can use guiding questions as you conceptualize your research question, such as:

• What are you trying to learn or achieve from a semi-structured interview?
• Why are you choosing a semi-structured interview as opposed to a different type of interview, or another research method?

If you want to proceed with a semi-structured interview, you can start designing your questions.

Step 2: Design your questions

Try to stay simple and concise, and phrase your questions clearly. If your topic is sensitive or could cause an emotional response, be mindful of your word choices.

One of the most challenging parts of a semi-structured interview is knowing when to ask follow-up or spontaneous related questions. For this reason, having a guide to refer back to is critical. Hypothesizing what other questions could arise from your participants’ answers may also be helpful.

Step 3: Assemble your participants

There are a few sampling methods you can use to recruit your interview participants, such as:

• Voluntary response sampling : For example, sending an email to a campus mailing list and sourcing participants from responses.
• Stratified sampling of a particular characteristic trait of interest to your research, such as age, race, ethnicity, or gender identity.

Step 4: Decide on your medium

It’s important to determine ahead of time how you will be conducting your interview. You should decide whether you’ll be conducting it live or with a pen-and-paper format. If conducted in real time, you also need to decide if in person, over the phone, or via videoconferencing is the best option for you.

Note that each of these methods has its own advantages and disadvantages:

• Pen-and-paper may be easier for you to organize and analyze, but you will receive more prepared answers, which may affect the reliability of your data.
• In-person interviews can lead to nervousness or interviewer effects, where the respondent feels pressured to respond in a manner they believe will please you or incentivize you to like them.

Step 5: Conduct your interviews

As you conduct your interviews, keep environmental conditions as constant as you can to avoid bias. Pay attention to your body language (e.g., nodding, raising eyebrows), and moderate your tone of voice.

Relatedly, one of the biggest challenges with semi-structured interviews is ensuring that your questions remain unbiased. This can be especially challenging with any spontaneous questions or unscripted follow-ups that you ask your participants.

After you’re finished conducting your interviews, it’s time to analyze your results. First, assign each of your participants a number or pseudonym for organizational purposes.

The next step in your analysis is to transcribe the audio or video recordings. You can then conduct a content or thematic analysis to determine your categories, looking for patterns of responses that stand out to you and test your hypotheses .

Transcribing interviews

Before you get started with transcription, decide whether to conduct verbatim transcription or intelligent verbatim transcription.

• If pauses, laughter, or filler words like “umm” or “like” affect your analysis and research conclusions, conduct verbatim transcription and include them.
• If not, you can conduct intelligent verbatim transcription, which excludes fillers, fixes any grammatical issues, and is usually easier to analyze.

Transcribing presents a great opportunity for you to cleanse your data . Here, you can identify and address any inconsistencies or questions that come up as you listen.

Your supervisor might ask you to add the transcriptions to the appendix of your paper.

Coding semi-structured interviews

Next, it’s time to conduct your thematic or content analysis . This often involves “coding” words, patterns, or recurring responses, separating them into labels or categories for more robust analysis.

Due to the open-ended nature of many semi-structured interviews, you will most likely be conducting thematic analysis, rather than content analysis.

• You closely examine your data to identify common topics, ideas, or patterns. This can help you draw preliminary conclusions about your participants’ views, knowledge or experiences.
• After you have been through your responses a few times, you can collect the data into groups identified by their “code.” These codes give you a condensed overview of the main points and patterns identified by your data.
• Next, it’s time to organize these codes into themes. Themes are generally broader than codes, and you’ll often combine a few codes under one theme. After identifying your themes, make sure that these themes appropriately represent patterns in responses.

Analyzing semi-structured interviews

Once you’re confident in your themes, you can take either an inductive or a deductive approach.

• An inductive approach is more open-ended, allowing your data to determine your themes.
• A deductive approach is the opposite. It involves investigating whether your data confirm preconceived themes or ideas.

After your data analysis, the next step is to report your findings in a research paper .

• Your methodology section describes how you collected the data (in this case, describing your semi-structured interview process) and explains how you justify or conceptualize your analysis.
• Your discussion and results sections usually address each of your coded categories.
• You can then conclude with the main takeaways and avenues for further research.

Example of interview methodology for a research paper

Let’s say you are interested in vegan students on your campus. You have noticed that the number of vegan students seems to have increased since your first year, and you are curious what caused this shift.

You identify a few potential options based on literature:

• Perceptions about personal health or the perceived “healthiness” of a vegan diet
• Concerns about animal welfare and the meat industry
• Increased climate awareness, especially in regards to animal products
• Availability of more vegan options, making the lifestyle change easier

Anecdotally, you hypothesize that students are more aware of the impact of animal products on the ongoing climate crisis, and this has influenced many to go vegan. However, you cannot rule out the possibility of the other options, such as the new vegan bar in the dining hall.

Since your topic is exploratory in nature and you have a lot of experience conducting interviews in your work-study role as a research assistant, you decide to conduct semi-structured interviews.

You have a friend who is a member of a campus club for vegans and vegetarians, so you send a message to the club to ask for volunteers. You also spend some time at the campus dining hall, approaching students at the vegan bar asking if they’d like to participate.

Here are some questions you could ask:

• Do you find vegan options on campus to be: excellent; good; fair; average; poor?
• How long have you been a vegan?
• Follow-up questions can probe the strength of this decision (i.e., was it overwhelmingly one reason, or more of a mix?)

Depending on your participants’ answers to these questions, ask follow-ups as needed for clarification, further information, or elaboration.

• Do you think consuming animal products contributes to climate change? → The phrasing implies that you, the interviewer, do think so. This could bias your respondents, incentivizing them to answer affirmatively as well.
• What do you think is the biggest effect of animal product consumption? → This phrasing ensures the participant is giving their own opinion, and may even yield some surprising responses that enrich your analysis.

After conducting your interviews and transcribing your data, you can then conduct thematic analysis, coding responses into different categories. Since you began your research with several theories about campus veganism that you found equally compelling, you would use the inductive approach.

Once you’ve identified themes and patterns from your data, you can draw inferences and conclusions. Your results section usually addresses each theme or pattern you found, describing each in turn, as well as how often you came across them in your analysis. Feel free to include lots of (properly anonymized) examples from the data as evidence, too.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

• You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.

The four most common types of interviews are:

• Structured interviews : The questions are predetermined in both topic and order. 
• Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.

Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias can also occur in observations if the participants know they’re being observed. They might alter their behavior accordingly.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

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• What is a semi-structured interview?

Last updated

5 February 2023

Reviewed by

Cathy Heath

When designed correctly, user interviews go much deeper than surface-level survey responses. They can provide new information about how people interact with your products and services, and shed light on the underlying reasons behind these habits.

Semi-structured user interviews are widely considered one of the most effective tools for doing this kind of qualitative research , depending on your specific goals. As the name suggests, the semi-structured format allows for a more natural, conversational flow, while still being organized enough to collect plenty of actionable data .

Analyze semi-structured interviews

Bring all your semi-structured interviews into one place to analyze and understand

A semi-structured interview is a qualitative research method used to gain an in-depth understanding of the respondent's feelings and beliefs on specific topics. As the interviewer prepares the questions ahead of time, they can adjust the order, skip any that are redundant, or create new ones. Additionally, the interviewer should be prepared to ask follow-up questions and probe for more detail.

Semi-structured interviews typically last between 30 and 60 minutes and are usually conducted either in person or via a video call. Ideally, the interviewer can observe the participant's verbal and non-verbal cues in real-time, allowing them to adjust their approach accordingly. The interviewer aims for a conversational flow that helps the participant talk openly while still focusing on the primary topics being researched.

Once the interview is over, the researcher analyzes the data in detail to draw meaningful results. This involves sorting the data into categories and looking for patterns and trends. This semi-structured interview approach provides an ideal framework for obtaining open-ended data and insights.

• When to use a semi-structured interview?

Semi-structured interviews are considered the "best of both worlds" as they tap into the strengths of structured and unstructured methods. Researchers can gather reliable data while also getting unexpected insights from in-depth user feedback.

Semi-structured interviews can be useful during any stage of the UX product-development process, including exploratory research to better understand a new market or service. Further down the line, this approach is ideal for refining existing designs and discovering areas for improvement. Semi-structured interviews can even be the first step when planning future research projects using another method of data collection.

• Advantages of semi-structured interviews

Flexibility

This style of interview is meant to be adapted according to the answers and reactions of the respondent, which gives a lot of flexibility. Semi-structured interviews encourage two-way communication, allowing themes and ideas to emerge organically.

Respondent comfort

The semi-structured format feels more natural and casual for participants than a formal interview. This can help to build rapport and more meaningful dialogue.

Semi-structured interviews are excellent for user experience research because they provide rich, qualitative data about how people really experience your products and services.

Open-ended questions allow the respondent to provide nuanced answers, with the potential for more valuable insights than other forms of data collection, like structured interviews , surveys , or questionnaires.

• Disadvantages of semi-structured interviews

Can be unpredictable

Less structure brings less control, especially if the respondent goes off tangent or doesn't provide useful information. If the conversation derails, it can take a lot of effort to bring the focus back to the relevant topics.

Lack of standardization

Every semi-structured interview is unique, including potentially different questions, so the responses collected are very subjective. This can make it difficult to draw meaningful conclusions from the data unless your team invests the time in a comprehensive analysis.

Compared to other research methods, unstructured interviews are not as consistent or "ready to use."

• Best practices when preparing for a semi-structured interview

While semi-structured interviews provide a lot of flexibility, they still require thoughtful planning. Maximizing the potential of this research method will depend on having clear goals that help you narrow the focus of the interviews and keep each session on track.

After taking the time to specify these parameters, create an interview guide to serve as a framework for each conversation. This involves crafting a range of questions that can explore the necessary themes and steer the conversation in the right direction. Everything in your interview guide is optional (that's the beauty of being "semi" structured), but it's still an essential tool to help the conversation flow and collect useful data.

Best practices to consider while designing your interview questions include:

Prioritize open-ended questions

Promote a more interactive, meaningful dialogue by avoiding questions that can be answered with a simple yes or no, otherwise known as close-ended questions.

Stick with "what," "when," "who," "where," "why," and "how" questions, which allow the participant to go beyond the superficial to express their ideas and opinions. This approach also helps avoid jargon and needless complexity in your questions.

Open-ended questions help the interviewer uncover richer, qualitative details, which they can build on to get even more valuable insights.

Plan some follow-up questions

When preparing questions for the interview guide, consider the responses you're likely to get and pair them up with some effective, relevant follow-up questions. Factual questions should be followed by ones that ask an opinion.

Planning potential follow-up questions will help you to get the most out of a semi-structured interview. They allow you to delve deeper into the participant's responses or hone in on the most important themes of your research focus.

Follow-up questions are also invaluable when the interviewer feels stuck and needs a meaningful prompt to continue the conversation.

Avoid leading questions

Leading questions are framed toward a predetermined answer. This makes them likely to result in data that is biased, inaccurate, or otherwise unreliable.

For example, asking "Why do you think our services are a good solution?" or "How satisfied have you been with our services?" will leave the interviewee feeling pressured to agree with some baseline assumptions.

Interviewers must take the time to evaluate their questions and make a conscious effort to remove any potential bias that could get in the way of authentic feedback.

Asking neutral questions is key to encouraging honest responses in a semi-structured interview. For example, "What do you consider to be the advantages of using our services?" or simply "What has been your experience with using our services?"

Neutral questions are effective in capturing a broader range of opinions than closed questions, which is ultimately one of the biggest benefits of using semi-structured interviews for research.

Use the critical incident method

The critical incident method is an approach to interviewing that focuses on the past behavior of respondents, as opposed to hypothetical scenarios. One of the challenges of all interview research methods is that people are not great at accurately recalling past experiences, or answering future-facing, abstract questions.

The critical incident method helps avoid these limitations by asking participants to recall extreme situations or 'critical incidents' which stand out in their memory as either particularly positive or negative. Extreme situations are more vivid so they can be recalled more accurately, potentially providing more meaningful insights into the interviewee’s experience with your products or services.

• Best practices while conducting semi-structured interviews

Encouraging interaction is the key to collecting more specific data than is typically possible during a formal interview. Facilitating an effective semi-structured interview is a balancing act between asking prepared questions and creating the space for organic conversation. Here are some guidelines for striking the right tone.

Beginning the interview

Make participants feel comfortable by introducing yourself and your role at the organization and displaying appropriate body language.

Outline the purpose of the interview to give them an idea of what to expect. For example, explain that you want to learn more about how people use your product or service.

It's also important to thank them for their time in advance and emphasize there are no right or wrong answers.

Practice active listening

Build trust and rapport throughout the interview with active listening techniques, focusing on being present and demonstrating that you're paying attention by responding thoughtfully. Engage with the participant by making eye contact, nodding, and giving verbal cues like "Okay, I see," "I understand," and "M-hm."

Avoid the temptation to rush to fill any silences while they're in the middle of responding, even if it feels awkward. Give them time to finish their train of thought before interrupting with feedback or another prompt. Embracing these silences is essential for active listening because it's a sign of a productive interview with meaningful, candid responses.

Practicing these techniques will ensure the respondent feels heard and respected, which is critical for gathering high-quality information.

Ask clarifying questions in real time

In a semi-structured interview, the researcher should always be on the lookout for opportunities to probe into the participant's thoughts and opinions.

Along with preparing follow-up questions, get in the habit of asking clarifying questions whenever possible. Clarifying questions are especially important for user interviews because people often provide vague responses when discussing how they interact with products and services.

Being asked to go deeper will encourage them to give more detail and show them you’re taking their opinions seriously and are genuinely interested in understanding their experiences.

Some clarifying questions that can be asked in real-time include:

"That's interesting. Could you give me some examples of X?"

"What do you mean when you say "X"?"

"Why is that?"

"It sounds like you're saying [rephrase their response], is that correct?"

Minimize note-taking

In a wide-ranging conversation, it's easy to miss out on potentially valuable insights by not staying focused on the user. This is why semi-structured interviews are generally recorded (audio or video), and it's common to have a second researcher present to take notes.

The person conducting the interview should avoid taking notes because it's a distraction from:

Keeping track of the conversation

Engaging with the user

Asking thought-provoking questions

Watching you take notes can also have the unintended effect of making the participant feel pressured to give shallower, shorter responses—the opposite of what you want.

Concluding the interview

Semi-structured interviews don't come with a set number of questions, so it can be tricky to bring them to an end. Give the participant a sense of closure by asking whether they have anything to add before wrapping up, or if they want to ask you any questions, and then give sincere thanks for providing honest feedback.

Don't stop abruptly once all the relevant topics have been discussed or you're nearing the end of the time that was set aside. Make them feel appreciated!

• Analyzing the data from semi-structured interviews

In some ways, the real work of semi-structured interviews begins after all the conversations are over, and it's time to analyze the data you've collected. This process will focus on sorting and coding each interview to identify patterns, often using a mix of qualitative and quantitative methods.

Some of the strategies for making sense of semi-structured interviews include:

Thematic analysis : focuses on the content of the interviews and identifying common themes

Discourse analysis : looks at how people express feelings about themes such as those involving politics, culture, and power

Qualitative data mapping: a visual way to map out the correlations between different elements of the data

Narrative analysis : uses stories and language to unlock perspectives on an issue

Grounded theory : can be applied when there is no existing theory that could explain a new phenomenon

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Semi-Structured Interviews in Qualitative Research

Unveiling insights of semi-structured interviews in qualitative research, the methods for nuanced understanding and robust data analysis.

Qualitative research explores the rich complexities of human experiences, perceptions, and meanings. In the research area, semi-structured interviews emerge as a versatile method to gather in-depth insights from participants. Unlike rigidly structured interviews, semi-structured interviews provide a flexible framework that combines predetermined questions with the freedom to explore emergent topics and probe deeper into participants’ thoughts and experiences. This article aims to show the purpose, benefits, and best practices of utilizing semi-structured interviews in qualitative research. By understanding how this approach facilitates a nuanced exploration of research questions, researchers can harness its potential to capture the multifaceted nature of human phenomena and gain rich and meaningful data that enhances the understanding of diverse social, psychological, and cultural phenomena.

What Are Semi-structured Interviews In Qualitative Research?

A semi-structured interview is a qualitative research method that combines aspects of both structured and unstructured interviews. In a semi-structured interview, the researcher prepares a set of predetermined questions or topics to guide the conversation with the participant, but there is also room for flexibility and follow-up questions based on the participant’s responses. This allows for a more conversational and exploratory approach, enabling the researcher to delve deeper into specific areas of interest and capture detailed and nuanced information.

Also read: What’s the Difference: Qualitative vs Quantitative Research?

Semi-structured interviews enable researchers to explore participants’ perspectives, experiences, and perceptions in-depth. They can uncover rich narratives, personal insights, and contextual details that may not emerge in more standardized interview formats. The open-ended nature of semi-structured interviews allows for a holistic understanding of the research topic and captures the complexity of human experiences.

The Purpose Of Semi-Structured Interviews

Semi-structured interviews serve as a dynamic means of collecting qualitative data, allowing researchers to engage in a conversation with participants while maintaining a certain level of flexibility. These interviews enable researchers to explore research questions, delve into participants’ perspectives, and gain a comprehensive understanding of the studied phenomena. The purpose of semi-structured interviews extends beyond factual information; it aims to uncover participants’ perceptions, beliefs, values, and emotions, providing valuable insights into their subjective experiences.

When To Use A Semi-Structured Interview?

When conducting qualitative research, the decision to use a semi-structured interview approach is influenced by various factors. Semi-structured interviews are particularly suitable when exploring complex and multifaceted topics that require full understanding. They are valuable when researchers aim to capture participants’ perspectives, experiences, and narratives in a flexible and open-ended manner. Semi-structured interviews are effective when the research objectives involve exploring diverse viewpoints, identifying patterns and themes, and gaining insights into individuals’ thoughts and emotions. Additionally, this approach is advantageous when researchers seek to establish rapport and build a collaborative relationship with participants, as it allows for meaningful and interactive conversations. The use of semi-structured interviews empowers researchers to investigate the richness of participants’ experiences while maintaining a level of versatility and adaptability in data collection.

Benefits Of Semi-Structured Interviews

Flexibility and Adaptability: Semi-structured interviews offer a balance between structure and flexibility, allowing researchers to adapt their questioning based on participant responses. This approach enables researchers to examine specific areas of interest, explore unexpected avenues, and capture nuanced information that may not emerge in rigidly structured interviews.

Participant-Centered Approach: Semi-structured interviews place participants at the center of the research process, valuing their perspectives and experiences. By creating a conversational and comfortable atmosphere, researchers can foster trust and rapport, encouraging participants to share their thoughts openly. This approach facilitates a collaborative and co-constructed knowledge-building process, capturing the complexity of participants’ lived experiences.

In-Depth Exploration: Through semi-structured interviews, researchers can delve deeply into participants’ narratives, unraveling intricate details and uncovering hidden meanings. The open-ended nature of these interviews allows for rich descriptions, personal anecdotes, and contextual insights, enabling researchers to gain a comprehensive understanding of the research topic.

Disadvantages Of Semi-Structured Interviews

While semi-structured interviews offer several benefits, it is important to consider their potential disadvantages in qualitative research. One disadvantage is the possibility of interviewer bias or influence. As the interviewer plays an active role in guiding the interview, their personal biases, assumptions, or interpretations may inadvertently shape the participants’ responses. This can compromise the objectivity of the data collected. Another challenge is the time-consuming nature of semi-structured interviews. Conducting interviews, transcribing, and analyzing the data can be a lengthy process, requiring substantial time and resources.

Also read: A Problem Called Sampling Bias

Additionally, the quality of the data obtained may depend on the interviewer’s skills and experience in conducting interviews and eliciting rich responses from participants. If the interviewer lacks proper training or expertise, the quality and depth of the data collected may be compromised. Lastly, the open-ended nature of semi-structured interviews may lead to a vast amount of qualitative data that can be challenging to analyze and interpret, requiring careful attention and rigorous analysis techniques.

Key Considerations For Conducting Semi-Structured Interviews

After confirming that a semi-structured interview aligns with the research topic, the following sequential steps are used to prepare and conduct a semi-structured interview:

Step 1: Define The Objective And Research Scope

Begin by clarifying the purpose of the semi-structured interview and why it is the most suitable research method for the study. Consider the specific knowledge or insights that are intended to be gained through the interview process.

Step 2: Develop Well-Designed Interview Questions

Craft the interview questions to be open-ended, simple, and concise. Take care with the choice of words, particularly when discussing sensitive topics. Ensure that the questions allow for participants to provide detailed and nuanced responses.

Step 3: Identify The Target Group(s) For The Interview

Determine the specific population or groups to engage with during the semi-structured interview. Depending on the size of the target group, utilize random or stratified sampling techniques to select a representative sample. Alternatively, if the group is small, the interview may be with all potential participants.

Step 4: Plan The Logistics Of The Interview

Decide on the details of how, when, and where the interview will take place. Obtain consent from participants and provide them with advance notice of the interview date, time, and location. Choose an environment conducive to open and comfortable communication.

Step 5: Conduct The Interviews

Initiate the interviews by engaging in a casual conversation to establish rapport and build trust with the participants. During face-to-face interviews, actively listen to respondents, paying attention to their non-verbal cues such as body language, gestures, and vocal changes. Maintain a non-judgmental, empathetic, and friendly demeanor throughout the interview process.

Step 6: Transcribe The Interview Recordings

Transcribe the audio or video recordings of the semi-structured interviews. Transcription converts spoken content into written form, aiding in data analysis. Seek appropriate resources or tools to assist you in effectively transcribing the interviews.

Step 7: Code And Categorize The Data

Next, analyze the data collected from the semi-structured interviews. Coding involves carefully examining the transcribed data to identify recurring patterns, themes, and categories. This process helps in organizing and making sense of the information obtained. Consider using specialized coding interview software to streamline this task.

Also read: Mastering Analysis: The Role of Codebook Qualitative Research

Step 8: Analyze The Coded Data

Once the coding process is complete, analyze the coded data to gain meaningful insights. Utilize qualitative data analysis tools, such as Delve, to explore the data more deeply and uncover valuable findings. Draw connections between themes and patterns to develop a comprehensive understanding of the interview outcomes.

Step 9: Present Findings In A Research Paper Or Report

Transform the analysis into a coherent narrative by presenting the results in a research paper or report. Communicate the story behind the data, emphasizing key insights and supporting evidence. Structure the paper to effectively convey the significance and implications of findings in relation to research objectives.

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Qualitative research method-interviewing and observation

Shazia jamshed.

Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan Campus, Pahang, Malaysia

Buckley and Chiang define research methodology as “a strategy or architectural design by which the researcher maps out an approach to problem-finding or problem-solving.”[ 1 ] According to Crotty, research methodology is a comprehensive strategy ‘that silhouettes our choice and use of specific methods relating them to the anticipated outcomes,[ 2 ] but the choice of research methodology is based upon the type and features of the research problem.[ 3 ] According to Johnson et al . mixed method research is “a class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, theories and or language into a single study.[ 4 ] In order to have diverse opinions and views, qualitative findings need to be supplemented with quantitative results.[ 5 ] Therefore, these research methodologies are considered to be complementary to each other rather than incompatible to each other.[ 6 ]

Qualitative research methodology is considered to be suitable when the researcher or the investigator either investigates new field of study or intends to ascertain and theorize prominent issues.[ 6 , 7 ] There are many qualitative methods which are developed to have an in depth and extensive understanding of the issues by means of their textual interpretation and the most common types are interviewing and observation.[ 7 ]

Interviewing

This is the most common format of data collection in qualitative research. According to Oakley, qualitative interview is a type of framework in which the practices and standards be not only recorded, but also achieved, challenged and as well as reinforced.[ 8 ] As no research interview lacks structure[ 9 ] most of the qualitative research interviews are either semi-structured, lightly structured or in-depth.[ 9 ] Unstructured interviews are generally suggested in conducting long-term field work and allow respondents to let them express in their own ways and pace, with minimal hold on respondents’ responses.[ 10 ]

Pioneers of ethnography developed the use of unstructured interviews with local key informants that is., by collecting the data through observation and record field notes as well as to involve themselves with study participants. To be precise, unstructured interview resembles a conversation more than an interview and is always thought to be a “controlled conversation,” which is skewed towards the interests of the interviewer.[ 11 ] Non-directive interviews, form of unstructured interviews are aimed to gather in-depth information and usually do not have pre-planned set of questions.[ 11 ] Another type of the unstructured interview is the focused interview in which the interviewer is well aware of the respondent and in times of deviating away from the main issue the interviewer generally refocuses the respondent towards key subject.[ 11 ] Another type of the unstructured interview is an informal, conversational interview, based on unplanned set of questions that are generated instantaneously during the interview.[ 11 ]

In contrast, semi-structured interviews are those in-depth interviews where the respondents have to answer preset open-ended questions and thus are widely employed by different healthcare professionals in their research. Semi-structured, in-depth interviews are utilized extensively as interviewing format possibly with an individual or sometimes even with a group.[ 6 ] These types of interviews are conducted once only, with an individual or with a group and generally cover the duration of 30 min to more than an hour.[ 12 ] Semi-structured interviews are based on semi-structured interview guide, which is a schematic presentation of questions or topics and need to be explored by the interviewer.[ 12 ] To achieve optimum use of interview time, interview guides serve the useful purpose of exploring many respondents more systematically and comprehensively as well as to keep the interview focused on the desired line of action.[ 12 ] The questions in the interview guide comprise of the core question and many associated questions related to the central question, which in turn, improve further through pilot testing of the interview guide.[ 7 ] In order to have the interview data captured more effectively, recording of the interviews is considered an appropriate choice but sometimes a matter of controversy among the researcher and the respondent. Hand written notes during the interview are relatively unreliable, and the researcher might miss some key points. The recording of the interview makes it easier for the researcher to focus on the interview content and the verbal prompts and thus enables the transcriptionist to generate “verbatim transcript” of the interview.

Similarly, in focus groups, invited groups of people are interviewed in a discussion setting in the presence of the session moderator and generally these discussions last for 90 min.[ 7 ] Like every research technique having its own merits and demerits, group discussions have some intrinsic worth of expressing the opinions openly by the participants. On the contrary in these types of discussion settings, limited issues can be focused, and this may lead to the generation of fewer initiatives and suggestions about research topic.

Observation

Observation is a type of qualitative research method which not only included participant's observation, but also covered ethnography and research work in the field. In the observational research design, multiple study sites are involved. Observational data can be integrated as auxiliary or confirmatory research.[ 11 ]

Research can be visualized and perceived as painstaking methodical efforts to examine, investigate as well as restructure the realities, theories and applications. Research methods reflect the approach to tackling the research problem. Depending upon the need, research method could be either an amalgam of both qualitative and quantitative or qualitative or quantitative independently. By adopting qualitative methodology, a prospective researcher is going to fine-tune the pre-conceived notions as well as extrapolate the thought process, analyzing and estimating the issues from an in-depth perspective. This could be carried out by one-to-one interviews or as issue-directed discussions. Observational methods are, sometimes, supplemental means for corroborating research findings.

Designing a semi-structured interview guide for qualitative interviews

But what exactly do semi structured interviews mean? What exactly counts as in-depth? How structured are semi-structured interviews?

Daniel Turner

Interviews are a frequently used research method in qualitative studies. You will see dozens of papers that state something like “We conducted n in-depth semi-structured interviews with key informants”. But what exactly does this mean? What exactly counts as in-depth? How structured are semi-structured interviews?

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The term “in-depth” is defined fairly vaguely in the literature: it generally means a one-to-one interview on one general topic, which is covered in detail. Usually these qualitative interviews last about an hour, although sometimes much longer. It sounds like two people having a discussion, but there are differences in the power dynamics, and end goal: for the classic sociologist Burgess (2002) these are “conversations with a purpose”.

Qualitative interviews generally differ from quantitative survey based questions in that they are looking for a more detailed and nuanced response. They also acknowledge there is no ‘one-size fits all’, especially when asking someone to recall a personal narrative about their experiences. Instead of a fixed “research protocol” that asks the same question to each respondent, most interviewees adopt a more flexible approach. However there is still a need “...to ensure that the same general areas of information are collected from each interviewee; this provides more focus than the conversational approach, but still allows a degree of freedom and adaptability in getting information from the interviewee” – MacNamara (2009) .

Turner (2010) (who coincidentally shares the same name as me) describes three different types of qualitative interview; Informal Conversation, General Interview Guide, and Standardised Open-Ended. These can be seen as a scale from least to most structured, and we are going to focus on the ‘interview guide’ approach, which takes a middle ground.

An interview guide is like a cheat-sheet for the interviewer – it contains a list of questions and topic areas that should be covered in the interview. However, these are not to be read verbatim and in order, in fact they are more like an aide-mémoire. “Usually the interviewer will have a prepared set of questions but these are only used as a guide, and departures from the guidelines are not seen as a problem but are often encouraged” – Silverman (2013) . That way, the interviewer can add extra questions about an unexpected but relevant area that emerges, and sections that don’t apply to the participant can be negated.

So what do these look like, and how does one go about writing a suitable semi-structured interview guide? Unfortunately, it is rare in journal articles for researchers to share the interview guide, and it’s difficult to find good examples on the internet. Basically they look like a list of short questions and follow-on prompts, grouped by topic. There will generally be about a dozen. I’ve written my fair share of interview guides for qualitative research projects over the years, either on my own or with the collaboration of colleagues, so I’m happy to share some tips.

Questions should answer your research questions Your research project should have one or several main research questions, and these should be used to guide the topics covered in the interviews, and hopefully answer the research questions. However, you can’t just ask your respondents “Can the experience of male My Little Pony fans be described through the lens of Derridean deconstruction?”. You will need to break down your research into questions that have meaning for the participant and that they can engage with. The questions should be fairly informal and jargon free (unless that person is an expert in that field of jargon), open ended - so they can’t be easily answered with a yes or no, and non-leading so that respondents aren’t pushed down a certain interpretation.

Link to your proposed analytical approach The questions on your guide should also be constructed in such a way that they will work well for your proposed method of analysis – which again you should already have decided. If you are doing narrative analysis, questions should be encouraging respondents to tell their story and history. In Interpretative Phenomenological Analysis you may want to ask more detail about people’s interpretations of their experiences. Think how you will want to analyse, compare and write up your research, and make sure that the questioning style fits your own approach.

Specific ‘Why’ and prompt questions It is very rare in semi-structured interviews that you will ask one question, get a response, and then move on to the next topic. Firstly you will need to provide some structure for the participant, so they are not expected (or encouraged) to recite their whole life story. But on the other level, you will usually want to probe more about specific issues or conditions. That is where the flexible approach comes in. Someone might reveal something that you are interested in, and is relevant to the research project. So ask more! It’s often useful in the guide to list a series of prompt words that remind you of more areas of detail that might be covered. For example, the question “When did you first visit the doctor?” might be annotated with optional prompts such as “Why did you go then?”, “Were you afraid?” or “Did anyone go with you?”. Prompt words might reduce this to ‘Why THEN / afraid / with someone’.

Be flexible with order Generally, an interview guide will be grouped into several topics, each with a few questions. One of the most difficult skills is how to segue from one topic or question to the next, while still seeming like a normal conversation. The best way to manage this is to make sure that you are always listening to the interviewee, and thinking at the same time about how what they are saying links to other discussion topics. If someone starts talking about how they felt isolated visiting the doctor, and one of your topics is about their experience with their doctor, you can ask ‘Did you doctor make you feel less isolated?’. You might then be asking about topic 4, when you are only on topic 1, but you now have a logical link to ask the more general written question ‘Did you feel the doctor supported you?’. The ability to flow from topic to topic as the conversation evolves (while still covering everything on the interview guide) is tricky, and requires you to:

Know your guide backwards - literally I almost never went into an interview without a printed copy of the interview guide in front of me, but it was kind of like Dumbo’s magic feather : it made me feel safe, but I didn’t really need it. You should know everything on your interview guide off by heart, and in any sequence. Since things will crop up in unpredictable ways, you should be comfortable asking questions in different orders to help the conversational flow. Still, it’s always good to have the interview guide in front of you; it lets you tick off questions as they are asked (so you can see what hasn’t been covered), is space to write notes, and also can be less intimidating for the interviewee, as you can look at your notes occasionally rather than staring them in the eye all the time.

Try for natural conversation Legard, Keegan and Ward (2003) note that “Although a good in-depth interview will appear naturalistic, it will bear little resemblance to an everyday conversation”. You will usually find that the most honest and rich responses come from relaxed, non-combative discussions. Make the first question easy, to ease the participant into the interview, and get them used to the question-answer format. But don’t let it feel like a tennis match, where you are always asking the questions. If they ask something of you, reply! Don’t sit in silence: nod, say ‘Yes’, or ‘Of course’ every now and then, to show you are listening and empathising like a normal human being. Yet do be careful about sharing your own potentially leading opinions, and making the discussion about yourself.

Discuss with your research team / supervisors You should take the time to get feedback and suggestions from peers, be they other people on your research project, or your PhD supervisors. This means preparing the interview guide well in advance of your first interview, leaving time for discussion and revisions. Seasoned interviewers will have tips about wording and structuring questions, and even the most experienced researcher can benefit from a second opinion. Getting it right at this stage is very important, it’s no good discovering after you’ve done all your interviews that you didn’t ask about something important.

Adapting the guide While these are semi-structured interviews, in general you will usually want to cover the same general areas every time you do an interview, no least so that there is some point of comparison. It’s also common to do a first few interviews and realise that you are not asking about a critical area, or that some new potential insight is emerging (especially if you are taking a grounded theory approach). In qualitative research, this need not be a disaster (if this flexibility is methodologically appropriate), and it is possible to revise your interview guide. However, if you do end up making significant revisions, make sure you keep both versions, and a note of which respondents were interviewed with each version of the guide.

Test the timing Inevitably, you will not have exactly the same amount of time for each interview, and respondents will differ in how fast they talk and how often they go off-topic! Make sure you have enough questions to get the detail you need, but also have ‘lower priority’ questions you can drop if things are taking too long. Test the timing of your interview guide with a few participants, or even friends before you settle on it, and revise as necessary. Try and get your interview guide down to one side of paper at the most: it is a prompt, not an encyclopaedia!

Hopefully these points will help demystify qualitative interview guides, and help you craft a useful tool to shape your semi-structured interviews. I’d also caution that semi-structured interviewing is a very difficult process, and benefits majorly from practice. I have been with many new researchers who tend to fall back on the interview guide too much, and read it verbatim. This generally leads to closed-off responses, and missed opportunities to further explore interesting revelations. Treat your interview guide as a guide, not a gospel, and be flexible. It’s extra hard, because you have to juggle asking questions, listening, choosing the next question, keeping the research topic in your head and making sure everything is covered – but when you do it right, you’ll get rich research data that you will actually be excited to go home and analyse.

Don’t forget to check out some of the references above, as well as the myriad of excellent articles and textbooks on qualitative interviews. There’s also Quirkos itself , software to help you make the research process engaging and visual, with a free trial to download of this innovative tool. We also have a rapidly growing series of blog post articles on qualitative interviews. These now include 10 tips for qualitative interviewing , transcribing qualitative interviews and focus groups , and how to make sure you get good recordings . Our blog is updated with articles like this every week, and you can hear about it first by following our Twitter feed @quirkossoftware .

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• Published: 05 October 2018

Interviews and focus groups in qualitative research: an update for the digital age

• P. Gill 1 &
• J. Baillie 2  

British Dental Journal volume  225 ,  pages 668–672 ( 2018 ) Cite this article

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Highlights that qualitative research is used increasingly in dentistry. Interviews and focus groups remain the most common qualitative methods of data collection.

Suggests the advent of digital technologies has transformed how qualitative research can now be undertaken.

Suggests interviews and focus groups can offer significant, meaningful insight into participants' experiences, beliefs and perspectives, which can help to inform developments in dental practice.

Qualitative research is used increasingly in dentistry, due to its potential to provide meaningful, in-depth insights into participants' experiences, perspectives, beliefs and behaviours. These insights can subsequently help to inform developments in dental practice and further related research. The most common methods of data collection used in qualitative research are interviews and focus groups. While these are primarily conducted face-to-face, the ongoing evolution of digital technologies, such as video chat and online forums, has further transformed these methods of data collection. This paper therefore discusses interviews and focus groups in detail, outlines how they can be used in practice, how digital technologies can further inform the data collection process, and what these methods can offer dentistry.

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Introduction

Traditionally, research in dentistry has primarily been quantitative in nature. 1 However, in recent years, there has been a growing interest in qualitative research within the profession, due to its potential to further inform developments in practice, policy, education and training. Consequently, in 2008, the British Dental Journal (BDJ) published a four paper qualitative research series, 2 , 3 , 4 , 5 to help increase awareness and understanding of this particular methodological approach.

Since the papers were originally published, two scoping reviews have demonstrated the ongoing proliferation in the use of qualitative research within the field of oral healthcare. 1 , 6 To date, the original four paper series continue to be well cited and two of the main papers remain widely accessed among the BDJ readership. 2 , 3 The potential value of well-conducted qualitative research to evidence-based practice is now also widely recognised by service providers, policy makers, funding bodies and those who commission, support and use healthcare research.

Besides increasing standalone use, qualitative methods are now also routinely incorporated into larger mixed method study designs, such as clinical trials, as they can offer additional, meaningful insights into complex problems that simply could not be provided by quantitative methods alone. Qualitative methods can also be used to further facilitate in-depth understanding of important aspects of clinical trial processes, such as recruitment. For example, Ellis et al . investigated why edentulous older patients, dissatisfied with conventional dentures, decline implant treatment, despite its established efficacy, and frequently refuse to participate in related randomised clinical trials, even when financial constraints are removed. 7 Through the use of focus groups in Canada and the UK, the authors found that fears of pain and potential complications, along with perceived embarrassment, exacerbated by age, are common reasons why older patients typically refuse dental implants. 7

The last decade has also seen further developments in qualitative research, due to the ongoing evolution of digital technologies. These developments have transformed how researchers can access and share information, communicate and collaborate, recruit and engage participants, collect and analyse data and disseminate and translate research findings. 8 Where appropriate, such technologies are therefore capable of extending and enhancing how qualitative research is undertaken. 9 For example, it is now possible to collect qualitative data via instant messaging, email or online/video chat, using appropriate online platforms.

These innovative approaches to research are therefore cost-effective, convenient, reduce geographical constraints and are often useful for accessing 'hard to reach' participants (for example, those who are immobile or socially isolated). 8 , 9 However, digital technologies are still relatively new and constantly evolving and therefore present a variety of pragmatic and methodological challenges. Furthermore, given their very nature, their use in many qualitative studies and/or with certain participant groups may be inappropriate and should therefore always be carefully considered. While it is beyond the scope of this paper to provide a detailed explication regarding the use of digital technologies in qualitative research, insight is provided into how such technologies can be used to facilitate the data collection process in interviews and focus groups.

In light of such developments, it is perhaps therefore timely to update the main paper 3 of the original BDJ series. As with the previous publications, this paper has been purposely written in an accessible style, to enhance readability, particularly for those who are new to qualitative research. While the focus remains on the most common qualitative methods of data collection – interviews and focus groups – appropriate revisions have been made to provide a novel perspective, and should therefore be helpful to those who would like to know more about qualitative research. This paper specifically focuses on undertaking qualitative research with adult participants only.

Overview of qualitative research

Qualitative research is an approach that focuses on people and their experiences, behaviours and opinions. 10 , 11 The qualitative researcher seeks to answer questions of 'how' and 'why', providing detailed insight and understanding, 11 which quantitative methods cannot reach. 12 Within qualitative research, there are distinct methodologies influencing how the researcher approaches the research question, data collection and data analysis. 13 For example, phenomenological studies focus on the lived experience of individuals, explored through their description of the phenomenon. Ethnographic studies explore the culture of a group and typically involve the use of multiple methods to uncover the issues. 14

While methodology is the 'thinking tool', the methods are the 'doing tools'; 13 the ways in which data are collected and analysed. There are multiple qualitative data collection methods, including interviews, focus groups, observations, documentary analysis, participant diaries, photography and videography. Two of the most commonly used qualitative methods are interviews and focus groups, which are explored in this article. The data generated through these methods can be analysed in one of many ways, according to the methodological approach chosen. A common approach is thematic data analysis, involving the identification of themes and subthemes across the data set. Further information on approaches to qualitative data analysis has been discussed elsewhere. 1

Qualitative research is an evolving and adaptable approach, used by different disciplines for different purposes. Traditionally, qualitative data, specifically interviews, focus groups and observations, have been collected face-to-face with participants. In more recent years, digital technologies have contributed to the ongoing evolution of qualitative research. Digital technologies offer researchers different ways of recruiting participants and collecting data, and offer participants opportunities to be involved in research that is not necessarily face-to-face.

Research interviews are a fundamental qualitative research method 15 and are utilised across methodological approaches. Interviews enable the researcher to learn in depth about the perspectives, experiences, beliefs and motivations of the participant. 3 , 16 Examples include, exploring patients' perspectives of fear/anxiety triggers in dental treatment, 17 patients' experiences of oral health and diabetes, 18 and dental students' motivations for their choice of career. 19

Interviews may be structured, semi-structured or unstructured, 3 according to the purpose of the study, with less structured interviews facilitating a more in depth and flexible interviewing approach. 20 Structured interviews are similar to verbal questionnaires and are used if the researcher requires clarification on a topic; however they produce less in-depth data about a participant's experience. 3 Unstructured interviews may be used when little is known about a topic and involves the researcher asking an opening question; 3 the participant then leads the discussion. 20 Semi-structured interviews are commonly used in healthcare research, enabling the researcher to ask predetermined questions, 20 while ensuring the participant discusses issues they feel are important.

Interviews can be undertaken face-to-face or using digital methods when the researcher and participant are in different locations. Audio-recording the interview, with the consent of the participant, is essential for all interviews regardless of the medium as it enables accurate transcription; the process of turning the audio file into a word-for-word transcript. This transcript is the data, which the researcher then analyses according to the chosen approach.

Types of interview

Qualitative studies often utilise one-to-one, face-to-face interviews with research participants. This involves arranging a mutually convenient time and place to meet the participant, signing a consent form and audio-recording the interview. However, digital technologies have expanded the potential for interviews in research, enabling individuals to participate in qualitative research regardless of location.

Telephone interviews can be a useful alternative to face-to-face interviews and are commonly used in qualitative research. They enable participants from different geographical areas to participate and may be less onerous for participants than meeting a researcher in person. 15 A qualitative study explored patients' perspectives of dental implants and utilised telephone interviews due to the quality of the data that could be yielded. 21 The researcher needs to consider how they will audio record the interview, which can be facilitated by purchasing a recorder that connects directly to the telephone. One potential disadvantage of telephone interviews is the inability of the interviewer and researcher to see each other. This is resolved using software for audio and video calls online – such as Skype – to conduct interviews with participants in qualitative studies. Advantages of this approach include being able to see the participant if video calls are used, enabling observation of non-verbal communication, and the software can be free to use. However, participants are required to have a device and internet connection, as well as being computer literate, potentially limiting who can participate in the study. One qualitative study explored the role of dental hygienists in reducing oral health disparities in Canada. 22 The researcher conducted interviews using Skype, which enabled dental hygienists from across Canada to be interviewed within the research budget, accommodating the participants' schedules. 22

A less commonly used approach to qualitative interviews is the use of social virtual worlds. A qualitative study accessed a social virtual world – Second Life – to explore the health literacy skills of individuals who use social virtual worlds to access health information. 23 The researcher created an avatar and interview room, and undertook interviews with participants using voice and text methods. 23 This approach to recruitment and data collection enables individuals from diverse geographical locations to participate, while remaining anonymous if they wish. Furthermore, for interviews conducted using text methods, transcription of the interview is not required as the researcher can save the written conversation with the participant, with the participant's consent. However, the researcher and participant need to be familiar with how the social virtual world works to engage in an interview this way.

Conducting an interview

Ensuring informed consent before any interview is a fundamental aspect of the research process. Participants in research must be afforded autonomy and respect; consent should be informed and voluntary. 24 Individuals should have the opportunity to read an information sheet about the study, ask questions, understand how their data will be stored and used, and know that they are free to withdraw at any point without reprisal. The qualitative researcher should take written consent before undertaking the interview. In a face-to-face interview, this is straightforward: the researcher and participant both sign copies of the consent form, keeping one each. However, this approach is less straightforward when the researcher and participant do not meet in person. A recent protocol paper outlined an approach for taking consent for telephone interviews, which involved: audio recording the participant agreeing to each point on the consent form; the researcher signing the consent form and keeping a copy; and posting a copy to the participant. 25 This process could be replicated in other interview studies using digital methods.

There are advantages and disadvantages of using face-to-face and digital methods for research interviews. Ultimately, for both approaches, the quality of the interview is determined by the researcher. 16 Appropriate training and preparation are thus required. Healthcare professionals can use their interpersonal communication skills when undertaking a research interview, particularly questioning, listening and conversing. 3 However, the purpose of an interview is to gain information about the study topic, 26 rather than offering help and advice. 3 The researcher therefore needs to listen attentively to participants, enabling them to describe their experience without interruption. 3 The use of active listening skills also help to facilitate the interview. 14 Spradley outlined elements and strategies for research interviews, 27 which are a useful guide for qualitative researchers:

Greeting and explaining the project/interview

Asking descriptive (broad), structural (explore response to descriptive) and contrast (difference between) questions

Asymmetry between the researcher and participant talking

Expressing interest and cultural ignorance

Repeating, restating and incorporating the participant's words when asking questions

Creating hypothetical situations

Asking friendly questions

Knowing when to leave.

For semi-structured interviews, a topic guide (also called an interview schedule) is used to guide the content of the interview – an example of a topic guide is outlined in Box 1 . The topic guide, usually based on the research questions, existing literature and, for healthcare professionals, their clinical experience, is developed by the research team. The topic guide should include open ended questions that elicit in-depth information, and offer participants the opportunity to talk about issues important to them. This is vital in qualitative research where the researcher is interested in exploring the experiences and perspectives of participants. It can be useful for qualitative researchers to pilot the topic guide with the first participants, 10 to ensure the questions are relevant and understandable, and amending the questions if required.

Regardless of the medium of interview, the researcher must consider the setting of the interview. For face-to-face interviews, this could be in the participant's home, in an office or another mutually convenient location. A quiet location is preferable to promote confidentiality, enable the researcher and participant to concentrate on the conversation, and to facilitate accurate audio-recording of the interview. For interviews using digital methods the same principles apply: a quiet, private space where the researcher and participant feel comfortable and confident to participate in an interview.

Box 1: Example of a topic guide

Study focus: Parents' experiences of brushing their child's (aged 0–5) teeth

1. Can you tell me about your experience of cleaning your child's teeth?

How old was your child when you started cleaning their teeth?

Why did you start cleaning their teeth at that point?

How often do you brush their teeth?

What do you use to brush their teeth and why?

2. Could you explain how you find cleaning your child's teeth?

Do you find anything difficult?

What makes cleaning their teeth easier for you?

3. How has your experience of cleaning your child's teeth changed over time?

Has it become easier or harder?

Have you changed how often and how you clean their teeth? If so, why?

4. Could you describe how your child finds having their teeth cleaned?

What do they enjoy about having their teeth cleaned?

Is there anything they find upsetting about having their teeth cleaned?

5. Where do you look for information/advice about cleaning your child's teeth?

What did your health visitor tell you about cleaning your child's teeth? (If anything)

What has the dentist told you about caring for your child's teeth? (If visited)

Have any family members given you advice about how to clean your child's teeth? If so, what did they tell you? Did you follow their advice?

6. Is there anything else you would like to discuss about this?

Focus groups

A focus group is a moderated group discussion on a pre-defined topic, for research purposes. 28 , 29 While not aligned to a particular qualitative methodology (for example, grounded theory or phenomenology) as such, focus groups are used increasingly in healthcare research, as they are useful for exploring collective perspectives, attitudes, behaviours and experiences. Consequently, they can yield rich, in-depth data and illuminate agreement and inconsistencies 28 within and, where appropriate, between groups. Examples include public perceptions of dental implants and subsequent impact on help-seeking and decision making, 30 and general dental practitioners' views on patient safety in dentistry. 31

Focus groups can be used alone or in conjunction with other methods, such as interviews or observations, and can therefore help to confirm, extend or enrich understanding and provide alternative insights. 28 The social interaction between participants often results in lively discussion and can therefore facilitate the collection of rich, meaningful data. However, they are complex to organise and manage, due to the number of participants, and may also be inappropriate for exploring particularly sensitive issues that many participants may feel uncomfortable about discussing in a group environment.

Focus groups are primarily undertaken face-to-face but can now also be undertaken online, using appropriate technologies such as email, bulletin boards, online research communities, chat rooms, discussion forums, social media and video conferencing. 32 Using such technologies, data collection can also be synchronous (for example, online discussions in 'real time') or, unlike traditional face-to-face focus groups, asynchronous (for example, online/email discussions in 'non-real time'). While many of the fundamental principles of focus group research are the same, regardless of how they are conducted, a number of subtle nuances are associated with the online medium. 32 Some of which are discussed further in the following sections.

Focus group considerations

Some key considerations associated with face-to-face focus groups are: how many participants are required; should participants within each group know each other (or not) and how many focus groups are needed within a single study? These issues are much debated and there is no definitive answer. However, the number of focus groups required will largely depend on the topic area, the depth and breadth of data needed, the desired level of participation required 29 and the necessity (or not) for data saturation.

The optimum group size is around six to eight participants (excluding researchers) but can work effectively with between three and 14 participants. 3 If the group is too small, it may limit discussion, but if it is too large, it may become disorganised and difficult to manage. It is, however, prudent to over-recruit for a focus group by approximately two to three participants, to allow for potential non-attenders. For many researchers, particularly novice researchers, group size may also be informed by pragmatic considerations, such as the type of study, resources available and moderator experience. 28 Similar size and mix considerations exist for online focus groups. Typically, synchronous online focus groups will have around three to eight participants but, as the discussion does not happen simultaneously, asynchronous groups may have as many as 10–30 participants. 33

The topic area and potential group interaction should guide group composition considerations. Pre-existing groups, where participants know each other (for example, work colleagues) may be easier to recruit, have shared experiences and may enjoy a familiarity, which facilitates discussion and/or the ability to challenge each other courteously. 3 However, if there is a potential power imbalance within the group or if existing group norms and hierarchies may adversely affect the ability of participants to speak freely, then 'stranger groups' (that is, where participants do not already know each other) may be more appropriate. 34 , 35

Focus group management

Face-to-face focus groups should normally be conducted by two researchers; a moderator and an observer. 28 The moderator facilitates group discussion, while the observer typically monitors group dynamics, behaviours, non-verbal cues, seating arrangements and speaking order, which is essential for transcription and analysis. The same principles of informed consent, as discussed in the interview section, also apply to focus groups, regardless of medium. However, the consent process for online discussions will probably be managed somewhat differently. For example, while an appropriate participant information leaflet (and consent form) would still be required, the process is likely to be managed electronically (for example, via email) and would need to specifically address issues relating to technology (for example, anonymity and use, storage and access to online data). 32

The venue in which a face to face focus group is conducted should be of a suitable size, private, quiet, free from distractions and in a collectively convenient location. It should also be conducted at a time appropriate for participants, 28 as this is likely to promote attendance. As with interviews, the same ethical considerations apply (as discussed earlier). However, online focus groups may present additional ethical challenges associated with issues such as informed consent, appropriate access and secure data storage. Further guidance can be found elsewhere. 8 , 32

Before the focus group commences, the researchers should establish rapport with participants, as this will help to put them at ease and result in a more meaningful discussion. Consequently, researchers should introduce themselves, provide further clarity about the study and how the process will work in practice and outline the 'ground rules'. Ground rules are designed to assist, not hinder, group discussion and typically include: 3 , 28 , 29

Discussions within the group are confidential to the group

Only one person can speak at a time

All participants should have sufficient opportunity to contribute

There should be no unnecessary interruptions while someone is speaking

Everyone can be expected to be listened to and their views respected

Challenging contrary opinions is appropriate, but ridiculing is not.

Moderating a focus group requires considered management and good interpersonal skills to help guide the discussion and, where appropriate, keep it sufficiently focused. Avoid, therefore, participating, leading, expressing personal opinions or correcting participants' knowledge 3 , 28 as this may bias the process. A relaxed, interested demeanour will also help participants to feel comfortable and promote candid discourse. Moderators should also prevent the discussion being dominated by any one person, ensure differences of opinions are discussed fairly and, if required, encourage reticent participants to contribute. 3 Asking open questions, reflecting on significant issues, inviting further debate, probing responses accordingly, and seeking further clarification, as and where appropriate, will help to obtain sufficient depth and insight into the topic area.

Moderating online focus groups requires comparable skills, particularly if the discussion is synchronous, as the discussion may be dominated by those who can type proficiently. 36 It is therefore important that sufficient time and respect is accorded to those who may not be able to type as quickly. Asynchronous discussions are usually less problematic in this respect, as interactions are less instant. However, moderating an asynchronous discussion presents additional challenges, particularly if participants are geographically dispersed, as they may be online at different times. Consequently, the moderator will not always be present and the discussion may therefore need to occur over several days, which can be difficult to manage and facilitate and invariably requires considerable flexibility. 32 It is also worth recognising that establishing rapport with participants via online medium is often more challenging than via face-to-face and may therefore require additional time, skills, effort and consideration.

As with research interviews, focus groups should be guided by an appropriate interview schedule, as discussed earlier in the paper. For example, the schedule will usually be informed by the review of the literature and study aims, and will merely provide a topic guide to help inform subsequent discussions. To provide a verbatim account of the discussion, focus groups must be recorded, using an audio-recorder with a good quality multi-directional microphone. While videotaping is possible, some participants may find it obtrusive, 3 which may adversely affect group dynamics. The use (or not) of a video recorder, should therefore be carefully considered.

At the end of the focus group, a few minutes should be spent rounding up and reflecting on the discussion. 28 Depending on the topic area, it is possible that some participants may have revealed deeply personal issues and may therefore require further help and support, such as a constructive debrief or possibly even referral on to a relevant third party. It is also possible that some participants may feel that the discussion did not adequately reflect their views and, consequently, may no longer wish to be associated with the study. 28 Such occurrences are likely to be uncommon, but should they arise, it is important to further discuss any concerns and, if appropriate, offer them the opportunity to withdraw (including any data relating to them) from the study. Immediately after the discussion, researchers should compile notes regarding thoughts and ideas about the focus group, which can assist with data analysis and, if appropriate, any further data collection.

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Gill, P., Baillie, J. Interviews and focus groups in qualitative research: an update for the digital age. Br Dent J 225 , 668–672 (2018). https://doi.org/10.1038/sj.bdj.2018.815

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Issue Date : 12 October 2018

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• Volume 7, Issue 2
• Semistructured interviewing in primary care research: a balance of relationship and rigour
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• http://orcid.org/0000-0002-2660-3358 Melissa DeJonckheere 1 and
• Lisa M Vaughn 2 , 3
• 1 Department of Family Medicine , University of Michigan , Ann Arbor , Michigan , USA
• 2 Department of Pediatrics , University of Cincinnati College of Medicine , Cincinnati , Ohio , USA
• 3 Division of Emergency Medicine , Cincinnati Children's Hospital Medical Center , Cincinnati , Ohio , USA
• Correspondence to Dr Melissa DeJonckheere; mdejonck{at}med.umich.edu

Semistructured in-depth interviews are commonly used in qualitative research and are the most frequent qualitative data source in health services research. This method typically consists of a dialogue between researcher and participant, guided by a flexible interview protocol and supplemented by follow-up questions, probes and comments. The method allows the researcher to collect open-ended data, to explore participant thoughts, feelings and beliefs about a particular topic and to delve deeply into personal and sometimes sensitive issues. The purpose of this article was to identify and describe the essential skills to designing and conducting semistructured interviews in family medicine and primary care research settings. We reviewed the literature on semistructured interviewing to identify key skills and components for using this method in family medicine and primary care research settings. Overall, semistructured interviewing requires both a relational focus and practice in the skills of facilitation. Skills include: (1) determining the purpose and scope of the study; (2) identifying participants; (3) considering ethical issues; (4) planning logistical aspects; (5) developing the interview guide; (6) establishing trust and rapport; (7) conducting the interview; (8) memoing and reflection; (9) analysing the data; (10) demonstrating the trustworthiness of the research; and (11) presenting findings in a paper or report. Semistructured interviews provide an effective and feasible research method for family physicians to conduct in primary care research settings. Researchers using semistructured interviews for data collection should take on a relational focus and consider the skills of interviewing to ensure quality. Semistructured interviewing can be a powerful tool for family physicians, primary care providers and other health services researchers to use to understand the thoughts, beliefs and experiences of individuals. Despite the utility, semistructured interviews can be intimidating and challenging for researchers not familiar with qualitative approaches. In order to elucidate this method, we provide practical guidance for researchers, including novice researchers and those with few resources, to use semistructured interviewing as a data collection strategy. We provide recommendations for the essential steps to follow in order to best implement semistructured interviews in family medicine and primary care research settings.

• qualitative research

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https://doi.org/10.1136/fmch-2018-000057

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Introduction

Semistructured interviews can be used by family medicine researchers in clinical settings or academic settings even with few resources. In contrast to large-scale epidemiological studies, or even surveys, a family medicine researcher can conduct a highly meaningful project with interviews with as few as 8–12 participants. For example, Chang and her colleagues, all family physicians, conducted semistructured interviews with 10 providers to understand their perspectives on weight gain in pregnant patients. 1 The interviewers asked questions about providers’ overall perceptions on weight gain, their clinical approach to weight gain during pregnancy and challenges when managing weight gain among pregnant patients. Additional examples conducted by or with family physicians or in primary care settings are summarised in table 1 . 1–6

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Examples of research articles using semistructured interviews in primary care research

From our perspective as seasoned qualitative researchers, conducting effective semistructured interviews requires: (1) a relational focus, including active engagement and curiosity, and (2) practice in the skills of interviewing. First, a relational focus emphasises the unique relationship between interviewer and interviewee. To obtain quality data, interviews should not be conducted with a transactional question-answer approach but rather should be unfolding, iterative interactions between the interviewer and interviewee. Second, interview skills can be learnt. Some of us will naturally be more comfortable and skilful at conducting interviews but all aspects of interviews are learnable and through practice and feedback will improve. Throughout this article, we highlight strategies to balance relationship and rigour when conducting semistructured interviews in primary care and the healthcare setting.

Qualitative research interviews are ‘attempts to understand the world from the subjects’ point of view, to unfold the meaning of peoples’ experiences, to uncover their lived world prior to scientific explanations’ (p 1). 7 Qualitative research interviews unfold as an interviewer asks questions of the interviewee in order to gather subjective information about a particular topic or experience. Though the definitions and purposes of qualitative research interviews vary slightly in the literature, there is common emphasis on the experiences of interviewees and the ways in which the interviewee perceives the world (see table 2 for summary of definitions from seminal texts).

Definitions of qualitative interviews

The most common type of interview used in qualitative research and the healthcare context is semistructured interview. 8 Figure 1 highlights the key features of this data collection method, which is guided by a list of topics or questions with follow-up questions, probes and comments. Typically, the sequencing and wording of the questions are modified by the interviewer to best fit the interviewee and interview context. Semistructured interviews can be conducted in multiple ways (ie, face to face, telephone, text/email, individual, group, brief, in-depth), each of which have advantages and disadvantages. We will focus on the most common form of semistructured interviews within qualitative research—individual, face-to-face, in-depth interviews.

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Key characteristics of semistructured interviews.

Purpose of semistructured interviews

The overall purpose of using semistructured interviews for data collection is to gather information from key informants who have personal experiences, attitudes, perceptions and beliefs related to the topic of interest. Researchers can use semistructured interviews to collect new, exploratory data related to a research topic, triangulate other data sources or validate findings through member checking (respondent feedback about research results). 9 If using a mixed methods approach, semistructured interviews can also be used in a qualitative phase to explore new concepts to generate hypotheses or explain results from a quantitative phase that tests hypotheses. Semistructured interviews are an effective method for data collection when the researcher wants: (1) to collect qualitative, open-ended data; (2) to explore participant thoughts, feelings and beliefs about a particular topic; and (3) to delve deeply into personal and sometimes sensitive issues.

Designing and conducting semistructured interviews

In the following section, we provide recommendations for the steps required to carefully design and conduct semistructured interviews with emphasis on applications in family medicine and primary care research (see table 3 ).

Steps to designing and conducting semistructured interviews

Steps for designing and conducting semistructured interviews

Step 1: determining the purpose and scope of the study.

The purpose of the study is the primary objective of your project and may be based on an anecdotal experience, a review of the literature or previous research finding. The purpose is developed in response to an identified gap or problem that needs to be addressed.

Research questions are the driving force of a study because they are associated with every other aspect of the design. They should be succinct and clearly indicate that you are using a qualitative approach. Qualitative research questions typically start with ‘What’, ‘How’ or ‘Why’ and focus on the exploration of a single concept based on participant perspectives. 10

Step 2: identifying participants

After deciding on the purpose of the study and research question(s), the next step is to determine who will provide the best information to answer the research question. Good interviewees are those who are available, willing to be interviewed and have lived experiences and knowledge about the topic of interest. 11 12 Working with gatekeepers or informants to get access to potential participants can be extremely helpful as they are trusted sources that control access to the target sample.

Sampling strategies are influenced by the research question and the purpose of the study. Unlike quantitative studies, statistical representativeness is not the goal of qualitative research. There is no calculation of statistical power and the goal is not a large sample size. Instead, qualitative approaches seek an in-depth and detailed understanding and typically use purposeful sampling. See the study of Hatch for a summary of various types of purposeful sampling that can be used for interview studies. 12

‘How many participants are needed?’ The most common answer is, ‘it depends’—it depends on the purpose of the study, what kind of study is planned and what questions the study is trying to answer. 12–14 One common standard in qualitative sample sizes is reaching thematic saturation, which refers to the point at which no new thematic information is gathered from participants. Malterud and colleagues discuss the concept of information power , or a qualitative equivalent to statistical power, to determine how many interviews should be collected in a study. They suggest that the size of a sample should depend on the aim, homogeneity of the sample, theory, interview quality and analytic strategy. 14

Step 3: considering ethical issues

An ethical attitude should be present from the very beginning of the research project even before you decide who to interview. 15 This ethical attitude should incorporate respect, sensitivity and tact towards participants throughout the research process. Because semistructured interviewing often requires the participant to reveal sensitive and personal information directly to the interviewer, it is important to consider the power imbalance between the researcher and the participant. In healthcare settings, the interviewer or researcher may be a part of the patient’s healthcare team or have contact with the healthcare team. The researchers should ensure the interviewee that their participation and answers will not influence the care they receive or their relationship with their providers. Other issues to consider include: reducing the risk of harm; protecting the interviewee’s information; adequately informing interviewees about the study purpose and format; and reducing the risk of exploitation. 10

Step 4: planning logistical aspects

Careful planning particularly around the technical aspects of interviews can be the difference between a great interview and a not so great interview. During the preparation phase, the researcher will need to plan and make decisions about the best ways to contact potential interviewees, obtain informed consent, arrange interview times and locations convenient for both participant and researcher, and test recording equipment. Although many experienced researchers have found themselves conducting interviews in less than ideal locations, the interview location should avoid (or at least minimise) interruptions and be appropriate for the interview (quiet, private and able to get a clear recording). 16 For some research projects, the participants’ homes may make sense as the best interview location. 16

Initial contacts can be made through telephone or email and followed up with more details so the individual can make an informed decision about whether they wish to be interviewed. Potential participants should know what to expect in terms of length of time, purpose of the study, why they have been selected and who will be there. In addition, participants should be informed that they can refuse to answer questions or can withdraw from the study at any time, including during the interview itself.

Audio recording the interview is recommended so that the interviewer can concentrate on the interview and build rapport rather than being distracted with extensive note taking 16 (see table 4 for audio-recording tips). Participants should be informed that audio recording is used for data collection and that they can refuse to be audio recorded should they prefer.

Suggestions for successful audio recording of interviews

Most researchers will want to have interviews transcribed verbatim from the audio recording. This allows you to refer to the exact words of participants during the analysis. Although it is possible to conduct analyses from the audio recordings themselves or from notes, it is not ideal. However, transcription can be extremely time consuming and, if not done yourself, can be costly.

In the planning phase of research, you will want to consider whether qualitative research software (eg, NVivo, ATLAS.ti, MAXQDA, Dedoose, and so on) will be used to assist with organising, managing and analysis. While these tools are helpful in the management of qualitative data, it is important to consider your research budget, the cost of the software and the learning curve associated with using a new system.

Step 5: developing the interview guide

Semistructured interviews include a short list of ‘guiding’ questions that are supplemented by follow-up and probing questions that are dependent on the interviewee’s responses. 8 17 All questions should be open ended, neutral, clear and avoid leading language. In addition, questions should use familiar language and avoid jargon.

Most interviews will start with an easy, context-setting question before moving to more difficult or in-depth questions. 17 Table 5 gives details of the types of guiding questions including ‘grand tour’ questions, 18 core questions and planned and unplanned follow-up questions.

Questions and prompts in semistructured interviewing

To illustrate, online supplementary appendix A presents a sample interview guide from our study of weight gain during pregnancy among young women. We start with the prompt, ‘Tell me about how your pregnancy has been so far’ to initiate conversation about their thoughts and feelings during pregnancy. The subsequent questions will elicit responses to help answer our research question about young women’s perspectives related to weight gain during pregnancy.

Supplemental material

After developing the guiding questions, it is important to pilot test the interview. Having a good sense of the guide helps you to pace the interview (and not run out of time), use a conversational tone and make necessary adjustments to the questions.

Like all qualitative research, interviewing is iterative in nature—data collection and analysis occur simultaneously, which may result in changes to the guiding questions as the study progresses. Questions that are not effective may be replaced with other questions and additional probes can be added to explore new topics that are introduced by participants in previous interviews. 10

Step 6: establishing trust and rapport

Interviews are a special form of relationship, where the interviewer and interviewee converse about important and often personal topics. The interviewer must build rapport quickly by listening attentively and respectfully to the information shared by the interviewee. 19 As the interview progresses, the interviewer must continue to demonstrate respect, encourage the interviewee to share their perspectives and acknowledge the sensitive nature of the conversation. 20

To establish rapport, it is important to be authentic and open to the interviewee’s point of view. It is possible that the participants you recruit for your study will have preconceived notions about research, which may include mistrust. As a result, it is important to describe why you are conducting the research and how their participation is meaningful. In an interview relationship, the interviewee is the expert and should be treated as such—you are relying on the interviewee to enhance your understanding and add to your research. Small behaviours that can enhance rapport include: dressing professionally but not overly formal; avoiding jargon or slang; and using a normal conversational tone. Because interviewees will be discussing their experience, having some awareness of contextual or cultural factors that may influence their perspectives may be helpful as background knowledge.

Step 7: conducting the interview

Location and set-up.

The interview should have already been scheduled at a convenient time and location for the interviewee. The location should be private, ideally with a closed door, rather than a public place. It is helpful if there is a room where you can speak privately without interruption, and where it is quiet enough to hear and audio record the interview. Within the interview space, Josselson 15 suggests an arrangement with a comfortable distance between the interviewer and interviewee with a low table in between for the recorder and any materials (consent forms, questionnaires, water, and so on).

Beginning the interview

Many interviewers start with chatting to break the ice and attempt to establish commonalities, rapport and trust. Most interviews will need to begin with a brief explanation of the research study, consent/assent procedures, rationale for talking to that particular interviewee and description of the interview format and agenda. 11 It can also be helpful if the interviewer shares a little about who they are and why they are interested in the topic. The recording equipment should have already been tested thoroughly but interviewers may want to double-check that the audio equipment is working and remind participants about the reason for recording.

Interviewer stance

During the interview, the interviewer should adopt a friendly and non-judgemental attitude. You will want to maintain a warm and conversational tone, rather than a rote, question-answer approach. It is important to recognise the potential power differential as a researcher. Conveying a sense of being in the interview together and that you as the interviewer are a person just like the interviewee can help ease any discomfort. 15

Active listening

During a face-to-face interview, there is an opportunity to observe social and non-verbal cues of the interviewee. These cues may come in the form of voice, body language, gestures and intonation, and can supplement the interviewee’s verbal response and can give clues to the interviewer about the process of the interview. 21 Listening is the key to successful interviewing. 22 Listening should be ‘attentive, empathic, nonjudgmental, listening in order to invite, and engender talk’ 15 15 (p 66). Silence, nods, smiles and utterances can also encourage further elaboration from the interviewee.

Continuing the interview

As the interview progresses, the interviewer can repeat the words used by the interviewee, use planned and unplanned follow-up questions that invite further clarification, exploration or elaboration. As DiCicco-Bloom and Crabtree 10 explain: ‘Throughout the interview, the goal of the interviewer is to encourage the interviewee to share as much information as possible, unselfconsciously and in his or her own words’ (p 317). Some interviewees are more forthcoming and will offer many details of their experiences without much probing required. Others will require prompting and follow-up to elicit sufficient detail.

As a result, follow-up questions are equally important to the core questions in a semistructured interview. Prompts encourage people to continue talking and they can elicit more details needed to understand the topic. Examples of verbal probes are repeating the participant’s words, summarising the main idea or expressing interest with verbal agreement. 8 11 See table 6 for probing techniques and example probes we have used in our own interviewing.

Probing techniques for semistructured interviews (modified from Bernard 30 )

Step 8: memoing and reflection

After an interview, it is essential for the interviewer to begin to reflect on both the process and the content of the interview. During the actual interview, it can be difficult to take notes or begin reflecting. Even if you think you will remember a particular moment, you likely will not be able to recall each moment with sufficient detail. Therefore, interviewers should always record memos —notes about what you are learning from the data. 23 24 There are different approaches to recording memos: you can reflect on several specific ideas, or create a running list of thoughts. Memos are also useful for improving the quality of subsequent interviews.

Step 9: analysing the data

The data analysis strategy should also be developed during planning stages because analysis occurs concurrently with data collection. 25 The researcher will take notes, modify the data collection procedures and write reflective memos throughout the data collection process. This begins the process of data analysis.

The data analysis strategy used in your study will depend on your research question and qualitative design—see the study of Creswell for an overview of major qualitative approaches. 26 The general process for analysing and interpreting most interviews involves reviewing the data (in the form of transcripts, audio recordings or detailed notes), applying descriptive codes to the data and condensing and categorising codes to look for patterns. 24 27 These patterns can exist within a single interview or across multiple interviews depending on the research question and design. Qualitative computer software programs can be used to help organise and manage interview data.

Step 10: demonstrating the trustworthiness of the research

Similar to validity and reliability, qualitative research can be assessed on trustworthiness. 9 28 There are several criteria used to establish trustworthiness: credibility (whether the findings accurately and fairly represent the data), transferability (whether the findings can be applied to other settings and contexts), confirmability (whether the findings are biased by the researcher) and dependability (whether the findings are consistent and sustainable over time).

Step 11: presenting findings in a paper or report

When presenting the results of interview analysis, researchers will often report themes or narratives that describe the broad range of experiences evidenced in the data. This involves providing an in-depth description of participant perspectives and being sure to include multiple perspectives. 12 In interview research, the participant words are your data. Presenting findings in a report requires the integration of quotes into a more traditional written format.

Conclusions

Though semistructured interviews are often an effective way to collect open-ended data, there are some disadvantages as well. One common problem with interviewing is that not all interviewees make great participants. 12 29 Some individuals are hard to engage in conversation or may be reluctant to share about sensitive or personal topics. Difficulty interviewing some participants can affect experienced and novice interviewers. Some common problems include not doing a good job of probing or asking for follow-up questions, failure to actively listen, not having a well-developed interview guide with open-ended questions and asking questions in an insensitive way. Outside of pitfalls during the actual interview, other problems with semistructured interviewing may be underestimating the resources required to recruit participants, interview, transcribe and analyse the data.

Despite their limitations, semistructured interviews can be a productive way to collect open-ended data from participants. In our research, we have interviewed children and adolescents about their stress experiences and coping behaviours, young women about their thoughts and behaviours during pregnancy, practitioners about the care they provide to patients and countless other key informants about health-related topics. Because the intent is to understand participant experiences, the possible research topics are endless.

Due to the close relationships family physicians have with their patients, the unique settings in which they work, and in their advocacy, semistructured interviews are an attractive approach for family medicine researchers, even if working in a setting with limited research resources. When seeking to balance both the relational focus of interviewing and the necessary rigour of research, we recommend: prioritising listening over talking; using clear language and avoiding jargon; and deeply engaging in the interview process by actively listening, expressing empathy, demonstrating openness to the participant’s worldview and thanking the participant for helping you to understand their experience.

Further Reading

Edwards R, & Holland J. (2013). What is qualitative interviewing?: A&C Black.

Josselson R. Interviewing for qualitative inquiry: A relational approach. Guilford Press, 2013.

Kvale S. InterViews: An Introduction to Qualitative Research Interviewing. SAGE, London, 1996.

Pope C, & Mays N. (Eds). (2006). Qualitative research in health care.

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Contributors Both authors contributed equally to this work.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; internally peer reviewed.

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14 Unstructured and Semi-Structured Interviewing

Svend Brinkmann, Department of Communication & Psychology, University of Aalborg

• Published: 01 July 2014
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This chapter gives an introduction to qualitative interviewing in its unstructured and semistructured forms. Initially, the human world is depicted as a conversational reality in which interviewing takes a central position as a research method. Interviewing is presented as a social practice that has a cultural history and that today appears in a variety of different formats. A number of distinctions are introduced, which are relevant when mapping the field of qualitative interviewing between different levels of structure, numbers of participants, media of interviewing, and also interviewer styles. A more detailed exposition of semistructured life world interviewing is offered because this is arguably the standard form of qualitative interviewing today.

Qualitative interviewing has today become a key method in the human and social sciences and also in many other corners of the scientific landscape from education to the health sciences. Some have even argued that interviewing has become the central resource through which the social sciences—and society—engages with the issues that concern it ( Rapley, 2001 ). For as long as we know, human beings have used conversation as a central tool to obtain knowledge about others. People talk with others in order to learn about how they experience the world, how they think, act, feel, and develop as individuals and in groups, and, in recent decades, such knowledge-producing conversations have been refined and discussed as qualitative interviews. 1

This chapter gives an overview of the landscape of qualitative interviewing, with a focus on its unstructured and semistructured forms. But what are interviews as such? In a classic text, Maccoby and Maccoby defined the interview as “a face-to-face verbal exchange, in which one person, the interviewer, attempts to elicit information or expressions of opinion or belief from another person or persons” ( Maccoby & Maccoby, 1954 , p. 449). This definition can be used as a very general starting point, but we shall soon see that different schools of qualitative interviewing have interpreted, modified, and added to such a generic characterization in many different ways.

I begin this chapter by giving an introduction to the broader conversational world of human beings in which interviewing takes place. I then provide a brief history of qualitative interviewing before introducing a number of conceptual and analytical distinctions relevant for the central epistemological and theoretical questions in the field of qualitative interviewing. Particular attention is given to the complementary positions of experience-focused interviewing (phenomenological positions) and language-focused interviewing (discourse-oriented positions).

Qualitative Interviewing in a Conversational World

Human beings are conversational creatures who live a dialogical life. Humankind is, in the words of philosopher Stephen Mulhall, “a kind of enacted conversation” ( Mulhall, 2007 , p. 58). From the earliest days of our lives, we are able to enter into proto-conversations with caregivers in ways that involve subtle forms of turn-taking and emotional communication. The dyads in which our earliest conversations occur are known to be prior to the child’s own sense of self. We are therefore communicating, and indeed conversational, creatures before we become subjective and monological ones ( Trevarthen, 1993 ).

Of course, we do learn to talk privately to ourselves and hide our emotional lives from others, but this is possible only because there was first an intersubjective communicative process with others. Our relationships with other people—and also with ourselves—are thus conversational. To understand ourselves, we must use a language that was first acquired conversationally, and we try out our interpretations in dialogue with others and the world. The human self exists only within what philosopher Charles Taylor has called “webs of interlocution” ( Taylor, 1989 , p. 36). Our very inquiring and interpreting selves are conversational at their core; they are constituted by the numerous relationships we have and have had with other people ( Brinkmann, 2012 ).

Unsurprisingly, conversations are therefore a rich and indispensable source of knowledge about personal and social aspects of our lives. In a philosophical sense, all human research is conversational because we are linguistic creatures and language is best understood in terms of the figure of conversation ( Mulhall, 2007 ). Since the late nineteenth century (in journalism) and the early twentieth century (in the social sciences), the conversational process of knowing has been conceptualized under the name of interviewing . The term itself testifies to the dialogical and interactional nature of human life. An interview is literally an inter-view , an interchange of views between two persons (or more) conversing about a theme of mutual interest ( Kvale & Brinkmann, 2008 ). Conversation in its Latin root means “dwelling with someone” or “wandering together with.” Similarly, the root meaning of dialogue is that of talk ( logos ) that goes back and forth ( dia- ) between persons ( Mannheim & Tedlock, 1995 , p. 4).

Thus conceived, the concept of conversation in the human and social sciences should be thought of in very broad terms and not just as a specific research method. Certainly, conversations in the form of interviewing have been refined into a set of techniques—to be explicated later—but they are also a mode of knowing and a fundamental ontology of persons. As philosopher Rom Harré has put it: “The primary human reality is persons in conversation” ( Harré, 1983 , p. 58). Cultures are constantly produced, reproduced, and revised in dialogues among their members ( Mannheim & Tedlock, 1995 , p. 2). Thus conceived, our everyday lives are conversational to their core. This also goes for the cultural investigation of cultural phenomena, or what we call social science. It is fruitful to see language, culture, and human self-understanding as emergent properties of conversations rather than the other way around. Dialogues are not several monologues that are added together but the basic, primordial form of associated human life. In the words of psychologist John Shotter:

[W]e live our daily social lives within an ambience of conversation, discussion, argumentation, negotiation, criticism and justification; much of it to do with problems of intelligibility and the legitimation of claims to truth. ( Shotter, 1993 , p. 29)

The pervasiveness of the figure of conversation in human life is both a burden and a blessing for qualitative interviewers. On the one hand, it means that qualitative interviewing becomes a very significant tool with which to understand central features of our conversational world. In response to widespread critiques of qualitative research that it is too subjective, one should say—given the picture of the conversational world painted here—that qualitative interviewing is, in fact, the most objective method of inquiry when one is interested in qualitative features of human experience, talk, and interaction because qualitative interviews are uniquely capable of grasping these features and thus of being adequate to their subject matters (which is one definition of objectivity).

On the other hand, it is also a burden for qualitative interviewers that they employ conversations to study a world that is already saturated with conversation. If Mulhall is right that humankind is a kind of enacted conversation, then the process of studying humans by the use of interviewing is analogous to fish wanting to study water. Fish surely “know” what water is in a practical, embodied sense, but it can be a great challenge to see and understand the obvious, that with which we are so familiar ( Brinkmann, 2012 ). In the same way, some interview researchers might think that interviewing others for research purposes is easy and simple to do because it employs a set of techniques that everyone masters by virtue of being capable of asking questions and recording the answers. This, however, is clearly an illusory simplicity, and many qualitative interviewers, even experienced ones, will recognize the frustrating experience of having conducted a large number of interviews (which is often the fun and seemingly simple part of a research project) but ending up with a huge amount of data, in the form of perhaps hundreds or even thousand pages of transcripts, and not knowing how to transform all this material into a solid, relevant, and thought-provoking analysis. Too much time is often spent on interviewing, whereas too little time is devoted to preparing for the interviews and subsequently analyzing the empirical materials. And, to continue on this note, too little time is normally used to reflect on the role of interviewing as a knowledge-producing social practice in itself. Due to its closeness to everyday conversations, interviewing, in short, is often simply taken for granted.

A further burden for today’s qualitative interviewers concerns the fact that interviewees are often almost too familiar with their role in the conversation. As Atkinson and Silverman argued some years ago, we live in an interview society , where the self is continually produced in confessional settings ranging from talk shows to research interviews ( Atkinson & Silverman, 1997 ). Because most of us, at least in the imagined hemisphere we call the West, are acquainted with interviews and their more or less standardized choreographies, qualitative interviews sometimes become a rather easy and regular affair, with few breaks and cracks in its conventions and norms, even though such breaks and cracks are often the most interesting aspects of conversational episodes ( Roulston, 2010 ; Tanggaard, 2007 ).

On the side of interviewers, Atkinson and Silverman find that “in promoting a particular view of narratives of personal experience, researchers too often recapitulate, in an uncritical fashion, features of the contemporary interview society” in which “the interview becomes a personal confessional” ( Atkinson & Silverman, 1997 , p. 305). Although the conversation in a broad sense is a human universal, qualitative interviewers often forget that the social practice of research interviewing in a narrower sense is a historically and culturally specific mode of interacting, and they too often construe “face-to-face interaction” as “the primordial, natural setting for communication,” as anthropologist Charles Briggs has pointed out ( Briggs, 2007 , p. 554).

As a consequence, the analysis of interviews is generally limited to what takes place during the concrete interaction phase with its questions and responses. In contrast to this, there is reason to believe that excellent interview research does not simply communicate a number of answers to an interviewer’s questions (with the researcher’s interpretive interjections added on), but includes an analytic focus on what Briggs has called “the larger set of practices of knowledge production that makes up the research from beginning to end” ( Briggs, 2007 , p. 566). Just as it is crucial in quantitative and experimental research to have an adequate understanding of the technologies of experimentation, it is similarly crucial in qualitative interviewing to understand the intricacies of this quite specific knowledge-producing practice, and interviewers should be particularly careful not to naturalize the form of human relationship that is a qualitative research interview and simply gloss it over as an unproblematic, direct, and universal source of knowledge. This, at least, is a basic assumption of the present chapter.

The History of Qualitative Interviewing

This takes us directly to the history of qualitative interviewing because only by tracking the history of how the current practices came to be can we fully understand their contingent natures and reflect on their roles in how we produce conversational knowledge through interviews today.

In one obvious sense, the use of conversations for knowledge-producing purposes is likely as old as human language and communication. The fact that we can pose questions to others about things that we are unknowledgeable about is a core capability of the human species. It expands our intellectual powers enormously because it enables us to share and distribute knowledge between us. Without this fundamental capability, it would be hard to imagine what human life would be like. It is furthermore a capacity that has developed into many different forms and ramifications in human societies. Already in 1924 could Emory Bogardus, an early American sociologist and founder of one of the first US sociology departments (at the University of Southern California) declare that interviewing “is as old as the human race” ( Bogardus, 1924 , p. 456). Bogardus discussed similarities and differences between the ways that physicians, lawyers, priests, journalists, detectives, social workers, and psychiatrists conduct interviews, with a remarkable sensitivity to the details of such different conversational practices.

Ancient Roots

In a more specific sense, and more essentially related to qualitative interviewing as a scientific human enterprise, conversations were used by Thucydides in ancient Greece as he interviewed participants from the Peloponnesian Wars to write the history of the wars. At roughly the same time, Socrates famously questioned—or we might say interviewed —his fellow citizens in ancient Athens and used the dialogues to develop knowledge about perennial human questions related to justice, truth, beauty, and the virtues. In recent years, some interview scholars have sought to rehabilitate a Socratic practice of interviewing, not least as an alternative to the often long monologues of phenomenological and narrative approaches to interviewing (see Dinkins, 2005 , who unites Socrates with a hermeneutic approach to dialogical knowledge) and also in an attempt to think of interviews as practices that can create a knowledgeable citizenry and not merely chart common opinions and attitudes ( Brinkmann, 2007 a ). Such varieties of interviewing have come to be known as dialogic and confrontational ( Roulston, 2010 , p. 26), and I return to these later.

Psychoanalysis

If we jump to more recent times, interviewing notably entered the human sciences with the advent of Sigmund Freud’s psychoanalysis, emerging around 1900. Freud is famous for his psychoanalytic theory of the unconscious, but it is significant that he developed this revolutionary theory (which, in many ways, changed the Western conceptions of humanity) through therapeutic conversations, or what he referred to as the talking cure . Freud conducted several hundred interviews with patients that used the patients’ free associations as a conversational engine. The therapist/interviewer should display what Freud called an “even-hovering attention” and catch on to anything that emerged as important ( Freud, 1963 ).

Freud made clear that research and treatment go hand in hand in psychoanalysis, and scholars have more recently pointed to the rich potentials of psychoanalytic conversations for qualitative interviewing today (see Kvale, 2003 ). For example, Wendy Hollway and Tony Jefferson have developed a more specific notion of the interview that is based on the psychoanalytic idea of “the defended subject” ( Hollway & Jefferson, 2000 ). In their eyes, interviewees “are motivated not to know certain aspects of themselves and... they produce biographical accounts which avoid such knowledge” (p. 169). This, obviously, has implications for how interviewers should proceed with analysis and interpretation of the biographical statements of interviewees and is a quite different approach to interviewing compared to more humanistic forms, as we shall see.

Many human and social scientists from the first half of the twentieth century were well versed in psychoanalytic theory, including those who pioneered qualitative interviewing. Jean Piaget, the famous developmental researcher, had even received training as a psychoanalyst himself, but his approach to interviewing is also worth mentioning in its own right. Piaget’s (1930) theory of child development was based on his interviews with children (often his own) in natural settings, frequently in combination with different experimental tasks. He would typically let the children talk freely about the weight and size of objects, or, in relation to his research on moral development, about different moral problems ( Piaget, 1932/1975 ), and he would notice the manner in which their thoughts unfolded.

Jumping from psychology to industrial research, Raymond Lee, one of the few historians of interviewing, has charted in detail how Piaget’s so-called clinical method of interviewing became an inspiration for Elton Mayo, who was responsible for one of the largest interview studies in history at the Hawthorne plant in Chicago in the 1920s ( Lee, 2011 ). This study arose from a need to interpret the curious results of a number of practical experiments on the effects of changes in illumination on production at the plant: it seemed that work output improved when the lighting of the production rooms was increased but also when it was decreased. This instigated an interview study, with more than 21,000 workers being interviewed for more than an hour each. The study was reported by Roethlisberger and Dickson (1939) , but it was Mayo who laid out the methodological procedures in the 1930s, including careful—and surprisingly contemporary—advice to interviewers that is worth quoting at length:

Give your whole attention to the person interviewed, and make it evident that you are doing so.

Listen—don’t talk.

Never argue; never give advice.

what he wants to say

what he does not want to say

what he cannot say without help

As you listen, plot out tentatively and for subsequent correction the pattern (personal) that is being set before you. To test this, from time to time summarize what has been said and present for comment (e.g., “is this what you are telling me?”). Always do this with the greatest caution, that is, clarify in ways that do not add or distort.

Remember that everything said must be considered a personal confidence and not divulged to anyone. ( Mayo, 1933 , p. 65)

Many approaches to and textbooks on interviewing still follow such guidelines today, often forgetting, however, the specific historical circumstances under which this practice emerged.

Nondirective Interviewing

Not just Piaget, but also the humanistic psychologist Carl Rogers had influenced Mayo and others concerned with interviewing in the first half of the twentieth century. Like Freud, Rogers developed a conversational technique that was useful both in therapeutic contexts (so-called client-centered therapy), but also in research interviews, which he referred to as the “non-directive method as a technique for social research” ( Rogers, 1945 ). As he explained, the goal of this kind of research was to sample the respondent’s attitudes toward herself: “Through the non-directive interview we have an unbiased method by which we may plumb these private thoughts and perceptions of the individual.” (p. 282). In contrast to psychoanalysis, the respondent in client-centered research (and therapy) is a client rather than a patient, and the client is the expert (and hardly a “defended subject”). Although often framed in different terms, many contemporary interview researchers conceptualize the research interview in line with Rogers’s humanistic, nondirective approach, valorizing the respondents’ private experiences, narratives, opinions, beliefs, and attitudes.

As Lee recounts, the methods of interviewing developed at Hawthorne in the 1930s aroused interest among sociologists at the University of Chicago, who made it part of their methodological repertoire ( Lee, 2011 , p. 132). Rogers himself moved to Chicago in 1945 and was involved in different interdisciplinary projects. As is well known, the so-called Chicago School of sociology was highly influential in using and promoting a range of qualitative methods, not least ethnography, and it also spawned some of the most innovative theoretical developments in the social sciences, such as symbolic interactionism (e.g., Blumer, 1969 ).

As the Rogerian nondirective approach to interviewing gained in popularity, early critiques of this technique also emerged. In the 1950s, the famous sociologist David Riesman and his colleague Mark Benney criticized it for its lack of interviewer involvement (the nondirective aspects), and they warned against the tendency to use the level of “rapport” (much emphasized by interviewers inspired by therapy) in an interview to judge its qualities concerning knowledge. They thought it was a prejudice “to assume the more rapport-filled and intimate the relation, the more ‘truth’ the respondent will vouchsafe” ( Riesman & Benney, 1956 , p. 10). In their eyes, rapport-filled interviews would often spill over with “the flow of legend and cliché” (p. 11), since interviewees are likely to adapt their responses to what they assume the interviewer expects from them (see also Lee, 2008 , for an account of Riesman’s surprisingly contemporary discussion of interviewing). Issues such as these, originally raised more than fifty years ago, continue to be pertinent and largely unresolved in today’s interview research.

Classic Studies on Authoritarianism, Sexuality, and Consumerism

The mid-twentieth century witnessed a number of other large interview studies that remain classics in the field and that have also shaped public opinion about different social issues. I mention three examples here of such influential interview studies to show the variety of themes that have been studied through interviews: on authoritarianism, sexuality, and consumerism.

After World War II, there was a pressing need to understand the roots of anti-Semitism, and The Authoritarian Personality by the well-known critical theorist Adorno and co-workers controversially traced these roots to an authoritarian upbringing ( Adorno, Frenkel-Brunswik, Levinson, & Sanford, 1950 ). Their study was based on interviews and employed a combination of open qualitative interviews and much more structured questionnaires to produce the data. Although important knowledge of societal value may have been produced, the study has nonetheless been criticized on ethical grounds for using therapeutic techniques to get around the defenses of the interviewees in order to learn about their prejudices and authoritarian personality traits ( Kvale & Brinkmann, 2008 , p. 313).

Another famous interview study from the same period was Kinsey’s Sexual Behavior in the Human Male ( Kinsey, Pomeroy, & Martin, 1948 ). The research group interviewed about 6,000 men for an hour or more about their sexual behaviors, which generated results that were shocking to the public. In addition to the fascinating results, the book contains many interesting reflections on interviewing, and the authors discuss in great detail how to put the interviewees at ease, assure privacy, and how to frame the sequencing of sensitive topics (the contributions of Adorno and Kinsey are also described in Platt, 2002 ). As Kinsey put it in the book:

The interview has become an opportunity for him [the participant] to develop his own thinking, to express to himself his disappointments and hopes, to bring into the open things that he has previously been afraid to admit to himself, to work out solutions to his difficulties. He quickly comes to realize that a full and complete confession will serve his own interests. ( Kinsey et al., 1948 , p. 42)

The movie Kinsey , from 2004, starring Liam Neeson, is worth seeing from an interviewer’s point of view because it shows these early interviewers in action.

As a third example, it can be mentioned that qualitative interviewing quickly entered market research in the course of the twentieth century, which is hardly surprising as a consumer society developed ( Brinkmann & Kvale, 2005 ). A pioneer was Ernest Dichter, whose The Strategy of Desire (1960) communicates the results of an interview study about consumer motivation for buying a car. Interestingly, Dichter describes his interview technique as a “depth interview,” inspired both by psychoanalysis and also by the nondirective approach of Rogers. Market and consumer research continue to be among the largest areas of qualitative interviewing in contemporary consumer society, particularly in the form of focus groups, and, according to one estimate, as many as 5 percent of all adults in Great Britain have taken part in focus groups for marketing purposes, which certainly lends very concrete support to the thesis that we live in an “interview society” ( Brinkmann & Kvale, 2005 ).

Contemporary Conceptions of Qualitative Interviewing

Along with the different empirical studies, academics in the Western world have produced an enormous number of books on qualitative interviewing as a method, both in the form of “how to” books, but also in the form of more theoretical discussions. Spradley’s The Ethnographic Interview (1979) and Mishler’s Research Interviewing: Context and Narrative (1986) were two important early books, the former being full of concrete advice about how to ask questions and the latter being a thorough theoretical analysis of interviews as speech events involving a joint construction of meaning.

Also following from the postmodern philosophies of social science that emerged in the 1980s (e.g., Clifford & Marcus, 1986 ; Lyotard, 1984 ), in the past couple of decades there has been a veritable creative explosion in the kinds of interviews offered to researchers (see Fontana & Prokos, 2007 ), many of which question both the idea of psychoanalysis as being able to dig out truths from the psyche of the interviewee and that the nondirective approach to interviews can be “an unbiased method,” as Rogers had originally conceived it.

Roulston (2010) makes a comprehensive list of some of the most recent postmodern varieties of interviewing and also of more traditional ones (I have here shortened and adapted Roulston’s longer list):

Neo-positivist conceptions of the interview are still widespread and emphasize how the conversation can be used to reveal “the true self” of the interviewee (or the essence of her experiences), ideally resulting in solid, trustworthy data that are only accessible through interviews if the interviewer assumes a noninterfering role.

Romantic conceptions stress that the goal of interviewing is to obtain revelations and confessions from the interviewee facilitated by intimacy and rapport. These conceptions are somewhat close to neo-positivist ones, but put much more weight on the interviewer as an active and authentic midwife who assists in “giving birth” to revelations from the interviewee’s inner psyche.

Constructionist conceptions reject the romantic idea of authenticity and favor an idea of a subject that is locally produced within the situation. Thus, the focus is on the situational practice of interviewing and a distrust toward the discourse of data as permanent “nuggets” to be “mined” by the interviewer. Instead, the interviewer is often portrayed as a “traveler” together with the interviewee, with both involved in the co-construction of whatever happens in the conversation ( Kvale & Brinkmann, 2008 ).

Postmodern and transformative conceptions stage interviews as dialogic and performative events that aim to bring new kinds of people and new worlds into being. The interview is depicted as a chance for people to get together and create new possibilities for action. Some transformative conceptions focus on potential decolonizing aspects of interviewing, seeking to subvert the colonizing tendencies that some see in standard interviewing ( Smith, 1999 ). In addition, we can mention feminist ( Reinharz & Chase, 2002 ) and collaborative forms of interviewing ( Ellis & Berger, 2003 ) that aim to practice an engaged form of interviewing that focuses more on the researchers’ experience than in standard procedures, sometimes expressed through autoethnography, an approach that seeks to unite ethnographical and autobiographical intentions ( Ellis, Adams, & Bochner, 2011 ).

It goes without saying that the overarching line of historical development laid out here, beginning in the earliest years of recorded human history and ending with postmodern, transformative, and co-constructed interviewing, is highly selective, and it could have been presented in countless other ways. I have made no attempt to divide up the history of qualitative interviewing into historical phases because I believe this would betray the criss-crossing lines of inspiration from different knowledge-producing practices. Socrates as an active interviewer inspires some of today’s constructionist and postmodern interviewers (as we shall see), whereas Freud and Rogers—as clinical interviewers—in different ways became important to people who use interviewing for purposes related to marketing and the industry. Thus, it seems that the only general rule is that no approach is never completely left behind and that everything can be—and often is—recycled in new clothes. This should not surprise us, because the richness and historical variability of the human conversational world demand that researchers use different conversational means of knowledge production for different purposes.

An Example of Qualitative Interviewing

Before moving on, here I introduce an example of what a typical qualitative interview may look like, taken from my own research, to illustrate more concretely what we are talking about when we use the term “qualitative interviewing.”

The following excerpt is from an interview I conducted about ten years ago. It was part of a research project in which I studied ethical dilemmas and moral reasoning in psychotherapeutic practice. The project was exploratory and sought an understanding of clinical psychologists’ own experiences of ethical problems in their work. The excerpt in Box 14.1 is not meant to represent an ideal interview, but rather to illustrate a common choreography that is inherent in much qualitative interviewing across the different varieties.

These few exchanges of questions and answers follow a certain conversational flow common in qualitative interviews. This flow can be divided into (1) question , (2) negotiation of meaning concerning the question raised and the themes addressed, (3) concrete description from the interviewee, (4) the interviewer’s interpretation of the description, and (5) coda . Then the cycle can start over with a new question, or else—as in this case—further questions about the same description can be posed.

The sequence begins when I pose a question (1) that calls for a concrete description, a question that seems to make sense to the interviewee. However, she cannot immediately think of or articulate an episode, and she expresses doubt concerning the meaning of one of the central concepts of the opening question (an “ethical dilemma”). This happens very often, and it can be quite difficult for interviewees (as for all of us) to describe concretely what one has experienced; we often resort to speaking in general terms (this characterizes professionals in particular, who have many general scripts at their disposal to articulate). There is some negotiation and attunement between us (2), before she decides to talk about a specific situation, but even though this is interesting and well described by the interviewee (3), she ends by returning (in what I call the coda) to a doubt about the appropriateness of the example. Before this, I summarize and rephrase her description (4), which she validates before she herself provides a kind of evaluation (5). After this, I have a number of follow-up questions that ask the interviewee to tell me more about the situation before a new question is introduced, and a similar conversational flow begins again.

The uncertainty of the interviewee about her own example around (2) illustrates the importance of assuring the interviewee that he or she is the expert concerning personal experience. The interviewer should make clear that, in general, there are no right or wrong answers or examples in qualitative interviewing and that the interviewer is interested in anything the interviewee comes up with. It is very common to find that participants are eager to be “good interviewees,” wanting to give the researcher something valuable, and this can paradoxically block the production of interesting stories and descriptions (although it did not in the present case).

In this case, a key point of the study became the term “ethical dilemma” itself; a term that is currently a nodal point in a huge number of different discourses with many different meanings, and it was thus interesting to hear the respondents’ immediate understandings of the term. Their widespread uncertainty concerning the referents of the term (which was shared by the interviewer!) was not only understandable, but actually conducive to developing my ideas further about (professional) ethics as something occurring in a zone of doubt rather than certainty (as otherwise stressed by some of the standard procedural approaches to ethics).

At the time of the interview, the interviewee was in her early fifties and had been a practicing psychologist for about twenty-five years. The interview was conducted in Danish, and I have translated it into English myself.

After some introductory remarks and an initial briefing, I, the interviewer (SB), go straight to a question that I had prepared in advance and ask the interviewee (IE) for a description of a concrete ethical dilemma (the numbers in square brackets refer to elements of the conversation that are addressed in the text):

SB: ( 1 ) First, I’d like to ask you to think back and describe a situation from your work as a psychologist in which you experienced an ethical dilemma... or a situation that in some way demanded special ethical considerations from you. IE: ( 2 ) Actually, I believe I experience those all the time. Well... I believe that the very fact that therapeutic work with other people demands that you keep... I don’t know if it is a dilemma—that’s what you asked about, right?—well, I don’t know if it’s a dilemma, but I think I have ethical considerations all the time. Considerations about how best to treat this human being with respect are demanded all the time... with the respect that is required, and I believe that there are many ethical considerations there. Ahm... When you work therapeutically you become very personal, get very close to another human being, and I think that is something you have to bear in mind constantly: How far are you allowed to go? How much can you enter into someone else’s universe? But that is not a dilemma, is it? SB: I guess it can be. Can you think of a concrete situation in which you faced this question about how close you can go, for example? IE: ( 3 ) Yes, I can. I just had a... a woman, whose husband has a mental disorder, or he has had a severe personality disorder, so their family life is much affected by this. And she comes to me to process this situation of hers, having two small children and a husband, and a system of treatment, which sometimes helps out and sometimes doesn’t. And it is very difficult for her to accept that someone close to her has a mental disorder or is fragile, it’s actually a long process. She is a nurse and family life has more or less been idyllic before he... before the personality disorder really emerged. So it is extremely difficult for her to accept that this family, which she had imagined would be the place for her children to grow up, is not going to be like that. It is actually going to be very, very different. And she tries to fight it all the time: “It just might be... if only... I guess it will be...” And it is never going to be any different! And there lies a dilemma, I think: How much is it going to be: “This is something you have to face, it is never going to be different!” So I have to work to make her pose the question herself: “What do you think? How long time... What are your thoughts? Do you think it will be different? What do they tell you at the psychiatric hospital? What is your experience?” And right now she is getting closer to seeing... I might fear that it ends in a divorce; I am not sure that she can cope with it. But no one can know this. I think there is a dilemma here, or some considerations about how much to push and press forward. SB: ( 4 ) Yes, the dilemma is perhaps that you—with your experience and knowledge about these matters—can see that the situation is not going to change much from its current state? IE: It certainly won’t. SB: And the question is... IE: ... how much I should push, for she does actually know this intellectually. ( 5 ) We have talked about it lots of times. But emotionally she hasn’t... she doesn’t have the power to face it. One day I told her: “I don’t think you develop, I don’t think anything happens to you, before you accept emotionally that he is not going to change.” I put her on the spot and she kept evading it and so on, but it...“You don’t accept it; I can tell that you don’t accept it. You understand it intellectually, but you still hope that it passes.” I pushed her a lot then. But I don’t know if this is an ethical dilemma, I am not sure...

When I first set out to conduct this study, I had something like a neo-positivist conception of interviewing in mind, in Roulston’s sense, believing that there were certain essential features connected to the experience of ethically difficult situations. When working further with the theme, and after learning from my interviewees, I gradually grew suspicious of this idea, and I also came to appreciate a more constructionist conception of interviewing, according to which the interview situation itself—including the interviewer—plays an important role in the production of talk.

Other things to note about the example in Box 14.1 include the asymmetrical distribution of talk that can be observed between the two conversationalists: the interviewer poses rather short questions, and the interviewee gives long and elaborated answers. This is not always so (some respondents are more reluctant or simply less talkative), but this asymmetry has been highlighted as a sign of quality in the literature on qualitative interviewing (e.g., Kvale & Brinkmann, 2008 ). There is also quite a bit of dramatization in the interviewee’s talk in the excerpt; for example, when she uses reported speech to stage a dialogue between herself and her client, which signals that she is capable with words and a good storyteller. On the side of the interviewer, we see that no attempts are made to contradict or question the interviewee’s account, and the part of the interview quoted here thus looks quite a bit like that recommended by Mayo in the 1930s and by later nondirective interviewers: the interviewer listens a lot and does not talk much, he does not argue or give advice, and he plots out tentatively (in [4]) what the interviewee is saying, which is commented on and verified (cf. Mayo, 1933 , p. 65).

Different Forms of Qualitative Research Interviews

The semistructured, face-to-face interview in Box 14.1 is probably very typical, but it merely represents one form an interview may take, and there is a huge variety of other forms. Each form has certain advantages and disadvantages that researchers and recipients of research alike should be aware of. I here describe how qualitative interviews may differ in terms of structure, the number of participants in each interview, different media, and also different interviewer styles.

It is common to draw a distinction between structured, semistructured, and unstructured interviews. This distinction, however, should be thought of as a continuum ranging from relatively structured to relatively unstructured formats. I use the word “relatively” because, on the one end of the continuum, as Parker (2005) argues, there really is no such thing as a completely structured interview “because people always say things that spill beyond the structure, before the interview starts and when the recorder has been turned off” (p. 53). Utterances that “spill beyond the structure” are often important and are even sometimes the key to understanding the interviewee’s answers to the structured questions. One line of criticism against standardized survey interviewing actually concerns the fact that meanings and interpretive frames that go beyond the predetermined structure are left out, with the risk that the researcher cannot understand what actually goes on in the interaction.

We might add to Parker’s argument that there is also no such thing as a completely unstructured interview because the interviewer always has an idea about what should take place in the conversation. Even some of the least structured interviews, such as life history interviews that only have one question prepared in advance (e.g., “I would like you to tell me the story of your life. Please begin as far back as you remember and include as many details as possible”), provide structure to the conversation by framing it in accordance with certain specific conversational norms rather than others. Another way to put this is to say that there are no such things as nonleading questions. All questions lead the interviewee in certain directions, but it is generally preferably to lead participants only to talk about certain themes , rather than to specific opinions about these themes.

So, it is not possible to avoid structure entirely nor would it be desirable, but it is possible to provide a structure that it flexible enough for interviewees to be able to raise questions and concerns in their own words and from their own perspectives. Anthropologist Bruno Latour has argued that this is one definition of objectivity that human and social science can work with, in the sense of “allowing the object to object” ( Latour, 2000 ). Latour pinpoints a problem in the human and social sciences related to the fact that, for these sciences and unlike in the natural sciences “nothing is more difficult than to find a way to render objects able to object to the utterances that we make about them” (p. 115). He finds that human beings behave too easily as if they had been mastered by the researcher’s agenda, which often results in trivial and predictable research that tells us nothing new. What should be done instead is to allow research participants to be “interested, active, disobedient, fully involved in what is said about themselves by others” (p. 116). This does not imply a total elimination of structure, but it demands careful preparation and reflection on how to involve interviewees actively, how to avoid flooding the conversation with social science categories, and how to provoke interviewees in a respectful way to bring contrasting perspectives to light ( Parker, 2005 , p. 63).

In spite of this caveat—that neither completely structured nor completely unstructured interviews are possible—it may still be worthwhile to distinguish between more or less structure, with semistructured interviews somewhere in the middle as the standard approach to qualitative interviewing.

Structured Interviews

Structured interviews are employed in surveys and are typically based on the same research logic as questionnaires: standardized ways of asking questions are thought to lead to answers that can be compared across participants and possibly quantified. Interviewers are supposed to “read questions exactly as worded to every respondent and are trained never to provide information beyond what is scripted in the questionnaire” ( Conrad & Schober, 2008 , p. 173). Although structured interviews are useful for some purposes, they do not take advantage of the dialogical potentials for knowledge production inherent in human conversations. They are passive recordings of people’s opinions and attitudes and often reveal more about the cultural conventions of how one should answer specific questions than about the conversational production of social life itself. I do not address these structured forms in greater detail in this chapter.

Unstructured Interviews

At the other end of the continuum lie interviews that have little preset structure. These are, for example, the life story interview seeking to highlight “the most important influences, experiences, circumstances, issues, themes, and lessons of a lifetime” ( Atkinson, 2002 , p. 125). What these aspects are for an individual cannot be known in advance but emerge in the course of spending time with the interviewee, which means that the interviewer cannot prepare for a life story interview by devising a lot of specific questions but must instead think about how to facilitate the telling of the life story. After the opening request for a narrative, the main role of the interviewer is to remain a listener, withholding desires to interrupt and sporadically asking questions that may clarify the story. The life story interview is a variant of the more general genre of narrative interviewing about which Wengraf’s (2001)   Qualitative Research Interviewing gives a particularly thorough account, focusing on biographical-narrative depth interviews. These need not concern the life story as a whole, but may address other, more specific storied aspects of human lives, building on the narratological insight that humans experience and act in the world through narratives. Narratives, in this light, are a root metaphor for psychological processes ( Sarbin, 1986 ). With the more focused narrative interviews, we get nearer to semistructured interviews as the middle ground between structured and unstructured interviews.

Semistructured Interviews

Interviews in the semistructured format are sometimes equated with qualitative interviewing as such ( Warren, 2002 ). They are probably also the most widespread form of interviews in the human and social sciences and are sometimes the only format given attention to in textbooks on qualitative research (e.g., Flick, 2002 ). Compared to structured interviews, semistructured interviews can make better use of the knowledge-producing potentials of dialogues by allowing much more leeway for following up on whatever angles are deemed important by the interviewee; as well, the interviewer has a greater chance of becoming visible as a knowledge-producing participant in the process itself, rather than hiding behind a preset interview guide. And, compared to unstructured interviews, the interviewer has a greater say in focusing the conversation on issues that he or she deems important in relation to the research project.

One definition of the qualitative research interview (in a generic form, but tending toward the semistructured format) reads: “It is defined as an interview with the purpose of obtaining descriptions of the life world of the interviewee in order to interpret the meaning of the described phenomena” ( Kvale & Brinkmann, 2008 , p. 3). The key words here are purpose, descriptions, life world , and interpretation of meaning :

Purpose : Unlike everyday conversations with friends or family members, qualitative interviews are not conducted for their own sake; they are not a goal in themselves, but are staged and conducted to serve the researcher’s goal of producing knowledge (and there may be other, ulterior goals like obtaining a degree, furthering one’s career, positioning oneself in the field, etc.). All sorts of motives may play a role in the staging of interviews, and good interview reports often contain a reflexive account and a discussion of both individual and social aspects of such motives (does it matter, for example, if the interviewer is a woman, perhaps identifying as a feminist, interviewing other women?). Clearly, the fact that interviews are conversations conducted for a purpose, which sets the agenda, raises a number of issues having to do with power and control that are important to reflect on for epistemic as well as ethical reasons ( Brinkmann, 2007 b ).

Descriptions : In most interview studies, the goal is to obtain the interviewee’s descriptions rather than reflections or theorizations. In line with a widespread phenomenological perspective (explained more fully later), interviewers are normally seeking descriptions of how interviewees experience the world, its episodes and events, rather than speculations about why they have certain experiences. Good interview questions thus invite interviewees to give descriptions; for example, “Could you please describe a situation for me in which you became angry?,” “What happened?,” “How did you experience anger?,” “How did it feel?” (of course, only one of these questions should be posed at a time), and good interviewers tend to avoid more abstract and reflective questions such as “What does anger mean to you?,” “If I say ‘anger,’ what do you think of then?,” “Why do you think that you tend to feel angry?” Such questions may be productive in the conversation, but interviewers will normally defer them until more descriptive aspects have been covered.

Life world : The concept of the life world goes back to the founder of phenomenology, Edmund Husserl, who introduced it in 1936, in his book The Crisis of the European Sciences to refer to the intersubjectively shared and meaningful world in which humans conduct their lives and experience significant phenomena ( Husserl, 1954 ). It is a prereflective and pretheorized world in which anger, for example, is a meaningful human expression in response to having one’s rights violated (or something similar) before it is a process occurring in the neurophysiological and endocrinological systems (“before” should here be taken in a logical, rather than temporal, sense). If anger did not appear to human beings as a meaningful experienced phenomenon in their life world, there would be no reason to investigate it scientifically because there would, in a sense, be nothing to investigate (since anger is primarily identified as a life world phenomenon). In qualitative research in general, as in qualitative interviewing in particular, there is a primacy of the life world as experienced, as something prior to the scientific theories we may formulate about it. This was well expressed by Maurice Merleau-Ponty, another famous phenomenologist, who built on the work of Husserl:

All my knowledge of the world, even my scientific knowledge, is gained from my own particular point of view, or from some experience of the world without which the symbols of science would be meaningless. The whole universe of science is built upon the world as directly experienced [i.e., the life world], and if we want to subject science itself to rigorous scrutiny and arrive at a precise assessment of its meaning and scope, we must begin by re-awakening the basic experiences of the world of which science is the second order expression. ( Merleau-Ponty, 1945/2002 , p. ix)

Objectifying sciences give us second-order understandings of the world, but qualitative research is meant to provide a first-order understanding through concrete description. Whether interview researchers express themselves in the idiom of phenomenology, or use the language of some other qualitative paradigm (discourse analysis, symbolic interactionism, ethnomethodology, etc.), they most often decide to use interviews to elicit descriptions of the life world—or whatever term the given paradigm employs: the interaction order (to speak with Erving Goffman, an exponent of symbolic interactionism), the immortal ordinary society (to speak with Harold Garfinkel, the founder of ethnomethodology), or the set of interpretative repertoires that make something meaningful (to speak with Jonathan Potter and Margaret Wetherell, significant discursive psychologists). 2

Interpret the meaning : Even if interviewers are generally interested in how people experience and act in the world prior to abstract theorizations, they must nonetheless often engage in interpretations of people’s experiences and actions as described in interviews. One reason for this is that life world phenomena are rarely transparent and “monovocal” but are rather “polyvocal” and sometimes even contradictory, permitting multiple readings and interpretations. Who is to say what someone’s description of anger signifies? Obviously, the person having experienced the anger should be listened to, but if there is one lesson to learn from twentieth-century human science (ranging from psychoanalysis to poststructuralism) it is that we, as human subjects, do not have full authority concerning how to understand our lives because we do not have—and can never have—full insight into the forces that have created us ( Butler, 2005 ). We are, as Judith Butler has argued, authored by what precedes and exceeds us (p. 82), even when we are considered—as in qualitative interviews—to be authors of our own utterances. The interpretation of the meanings of the phenomena described by the interviewee can favorably be built into the conversation itself (as I tried to do at point (4) in the excerpt in Box 14.1 ) because this will at least give the interviewee a chance to object to a certain interpretation, but it is a process that goes on throughout an interview project.

In my opinion, too rarely do interview researchers allow themselves to follow the different, polyvocal, and sometimes contradictory meanings that emerge through different voices in interviewee accounts. Analysts of interviews are generally looking for the voice of the interviewee, thereby ignoring internal conflicts in narratives and descriptions. Stephen Frosh has raised this concern from a discursive and psychoanalytic perspective, and he criticizes the narrativist tendency among qualitative researchers to present human experience in ways that set up coherent themes that constitute integrated wholes ( Frosh, 2007 ). Often, it is the case that the stories people tell are ambiguous and full of gaps, especially for people “on the margins of hegemonic discourses” (p. 637). Like Butler, Frosh finds that the human subject is never a whole, “is always riven with partial drives, social discourses that frame available modes of experience, ways of being that are contradictory and reflect the shifting allegiances of power as they play across the body and the mind” (p. 638). If this is so, it is important to be open to multiple interpretations of what is said and done in an interview. Fortunately, some qualitative approaches do have an eye to this and have designed ways to comprehend complexity; for example, the so-called listening guide developed by Carol Gilligan and co-workers and designed to listen for multiple voices in interviewee accounts (for a recent version of this approach, see Sorsoli & Tolman, 2008 ).

To sum up, the “meanings” that qualitative interviewers are commonly looking for are often multiple, perspectival, and contradictory and thus demand careful interpretation. And there is much controversy in the qualitative communities concerning whether meanings are essentially “there” to be articulated by the interviewee and interpreted by the interviewer (emphasized in particular by phenomenological approaches) or whether meanings are constructed locally (i.e., arise dialogically in a process that centrally involves the interviewer as co-constructor, as stressed by discursive and constructionist approaches). Regardless of one’s epistemological standpoint, it remains important for interviewers to make clear, when they design, conduct, and communicate their research, how they approach this thorny issue because this will make it much easier for readers of interview reports to understand and assess what is communicated.

I have now introduced a working definition of the relatively unstructured and semistructured qualitative research interview and emphasized four vital aspects: such interviews are structured by the interviewer’s purpose of obtaining knowledge; they revolve around descriptions provided by the interviewee; such descriptions are commonly about life world phenomena as experienced; and understanding the meaning of the descriptions involves some kind of interpretation . Although these aspects capture what is essential to a large number of qualitative interview studies now and in the past (and likely many in the future as well), it is important to stress that all these aspects can be and have been challenged in the methodological literature.

In relation to qualitative interviewing, as in qualitative research in general, there is never one correct way to understand or practice a method or a technique because everything depends on concrete circumstances and on the researcher’s intentions when conducting a particular research project. This does not mean that “anything goes” and that nothing is never better than something else, but it does mean that what is “better” is always relative to what one is interested in doing or knowing. The answer to the question “What’s the proper definition of and approach to qualitative interviewing?” must thus be: “It depends on what you wish to achieve by interviewing people for research purposes!” Unfortunately, too many interview researchers simply take one or another approach to interviewing for granted as the only correct one and forget to reflect on the advantages and disadvantages of their favored approach (sometimes they are not even aware that other approaches exist). These researchers thus proceed without properly theorizing their means of knowledge production.

Individual and Group Interviews

It is not only the interviewer’s agenda and research interests that structure the interaction in an interview. Unsurprisingly, the number of participants also plays an important role. As the history of interviewing testifies, the standard format of qualitative interviewing is with one person interviewing another person. This format was illustrated in the example in Box 14.1 , and although this chapter is not about group interviews, I briefly mention these to illustrate how they differ from conventional forms of qualitative interviewing.

Group Interviews

There is an increasing use of group interviews. These have been in use since the 1920s but became standard practice only after the 1950s, when market researchers in particular developed what they termed “focus group interviews” to study consumer preferences. Today, focus groups dominate consumer research and are also often used in health, education, and evaluation research; they are in fact becoming increasingly common across many disciplines in the social sciences.

In focus groups, the interviewer is conceived as a “moderator” who focuses the group discussion on specific themes of interest, and she or he will often use the group dynamic instrumentally to include a number of different perspectives on the give themes ( Morgan, 2002 ). Often, group interviews are more dynamic and flexible in comparison with individual interviews, and they may be closer to everyday discussions. They can be used, for example, when the researcher is not so much interested in people’s descriptions of their experiences as in how participants discuss, argue, and justify their opinions and attitudes.

The standard size for a focus group is between six to ten participants, led by a moderator ( Chrzanowska, 2002 ). Recently, qualitative researchers have also experimented with groups of only two participants (sometimes referred to as “the two-person interview,” although there are literally three people if one counts the interviewer), mainly because it makes the research process easier to handle than with larger groups, where people will often not show up. The moderator introduces the topics for discussion and facilitates the interchange. The point is not to reach consensus about the issues discussed but to have different viewpoints articulated about an issue. Focus group interviews are well suited for exploratory studies in little-known domains or about newly emerging social phenomena because the dynamic social interaction that results may provide more spontaneous expressions than occur in individual interviews.

Individual Interviews

Individual interviews with one interviewer and one interviewee may sometimes be less lively than group interviews, but they have a couple of other advantages: First, it is often easier for the interviewer in one-on-one interviews to lead the conversation in a direction that is useful in relation to the interviewer’s research interests. Second, when studying aspects of people’s lives that are personal, sensitive, or even taboo, it is preferable to use individual interviews that allow for more confidentiality and often make it easier for the interviewer to create an atmosphere of trust and discretion. It is very doubtful, to take a rather extreme example, that Kinsey and his colleagues could have achieved the honest descriptions of sexual behaviors from their respondents had they conducted group rather than individual interviews. And there are obviously also certain themes that simply demand one person telling a story without being interrupted or gainsaid by other participants, such as in biographical research.

Although late-modern Western culture now looks on the individual, face-to-face interview as a completely common and natural occurrence, we should be very careful not to naturalize this particular form of human relationship, as I emphasized earlier. Briggs (2007) has argued that this form of relationship implies a certain “field of communicability,” referring to a socially situated construction of communicative processes (p. 556). This construction is an artefact of cultural-historical practices and is placed within organized social fields that produce different roles, positions, relations, and forms of agency that are frequently taken for granted. There are thus certain rights, duties, and a repertoire of acts that open up when entering the field of communicability of qualitative interviewing—and others that close down. Much about this field of communicability may seem trivial—that the interviewer asks questions and the interviewee answers, that the interviewee conveys personal information that he or she would not normally tell a stranger, that the interviewee is positioned as the expert on that person’s own life, and so on—but the role of this field in the process of knowledge production is very rarely addressed by interview researchers. We too seldom stop and consider the “magic” of interviewing—that a stranger is willing to tell an interviewer so many things about her life simply because the interviewer presents herself as a researcher. Rather than naturalize this practice, we should defamiliarize ourselves with it—like ethnographers visiting a strange “interview culture”—in order to understand and appreciate its role in scientific knowledge production.

Interviewing Using Different Media

Following from Briggs’s analysis of the communicability of interviewing, it is noteworthy that the otherwise standardized format of “face-to-face interaction” was named as late as the early twentieth century by the sociologist Charles Horton Cooley but was since constructed as “primordial, authentic, quintessentially human, and necessary” ( Briggs, 2007 , p. 553). It is sometimes forgotten that the face-to-face interview, as a kind of interaction mediated by this particular social arrangement, also has a history. Other well-known media employed in qualitative interviewing include the telephone and the internet, and here we briefly look at differences among face-to-face, telephone, and internet interviews.

Face-to-Face Interviews

In face-to-face interviews, people are present not only as conversing minds, but as flesh-and-blood creatures who may laugh, cry, smile, tremble, and otherwise give away much information in terms of gestures, body language, and facial expressions. Interviewers thus have the richest source of knowledge available here, but the challenge concerns how to use it productively. In most cases, how people look and act is forgotten once the transcript is made, and the researcher carries out her analyses using the stack of transcripts rather than the embodied interaction that took place. This is a problem especially when a research assistant or someone other than the interviewer transcribes the interview because, in that case, it is not possible to note all the nonverbal signs and gestures that occurred. If possible, it is therefore preferable for the interviewer herself to transcribe the conversations, and it is optimal to do so relatively soon after the conversations are over (e.g., within a couple of days) because this guarantees better recollection of the body language, the atmosphere, and other nontranscribable features of the interaction.

Telephone Interviews

According to Shuy (2002) , the telephone interview has “swept the polling and survey industry in recent years and is now the dominant approach” (p. 539). It often follows a very structured format. In a research context, the use of telephone conversations was pioneered by conversation analysts, who were able to identify a number of common conversational mechanisms (related to turn-taking, adjacency pairs such as questions–answers, etc.) from the rather constricted format that is possible over the telephone. The constricted format may in itself have been productive in throwing light on certain core features of human talk.

Shuy emphasizes a number of advantages of telephone interviewing, such as reduced interviewer effects (important in structured polling interviews, for example), better interviewer uniformity, greater standardization of questions, greater cost-efficiency, increased researcher safety ( Shuy, 2002 , p. 540), and—we might add—better opportunities for interviewing people who live far from the interviewer. In qualitative interviewing, however, it is not possible (nor desirable) to avoid these “interviewer effects” because the interviewer herself is the research instrument, so only the latter couple of points are relevant in this context. However, Shuy also highlights some advantages of in-person interviewing versus telephone interviewing, such as more accurate responses due to contextual naturalness, greater likelihood of self-generated answers, more symmetrical distribution of interactive power, greater effectiveness with complex issues, more thoughtful responses, and the fact that such interviews are better in relation to sensitive questions (pp. 541–544). The large majority of interviews characterized as “qualitative” are conducted face-to-face, mainly because of the advantages listed by Shuy.

Internet Interviews

E-mail and chat interviews are varieties of internet interviewing, with e-mail interviewing normally implying an asynchronous interaction in time, with the interviewer writing a question and then waiting for a response, and chat interviews being synchronous or occurring in “real time” ( Mann & Stewart, 2002 ). The latter can approach a conversational format that resembles face-to-face interviews, with its quick turn takings. When doing online ethnographies (e.g., in virtual realities on the internet), chat interviews are important (see Markham, 2005 , on online ethnography). One advantage of e-mail and chat interviews is that they are “self-transcribing” in the sense that the written text itself is the medium through which researcher and respondents express themselves, and the text is thus basically ready for analysis the minute it has been typed ( Kvale & Brinkmann, 2008 , p. 149).

Disadvantages of such interview forms are related to the demanded skills of written communication. Not everyone is sufficiently skilled at writing to be able to express themselves in rich and detailed ways. Most research participants are also more comfortable when talking, rather than writing, about their lives and experiences. However, as the psychiatrist Finn Skårderud has pointed out, there are some exceptions here, and Skårderud emphasizes in particular that internet conversations can be useful when communicating with people who have problematic relationships to their bodies (e.g., eating disorders). For such people, the physical presence of a problematic body can represent an unwanted disturbance ( Skårderud, 2003 ).

In concluding on the different media of interviewing, it should be emphasized that all interviews are mediated, even if only by the spoken words and the historical arrangement of questioning through face-to-face interaction, and there is no universally correct medium that will always guarantee success. Interviewers should choose their medium according to their knowledge interests and should minimally reflect on the effects of communicating through one medium rather than another. That said, most of the themes that qualitative interviewers are interested in lend themselves more easily to face-to-face interviewing because of the trust, confidentiality, and contextual richness that this format enables.

Different Styles of Interviewing

We have now seen how interviews may differ in terms of structure, number of participants, and media. Another crucial factor is the style of interviewing; that is, the way the interviewer acts and positions herself in the conversation. In relation to this, Wengraf (2001) has introduced a general distinction between “receptive” interviewer styles and assertive styles (or strategies, as he calls them), with the former being close to Carl Rogers’s model of psychotherapy and the latter being more in line with active and Socratic approaches to interviewing (both of which were addressed earlier). Here, I describe these in greater detail as two ends on a continuum.

Receptive Interviewing

According to Wengraf, a receptive style empowers informants and enables them to have “a large measure of control in the way in which they answer the relatively few and relatively open questions they are asked” ( Wengraf, 2001 , p. 155). Much of what was said earlier on the historical contributions of Elton Mayo and Carl Rogers and on semistructured life world interviewing addressed the receptive style in a broad sense; this is often thought of as self-evidently correct, so that no alternatives are considered. Therefore, I devote more space to articulate the somewhat more unusual assertive style, which is attracting more and more attention today.

Assertive Interviewing

Wengraf states that an assertive style may come close to a legal interrogation and enables the interviewer “to control the responses, provoke and illuminate self-contradiction, absences, provoke self-reflexivity and development” (2001, p. 155), perhaps approaching transformative conceptions of interviewing to use Roulston’s terminology mentioned earlier.

A well-known and more positive exposition of the assertive style was developed by Holstein and Gubrium in their book on The Active Interview ( Holstein & Gubrium, 1995 ). They argued that, in reality, there is not much of a choice because interviews are unavoidably interpretively active, meaning-making practices, and this would apply even when interviewers attempt a more receptive style. In this case, however, their role in meaning-making would simply be more elusive and more difficult to take into account when analyzing interview talk. A consequence of this line of argument is that it is preferable for interviewers to take their inevitable role as co-constructors of meaning into account rather than trying to downplay it.

Discourse analysts such as Potter and Wetherell (1987) have also developed an active, assertive practice of interviewing. In a classic text, they describe the constructive role of the interview researcher and summarize discourse analytic interviewing as follows:

First, variation in response is as important as consistency. Second, techniques, which allow diversity rather than those which eliminate it are emphasized, resulting in more informal conversational exchanges and third, interviewers are seen as active participants rather than like speaking questionnaires. ( Potter & Wetherell, 1987 , p. 165)

Variation, diversity, informality, and an active interviewer are key, and the interview process, for Potter and Wetherell, is meant to lead to articulations of the “interpretative repertoires” of the interviewees, but without the interviewer investigating the legitimacy of these repertoires in the interview situation or the respondent’s ways of justifying them. This is in contrast to Socratic and other confronting variants of active interviews, which are designed not just to map participants’ understandings and beliefs, but also to study how participants justify their understandings and beliefs.

To illustrate concretely what a confrontative assertive style looks like, we turn to a simple and very short example from Plato’s The Republic , with Socrates as interviewer (discussed in Brinkmann, 2007 a ). The passage very elegantly demonstrates that no moral rules are self-applying or self-interpreting but must always be understood contextually. Socrates is in a conversation with Cephalus, who believes that justice ( dikaiosune )—here “doing right”—can be stated in universal rules, such as “tell the truth” and “return borrowed items”:

“That’s fair enough, Cephalus,” I [Socrates] said. “But are we really to say that doing right consists simply and solely in truthfulness and returning anything we have borrowed? Are those not actions that can be sometimes right and sometimes wrong? For instance, if one borrowed a weapon from a friend who subsequently went out of his mind and then asked for it back, surely it would be generally agreed that one ought not to return it, and that it would not be right to do so, not to consent to tell the strict truth to a madman?” “That is true,” he [Cephalus] replied. “Well then,” I [Socrates] said, “telling the truth and returning what we have borrowed is not the definition of doing right.” ( Plato, 1987 , pp. 65–66)

Here, the conversation is interrupted by Polemarchus who disagrees with Socrates’ preliminary conclusion, and Cephalus quickly leaves to go to a sacrifice. Then Polemarchus takes Cephalus’s position as Socrates’ discussion partner and the conversation continues as if no substitution had happened.

The passage is instructive because it shows us what qualitative interviewing normally is not . Socrates violates almost every standard principle of qualitative research interviewing, and we can see that the conversation is a great contrast to my own interview excerpt in Box 14.1 . Socrates talks much more than his respondent, he has not asked Cephalus to “describe a situation in which he has experienced justice” or “tell a story about doing right from his own experience” or a similar concretely descriptive question probing for “lived experience.” Instead, they are talking about the definition of an important general concept. Socrates contradicts and challenges his respondent’s view. There is no debriefing or attempt to make sure that the interaction was a pleasant experience for Cephalus, the interview is conducted in public rather than private, and the topic is not private experiences or biographical details, but justice, a theme of common human interest, at least of interest to all citizens of Athens.

Sometimes, the conversation partners in the Platonic dialogues settle on a shared definition, but more often the dialogue ends without any final, unarguable definition of the central concept (e.g., justice, virtue, love). This lack of resolution— aporia in Greek—can be interpreted as illustrating the open-ended character of our conversational reality, including the open-ended character of the discursively produced knowledge of human social and historical life. If humankind is a kind of enacted conversation, to return to my opening remarks in this chapter, the goal of social science is perhaps not to arrive at “fixed knowledge” once and for all, but to help human beings improve the quality of their conversational reality, to help them know their own society and social practices, and debate the goals and values that are important in their lives ( Flyvbjerg, 2001 ).

Interviews can be intentionally assertive, active, and confronting (good examples are found in Bellah, Madsen, Sullivan, Swidler, & Tipton, 1985 , who explicitly acknowledge a debt to Socrates), but the assertive approach can also be employed post hoc as a more analytic perspective. Consider, for example, the excerpt in Box 14.2 from a study by Shweder and Much (1987) , discussed in detail by Valsiner (2007 , pp. 385–386). The interview is set in India and was part of a research project studying moral reasoning in a cross-cultural research design. Earlier in the interview, Babaji (the interviewee) has been presented with a variant of the famous Heinz dilemma (here called the Ashok dilemma), invented by moral developmental psychologist Lawrence Kohlberg to assess people’s moral capabilities ( Kohlberg, 1981 ): a man (Heinz/Ashok) has a wife who is ill and will die if he does not steal some medicine from a pharmacist (who refuses to sell the medicine at a price that the man can afford). According to Babaji’s Hinduism, stealing is not permitted, and the interview unfolds from there (see Box 14.2 ).

According to Valsiner (2007) , we see in the interview how the interviewer (Richard Shweder), in a very active or assertive way, does everything he can to persuade Babaji to accept the Western framing of the dilemma and see the tension between stealing for a moral reason and stealing as an immoral act. But Babaji fails to, or refuses to, see the situation as a dilemma and first attempts to articulate other possibilities in addition to stealing/not stealing (viz. give shamanistic instructions) before finally suggesting that Ashok sells himself in order to raise the money. As such, the interview flow is best understood as an active and confrontational encounter between two quite different worldviews that are revealed exactly because the interviewer acts in a confronting, although not disrespectful, way. 3

Furthermore, the excerpt illustrates how cross-cultural interviewing can be quite difficult—but also extremely interesting—not least when conducted in “noninterview societies” ( Ryen, 2002 , p. 337); that is, in societies where interviewing is not common or recognized as a knowledge-producing instrument. All qualitative interviewing is a collaborative accomplishment, but this becomes exceedingly visible when collaborating cross-culturally.

Analytic Approaches to Interviewing

Before closing this chapter, I give a very brief introduction to different perspectives on how to analyze interviews. Obviously, I cannot here cover the immense variety of phenomenological, discursive, conversation analytic, feminist, poststructuralist, psychoanalytic perspectives, so instead I present a simplified dichotomy that should really be thought of as a continuum. The dichotomy has already played an implicit role earlier because it implies a distinction between interview talk as primarily descriptive (phenomenological) reports (concentrating on the “what” of communication) and interview talk as primarily (discursive) accounts (chiefly concerned with the “how” of talk). Phenomenological approaches to interviewing in a broad sense (exemplified in my exposition of semistructured life world interviewing) try to get as close as possible to precise descriptions of what people have experienced, whereas other analytical approaches (found, e.g., in certain schools of discourse analysis and conversation analysis) focus on how people express themselves and give accounts occasioned by the situation in which they find themselves. The two approaches are contrasted in Table 14.1 , with “what” approaches on the left-hand side and “how” approaches on the right-hand side.

Interviewer: Why doesn’t Hindu dharma permit stealing? Babaji: If he steals, it is a sin—so what virtue is there in saving a life. Hindu dharma keeps man from sinning. Interviewer: Why would it be a sin? Isn’t there a saying “On must jump into fire for others”? Babaji: That is there in our dharma—sacrifice, but not stealing. Interviewer: But if he doesn’t provide the medicine for his wife, she will die. Wouldn’t it be a sin to let her die? Babaji: That’s why, according to the capacities and powers which God has given him, he should try to give her shamanistic instructions and advice. Then she can be cured. Interviewer: But, that particular medicine is the only way out. Babaji: There is no reason to necessarily think that that particular drug will save her life. Interviewer: Let’s suppose she can only be saved by that drug, or else she will die. Won’t he face lots of difficulties if his wife dies? Babaji: No. Interviewer: But his family will break up. Babaji: He can marry other women. Interviewer: But he has no money. How can he remarry? Babaji: Do you think he should steal? If he steals, he will be sent to jail. Then what’s the use of saving her life to keep the family together. She has enjoyed the days destined for her. But stealing is bad. Our sacred scriptures tell that sometimes stealing is an act of dharma. If by stealing for you I can save your life, then it is an act of dharma. But one cannot steal for his wife or his offspring or for himself. If he does that, it is simply stealing. Interviewer: If I steal for myself, then it’s a sin? Babaji: Yes. Interviewer: But in this case I am stealing for my wife, not for me. Babaji: But your wife is yours. Interviewer: Doesn’t Ashok have a duty or obligation to steal the drug? Babaji: He may not get the medicine by stealing. He may sell himself. He may sell himself to someone for say 500 rupees for six months or one year. ( Shweder & Much, 1987 , p. 236)

My inspiration for slicing the cake of qualitative interviewing in this manner comes from Talmy (2010) and Rapley (2001) , who builds on a distinction from Clive Seale between interview-data-as-resource and interview-data-as-topic.

Interviews as Research Instrument

Researchers working from the former perspective (corresponding to the left-hand side of Table 14.1 ) believe that interview data can reflect the interviewees’ reality outside the interview and consequently seek to minimize the interviewer’s effects on coloring interviewees’ reports of their everyday reality. The interview becomes a research instrument in the hands of interviewers, who are supposed to act receptively and interfere as little as possible with the interviewee reporting. The validity of the interviewees’ reports becomes a prime issue when one approaches interviewing as a research instrument. And because interviews normally concern things experienced in the past, this significantly involves considerations about human memory and about how to enhance the trustworthiness of human recollections.

In one of the few publications to discuss the role of memory in interviewing, Thomsen and Brinkmann (2009) recommend that interviewers take the following points into account if they want to help interviewees’ improve the reporting and description of specific memories:

Allow time for recall and assure the interviewee that this is normal.

Provide concrete cues; for example, “the last time you were talking to a physician/nurse” rather than “a communication experience.”

Use typical content categories of specific memories to derive cues (i.e., ongoing activity, location, persons, other people’s affect and own affect).

Ask for recent specific memories.

Use relevant extended time line and landmark events as contextual cues; such as “when you were working at x” to aid the recall of older memories.

Ask the interviewee for a free and detailed narrative of the specific memory (adapted from Thomsen & Brinkmann, 2009 ).

Following such guidelines results in interviewee descriptions that are valid (they are about what the researcher intends them to be about) and close to the “lived experience” of something, or what was earlier referred to as “life world phenomena.” Although phenomenology is one typical paradigm to frame interviews analytically as research instruments, many other paradigms do so as well, for example grounded theory, developed by Glaser and Strauss (1967) with the intent of developing theoretical understandings of phenomena grounded in empirical materials through meticulous coding of data.

A typical goal of qualitative analysis within a broad phenomenological perspective is to arrive at an understanding of the essential structures of conscious experience. Analysts can here apply an inductive form of analysis known as meaning condensation ( Kvale & Brinkmann, 2008 , p. 205). This refers to an abridgement of the meanings articulated by the interviewees into briefer formulations. Longer utterances are condensed into shorter statements in which the main sense of what is said is rephrased in a few words. This technique rests on the idea in phenomenology that there is a certain essential structure to the way we experience things in the life world, and this constitutes an experience as an experience of a given something (shame, anxiety, love, learning something new, etc.).

A specific approach to phenomenological analysis has been developed in a psychological context by Amedeo Giorgi (e.g., Giorgi & Giorgi, 2003 ). Giorgi breaks the analytic process down into four steps: (1) obtain a concrete description of a phenomenon (through an interview) as lived through by someone; read the description carefully and become familiar with it to get a sense of the whole, (2) establish meaning units in the description, (3) transform each meaning unit into expressions that communicate the psychological sense of the data, and (4) based on the transformed meaning units, articulate the general structure of the experience of the phenomenon (p. 170).

A large number of books exist on how to do a concrete analysis (e.g., Silverman, 2001 ), so I will refer the reader to these and also to relevant chapters of this handbook.

Interviewing as a Social Practice

In contrast to those approaches that see interviewing as a research instrument designed to capture the “what” of what is reported as accurately as possible, others working from more constructionist, localist, and situated perspectives have much greater analytic focus on the “how” of interviewing. They view interviewing as a social practice, as a site for a specific kind of situated interaction, which means that interview data primarily reflect “a reality constructed by the interviewee and interviewer” ( Rapley, 2001 , p. 304). The idea of obtaining valid reports that accurately reflect a reality outside the conversational situation is thus questioned, and the main challenge becomes instead how to explain the relevance of interview talk. That is, if what is said in an interview is a product of this social practice itself, why is it relevant to conduct interviewing? Postmodern interviews, emphasizing performative and transformative aspects of interviewing, attempt to meet this challenge by arguing that if interviews do not concern a reality outside themselves, they can instead be used to perform or facilitate social change.

People subscribing to the right-hand side of Table 14.1 believe that interview talk should be conceived of as accounts. Unlike reports, which refer to experiences from the interviewee’s past that can be articulated when prompted, accounts are answers that are “normatively oriented to and designed for the questions that occasion them” ( Talmy, 2010 , p. 136). If interviewee talk is best understood as accounts, it must be seen as a kind of social action that has effects and does something in the situation of which it is a part. This perspective on interviewing is shared by some discourse and conversation analysts who limit themselves to analyzing interview talk as situated interaction.

Readers may wonder if these approaches are mutually exclusive. My own pragmatic answer is that they are not, but that none of the approaches should be brought to an extreme: it is true that huge problems are associated with viewing the interview as a site for pure, “unpolluted” reports of the past (we know too much about the constructive role of human memory and of how the social practice of interviewing mediates what is said to take this seriously). But it is also true that there are problems associated with denying that we can use our communicative powers to refer more or less accurately to past experiences. Those who follow the right-hand side of Table 14.1 to the extreme and deny that data can be resources for understanding experiences of the past still believe that their own communicative practice, materialized in their texts, are about matters outside this specific text. So, taken to extremes, both approaches become absurd, and I believe that it is now time for the two (sometimes opposed) camps to learn from one another and realize that they need not exclude one another. In my view, some of the most interesting interview studies are those in which analyses of the “what” and the “how” fertilize each other in productive ways. I end this chapter with a brief illustration of this, taken (rather shamelessly!) from a paper co-authored by myself ( Musaeus & Brinkmann, 2011 ) that shows how an analytic look at interviews can employ perspectives from both sides at the same time. The two forms thus need not exclude each other, and some interviews can favorably be analyzed using a combination of the two broad analytic approaches.

First a little contextualization to render the example meaningful: my colleague, Peter Musaeus, conducted in their home a relatively unstructured group qualitative interview with four members of a family that was receiving family therapy. We were interested in understanding the effects of the therapeutic process on the everyday life of the family. In the excerpt in Box 14.3 , we meet Maren and Søren, a married couple, and Maren’s daughter Kirstina, who was thirteen years old at the time (and we also see the interviewer’s voice). 4 In the following extract, Maren (the mother) has just made a joke about the movie The Planet of the Apes (a science-fiction movie telling the story of how apes are in control of the earth and keep humans as pets or slaves), and they have talked about the scene where the apes jokingly remark that females are cute, just as long as you get rid of them before puberty.

Toward the end of this sequence Søren, the father of the family, denies—as he does throughout the interview—that Maren is hitting her daughter, and he uses what the family calls a “stop sign” (line 17), which they were taught to employ in their therapy sessions. The verbal sign “STOP” (said in a loud voice) is supposed to bring the conflict cycle to a halt before it accelerates. In the interview, however, the stop sign (like other similar signs from therapy that have been appropriated by the family members) sometimes function counter-productively to raise the conflict level because it is almost shouted by family members. The sudden question in line 20 is actually much more effective in defusing the conflict by diverting the participants’ attention from the problem.

I have here just provided a glimpse of our analysis, which tries to bring forth the role of semiotic mediation—the use of signs (like the stop sign and other therapeutic tools)—in regulating social interaction in a troubled family. The point is, however, that the interview both contains family members’ descriptions of their problems and challenges, thus giving us their reports of what they experience; but we also see the persons’ shared past being formative of the present in the interview situation itself, resulting in quite significant accounts occasioned by the social episode itself. In short, the two analytic perspectives on interviewing (both as a resource providing reports and also as a topic in its own right, i.e., a social practice providing accounts) are mutually reinforcing in this case and have given us what we (as authors of the paper) believe is a valid analysis. Rather than just hearing people describing their problems, the interviewer is in fact witnessing the family members’ problems as they play out in their interaction, in front of him so to speak, thus offering him a chance to validate his analysis. The “what” and the “how” here intersect very closely.

Maren: And the comment that followed was: “Get rid of it before... ha, ha = “

Interviewer: Before it becomes a teenager?

Maren: Because it simply is so hard.

Interviewer: Yes, right, but it =

Kirstina: Should you also simply get rid of me?

Interviewer: Ha, ha.

Maren: No, are you crazy, I love you more than anything. But it’s really hard

for all of us sometimes, I think.

Kirstina: Are you also in puberty when you hit me?

Maren: No, I am in the menopause, that is different.

Søren: You don’t hit, do you? You say “when you hit”? Your mother doesn’t

Kirstina: She has hit me today and yesterday.

Maren: I probably did hit her but well =

Kirstina: Yes, but still, you may say that it isn’t hitting, when you miss.

Søren: STOP Kirstina, it isn’t true. Your mother hasn’t hit you and you don’t

Kirstina: No, no let’s just say that.

Maren: Does anyone want a cream roll?

In this chapter, I have given a broad introduction to qualitative interviewing. I have tried to demonstrate that the human world is a conversational reality in which interviewing takes a privileged position as a research method, at least in relation to a number of significant research questions that human and social scientists want to ask. Qualitative interviewing can be both a useful and valid approach, resulting in analyses with a certain objectivity in the sense that I introduced earlier. Throughout the chapter, I have kept a focus on interviewing as a social practice that has a cultural history, and I have warned against unreflective naturalization of this kind of human interaction (i.e., viewing it as a particularly natural and unproblematic way of staging human relationships).

Furthermore, I introduced a number of distinctions that are relevant when mapping the field of qualitative interviewing (e.g., between different levels of structure, numbers of participants, media of interviewing, and also interviewer styles). I also provided a detailed presentation of semistructured life world interviewing as the standard form of qualitative interviewing today.

I finally gave particular attention to two broad analytic approaches to interviewing: on the one side, experience-focused interviewing that seek to elicit accurate reports of what interviewees have experienced (in broad terms, the phenomenological positions), and, on the other side, language- and interaction-focused interviewing (discourse-oriented positions) that focus on the nature of interview interaction in its own right. In my eyes, none of these is superior per se, but each enables researchers to pose different kinds of questions to their materials. Too often, however, interviewers forget to make clear what kinds of questions they are interested in and also forget to consider whether their practice of interviewing and their analytic focus enable them to answer their research questions satisfactorily.

Future Directions

In the future, the field of qualitative interviewing is likely to continue its expansion. It is now among the most popular research tools in the human and social sciences, and nothing indicates that this trend will stop. However, a number of issues confront qualitative interviewing as particularly pressing in my opinion:

Using conversations for research purposes is close to an everyday practice of oral communication. We talk to people to get to know them, which—in a trivial sense—is also the goal of qualitative research. Will the focus on interviewing as a “method” (that can be articulated and perhaps spelled out procedurally) be counterproductive when the goal is human communication and getting to know people? Are we witnessing a fetishization of methods in qualitative research that is blocking the road to knowledge? And are there other ways of thinking about interviews and other “qualitative methods” than in the idiom of “methods”?

Qualitative interviewers can now find publication channels for their work, but has the practice of interviewing become so unproblematic that people are forgetting to justify and theorize their means of knowledge production in concrete contexts? In my view, more work should be done to theorize interviewing as a social practice (the “how”), as essential to what goes on in interview interactions.

When reporting qualitative analyses, researchers too often decontextualize interviewee statements and utterances. What person A has said is juxtaposed with the statements of person B, without any contextual clues. If an interview is a form of situated interaction, then readers of interview reports need to be provided with temporal and situational context in order to be able to interpret the talk (What question was this statement an answer to? What happened before and what came after?).

Some qualitative researchers remain convinced that they are “on the good side” in relation to ethical questions. They “give voice” to individuals, listen to their “subjective accounts,” and are thus against the quantitative and “objectifying” approaches of other, more traditional researchers. However, qualitative interviewers should, in my view, be aware that very delicate ethical questions are an inherent part of interviewing. They should avoid the “qualitatative ethicism” that sometimes characterizes qualitative inquiry, viz. that “we are good because we are qualitative.” Especially in an “interview society,” there is a need to think about the ethical problems of interviewing others (often about intimate and personal matters), when people are often seduced by the warmth and interest of interviewers to say “too much.”

The first journalistic interviews appeared in the middle of the nineteenth century ( Silvester, 1993 ), and social science interviews emerged in the course of the twentieth century (see the history of interviewing recounted later in this chapter).

Obviously, these traditions are not identical, nor are their main concepts, but I believe that they here converge on the idea of a concretely lived and experienced social reality prior to scientific abstractions of it, which Husserl originally referred to as the life world and which remains central to most (if not all) paradigms in qualitative research.

Confronting interviews are sometimes misunderstood to imply a certain aggressive or disrespectful attitude, which, of course, is a misunderstanding. An interviewer can be actively and confrontingly curious and inquiring in a very respectful way, especially if she positions herself as not-knowing (ad modum Socrates in some of the dialogues) in order to avoid framing the interview as an oral examination.

Kirstina has an older sister, who no longer lives at home, and Søren is not the biological father of the girls. He has two children from a previous marriage. One of them has attempted suicide, which, however, is not the reason for the family’s referral to therapy. The reason, instead, is Maren’s violent behavior toward her daughter Kirstina.

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Development of Qualitative Semi-Structured Interview Guide for Case Study Research

• Nuzhat Naz, Fozia Gulab, Mahnaz Aslam

Interviewing is an effective strategy to acquire data for qualitative research that uses case studies as a research methodology.  It helps to explain, understand, and explore research subjects' opinions, behavior, and experiences to narrow down the area of research that researcher is interested to discover while listening to them being involved through dialogue. Therefore, structured or semi-structured interviews become effective tools of knowing the experiences and perceptions of research subjects relating to central themes of area of investigation. The aim of this research is to share with researchers the systematic process to be followed in developing semi-structured interview guides. Literature review suggests five distinct phases that the researcher needs to be mindful of when developing a qualitative semi-structured interview guide; they must identify if the prerequisites for conducting a semi-structured interview are met, utilize previously acquired knowledge, formulate a preliminary guide, pilot test it, and then present the completed semi-structured interview guide. Salient features of each phase are explained through literary support followed by researcher’s experience of working on each phase to proceed in developing the interview guide.  A well-developed semi- structured interview guide becomes an authentic and valid source of data collection whereas weakly developed semi-structured interview guide distorts the findings of research resulting in unreliable, inaccurate and invalid data collected.

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Semi-structured Interviews

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• Matthew Berler 4  
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• First Online: 13 July 2018

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Open-ended interview ; Qualitative interview ; Systematic exploratory interview ; Thematic interview

The semi-structured interview is an exploratory interview used most often in the social sciences for qualitative research purposes or to gather clinical data. While it generally follows a guide or protocol that is devised prior to the interview and is focused on a core topic to provide a general structure, the semi-structured interview also allows for discovery, with space to follow topical trajectories as the conversation unfolds.

Introduction

Qualitative interviews exist on a continuum, ranging from free-ranging, exploratory discussions to highly structured interviews. On one end is unstructured interviewing, deployed by approaches such as ethnography, grounded theory, and phenomenology. This style of interview involves a changing protocol that evolves based on participants’ responses and will differ from one participant to the next. On the other end of the continuum...

• Semi-structured Interview Process
• Interview Guides
• Rapport Building
• Funnel Strategy
• Interpretative Qualitative Approaches

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Magaldi, D., Berler, M. (2018). Semi-structured Interviews. In: Zeigler-Hill, V., Shackelford, T. (eds) Encyclopedia of Personality and Individual Differences. Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_857-1

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• Published: 05 April 2024

Healthcare staff’s perspectives on long-acting injectable buprenorphine treatment: a qualitative interview study

• Johan Nordgren   ORCID: orcid.org/0000-0002-6975-6645 1 ,
• Bodil Monwell 2 , 5 ,
• Björn Johnson 3 ,
• Nina Veetnisha Gunnarsson 2 &
• Andrea Johansson Capusan 4  

Addiction Science & Clinical Practice volume  19 , Article number:  25 ( 2024 ) Cite this article

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Long-acting injectable buprenorphine (LAIB) formulations are a novel treatment approach in opioid agonist treatment (OAT), which provide patients with a steady dose administered weekly or monthly and thus reduce the need for frequent clinic visits. Several studies have analyzed patient experiences of LAIB but the perspective of OAT staff is unknown. This study aimed to explore how healthcare staff working in OAT clinics in Sweden perceive and manage treatment with LAIB.

Individual qualitative interviews were conducted with OAT physicians (n = 10) in tandem with nine focus group sessions with OAT nurses and other staff categories (n = 41). The data was analyzed with thematic text analysis.

Five central themes were identified in the data: (1) advantages and disadvantages of LAIB, (2) patient categories that may or may not need LAIB, (3) patients’ degrees of medication choice, (4) keeping tabs, control and treatment alliance, and (5) LAIB’s impact on risk and enabling environments in OAT. Overall staff found more advantages than disadvantages with LAIB and considered that patients with ongoing substance use and low adherence were most likely to benefit from LAIB. However, less frequent visits were viewed as problematic in terms of developing a treatment alliance and being able to keep tabs on patients’ clinical status. Clinics differed regarding patients' degrees of choice in medication, which varied from limited to extensive. LAIB affected both risk and enabling environments in OAT.

Conclusions

LAIB may strengthen the enabling environment in OAT for some patients by reducing clinic visits, exposure to risk environments, and the pressure to divert medication. A continued discussion about the prerequisites and rationale for LAIB implementation is needed in policy and practice.

Introduction

Long-acting, weekly or monthly, injectable depot buprenorphine (LAIB) formulations in the treatment of opioid use disorder reduce the need for daily supervised dosing, enabling clinicians to provide medication with similar efficacy as with sublingual dosing [ 1 , 2 ]. LAIB results in lower healthcare service attendance and entails practically no risk for diversion [ 2 ]. LAIB thus has the potential to reduce the treatment burden for both patients and clinicians, for example by reducing the time-consuming activity of monitoring sublingual buprenorphine administration [ 3 ]. LAIB has been described as a more convenient and flexible treatment option in which longer treatment intervals allow patients to visit opioid agonist treatment (OAT) clinics less frequently compared to the “traditional” OAT structure [ 4 ]. This flexibility might mean more time available for patients to work, study and distance themselves from drug use subcultures [ 5 ].

When asked about their experiences of LAIB, patients report a sense of freedom, stability and normalcy, based on not having to go through a short-temporal daily dosing cycle [ 3 , 5 , 6 ]. However, the longer interval may disrupt engagement with psychosocial and practical support offered at clinics [ 5 ], which can be felt as a loss of social interaction and daily routine [ 3 ]. The sense of freedom to visit a clinic weekly or monthly instead of daily, tethered with a sense of loss of social connection and informal care offered by the clinic, is a dilemma in LAIB treatment [ 3 , 6 ]. OAT clinics offer a range of medical treatment interventions, psychosocial support, and sociality both between patients and staff and between patients, enabling health and well-being. At the same time, OAT clinics may be understood as risk environments [ 7 ], where patients may face stigmatization and control, or encounter other patients who sell illicit drugs or who act in threatening or violent ways [ 8 ]. Such aspects of a risk environment can jeopardize patients’ desire and opportunity to move towards a more stable treatment phase and life situation.

Studies of LAIB focusing on patients’ experience have shown high patient satisfaction in reducing drug craving, withdrawal symptoms and self-reported reduction in ongoing illicit drug use [ 9 ]. LAIB may break a daily ritual of taking sublingual tablets and significantly decrease the number of clinic visits [ 10 ]. Patients report a preference for monthly LAIB compared to weekly [ 11 ], but some patients may reject LAIB because it can limit their control over dosing [ 5 , 6 ]. Patients report that LAIB enables them to “pass” as people who are not enrolled in OAT, which may reduce the stigma associated with OAT and with being a person with former illicit drug use [ 12 ]. LAIB also precludes the risk of diversion of OAT medications, a risk that is a continuous concern in OAT with methadone and sublingual buprenorphine [ 13 ]. However, some patients might be reluctant to accept LAIB because it removes an opportunity for income generation when selling medication [ 5 ]. In general, LAIB may benefit patients who risk missing daily appointments, those at risk of diverting medication, [ 9 , 10 ], patients living in rural areas [ 14 ], and patients incarcerated in prison [ 15 ].

In Sweden, OAT has long been regarded as controversial, with high thresholds to treatment and various limitations to treatment modalities [ 16 ]. Current national guidelines emphasize access to treatment and to harm reduction measures [ 17 ] while still mandating three months of daily supervised dosing for sublingual/oral OAT medications, which in practice can be longer for patients with low adherence and continued illicit substance use [ 16 ]. To a certain extent, there are still large regional variations both in the professional doxa of OAT clinics, and in access to OAT [ 18 ]. Implementation of LAIB also varies between clinics, since some clinics have been quick to implement LAIB while others have been slower to do so.

Due to the relatively recent introduction of LAIB, research regarding the viewpoint of healthcare staff and how this novel treatment option has been introduced in clinical practice is lacking. Although several studies have investigated patients’ perspectives on LAIB, we have not found any previously published research on professional and staff perspectives in healthcare settings. Staff are responsible for implementing LAIB and adapting OAT to these new formulations. Health care staff experience and perception of LAIB and how they consider and respond to patients’ perceptions and experiences of LAIB, will potentially influence the therapeutic alliance and staff's capacity to create a positive pharmaceutical atmosphere [ 19 ]. This study aims to explore how healthcare staff working in OAT clinics in Sweden perceive and manage treatment with LAIB.

We employed a qualitative research strategy to study how the staff perceived and managed LAIB in their clinical practice. Semi-structured interviews were conducted individually with physicians at the OAT clinics. We also conducted focus group interviews with treatment staff, including nurses, counselors and other clinical caretakers.

Recruitment and participants

We started with a pilot, where we invited staff from two clinics to participate (not included in the final data analysis). Because physicians tended to set the tone in the discussion, and some of the staff were reluctant to express their opinions freely, we decided to conduct semi-structured interviews with the OAT physicians and focus groups with the remaining staff from each clinic separately. All staff members who worked with treatment were invited to participate in the focus group interviews.

Focus group interviews with OAT nurses and clinical caretakers

Focus group sessions with nurses, counselors and clinical caretakers were conducted via Zoom [ 20 ] by the second and fourth authors. In total, 41 persons attended nine different focus groups. The average length of the interview sessions was 52 min, with a range of 47–60 min. The semi-structured focus group discussion guide contained the following main topics: (1) positive and negative aspects of LAIB, (2) impact on social support, (3) factors affecting which medication was prescribed, (4), information received about LAIB, (5), the extent to which staff decide about medication choice, (6) views on support versus control in OAT, and (7) views on medication diversion.

Semi-structured interviews with OAT physicians

Ten physicians were interviewed individually via Zoom. The average length of the interviews was 50 min (range 34–60 min). The semi-structured interview guide contained the following topics: (1) demographic information and professional background, (2) views about OAT, cooperation with other services, clinical routines, clinic “culture” and control versus support, (3) introduction and implementation of LAIB, (4) administration of LAIB (positive and negative experiences, comparison to other medications, dosage period aspects, social support), (5) patients’ and staff’s views of LAIB, and 6) views on future developments in OAT.

Data analysis

The interview transcripts were read and inductively coded in NVivo by the first author. The coding process followed principles of thematic text analysis [ 21 , 22 ]. The sorting of the transcribed material involved an initial open coding in which each phenomenon contained in the data was assigned a code that clarified its meaning [ 22 ]. In this way, a text can be broken down, processed, conceptualized and split into categories, with the aim of discovering categories that capture the fullness of the experiences and actions that are studied [ 21 ]. This initial coding process resulted in 52 categories relating to understandings and practices regarding LAIB among OAT clinic staff, such as: “Reduced insight about the patients by staff” and “A sense of security for staff”.

The categories were subsequently discussed by all authors to reach consensus about which to include in the thematic analysis. Authors two and three conducted an additional full coding of the data as a validation to the initial coding. After consensus on relevant categories was achieved, the first author conducted an additional analysis of the categories with the aim of identifying themes and subthemes. The criterium for theme inclusion was that it should capture a prominent aspect of the data in a patterned way, in alignment with the research questions [ 21 ]. The themes were then discussed by all authors and a final decision on inclusion of themes was taken. In the final analytical step, quotations that exemplified and illuminated each theme and subtheme were selected. The quotations were then translated from Swedish to English by the first author (Additional file 1 ).

The participants, namely physicians (n = 10), and treatment staff (nurses, counselors, and other clinical caretakers) (n = 41), were recruited from 10 OAT clinics in Sweden. Clinics were situated in various parts of Sweden, including both large cities, and rural and small-town areas. Distribution between the sexes was eight men and two women among the physicians, while nurses and clinical caretakers were mainly female (34 women and 7 men). The participants had worked with OAT for an average of 7.0 years; physicians for 6.9 years (range 1–17 years), nurses and clinical caretakers for 7.3 years (range 1–22 years).

In the following we present the five themes identified in the data. We first present advantages and disadvantages of LAIB as assessed by the staff. We then turn to how staff discussed different patient categories that may or may not need LAIB. Next, we report on degrees of choice in medication and how staff viewed keeping tabs on patients, aspects of control and treatment alliance. Finally, we present how staff viewed LAIB's impact on risk and enabling environments in OAT.

Advantages of long-acting injectable buprenorphine

The staff reported a wide range of advantages with LAIB and viewed LAIB as a valuable treatment option in OAT. The most mentioned advantage was that patients do not have to come to the clinic as often as they used to, which at least in theory open new possibilities of working or studying. Increased stability in terms of having an even buprenorphine dosage compared to the sublingual dispensation was another advantage that several interviewees mentioned. Another advantage expressed by the interviewees was that LAIB enables staff to feel more secure about patients using their medication as intended. One interviewee described this as the patients having a “buprenorphine-protection in them” (Participant 11, nurse) and a physician described it as having an “overdose protection” (Participant 10, physician).

This aspect of “protection” was often coupled with the pharmacology of buprenorphine with high-affinity binding to the mu-opioid receptor, which gives relative protection against overdose with full agonists with lower receptor affinity (such as heroin or methadone). It was also coupled with the issue of diversion and the ability to trust patients with their medications, as exemplified by the following quote from a physician:

/…/ the nice thing about the injection is that you never have to think about if the patient has an ulterior motive. /…/ Otherwise, you always have to keep in mind if the patient wants to sell surplus or if he’s honest about having too small a dose. /…/so you can trust the patient, which you couldn’t before, to be honest (Participant 3, physician).

Reduced diversion was another aspect mentioned, as illustrated by the following quote: “It feels good as a prescriber to know that the medicine ends up where it should. /…/ We simply remove the risk that they [patients] misuse their medicines” (Participant 6, physician). The staff also mentioned advantages related to patients moving away from a mindset of “wheeling and dealing” medicines. Also, by reducing the need for control, LAIB free up time for other work-related tasks among staff.

Disadvantages of long-acting injectable buprenorphine

The main disadvantages described by the interviewees were: a reduced overview of the patients, reduction in social support to patients, physical side effects, and patient experiences that LAIB do not fully treat withdrawal symptoms.

Some staff reported that LAIB had a shorter effect duration than the expected week or month. Patients reported withdrawal symptoms and had to take the next injection earlier than expected. This was most common in the induction phase, but a few interviewees also reported that the problem persisted, as in the following excerpt:

With [LAIB] specifically there was a difficult period in the beginning for the patients because they end up in withdrawal in the initiation phase or risk going into withdrawal. So, a little bit of craftmanship is needed to minimize risks. Very clear information to the patients is also needed so that they know what to expect. We put much effort into doing that. But otherwise I think that, sometimes it may be that even later, after induction, they don’t really last four weeks and then you have to give an injection earlier (Participant 8, physician).

Physical side effects reported by patients to staff included lumps, rashes, pain or aching at the injection site, abscesses, feeling intoxicated, feeling depressed and tired, and swollen arms and legs, in line with previous research on patient experiences [ 6 , 23 ]. In some cases, the experienced side effects were so severe that patients had to switch to another depot formulation, or back to tablets.

Staff reported that patients have rituals surrounding their OAT medication and that some found it hard not being able to adjust their dosage themselves, as indicated in the following exchange from one of the focus groups:

Several, but not all, have said that there’s a kind of ritual with the tablets. They’re used to doing it a certain way every morning. And some split the dose and they all do it differently. […] With the injection [the effects] becomes featureless. And that is what you want with an even concentration. But they are used to things happening. […] (Participant 27, nurse).

Loss of control I would say. That they don’t have the possibility to control their intake themselves. I think many are bothered by that (Participant 28, nurse).

For some patients this aspect was important enough to make them quit LAIB, as indicated in the following quotation:

In our experience those who get a lot of anxiety cannot cope with making this transition: ‘Oh I’m not allowed to take this, I must have my tablet, it’s so psychologically important to me’. They cannot handle this deprogramming. It’s usually those patients that quit LAIB (Participant 8, physician).

Although these disadvantages were discussed in detail by the interviewees, it is worth noting that the overall experience of staff was that the advantages of LAIB outweighed the disadvantages.

Patient categories that may or may not need LAIB

The different clinics made somewhat different assessments about which types of patients LAIB is most suitable for. Although the overall view was that initiation of LAIB must be based on individual assessment of patients, we found a dividing line between the categories of so-called “well-functioning” and “harm reduction” patients. It should be noted however that the issue of prioritization was complex, since some of the clinics faced local, non-medical, economic or administrative restrictions regarding the number of patients to whom they could offer LAIB.

”Harm reduction” patients with complex needs

Patients with complex needs, described by the staff as “harm reduction” patients was a patient category with more severe problems, discussed by staff as engaging in illicit drug use, having difficulties in coming to appointments, and experiencing psychiatric comorbidities.

The majority of the clinics in the sample had decided or had learned over time that LAIB was best suited for this category of patients. The main motive was to help these patients to adequate medication, which also sustained a sense of patient safety among staff. Initially, as one nurse explained, “well-functioning” patients who had progressed well in treatment, were thought to have the most need for LAIB:

Initially, we thought that it was a formulation that we would give to patients who were in a state of rehabilitation, and that they needed it to be able to work and so on. But we discovered that it might save patients who were in a really bad situation (Participant 14, nurse).

A physician said that they mainly used LAIB for patients with low treatment adherence: ”We mostly use it if there are significant problems with adherence and if they don’t come [to the clinic]” (Participant 10, physician). There were a small number of cases in the data when LAIB had been used for patients that were seen as threatening, as in the following example:

Some who had made threats, I think, where they didn’t want them at the clinic that often. It was because they were acting in a threatening manner in meetings and being really disruptive at the clinic. That’s why they gave them weekly or monthly injections to make them come less frequently (Participant 5, physician).

Although this was an infrequent aspect in the data, it is a novel finding that we have not seen reported before.

The staff discussed ambivalence related to the challenges of monitoring the situation of patients with complex needs, when meeting them less frequently:

We have used [LAIB] to a very high degree to be able to help patients who have low adherence. /…/ I think [LAIB] has been a revolution in treatment for these patients, but I also think that there is uncertainty about the situation of the patient when they are away [from the clinic] for a month (Participant 11, nurse).

Overall, the discussion revolved around the dilemma of keeping tabs on “harm reduction” patients with complex needs in terms of medical risks in relation to less frequent clinic visits. One of the physicians avoided introducing LAIB to this patient category:

Our main concern is medical safety. Because if the patient gets sublingual treatment and comes to us daily then we see day-to-day what shape they are in and then we can quickly alert the social services or call an ambulance or send them to detox. But if they are away for a whole week or even worse a whole month and they have no reason to come to us, then we lose the possibility to act swiftly (Participant 7, physician).

“Well-functioning” and stable patients

Patients with high adherence were defined as “well-functioning” or “stable” and were described as working or studying. These patients commonly picked up their medicines at pharmacies and generally visited the OAT clinics seldom. A minority of the clinics prioritized LAIB for patients with high adherence to treatment. One physician talked about patients for whom his clinic would prefer to use LAIB: ”Let’s say that they have a job or the possibility to get a job or to study. Then we would push a bit more for [LAIB] and for the possibility to get that” (Participant 5, physician). This physician elaborated further, saying that “well-functioning” patients were prioritized either by staff or because the patients themselves had requested LAIB:

It has been for relatively well-functioning patients that still have jobs where we have recommended it on some occasions, or if they themselves have asked for it because they have heard about the treatment. Where we can avoid them having to come to the clinic every day for the first three months and instead come once or twice per week. In the beginning [they come] twice per week because we have to give the injections more frequently but also because we want to follow up on how they feel (Participant 5, physician).

Staff often motivated prioritization of LAIB to “well-functioning” patients based on increased possibilities to facilitate work or studying or to encourage patients to seek employment or education.

Another reason for offering LAIB to “well-functioning” patients was to reduce the amount of take-home medicines for patients who seldom visited the clinic or who picked up their medicines at pharmacies. However, infrequent clinic visits were also mentioned as a reason not to offer LAIB to this patient category:

For a pharmacy patient who only comes to the clinic a couple of times each year [LAIB] results in an increased frequency to come here. It might even mean that they feel more bound up [to the clinic] in a negative way (Participant 8, physician).

Overall, we found that some patients with high adherence could be considered for LAIB, based on their need for fewer visits due to other obligations such as work or study. However, there was a breaking point at which depot injections would actually increase the number of visits.

Patients’ degrees of medication choice

The extent to which patients were allowed to freely choose whether to initiate LAIB or not differed between the clinics. The overall view was that patients were allowed to choose in cooperation with staff, but some clinics had forced some patients to initiate LAIB. Also, some clinics operated under economic or administrative restrictions limiting access to LAIB.

Extensive choice

Most clinics had a clear aim to allow as much patient choice as possible and would discuss different options with the patients. In the following excerpt, a physician discusses the extent to which patients were allowed to make a choice regarding medication:

Interviewer: To what extent can the patient influence the choice of medicine?

They can influence it quite a lot. I don’t think it will be a good treatment if you force the patient to take something they don’t want. Exceptions are… They will get Suboxone if they use illicit drugs and when I have a really big suspicion about diversion of doses. Then I use either depot or Suboxone and I’m restrictive with mono buprenorphine. But otherwise, I try to listen to what the patients want (Participant 7, physician).

In Sweden, since 2015 mono buprenorphine has had a low priority as first-choice medication for OAT in the national guidelines. One clinic was in the process of phasing out mono buprenorphine, and in that case, non-pharmacy patients treated with buprenorphine would have to choose between either a buprenorphine-naloxone combination or LAIB.

Limited choice

At one of the clinics, staff were open to the fact that some patients had been forced to initiate LAIB. This was seen as problematic by the interviewees, as exemplified in the excerpt below:

It [LAIB] having been forced on some patients can make them feel rather powerless and as not having the possibility… before everyone had the possibility to take part and guide their own treatment but then there was a rather big shift about that. ‘Now we have [LAIB] and you can no longer decide for yourself but we will decide for you’ (Participant 21, nurse).

This clinic stopped using mono buprenorphine and forced those patients to start LAIB. This was described by one nurse as problematic both in terms of an exercise of power, but also since it increased the staff workload:

All patients had to try [LAIB], whether they wanted to or not. So, it was kind of enforced. Staff became split about that and, also toward the patients. It became tiresome for the staff to have to take on these battles as well. And for the patients, who usually also have their own willpower, it became extreme and painful to all the time have to work actively, pushing the patients to switch formulation. To some extent, I think it meant that it resulted in an increase in staff sick leave (Participant 21, nurse).

The overall tendency in the data was that “harm reduction” patients with complex needs were allowed a lesser degree of choice, as exemplified in the following quotation:

We might end up in a situation where the patient takes a lot of heroin mixed with a whole lot of other substances and where they don’t have the ability to come to the clinic. And where the situation might be that we say: ‘Well, either you take [LAIB] or nothing”. And then that is not to have a choice (Participant 11, nurse).

We found that the degree of choice for patients on whether to initiate LAIB or not varied between the clinics in the study, from an explicit patient choice perspective and shared decision making to a more enforced demand from staff to patients.

Keeping tabs, control, and treatment alliance

A central theme in the interviews concerned the importance staff attached to keeping tabs on the patients and having knowledge about their current status. Several interviewees saw weekly and monthly meetings as a significant challenge, compared to daily clinic visits during treatment initiation with sublingual buprenorphine or methadone. In the following quote a nurse describes a sense of loss of both a treatment alliance and of being updated about the patients’ lives and progress in treatment:

For tablets they must come daily for the first three months. When you meet someone at least five days per week, you get to know them well and know what it looks like at home and what kind of relationships they have with their family, and… friends and if they have a job or not. You develop quite a close bond. But you lose a lot of that when they have the injection. And then you cannot keep tabs the way we would like to (Participant 30, nurse).

Another nurse said: ”I think that you miss quite a lot when you don’t meet the patient more than perhaps once a week. I think that what is a freedom for them turns into a disadvantage for us sometimes” (Participant 29, nurse). Less frequent visits were described as challenging from a medical safety standpoint, as in the following example:

You don’t know exactly what they do between the visit days. I’ve had a patient who got LAIB quite quickly and where it turned out that… several months passed before we found out that this patient was testing positive for cocaine sometimes. So, when you don’t meet them that often, you don’t get to know what’s happening between the meetings (Participant 36, nurse).

Control can also be regarded as an exercise of power. The following excerpt is an isolated one in the data, but exemplifies how some staff might view LAIB as reducing their ability to “punish” patients who use illicit drugs:

There were problems in the beginning, a lot of discussions about ‘this patient will have to go back to tablets’. There was uncertainty among staff, particularly nurses. They lost the possibility to teach a lesson. You cannot reduce the dose when they use illicit drugs. That possibility disappeared and the nurses did not appreciate that (Participant 2, physician).

This was an initial reaction to LAIB, but the quote reveals how power dynamics between staff and patients in OAT may influence the introduction of a new treatment option.

Although a minor theme, another aspect of the treatment alliance concerned the way LAIB might increase the workload of staff. Less frequent meetings with more patients can increase the number of requests for support from patients. This aspect was commented upon by one physician:

It’s a bit surprising, because I thought that they would be thankful to get rid of the daily contacts and instead meet more patients who come seldom. But the opposite was true, they feel that the workload is heavier, because the patients who they meet daily, it’s not a big thing for them, they keep tabs on them, they know exactly in what shape they are, and they know what’s happening. But for those who come more seldom, like once per month, so much has happened since the last time and then the patients want to sit a really long time and talk and bring up all kinds of things. They want dental and medical certificates and renewed prescriptions. So it becomes a bit overwhelming to have these patients (Participant 7, physician).

Particularly among staff such as nurses, who often meet patients daily, the implementation of LAIB was found to negatively affect their abilities to follow up the patients’ current health and social situation. Although patients on LAIB were viewed as having a form of overdose protection, the weekly or monthly meetings for “harm reduction” patients were mainly seen as a risk that impeded the ability to act in cases of impending problematic situations, such as increased illicit drug use or worsening mental health.

Impacts on risk and enabling environments in OAT

The way that LAIB significantly limits the diversion of other OAT medications was frequently brought up as an important advantage of the treatment option. This aspect related mostly to the possibility of ensuring that patients with low adherence used their medications as intended, without the possibility of giving, trading or selling take-home doses.

Staff also discussed the way that LAIB, by reducing the frequency of visits, can reduce the risks of patients meeting other patients or dealers who want to sell illicit drugs to them. One nurse brought up this issue in relation to the risk of meeting patients with continual drug use:

I think it’s an advantage to not come here and meet other patients who continually use illicit drugs. That can be a risk factor for them to relapse. But also, to not have to meet with the people who, unfortunately, come around here, by the clinics, and who want to sell illicit substances. If you come once per week or once per month you minimize the risk of being exposed to that (Participant 35, nurse).

A nurse brought up that patients found it relieving to have LAIB so that they could avoid being asked to sell their medications:

I have a patient who says that she has the injection even though she’s on tablets to get rid of the nagging in the waiting room that she should sell her tablets. She pats herself like this [pats the thigh] to make everyone think she has gotten an injection instead (Participant 27, nurse).

These excerpts indicate a strong sense of how staff perceived that LAIB significantly reduced risks experienced by patients when coming for daily visits to OAT clinics.

Our findings from focus groups and interviews with healthcare staff highlight both the opportunities and dilemmas that LAIB entail in the clinical practice of OAT. Overall, the staff perceived more advantages than disadvantages with LAIB. Advantages and disadvantages described were similar to those resulting from interviews with patients [ 5 , 6 , 11 ].

We found a significant dividing line in the staff’s perceptions of whether LAIB was most suitable for low versus high adherence patients. Staff described a learning process, in which they initially assumed that LAIB would be more beneficial for high adherence patients, but later found that LAIB can offer significant benefits for patients with complex needs described as “harm reduction” or low adherence patients. Both of these patient categories were positive towards LAIB and reported similar advantages and to some extent similar disadvantages [ 6 , 24 ]. The notion of “harm reduction” patients as a homogenous patient category is problematic since the category is broad, and different practitioners of OAT may define and view harm reduction differently [ 25 ]. The treatment process is also dynamic, and a patient might need harm reduction interventions at some points in the process and not others. Nonetheless, the category seems to act as a proxy for problem severity and may have been useful for OAT clinics in differentiating between patients in terms of the usefulness of LAIB.

Less frequent visits made keeping tabs on the patients more difficult. According to our interviewees, this may negatively impact the staff’s ability to identify needs and respond promptly to reduce medical risks or offer social support. It can also be perceived as detrimental to the treatment alliance, especially if LAIB was offered as a first-line treatment option, when staff had not yet had the possibility to develop an alliance with the patients. This is noteworthy since the treatment alliance is not necessarily a function of daily visits. Daily visits are in fact very rare in psychiatric or addiction medicine settings. Also, historically in the Swedish setting, OAT has been described as fraught with tensions, defined by tight control, and verging on abuse of power, where positive drug screens could result in dose reductions as “punishment”, or, in the worst case, involuntary discharge and denial of further treatment [ 26 ]. That sporadic cocaine use in an otherwise well-functioning patient is seen as a problem may be related to the same Swedish OAT tradition, where abstinence and rehabilitation are often the main goals of treatment [ 18 ]. OAT clinics in Sweden differ in pharmaceutical atmosphere [ 6 ] and may to some extent have different interpretations and implementation of local and national guidelines.

It was also notable that some staff categories, such as nurses and counselors, found an increased workload because of having to handle more practical issues during weekly or monthly patient meetings instead of splitting them up on an everyday basis. Some of the increased workload could be attributed to increased number of patients in treatment during the same period. However, the issues concerning how to deliver social support with less frequency has also been raised in studies of patient experiences [ 3 , 9 ] and constitutes an important point for further consideration in managing in clinical practice. As noted by Allen et al. [ 9 ], we also found that OAT staff often made sure that patients could contact the clinic outside of their weekly or monthly appointments if necessary. Nonetheless, we agree with Lancaster and colleagues about the need to make the social support component of OAT more present [ 3 ].

Staff also recurrently spoke about how LAIB reduces diversion and viewed diversion as a point of concern in OAT and as a destructive phenomenon in terms of medical risks and of damaging the legitimacy of OAT [ 27 ]. In one sense, the way that staff highlighted how less frequent visits could decrease risks surrounding relapse, drug dealing offers, violence and threats identified OAT clinics as a risk environment. Previous studies have described OAT clinics as both enabling and as risky environments. [ 8 , 28 , 29 ]. Our findings indicate the ways in which LAIB can be understood as affecting both the enabling and risky practices. For instance, from a medical perspective, LAIB offers “overdose protection” for “harm reduction” patients with complex needs, in an enabling way. From a nursing or social work perspective, less frequent client meetings may create a risk environment for this group. Another example is staff’s concern over the difficulties in maximizing social support and developing treatment alliances when patient contact is reduced, while being aware of the way OAT clinics become risk environments when patients are continually offered illicit drugs in connection with clinic visits [ 30 ]. LAIB may have an important role to play in enabling patients to avoid those kinds of risk situations. The findings strongly suggest that OAT staff who administer LAIB actively assess risks and possibilities with this new treatment and strategically work to reduce risks and develop the treatment toward enabling aspects for each individual patient.

LAIB and its introduction into Swedish OAT highlight some concerns about low versus high threshold treatment and the ways in which guidelines and rules are applied. In Sweden, traditional OAT has had a high degree of control through daily supervised sublingual/oral dosing, and frequent testing for illicit drugs [ 18 , 31 ]. LAIB was introduced during a period when OAT access had increased due to changes in the national guidelines [ 17 ], which lowered thresholds for patients to enroll in treatment and no longer sanctioned exclusion from treatment due to noncompliance or rule-breaking. The less frequent clinic visits have in some settings resulted in new ways of working in OAT in which the previous strong notions of control are no longer possible. Staff in the present study problematized the changes mainly by reference to the reduced possibility of keeping tabs on patients. This aspect of problematizing stems from an increased worry that they will not be able to intervene when patients experience a negative development in their life situation and/or treatment and is as such related to a concern for the patients’ wellbeing. However, there is evidence that patients in OAT are highly critical of limited access to take-home doses since this impedes their possibility of finding and keeping employment, as well as being perceived as dehumanizing [ 30 ]. These aspects of limitations in access to take-home doses provide a useful point of comparison between daily supervised oral dispensation and LAIB.

Implications for policy and practice

In this study, we found that LAIB is a useful treatment option that is appreciated by staff. Staff perceive LAIB to match the treatment needs of different patient groups and believe that patients view LAIB treatment favorably. However, our results also indicate that LAIB is not appreciated by all patients. Forcing patients to switch over from sublingual buprenorphine to LAIB may negatively influence relationships with staff and potentially the perception of effects and side effects in the implementation phase [ 6 ]. We argue that staff need to discuss the exact prerequisites and reasons for implementing LAIB in clinical practice at their unit/region and in each individual patient.

While a one-sided focus on reducing diversion may create ethical distress among staff, who must navigate between different often conflicting roles in their clinical practice, diversion remains a significant problem in OAT. Strategies that reduce diversion may help patients who experience a pressure to divert their medication and strengthen enabling aspects of OAT.

Although it was an isolated example in the data, the notion that LAIB could be seen as an obstacle to “punishing” patients who relapse by reducing medication doses highlights the unequal power dynamics operating in some OAT settings [ 32 , 33 , 34 ]. Patient and drug users’ unions, as well as OAT staff, may need to monitor these kinds of practices in OAT and we suggest that anti-stigma education [ 35 ] and shared decision making tools [ 36 ] should be incorporated with the clinical implementation of LAIB.

Strengths and limitations

The present study has both strengths and limitations. Among strengths we note data collection from many different clinics, in urban and rural settings. We used data from a pilot study to optimize methods for getting information from different categories of clinical staff (doctors, nurses, assistant nurses). The interviews were conducted at OAT clinics with varying degrees of implementation of LAIB, which limits generalizability across all OAT clinics. The study was conducted in a Swedish context, with a tradition of paternalistic, controlling and rehabilitation-oriented OAT which may be another factor limiting generalizability to other contexts.

Healthcare staff working with OAT in Sweden found LAIB to be more advantageous than disadvantageous, but the treatment requires a continuous discussion about which patients it is most suitable for. The long-acting nature of the medication presents a challenge for staff regarding keeping tabs on patients but may also provide new perspectives on therapeutic alliance in OAT, building on patient’s needs rather than daily or frequent supervised intake over extended periods of time. LAIB was seen as strengthening the enabling environment for most patients, while at the same time highlighting the OAT clinic as a potential risk environment especially for patients struggling with ongoing use who are not on LAIB and must visit the clinic frequently. This study provides new knowledge on OAT staff’s perspectives and strategies in working with LAIB. Further research is needed regarding the day-to-day work that is carried out in different national and regional settings.

Availability of data and materials

The datasets generated during and/or analysed during the current study are not publicly available due to pseudo anonymity of research participants, but are available from the corresponding author on reasonable request.

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Acknowledgements

We want to thank the health care staff who agreed to be interviewed for this study.

Open access funding provided by Malmö University. This study was funded by the Swedish Research Council for Health, Working Life and Welfare, Forte (2022–00228) main recipient AJC, and the Research Council of Southeast Sweden, FORSS (931904, 940502, 969130 and 982042), main recipient AJC. Open access funding provided by Malmö University.

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Johan Nordgren

Department of Social Work, Jönköping University, Jönköping, Sweden

Bodil Monwell & Nina Veetnisha Gunnarsson

School of Social Work, Lund University, Lund, Sweden

Björn Johnson

Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden

Andrea Johansson Capusan

Psychiatric clinic, County Hospital Ryhov, Jönköping, Sweden

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Contributions

Johan Nordgren: Formal analysis, Data curation, Writing—original draft, Writing—review & editing. Björn Johnson: Conceptualization, Validation, Writing—review & editing. Bodil Monwell: Methodology, Formal analysis, Data curation, Validation, Writing—review & editing. Nina Veetnisha Gunnarsson: Methodology, Writing – review & editing. Andrea Johansson Capusan: Conceptualization, Methodology, Funding acquisition, Project administration, Writing—review & editing.

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Correspondence to Johan Nordgren .

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Ethics approval and consent to participate.

The study was approved by the Swedish Ethical Review Authority (Dnr. 2020–00796). We have anonymized each OAT clinic and have given the interviewed participants numbers. We have excluded or altered quotations that would make it possible to identify a specific OAT clinic or participant.

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AJC has received speaker’s fees and participated in advisory board meetings for Indivior, dne pharma, Camurus, Nordic Drugs, Lundbeck, all outside the scope of this study. The remaining authors declare that they have no competing interests.

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Nordgren, J., Monwell, B., Johnson, B. et al. Healthcare staff’s perspectives on long-acting injectable buprenorphine treatment: a qualitative interview study. Addict Sci Clin Pract 19 , 25 (2024). https://doi.org/10.1186/s13722-024-00458-6

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Acceptability and experience of a smartphone symptom monitoring app for people with psychosis in China (YouXin): a qualitative study

• Xiaolong Zhang   ORCID: orcid.org/0000-0003-2964-0485 1 , 2 ,
• Shôn Lewis   ORCID: orcid.org/0000-0003-1861-4652 1 , 3 ,
• Xu Chen 2 , 4 ,
• Jiaojiao Zhou 2 , 4 ,
• Xingyu Wang 1 &
• Sandra Bucci   ORCID: orcid.org/0000-0002-6197-5333 1 , 3  

BMC Psychiatry volume  24 , Article number:  268 ( 2024 ) Cite this article

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Access to high-quality mental healthcare remains challenging for people with psychosis globally, including China. Smartphone-based symptom monitoring has the potential to support scalable mental healthcare. However, no such tool, until now, has been developed and evaluated for people with psychosis in China. This study investigated the acceptability and the experience of using a symptom self-monitoring smartphone app (YouXin) specifically developed for people with psychosis in China.

Semi-structured interviews were conducted with 10 participants with psychosis to explore the acceptability of YouXin. Participants were recruited from the non-randomised feasibility study that tested the validity, feasibility, acceptability and safety of the YouXin app. Data analysis was guided by the theoretical framework of acceptability.

Most participants felt the app was acceptable and easy to use, and no unbearable burdens or opportunity costs were reported. Participants found completing the self-monitoring app rewarding and experienced a sense of achievement. Privacy and data security were not major concerns for participants, largely due to trust in their treating hospital around data protection. Participants found the app easy to use and attributed this to the training provided at the beginning of the study. A few participants said they had built some form of relationship with the app and would miss the app when the study finished.

Conclusions

The YouXin app is acceptable for symptom self-monitoring in people with experience of psychosis in China. Participants gained greater insights about their symptoms by using the YouXin app. As we only collected retrospective acceptability in this study, future studies are warranted to assess hypothetical acceptability before the commencement of study to provide a more comprehensive understanding of implementation.

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Introduction

Access to high-quality mental healthcare remains challenging for people with psychosis globally [ 1 ]. Digital mental health, especially smartphone-based symptom monitoring and interventions, have received greater attention in recent years, given their potential to scale up mental health service provision [ 2 , 3 ]. Conventional symptom monitoring approaches face several practical and methodological challenges, including overly relying on clinic-based face-to-face interviews or comprehensive assessment batteries, which lack ecological validity [ 4 , 5 ] and the reporting is prone to recall bias [ 2 , 4 ]. Smartphones can be used to generate a wealth of data through active and passive real-time monitoring methods [ 2 ]. Active monitoring is typically defined as a user actively inputting psychological and behavioural data through ecological momentary assessment or other ambulatory assessment methods [ 5 ]. Passive monitoring refers to using smartphone or wearable sensors to measure the user’s behaviour or contextual information [ 6 ]. Through the integration of both active and passive monitoring, smartphone-based symptom monitoring enables the tracking of a more dynamic, personal, and valid representation of an individual’s emotional and behavioural state [ 7 , 8 ].

With the unprecedented developments in digital technology in the past decade, smartphones are widely accessible by people with psychosis [ 9 , 10 ]. In China, around 90% of people with psychosis have access to the internet [ 11 ], and people with mental health problems in general are not only willing to use digital health interventions (DHIs) but consider them to be helpful for their recovery [ 12 ]. Moreover, evidence shows that smartphone-based monitoring or interventions appear safe to use and are well tolerated by people with psychosis [ 13 , 14 , 15 , 16 , 17 ]. One of the key advantages of digital mental health tools is their ability to increase access to care [ 18 ]. The significant shortage of mental health resources affects countries worldwide and has been further exacerbated by the COVID-19 pandemic [ 19 , 20 ]. China, like many other countries, has been no exception to this challenge. The estimated shortage of mental health professionals in China relative to the population need was 40,000 [ 21 ]. Despite the efforts China has put into improving the accessibility and quality of mental health services in the past decades, the outcome has only been partially successful and the gap remains significant [ 22 , 23 ]. In China, mental health services, including the treatment and management of psychosis, are predominantly provided by public psychiatric hospitals and supported by psychiatric units in general hospitals, community-based health facilities and rehabilitation centres [ 24 , 25 ]. Outpatient clinical visits at psychiatric hospitals tend to be scheduled mostly monthly, and unlike most mental health systems in Western countries, a care co-ordinator is not available in China [ 26 ]. Moreover, most well-trained mental health professionals are concentrated in psychiatric hospitals located in urban areas [ 27 ], as mental health services are primarily delivered through psychiatric hospitals in China [ 24 , 25 , 28 ], which makes it difficult for people in rural or remote communities to access care [ 29 , 30 ].

Digital mental health holds enormous promise to address the challenges mentioned above, including overcoming some of the barriers faced by conventional symptom monitoring approaches [ 2 ] and the shortfall of mental health resources in China [ 31 , 32 ]. Several studies exploring digital mental health have been conducted in China; for example, smartphone apps have been developed to prevent postpartum depression [ 33 ], facilitate training for children with autism spectrum disorder [ 34 ], support drug addiction [ 35 ], promote well-being in the general population [ 36 ], and establish ecological momentary assessment for depression [ 37 ]. Despite its potential, the generally low real-world usage rates remain a key obstacle to realising the full potential of DHIs in psychosis [ 38 ]. Users attitudes and beliefs about interventions and the complexity of interventions are key factors affecting implementation of DHIs [ 39 ]. Therefore, an in-depth understanding of users expectations, views and experiences of using DHIs in both the development and the evaluation phases of DHIs is needed to maximise user engagement [ 40 , 41 ].

Although smartphone-based symptom monitoring in people with psychosis has proved to be feasible in the Western context [ 42 ], to date, no such tool has been developed and evaluated for people with psychosis in China [ 31 ]. To address this gap, we co-produced with service users and staff the YouXin app, a symptom self-monitoring smartphone app for people with psychosis. This study aimed to explore the acceptability of YouXin and the experience of using the app through interviews with people who participated in the larger feasibility study evaluating the validity, feasibility, acceptability and safety of the YouXin app [ 43 ].

Study setting and participants

This qualitative study was nested in the YouXin non-randomised feasibility study of a smartphone symptom self-monitoring app for people with psychosis in China [ 43 , 44 ]. As the data generated from the qualitative interview was rich, we were not able to give it full justice in the main outcome feasibility study paper. Therefore, we reported the findings in their own right in order to give a full account of the data. Participants were recruited from the outpatient department of Beijing Anding Hospital of Capital Medical University, a major tertiary psychiatric hospital in Beijing, China. Participants were asked to use YouXin to self-monitor their psychotic and mood symptoms over four weeks. At the end, the research team invited participants to take part in a qualitative exit interview. Of the 40 participants who participated in the non-randomised feasibility study, seven were lost to follow-up, 23 were not interested in taking part in the interview, and 10 took part in the post-intervention interviews. Eligibility criteria of the YouXin study were deliberately inclusive to assess feasibility and acceptability of the app. Inclusion criteria were: (1) diagnosed with a DSM-5 (F20-F29) schizophrenia spectrum disorder or met criteria for being at clinical high risk for psychosis according to the Structured Interview for Prodromal Syndromes (SIPS); (2) aged 16 to 65; (3) receiving care from Beijing Anding Hospital, China and continued to be actively supported by the hospital for the trial duration (5 weeks); (4) owned and able to use a smartphone; and (5) clinically stable as judged by the responsible clinician. Exclusion criteria were: (1) diagnosed with organic or substance induced psychosis; (2) lack of capacity to provide informed consent as judged by the responsible clinician; and (3) judged to be at risk for self-harm or harm others.

Intervention

YouXin is a smartphone app-based symptom self-monitoring tool designed for people with psychosis. The app is adapted from the ClinTouch app [ 45 ]. To develop the YouXin app, we selected the validated ClinTouch psychotic and mood symptom items and translated the items into Chinese. We added a passive monitoring function to the app to extract objective mobility and activity indicators to primarily assess negative symptoms. The YouXin app was developed by a multidisciplinary team, including academics, clinicians, software engineers and experts by experience. We adopted a systematic co-production approach to development, aiming to optimise usability and acceptability from both service user and clinician perspectives. The core functions of YouXin consist of active monitoring of current symptoms (termed ASM; including psychotic and mood symptoms and contextual information) in near real-time and passive monitoring of behavioural activity (i.e. Global Positioning System, GPS; step count). Examples of ASM items are shown in Table  1 . The ASM prompts were set to alert at two pseudo-random timepoints per day in a 12-hour interval from 10:00 am to 10:00 pm seven days a week for four weeks. This prompt frequency was set to minimise participant assessment burden. Participants could snooze the prompt for 5 or 30 min or decline to answer. GPS and step count data were passively collected from smartphone sensors to measure users’ mobility and activity levels. A line chart will visualise the results of monitoring based on the data entered into the app. The screenshots of the YouXin app are shown in Supplementary Fig. 1.

Participants were given a training session to help them navigate the app. A member of the research team supported the download and installation of the app onto a participant’s smartphone and demonstrated the app. Participants could practice using the app and ask questions during the process. We encouraged participants to use the app from the training session until the 4-week assessment timepoint. We implemented an opt-out approach, allowing participants to turn the passive sensing on or off at their discretion throughout the study. Participants were informed at the training sessions that the app was not suitable for seeking urgent medical care. Further details of the study procedure can be found elsewhere [ 43 ].

Participants were informed about the exit interview when the research team contacted them to participate in the YouXin study. Consent was obtained together with the larger feasibility study. All participants who consented to the feasibility study were invited to the semi-structured qualitative interviews at the 4-week follow-up meeting. Participants were interviewed in person or remotely per their preference. Participants received a 100 RMB (approximately £10) gift voucher at the end as a thank you for their time and to cover any costs incurred due to their participation. An interview topic guide was designed based on our own research group’s previous work. It aimed to explore the feasibility and acceptability of using the app, experience of participating in the study, and potential barriers and facilitators to the app’s implementation. More specifically, topics covered were: (a) overall impressions of YouXin; (b) positive and negative aspects of the app in terms of content and usability; (c) how it helped and/or did not help; (d) what changes they would make; (e) barriers and facilitators to engagement; (f) views on the training session. The topic guide is shown in Supplementary Table 2.

The interviews were conducted in Mandarin Chinese. To enable the larger research team to analyse and interpret the data, audio-recordings were transcribed verbatim in Chinese and translated into English by XZ. Back translations were performed by XW independently, and then XZ and XW met to discuss the accuracy of the translations until an agreement was reached. The finalised English transcripts were then imported into Nvivo 12 software [ 46 ]. Data were analysed following Braun and Clarke’s [ 47 ] thematic analysis approach, which consists of six phases: familiarisation, transcription, generating initial codes, searching for themes, reviewing themes, and then defining and deciding on meaningful themes. The analysis was also guided by the theoretical framework of acceptability (TFA), an established multi-construct theoretical framework of acceptability of healthcare interventions [ 41 ]. This framework comprises seven constructs: affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness, and self-efficacy. After open-coding the transcripts, the theme ethicality was deemed irrelevant to this data; therefore we coded the data into the remaining six TFA constructs (Table  2 ). One additional theme, privacy, was added. Data regarding how YouXin can be implemented and improved was coded and reported separately.

Ten participants took part in the interview. Participant demographic and clinical characteristics are shown in Table  3 . The median age was 29 (IQR = 21–41). Most participants were male, Han Chinese, and received a diagnosis of schizophrenia. All the participants received antipsychotic medication. Interviews lasted from 16 to 45 min. The demographic and clinical information for each participant are summarised in Supplementary Table 1.

Theme 1: affective attitude

Most participants felt positive about participating in the study and using the app. Moreover, completing the monitoring gave them a sense of achievement:

“There is a sense of joy in answering the questions, a sense of joy and then you feel quite a sense of achievement… then you feel motivated to do things” (Participant 1). “The overall feeling is, ah, every day I answer the questions as soon as the alarm clock goes off, and I feel quite fulfilled, I feel like I’m helping people do research or something, and I’m quite fulfilled to finish answering the questions” (Participant 21).

More specifically, some participants described feeling good about being more aware of their symptoms, a sense of achievement when completing the item set, and a sense of fulfilment that when they could see that their symptoms appeared stable:

“Especially after I finish the second set of questions at night, I feel that my state is very stable and good today, and I feel a sense of achievement and joy, I feel good, that’s the main thing” (Participant 1).

Many participants reported they liked the design features of the app and found the content of the app relevant to their mental health condition:

“My feeling is that the interface is quite new, gives people the feeling that the software is quite newly developed, quite similar to the app I usually use… what I like is that I can change the avatar and the background of the home page, I like that” (Participant 21). “At first glance, I felt that it was quite right for my situation, ah, for my condition, and then, it was quite relevant” (Participant 9).

In contrast, some participants felt the app was less meaningful for them. In particular, the repetitiveness of the ASM items and the simplicity of the app functionality decreased some participants’ motivation to engage in or use the app in a sustained way:

“It’s like this is what I do every day anyway, my work and life is like this, just record it, it also does not matter if you record it or not” (Participant 3). “The same few questions every day, no change… it doesn’t really fit in, it can’t socialise with other users, the app is a single-player game” (Participant 14). “I feel that everything is like this, just when I first started to do it, I was quite punctual, but later… because it is always repeated, every day repeat the same questions, so I sometimes may not be particularly serious, at the end may be a little bit like this” (Participant 18).

When asked if they would miss the app at the end of the study, some participants indicated that they got used to having the app on their phones, that they felt a sense of attachment and connection with the app, and that they would miss it when they were no longer able to access it:

“It’s true that I miss it a little bit… I didn’t want to uninstall it, I still want to continue to use it, I think it’s quite good, yes, it’s similar to a kind of life punch card” (Participant 1). “It gives me the same feeling as a doctor… it is a sense of attachment [laugh]” (Participant 5).

However, some participants did not have any strong feelings about deleting the app and losing access at the end of the study. Instead, some participants described feeling relieved since they did not have to think about answering the question set in the app, and they couldn’t necessarily see a direct impact on how completing the items might support their care:

“There is no impact, answer it or do not answer it, it does not matter, anyway it is just a kind of game, if I don’t need to answer it again, it seems to be a little easier [laugh], I do not have to do a task” (Participant 3). “I probably don’t miss it particularly… I probably feel temporarily like there’s one less thing to do, like it’s a bit more relaxed” (Participant 21).

Of note, one participant reported that it felt uncomfortable to give “truthful” answers in response to ASM questions in the event their treating clinician will view their responses or they themselves will have evidence of possible deterioration in their mental health:

“There are some questions that are, I’m afraid to, umm, dare not express some of the real thoughts, for example, whether paranoid, then I will think am I paranoid today, just kind of let myself think back to these things, but I do not dare to fill in the accurate answer… for example, it has reached 7 but my response is 3, just like that… it’s not exactly hiding, but I’m just afraid to answer the most accurate one anyway… maybe because I will think of the doctor will look at my answers, or if I give a real answer, I can see the parameters of the data, ah, every time it reaches three I will feel pressure, yes, maybe it is about this aspect of it… it’s too stressful, that’s what it feels like” (Participant 1).

Theme 2: Burden

Participants overall found the effort they made to engage in the study and the app acceptable and that involvement was not too intrusive or effortful:

“Well, it was okay, not too intrusive, the processes were actually quite fast” (Participant 4). “Well, no, I just finished it easily, it took one or two minutes” (Participant 5).

Some burden was reported by participants; however, participants did not report this sense of burden to be distressing or intolerable. A few participants felt that the two randomised prompts a day were unnecessary and the randomness with which these were sent was problematic as they preferred to know when the prompts would be sent so they could plan their day better. Participants also said that the repetitiveness of items was problematic:

“Well, that time is always random… it’s twice a day, it’s not the same time, sometimes you can’t catch up and it’s over, why can’t it be fixed time, why it has to be random” (Participant 14). “I actually don’t think that twice a day is necessary, I think once a day is about right, and then the questions, well, it’s sometimes repetitive… I don’t know how to improve it, but, just, it’s true that in the process of answering the questions, well, some of them are a bit problematic… it’s the same question it always repeats” (Participant 18).

Burden related to technology issues were reported, including setting one’s own alarm clock to complete the ASM questions set due to the alarm volume of the app being too soft, and the need to charge the phone more often than usual:

“It’s just that sometimes I can’t remember, so I end up setting an alarm clock, and answering the questions as soon as the alarm goes off 5 minutes earlier… its [own] alert volume is too small, sometimes you can’t hear it, it is too small” (Participant 19). “So the power consumption is a bit more, the phone loses power… before I use this app, I charge the phone once a day and with no problem, now it will run out of power at 6 or 7 pm, 7 or 8 pm… [but] it doesn’t matter too much, because you can recharge at lunchtime too” (Participant 21).

Regarding burden related to study procedures, all participants felt the study procedures were acceptable, except one participant who reported that participating in the study was time-consuming:

“I spent much time on it [laugh], so I can’t do other things… It does take some time, some time costs” (Participant 3).

Theme 3: intervention coherence

All participants reported the YouXin app was easy to use, understood how it works, and its content was relevant to their mental health condition. However, a small number of participants found some of the terms in the ASM items and the results graph difficult to understand:

“It has the word ‘grandiosity’, and I’m not quite sure what this ‘grandiosity’ means, that’s what I don’t quite understand” (Participant 18). “I don’t know how to read the results, because that line [graph], that curve, I don’t know how to read, it overlaps in many places, just doesn’t look good at a glance, it would be better if it can be presented more straightforward” (Participant 19).

The training provided at the beginning of the study was deemed useful by all participants. More specifically, participants felt the training gave them detailed information on how to operate the app:

“It gave me some ideas to better complete this thing, if you do not tell me this, it will cost me a long time to figure it out, after the introduction, I can use the app easily, or I have to figure it out myself” (Participant 3).

A small number of participants reported, however, errors in the app when they recorded their response to ASM items or when passive data was recorded:

“I finished this question, and then I tried to review the previous question, but the answer it showed me was not the answer I gave” (Participant 18). “It’s the step counting, it is not very clear… sometimes it doesn’t record when I walk, but sometimes it does” (Participant 5).

Theme 4: opportunity costs

In general, participants indicated that the YouXin app fit well in their daily lives, and participants did not need to significantly sacrifice aspects of their time or day to engage in the app and the study procedures. On occasion, some participants said that they missed responding to alert notifications that clashed with other aspects of their routine or when they forgot to take their phone with them:

“Actually, I don’t think it affects me very much, but I think for some work or some family gatherings or something, for example, if I miss it, or if I can’t answer the question at that time, it will have a reminder for 20 minutes later, but if you don’t click on the reminder for 20 minutes later, it will miss the question, I feel like I haven’t finished the question again today” (Participant 1). “Just don’t put it too late to answer the questions, I was sleeping at that time so I missed a lot of prompts… after 9 o’clock, I think, I go to bed quite early” (Participant 5). “I remember just a few times I forgot to take the phone and didn’t do it… I didn’t take the phone for a while, so I missed one or two, I can’t remember, maybe because I was doing something else” (Participant 2).

Some participants said that they prioritised responding to the app over other activities, but this did not have any negative consequences on their day-to-day life and did not cause distress:

“Basically, if I was busy at the moment, I just put things aside for the time being, the app doesn’t take long, just one or two minutes, two or three minutes to answer, after answering [it] I’ll continue to do my things… it just a couple of minutes, it doesn’t matter” (Participant 3). “Sometimes, for example, when I want to take a nap in the noon or afternoon, I have to think of that there is an alarm clock that will go off later, so I may not be able to sleep for too long” (Participant 21).

Theme 5: perceived effectiveness

All participants agreed the app achieved the goal of symptom self-monitoring. Specifically, participants found that answering the questions facilitated self-management of their mental health:

“What is helpful is that it will detect whether you have that strange thought, for example, if I have a relapse, and then when I answer the questions, the delusions score may be quite high, it may be able to remind me that I may have a relapse soon, and I may need to go to the doctor as soon as possible… I feel like I have some sense of control over my mental health, that I feel like I’m in control, I know if I’m going to have a relapse, I have that sense of control” (Participant 21).

Responding to ASM items supported participants to better understand and communicate their mental health with others, including their doctor and family members:

“The questions, I think the questions are quite comprehensive, and it’s also quite straightforward, well, some of the questions it reflects directly, like, it might be like after you answering this question you will know what aspect it reflects” (Participant 18). “It helps the doctor to treat me [laugh]… just show her the results straight away… it’s convenient, because there are things I can’t describe clearly, but the assessment is straightforward… it just doesn’t help me with my specific condition, but it’s nice to be able to communicate with my doctor” (Participant 5).

Passive monitoring provided feedback on mobility and activity level and served as a reminder to participants to exercise, which resulted in positive effects on both mental health and physical health:

“I check the step count every day, so I know whether I’ve exercised today, and then if I am on rest and not exercising, I’ll tell myself get up and walk, don’t stay still” (Participant 1). “This passive monitoring… it is good for the patient to be more active, strengthen the physical well-being, strengthen the immune system, and then enhance confidence… I think this physical exercise is particularly good for the treatment of this condition [psychosis], and it has a positive treatment effect” (Participant 19).

However, a few participants felt the app was not helpful because they were not particularly symptomatic and therefore the questions did not seem relevant at the time. Also, the repetitiveness of the ASM items meant that participants felt they were responding to questions not relevant to their situation repeatedly:

“The symptoms that I have had before, some of the symptoms are in the app, but I experience none of them at the moment, so the app is not too useful, my symptom was quite severe before, back then, it would be more useful, now it seems I am normal as I take medicine and other treatments, so it is not particularly helpful to me anymore… it doesn’t mean much to me, it is useful for people who have some symptoms, so that it can record fluctuations in a certain way, for example, today the score is 1, and tomorrow maybe 2 or 3, it is more useful for people experiencing symptoms” (Participant 3). “Because the questions generally, um, it seems that there are not many changes in each day’s questions, all my answers were absence of symptoms, so I do not feel the app has any effect on me” (Participant 21).

Additionally, participants indicated that the app was useful when in-person mental health services were unavailable, such as during the COVID-19 pandemic, but felt that digital tools cannot replace face-to-face mental healthcare:

“If it is under a situation like the pandemic, it is not convenient to see a doctor, then this is helpful, but it is still not as good as seeing a doctor face-to-face, face-to-face is more effective and better” (Participant 19).

Theme 6: self-efficacy

Participants were confident that they could operate the YouXin app and found the user interface and contents of both the ASM and passive monitoring components straightforward. Some participants reported they were more proficient using the app as they became more familiar with the content:

“The change is probably that the speed of answering the questions is a little bit faster, well, there are questions that I know are three or four questions in a row, and then I know that the first choice, for example, if I chose no delusion, and the next three should all be score 1, and then I answer it very quickly” (Participant 21).

Though participants themselves were competent in using the app, concerns were expressed that it might be difficult for some populations to use the app effectively, such as people who are not so familiar with digital technology, and children:

“There is something I don’t like is that it may need to set some parameters on the Android phone, for example, you need to turn on some permissions or something like this when you are recording steps, I think I am able to set this thing in the background, but there are some people, for example, they may not know much about electronic products, they may feel difficult to set it up” (Participant 1). “But some patients are not easy to manage themselves very obediently [laugh]… for example, children… a child self-manage mental health condition through an app is quite difficult to achieve” (Participant 5).

Theme 7: privacy

Participants were not concerned about privacy and data security issues, mainly as they had been informed what data would be collected in the consent and training session and because they reported an inherent trust in the hospital in relation to data protection. Participants also reported that conducting this type of research was consistent with the hospital’s role and remit:

“I have been clearly told that it will monitor some of my data in the training, so I already knew that before, so I think it is not a big concern” (Participant 1). “Because I know that my steps and records and stuff will not be leaked to any strange people, I know you will add privacy protections, so it is fine, so I didn’t feel that way” (Participant 21). “Security, privacy, no, no worries, because the hospital is meant to study the disease with patients, and then it can benefit you, so I cooperate with the hospital to do research” (Participant 9).

Despite the sensitive nature of GPS data, participants felt that it was acceptable and appropriate to record their location data in the app:

“No, no, I think the privacy is similar to you answering questions” (Participant 18). “I didn’t care too much of it, just always on, and I didn’t feel being monitored all the time, it’s just very natural” (Participant 21).

Although no concerns were raised regarding privacy, participants mentioned the importance of informing users about privacy issues:

“Well, it’s still the privacy issue, maybe, yeah, if you do not tell me exactly why I’m answering this question, I would be concerned about the privacy issue, so I won’t tell the most accurate and direct answer, I will provide an ambiguous [answer]” (Participant 1).

Some participants were comfortable using the app when other people were around as they perceived it to be similar to other apps they usually use. Additionally, some participants said the question set could be completed quickly, so they felt people around would not notice what app or content they were interacting with. However, some participants expressed their discomfort at others knowing what content they might be interacting with in the app, mainly due to the stigma associated with mental health problems:

“I won’t tell them, and if I have to tell them when answering this question, I will just say it is a learning app so I need to answer some questions, and they will not pay special attention to what you are doing, anyway it is very simple to complete, but I will not open the conversation and tell them that I am using a software [for mental health purpose]” (Participant 1). “[If] they see me answer [the app] and ask me what I am answering, how can I explain this to them, [if] I say I am doing research and they will look at me differently… it’s better to answer by yourself, so no one can read it” (Participant 14). “I just don’t want other people to know that I have this disease, nowadays society is still discriminating against this kind of disease, but it’s getting better and better, and sometimes you can’t hide it even if you want to… basically I just let it be” (Participant 19).

Suggestions for implementation and improvement

Participants’ willingness to use the app in the future and their perceived barriers and facilitators of implementation were explored (see Table  4 ). Overall, participants were willing to use the app in the future, anywhere from two weeks until recovery. Regarding barriers to implementation, the popularity of digital mental health apps, access to smartphones, family member/carer opinion, symptom severity, and burden to engage in the app were identified. Participants considered doctor recommendations and advertising in hospitals (e.g. posters) could facilitate the use of the YouXin app in the hospital.

Suggestions for improvement to the app, the training session, and the study procedures were collected. Many participants suggested adding more ASM items to cover more symptom domains, including sleep problems, cognitive function, and mood symptoms in a specific environment (e.g. feeling anxious when walking in a crowded environment). Contradictory suggestions on the number of questions were identified; some participants wanted fewer items so that it took less time to complete the ASM question set, while others suggested adding more items so that more symptom domains could be explored.

“Just make the questions a little less, a little more precise, add sleep to it… other than that it’s fine, just fewer questions, so it doesn’t have any impact on life or anything” (Participant 3). “You can add some more, I think the number of questions is still a little bit small, for example, say anxiety, you can have 5 to 7 questions like this kind… and then, for example, sleep disorders or something, emotional instability, also add 5 to 7 questions, now the number of questions is a little bit low” (Participant 19).

A few participants suggested fixing the alert notification schedule to a particular time (rather than notifications being sent pseudo-randomly) or increasing the snooze period so that they could respond at a time that suited them, which would in turn reduce the chance of prompts being missed. Some participants also said that they would have liked the app to provide personalised advice for their mental health following responses they made to the ASM item set and their daily entries. Participants suggested modifications to line graph are needed to so that it is easier to read; the overlapping lines representing different symptom domains was too complex to meaningfully interpret for some. Participants proposed adding some new functionalities to the app, including gamification to make it more rewarding to engage with, fitness tracking, relapse prevention strategies, and a photo diary.

“I’d like to have some pictures, like, I’ve seen something good recently, I’d take a picture of it and add a picture of my mood, pictures and text are important nowadays, just plain text is a bit too boring… for example, if you ride a bus today, take a picture of what you’ve seen, or where you’ve been, take a picture” (Participant 14).

Regarding the training session, a few participants expected the researcher to provide more detailed information about the rationale and purpose behind the ASM items and the app so they could have a deeper understanding of the items and their own symptoms. Finally, participants indicated that the study procedure was well-designed and no improvements to this was needed.

The aim of this study was to explore the acceptability of the YouXin app and how participants experienced it. Most participants felt the app was acceptable and easy to use. Participants found completing the self-monitoring rewarding and experienced a sense of achievement. Most participants tolerated receiving two prompts per day, and no unbearable burden or opportunity costs were reported. Privacy and data security were not expressed as a concern by participants largely due trusting the hospital’s data protection procedures. Nevertheless, some participants preferred to answer the app alone without other people around for reasons related to stigma associated with mental health problems. The app was considered helpful in symptom self-monitoring, making participants more aware of their symptoms, and better communicating their mental health with mental healthcare providers and family members. All participants found no difficulties using the app; some participants attributed this to the training provided at the beginning of the study. Several participants said they had built some form of relationship with the app and would miss the app after completion of the study. Nonetheless, some improvements were suggested by participants, including optimising the alert nonfiction schedule for better time planning and fewer missed prompts, adding more symptom domains in ASM items so the app can be more meaningful for people wanting to monitor mental health conditions other than psychotic and mood symptoms, refining result graph layout with textual advice to enhance comprehension, and expanding the functions of the app to make it more engaging.

Effective symptom monitoring is arguably a critical element for high-quality mental health services. However, due to the limited mental health resources in China, timely symptom assessment is not widely accessible [ 23 , 27 ]. Most participants emphasised the app increased their awareness and deepened their understanding of their symptoms, subsequently aiding them in making adjustments to their daily life and putting strategies in place to help manage their mental health. The app was described as a platform to help participants communicate their mental health condition with both mental health professionals and family members. Many participants reported that, before using the app, they did not have the means to measure their symptoms and sometimes found it difficult to communicate their exact feelings to their healthcare professional as they felt they did not have the language (terminology) or ability to express how they were thinking/feeling. These findings support the idea that using smartphone apps to self-monitor symptoms is acceptable and beneficial for people with psychosis and serves a purposeful function [ 14 , 45 , 48 ]. However, as participants mentioned the line graph displaying their symptom reports was difficult to understand, refinement is needed support users to interpret graphical read out of symptom monitoring and ensure meaningful comprehension of their mental health condition.

Perceived level of usefulness of YouXin seemed to be a factor that influenced the extent to which participants engaged with the app. For example, a few participants with milder symptoms expressed that the monitoring results did not change or fluctuate over the app exposure window and so they felt it had little utility, resulting in the feeling less motivated to use the app over a longer duration. Additionally, the repetitiveness of the ASM items and the simplicity of functionality for some led to disinterest. Boredom and fatigue effects caused by the repetitiveness of items has also been reported in previous digital remote monitoring studies [ 13 , 48 ]. Some participants suggested adding gamification elements to make self-monitoring health apps more engaging and rewarding. Moreover, some participants proposed adding more functions to the app to further enhance the user experience and promote meaningful engagement with the content, including fitness tracking, a photo diary, and relapse prevention strategies. As complex smartphone-based self-management tools have been shown to be feasible and beneficial [ 13 , 15 , 16 ], updates for the YouXin app are needed to adapt more elements to expand its functions to meet the broader needs of users and maximise longer term engagement.

Most participants felt passive monitoring was acceptable and non-intrusive, with many participants describing that they were comfortable to leave passive data collection running in the background without actively attending to it. This finding is in contrast to some studies that have found that people with psychosis might feel paranoid about routine monitoring in the context of their healthcare [ 17 , 49 , 50 , 51 , 52 ]. While non-intrusiveness is viewed as positive from an acceptability perspective, a downside of passive monitoring is that the smartphone’s operating system may halt background data collection for performance or battery reasons when users do not interact with the app after an extended period, without sending any notification [ 53 ]. This fact may explain the high rates of missing data for passive monitoring found in the YouXin study [ 54 ], and in other passive monitoring studies [ 53 , 55 , 56 ]. In addition, participants mentioned power consumption was higher than before using the app, which is likely caused by passive monitoring [ 57 ]. Therefore, optimising passive data collection strategies to reduce missing data and power consumption is needed.

Unlike previous qualitative studies [ 58 , 59 , 60 ], we found participants were not overly concerned about privacy and data security despite the intense collection of data by the app. Most participants said it was because they consented to the study and trusted the hospital around data protection. This finding suggests that, within the context of Chinese tertiary psychiatric hospitals, if service users put trust in the hospital, it alleviates concerns around privacy and data security issues, thereby not hindering people from using the technology. Trust and transparency are core elements for successful implementation of digital mental health [ 18 , 61 ], especially for symptom monitoring tools which often requires sharing a considerable amount of data [ 62 ]. Building trust requires adequate governance and regulation [ 63 ]. Despite lagging behind in the regulation of digital health compared to most Western countries, China has recently launched a policy on internet healthcare aiming to regulate and strengthen the development of the online healthcare system [ 64 ]. Nevertheless, further efforts are needed from regulators in China to develop policies specific to digital mental healthcare to foster a healthy, transparent, and trustworthy development environment.

Most participants found the app seamlessly integrated into their daily lives, and some participants described a sense of connection with the app and would miss it when the study stopped. This reflects the concept of Digital Therapeutic Alliance (DTA), which describes the therapeutic alliance built between the users and a digital mental health app [ 65 ]. Even though the YouXin app was a stand-along automated app with no active human support, we found participants reported establishing a connection or bond with the app, in line with Tong et al’s [ 66 ] finding that DTA could be built between users and a fully automated mental health app. Although DTA is a relatively new concept [ 67 ], our finding underscores the importance of considering DTA in the development of mental health apps. As therapeutic alliance has shown to be important in predicting outcomes in traditional psychological therapy, we expect DTA might have similar effects on DHIs.

Strengths and limitations

To our knowledge, this is the first study to use qualitative interviews to explore the acceptability of symptom self-monitoring using digital tools in people with psychosis in China. We systematically examined the acceptability of the YouXin app, the training session, and the study procedures, gaining insights into participants experiences on the app and the study. We also identified barriers and facilitators that may influence the implementation of digital mental health apps in people with psychosis in China.

There are some limitations of this study. Participants were recruited from the YouXin feasibility study and owned a smartphone. Therefore, our sample may have had higher digital literacy and interest in digital health compared with the broader psychosis community in China. Moreover, we did not explore acceptability before and during the study and only collected retrospective acceptability at the end of the study. This limited our understanding of the hypothetical acceptability of people with psychosis on the app, which is increasingly considered an important factor in fully understanding the implementation of digital mental health [ 40 , 68 ]. Future studies should explore participants’ views prior to the commencement of the study to be able to compare and contrast acceptability before, during and after the intervention, which has the potential to provide a more comprehensive understanding of implementation factors to be considered when integrating digital health interventions into routine clinical practice.

This qualitative study indicates the YouXin app is acceptable for symptom self-monitoring to people with psychosis in China. Participants gained greater insights about their symptoms by using the YouXin app, while suggestions for improving user experiences, functionality, and perceived effectiveness were reported. We found some form of DTA was developed between participants and the YouXin app, suggesting more comprehensive investigations on DTA are needed, especially for long-term symptom monitoring. We only collected participants views at the end of the study; future studies are warranted to assess acceptability before and during the commencement of study to provide a more comprehensive understanding of implementation factors. This study not only informs the refinement of YouXin, but also provides valuable information for the development and implementation of other DHIs for psychosis in China more broadly.

Data availability

The data sets generated during or analysed during this study are available from the corresponding author on reasonable request.

Abbreviations

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

Structured Interview for Prodromal Syndromes

active symptom monitoring

theoretical framework of acceptability

Digital health intervention

Digital Therapeutic Alliance

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Acknowledgements

The authors would like to thank the participants who took part in the study. We would also like to thank the staff who referred people to the study.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The development of the YouXin smartphone app was supported by Beijing Anding Hospital of Capital Medical University.

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XZ and SB conceptualised the study. SB and SL supervised data collection. XZ collected the data with support from XC and JZ. XZ and SB were involved in analysing data. XW performed the back translation of data. XZ wrote the first draft of the paper. All authors contributed to the article, reviewed the paper and approved the submitted version.

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The study was approved by the University of Manchester (Ref: 2022-13262-24297) and Beijing Anding Hospital (Ref: (2021)Research No.58) Research Ethics Committee. Participants provided their written informed consent to participate in this study.

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Lewis is Academic lead of Mental Health in Health Innovation Manchester. Lewis and Bucci are Directors and shareholders of CareLoop Health Ltd, a spin out from the University of Manchester to develop and market digital solutions for remote monitoring using smartphones for mental health conditions, currently schizophrenia and postnatal depression. Bucci also reports research funding from the National Institute for Health and Care Research (NIHR) and The Wellcome Trust. All other authors declare no competing interests.

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Supplementary Figure 1. Screenshots of the app prototype, Supplementary Table 2. Interview Topic guide

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Zhang, X., Lewis, S., Chen, X. et al. Acceptability and experience of a smartphone symptom monitoring app for people with psychosis in China (YouXin): a qualitative study. BMC Psychiatry 24 , 268 (2024). https://doi.org/10.1186/s12888-024-05687-2

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Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study

• Jasmin Hennrich 1 ,
• Eva Ritz 2 ,
• Peter Hofmann 1 , 4 &
• Nils Urbach 1 , 3  

BMC Health Services Research volume  24 , Article number:  420 ( 2024 ) Cite this article

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Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications’ potential.

We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC.

Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery.

We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.

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Applications based on artificial intelligence (AI) have the potential to transform the healthcare (HC) industry [ 1 ]. AI applications can be characterized as applications or agents with capabilities that typically demand intelligence [ 2 , 3 ]. In our context, we understand AI as a collection of technological solutions from the field of applied computer science, in which algorithms are trained on medical and HC data to perform tasks that are normally associated with human intelligence (i.e., medical decision-making) [ 4 ]. AI is not a single type of technology, instead, it encompasses a diverse array of technologies spread across various application areas in HC, such as diagnostics (e.g., [ 5 ], biomedical research (e.g., [ 6 ], clinical administration (e.g., [ 7 ], therapy (e.g., [ 8 ], and intelligent robotics (e.g., [ 9 ]. These areas are expected to benefit from AI applications’ capabilities, such as accuracy, objectivity, rapidity, data processing, and automation [ 10 , 11 ]. Accordingly, AI applications are said to have the potential to drive business value and enhance HC [ 12 ], paving the way for transformative innovations in the HC industry [ 13 ]. There are already many promising AI use cases in HC that are expected to improve patient care and create value for HC organizations. For instance, AI applications can advance the quality of patient care by supporting radiologists with more accurate and rapid diagnosis, compensating for humans’ limitations (e.g., data processing speeds) and weaknesses (e.g., inattention, distraction, and fatigue) [ 10 , 14 ]. Klicken oder tippen Sie hier, um Text einzugeben.While the use of AI applications in HC has the overarching goal of creating significant value for patients through improved care, they also come with the potential for business value creation and the opportunity for HC organizations to gain a competitive edge (e.g., [ 15 , 16 ]).

Despite the promised advantages, AI applications’ implementation is slow, and the full realization of their potential within the HC industry is yet to be achieved [ 11 , 17 ]. With just a handful of practical examples of AI applications in the HC industry [ 13 , 18 ], the adoption of AI applications is still in its infancy. The AI in Healthcare Survey Report stated that in 2021, only 9% of respondents worldwide have reached a sophisticated adoption of AI Models, while 32% of respondents are still in the early stages of adopting AI models. According to the survey, the majority of HC organizations (60%) are not actively considering AI as a solution, or they are currently evaluating AI use cases and experimenting with the implementation [ 19 ]. Nevertheless, HC startups are increasingly entering the market [ 20 ], pressuring incumbent HC organizations to evaluate and adopt AI applications. Existing studies already investigate AI technologies in various use cases in HC and provide insights on how to design AI-based services [ 21 ], explain in detail the technical functions and capabilities of AI technologies [ 10 , 11 ], or take on a practical perspective with a focus on concrete examples of AI applications [ 14 ]. However, to foster the adoption of AI applications, HC organizations should understand how they can unfold AI applications’ capabilities into business value to ensure effective investments. Previous studies on the intersection of information systems and value creation have expressed interest into how organizations can actually gain value through the use of technology and thus, enhance their adoption [ 22 , 23 ]. However, to the best of our knowledge, a comprehensive investigation of the value creation of AI applications in the context of HC from a managerial level is currently missing. Thus, our study aims to investigate AI applications’ value creation and capture mechanisms in the specific HC context by answering the following question: How can HC organizations create and capture AI applications’ value?

We conduct a systematic literature analysis and semi structured expert interviews to answer this research question. In the systematic literature analysis, we identify and analyze a heterogeneous set of 21 AI use cases across five different HC application fields and derive 15 business objectives and six value propositions for HC organizations. We then evaluate and refine the categorized business objectives and value propositions with insights from 11 expert interviews. Our study contributes to research on the value creation mechanism of AI applications in the HC context. Moreover, our results have managerial implications for HC organizations since they can draw on our results to evaluate AI applications, assess investment decisions, and align their AI application portfolio toward an overarching strategy.

In what follows, this study first grounds on relevant work to gain a deeper understanding of the underlying constructs of AI in HC. Next, we describe our qualitative research method by describing the process of data collection and analysis, followed by our derived results on capturing AI applications’ value proposition in HC. Afterward, we discuss our results, including this study’s limitations and pathways for further research. Finally, we summarize our findings and their contribution to theory and practice in the conclusion.

Relevant work

In the realm of AI, a thorough exploration of its key subdiscipline, machine learning (ML), is essential [ 24 , 25 ]. ML is a computational model that learns from data without explicitly programming the data [ 24 ] and can be further divided into supervised, unsupervised, and reinforcement learning [ 26 ]. In supervised learning, the machine undergoes training with labeled data, making it well-suited for tasks involving regression and classification problems [ 27 ]. In contrast, unsupervised learning is designed to automatically identify patterns within unlabeled datasets [ 28 ], with its primary utility lying in the extraction of features [ 11 ]. Reinforcement learning, characterized as a method of systematic experimentation or trial and error, involves a situated agent taking specific actions and observing the rewards it gains from those actions, facilitating the learning of behavior in a given environment [ 29 ]. The choice of which type of ML will be used in the different application areas depends on the specific problem, the availability of labeled data, and the nature of the desired outcome.

In recent years, the rapid advances in AI have triggered a revolution in various areas, with numerous impressive advantages. In the financial sector, AI applications can significantly improve security by detecting anomalies and preventing fraud [ 30 ]. Within education, AI has emerged as a powerful tool for tailoring learning experiences, aiming to enhance engagement, understanding, and retention [ 31 ]. In the energy market, the efficacy of AI extends to fault detection and diagnosis in building energy systems, showcasing its robust capabilities in ensuring system integrity [ 32 ]. Moreover, the HC industry is expected to be a promising application area for AI applications. The HC sector is undergoing a significant transformation due to the increasing adoption of digital technologies, with AI technologies at the forefront of this shift. The increasing relevance of AI technologies in HC is underlined by a growing and multidisciplinary stream of AI research, as highlighted by Secinaro et al. [ 33 ]. Taking a closer look at the different application areas in HC, AI applications offer promising potential, as demonstrated by the following exemplary AI use cases. In diagnosis, AI applications can identify complex patterns in medical image data more accurately, resulting in precise and objective disease recognition. This can improve patient safety by reducing the risks of misinterpretation [ 5 ]. Another use case can be found in biomedical research. For example, AI technology is commonly used for de novo drug design. AI can rapidly browse through molecule libraries to detect nearly \({10}^{60}\) drug-like molecules, accelerating the drug development process [ 6 ]. Furthermore, AI applications are used in clinical administration. They enable optimized operation room capacities by automating the process and by including information about absence or waiting times, as well as predicting interruptions [ 34 ]. Furthermore, AI applications are used in therapy by predicting personalized medication dosages. As this helps to reduce the mortality risk, it leads to enhanced patient outcomes and quality of care [ 35 ]. Intelligent prostheses by which patients can improve interactions are another use case. The AI algorithm continuously detects and classifies myoelectric signal patterns to predict movements, leading to reduced training expenditure and more self-management by the patient [ 36 ]. In summary, envisioning that AI applications successfully address persisting challenges, such as lack of transparency (e.g., [ 37 ], bias (e.g., [ 38 ], privacy concerns, and trust issues (e.g., [ 39 ], the potential of AI applications is vast. The conceivable benefits extend to individual practitioners and HC organizations, including hospitals, enabling them to harness AI applications for creating business value and ultimately enhancing competitiveness. Thereby, we follow Schryen’s (p. 141) revisited definition of business value of technologies: “the impact of investments on the multidimensional performance and capabilities of economic entities at various levels, complemented by the ultimate meaning of performance in the economic environment” [ 40 ]. His perspective includes all kinds of tangible value (such as an increase in productivity or reduced costs) to intangible value (such as service innovation or customer satisfaction), as well as internal value for the HC organizations and external value for stakeholders, shareholders, and customers. To create business value, it is essential to have a clear understanding of how the potential of AI applications can be captured. The understanding of how information systems, in general, create value is already covered in the literature. For example, Badakhshan et al. [ 31 ] focus on how process mining can pave the way to create business value. Leidner et al. [ 32 ] examine how enterprise social media adds value for new employees, and Lehrer et al. [ 33 ] answer the question of how big data analytics can enable service. There are also studies focusing on the value creation of information systems in the context of HC. For instance, the study by Haddad and Wickramasinghe [ 41 ] shows that information technology in HC can capture value by improving the quality of HC delivery, increasing safety, or offering additional services. Strong et al. [ 42 ] analyze how electronic health records afford value for HC organizations and determine goal-oriented actions to capture this potential. There is even literature on how machine learning adds value within the discipline of radiology (e.g., [ 43 ].

However, these studies either do not address the context of HC, consider technologies other than AI or information systems in general, or focus only on a small area of HC (e.g., radiology) and a subset of AI technology (e.g., machine learning). Although these studies deliver valuable insights into the value creation of information systems, a comprehensive picture of how HC organizations can capture business value with AI applications is missing.

To answer our research question, we adopted a qualitative inductive research design. This research design is consistent with studies that took a similar perspective on how technologies can create business value [ 44 ]. In conducting our structured literature review, we followed the approach of Webster and Watson [ 45 ] and included recommendations of Wolfswinkel et al. [ 46 ] when considering the inclusion and exclusion criteria. We started by collecting relevant data on different successful AI use cases across five application areas in HC. Siggelkow [ 47 ] argued that use cases are able to provide persuasive arguments for causal relationships. In an initial literature screening, we identified five promising application domains focusing on AI applications for patients and HC providers: disease diagnostics (DD) (e.g., [ 5 ], biomedical research (BR) (e.g., [ 6 ], clinical administration (CA) (e.g., [ 7 ], therapy (T) (e.g., [ 8 ], and intelligent robotics (IR) (e.g., [ 9 ]. Second, to sample AI use cases, we aimed to collect a heterogeneous set of AI use cases within these application domains and consider the heterogeneity in AI applications, underlying data, innovation types, and implementation stages when selecting 21 AI use cases for our in-depth analysis. The AI use case and an exemplary study for each use case are listed in Table  1 .

After sampling the AI use cases, we used PubMed to identify papers for each use case. PubMed is recognized as a common database for biomedical and medical research for HC topics in the information systems domain (e.g., [ 62 , 63 ]. Our search included journal articles, clinical conferences, clinical studies, and comparative studies in English as of 2010. Based on the AI use case sample, we derived a search string based on keywords [ 45 ] considering titles and abstracts by following Shepherd et al. [ 62 ] guidelines. It was aimed to narrow and specific selection to increase data collection replicability for the use cases. Boolean operators (AND, OR) are used to improve results by combining search terms [ 62 ].

((artificial intelligence AND (radiology OR (cancer AND imaging) OR (radiology AND error) OR (cancer AND genomics) OR (speech AND cognitive AND impairment) OR (voice AND parkinson) OR EEG OR (facial AND analysis) OR (drug AND design) OR (Drug AND Biomarker) OR De-identification OR Splicing OR (emergency AND triage) OR (mortality AND prediction) OR (operating AND room) OR text summarization OR (artificial AND pancreas) OR vasopressor OR Chatbot OR (myoelectric prosthesis) OR (automated surgery task) OR (surgery AND workflow)))

The initial search led to 877 results (see Fig.  1 ). After title screening, we eliminated 516 papers that are not relevant (i.e., not covering a specific AI application, only including the description of AI algorithm, or not including a managerial perspective and the value created by AI applications). We further excluded 162 papers because their abstract is not concurrent with any specific use case (e.g., because they were literature reviews on overarching topics and did not include a specific AI application). We screened the remaining 199 papers for eligibility through two content-related criteria. First, papers need to cover an AI use case’s whole value proposition creation path, including information on data, algorithms, functions, competitive advantage, and business value of a certain AI application. The papers often only examine how a certain application works but lack the value proposition perspective, which leads to the exclusion of 63 articles. Second, we removed 89 papers that do not match any of our use cases. This step led to a remaining set of 47 relevant papers. During a backward-forward search according to Webster and Watson [ 45 ] and Levy and Ellis [ 64 ], we additionally included 35 papers. We also incorporated previous and subsequent clinical studies of the same researcher, resulting in an additional six papers. The final set contains 88 relevant papers describing the identified AI use cases, whereby at least three papers describe each AI use case.

Search strategy

In the second step, we engaged in open, axial, and selective coding of the AI use cases following analysis techniques of grounded theory [ 65 ]. We focused on extracting business objectives, detailing how each AI application drives value. We documented these for each AI use case by recording codes of business objectives and value propositions and assigning relationships among the open codes. For example, from the following text passage of Berlyand et al. [ 56 ], who investigate the use case CA1: “Rapidly interpreting clinical data to classify patients and predict outcomes is paramount to emergency department operations, with direct impacts on cost, efficiency, and quality of care”, we derived the code rapid task execution.

After analyzing the AI use cases, we revised the documented tuples to foster consistency and comparability. Then, we iteratively coded the identified tuples by relying on selective coding techniques which is a process to identify and refine categories at a highly generalizable degree [ 65 ]. In all 14 coding iterations, one author continuously compares, relates, and associates categories and properties and discusses the coding results with another author. We modified some tuples during the coding process in two ways. First, we equalized small phrasing disparities for homogenous and refined wording. Second, we carefully adjusted the tuples regarding coherency. Finally, we reviewed the coding schema for internal validity through a final comparison with the data [ 66 ]. Then, we set the core variables “business objectives” and “value propositions”. We refer to business objectives as improvements through implementing the technology that drives a value proposition. We define value proposition as the inherent commitment to deliver reciprocal value to the organization, its customers, and/or partners [ 67 ].

In the third step following Schultze and Avital [ 68 ], we conducted semi structured expert interviews to evaluate and refine the value propositions and business objectives. We developed and refined an interview script following the guidelines of Meyers and Newman [ 69 ] for qualitative interviews. An additional file shows the used interview script (see Additional file 1 ). We conducted expert sampling to select suitable interviewees [ 70 ]. Due to the interdisciplinarity of the research topic, we chose experts in the two knowledge areas, AI and HC. In the process of expert selection, we ensured that interviewees possessed a minimum of two years of experience in their respective fields. We aimed for a well-balanced mix of diverse professions and positions among the interviewees. Additionally, for those with a primary background in HC, we specifically verified their proficiency and understanding of AI, ensuring a comprehensive perspective across the entire expert panel. Table 2 provides an overview of our expert sample. The interviewees were recruited in the authors’ networks and by cold calling. Identified experts were first contacted by email, including some brief information regarding the study. If there was no response within two weeks, they were contacted again by telephone to arrange an interview date. In total, we conducted 11 interviews that took place in a time range between 40 and 75 min. The expert interviews are transcribed verbatim using the software f4. As a coding aid, we use the software MAXQDA—a tool for qualitative data analysis which is frequently used in the analyses of qualitative data in the HC domain (e.g., [ 38 , 71 , 72 ]).

To systematically decompose how HC organizations can realize value propositions from AI applications, we identified 15 business objectives and six value propositions (see Fig.  2 ). These business objectives and value propositions resulted from analyzing the collected data, which we derived from the literature and refined through expert interviews. In the following, we describe the six value propositions and elaborate on how the specific AI business objectives can result in value propositions. This will be followed by a discussion of the results in the discussion of the paper.

Business objectives and value propositions risk-reduced patient care

This value proposition follows business objectives that may identify and reduce threats and adverse factors during medical procedures. HC belongs to a high-risk domain since there are uncertain external factors (E4), including physicians’ fatigue, distractions, or cognitive biases [ 73 , 74 ]. AI applications can reduce certain risks by enabling precise decision support, detecting misconduct, reducing emergent side effects, and reducing invasiveness.

Precise decision support stems from AI applications’ capability to integrate various data types into the decision-making process, gaining a sophisticated overview of a phenomenon. Precise knowledge about all uncertainty factors reduces the ambiguity of decision-making processes [ 49 ]. E5 confirms that AI applications can be seen as a “perceptual enhancement”, enabling more comprehensive and context-based decision support. Humans are naturally prone to innate and socially adapted biases that also affect HC professionals [ 14 ]. Use Case CA1 highlights how rapid decision-making by HC professionals during emergency triage may lead to overlooking subtle yet crucial signs. AI applications can offer decision support based on historical data, enhancing objectivity and accuracy [ 56 ].

Detection of misconduct is possible since AI applications can map and monitor clinical workflows and recognize irregularities early. In this context, E10 highlights that “one of the best examples is the interception of abnormalities.” For instance, AI applications can assist in allocating medications in hospitals (Use case T2). Since HC professionals can be tired or distracted in medication preparation, AI applications may avoid serious consequences for patients by monitoring allocation processes and patients’ reactions. Thus, AI applications can reduce abuse and increase safety.

Reduction of emergent side effects is enabled by AI applications that continuously monitor and process data. If different treatments and medications are combined during a patient’s clinical pathway, it may cause overdosage or evoke co-effects and comorbidities, causing danger for the patient [ 75 ]. AI applications can prevent these by detecting and predicting these effects. For instance, AI applications can calculate the medication dosage for the individual and predict contraindications (Use case T2) [ 76 ]. E3 adds that the reduction of side effects also includes “cross-impacts between medications or possible symptoms that only occur for patients of a certain age or disease.” Avoidable side effects can thus be detected at an early stage, resulting in better outcomes.

Reduction of invasiveness of medical treatments or surgeries is possible by allowing AI applications to compensate for and overcome human weaknesses and limitations. During surgery, AI applications can continuously monitor a robot’s position and accurately predict its trajectories [ 77 ]. Intelligent robots can eliminate human tremors and access hard-to-reach body parts [ 60 ]. E2 validates, “a robot does not tremble; a robot moves in a perfectly straight line.” The precise AI-controlled movement of surgical robots minimizes the risk of injuring nearby vessels and organs [ 61 ]. Use cases DD5 and DD7 elucidate how AI applications enable new methods to perform noninvasive diagnoses. Reducing invasiveness has a major impact on the patient’s recovery, safety, and outcome quality.

Advanced patient care

Advanced patient care follows business objectives that extend patient care to increase the quality of care. One of HC’s primary goals is to provide the most effective treatment outcome. AI applications can advance patient care as they enable personalized care and accurate prognosis.

Personalized care can be enabled by the ability of AI technologies to integrate and process individual structured and unstructured patient data to increase the compatibility of patient and health interventions. For instance, by analyzing genome mutations, AI applications precisely assess cancer, enabling personalized therapy and increasing the likelihood of enhancing outcome quality (Use case DD4). E11 sums up that “we can improve treatment or even make it more specific for the patient. This is, of course, the dream of healthcare”. Use case T1 exemplifies how the integration of AI applications facilitates personalized products, such as an artificial pancreas. The pancreas predicts glucose levels in real time and adapts insulin supplementation. Personalized care allows good care to be made even better by tailoring care to the individual.

Accurate prognosis is achieved by AI applications that track, combine, and analyze HC data and historical data to make accurate predictions. For instance, AI applications can precisely analyze tumor tissue to improve the stratification of cancer patients. Based on this result, the selection of adjuvant therapy can be refined, improving the effectiveness of care [ 48 ]. Use case DD6 shows how AI applications can predict seizure onset zones to enhance the prognosis of epileptic seizures. In this context, E10 adds that an accurate prognosis fosters early and preventive care.

Self-management

Self-management follows the business objectives that increase disease controllability through the support of intelligent medical products. AI applications can foster self-management by self-monitoring and providing a new way of delivering information.

Self-monitoring is enhanced by AI applications, which can automatically process frequently measured data. There are AI-based chatbots, mobile applications, wearables, and other medical products that gather periodic data and are used by people to monitor themselves in the health context (e.g., [ 78 , 79 ]. Frequent data collection of these products (e.g., using sensors) enables AI applications to analyze periodic data and become aware of abnormalities. While the amount of data rises, the applications can improve their performance continuously (E2). Through continuous tracking of heartbeats via wearables, AI applications can precisely detect irregularities, notify their users in the case of irregularities, empower quicker treatment (E2), and may reduce hospital visits (E9). Self-monitoring enhances patient safety and allows the patient to be more physician-independent and involved in their HC.

Information delivery to the patient is enabled by AI applications that give medical advice adjusted to the patient’s needs. Often, patients lack profound knowledge about their anomalies. AI applications can contextualize patients’ symptoms to provide anamnesis support and deliver interactive advice [ 59 ]. While HC professionals must focus on one diagnostic pathway, AI applications can process information to investigate different diagnostic branches simultaneously (E5). Thus, these applications can deliver high-quality information based on the patient’s feedback, for instance, when using an intelligent conversational agent (use case T3). E4 highlights that this can improve doctoral consultations because “the patient is already informed and already has information when he comes to talk to doctors”.

Process acceleration

Process acceleration comprises business objectives that enable speed and low latencies. Speed describes how fast one can perform a task, while latency specifies how much time elapses from an event until a task is executed. AI applications can accelerate processes by rapid task execution and reducing latency.

Rapid task execution can be achieved by the ability of AI applications to process large amounts of data and identify patterns in a short time. In this context, E4 mentions that AI applications can drill diagnosis down to seconds. For instance, whereas doctors need several minutes for profound image-based detection, AI applications have a much faster report turnaround time (use case DD1). Besides, rapid data processing also opens up new opportunities in drug development. AI applications can rapidly browse through molecule libraries to detect nearly 10^60 molecules, which are synthetically available (use case BR1). This immense speed during a discovery process has an essential influence on the business potential and can enormously decrease research costs (E10).

Latency reduction can be enabled by AI technologies monitoring and dynamically processing information and environmental factors. By continuously evaluating vital signs and electrocardiogram records, AI applications can predict the in-house mortality of patients in real time [ 57 ]. The AI application can detect an increased mortality risk faster than HC professionals, enabling a more rapid emergency intervention. In this case, AI applications decrease the time delay between the cause and the reaction, which positively impacts patient care. E7 emphasizes the importance of short latencies: “One of the most important things is that the timeframe between the point when all the data is available, and a decision has been made, […] must be kept short.”

Resource optimization

Resource optimization follows the business objectives that manage limited resources and capacities. The HC industry faces a lack of sufficient resources, especially through a shortage of specialists (E8), which in turn negatively influences waiting times. AI applications can support efficient resource allocation by optimizing device utilization, organizational capacities and unleashing personnel capabilities.

Optimized device utilization can be enhanced by AI applications that track, analyze, and precisely predict load of times of medical equipment in real-time. For instance, AI applications can maximize X-Ray or magnetic resonance tomography device utilization (use case CA3). Besides, AI applications can enable a dynamic replanning of device utilization by including absence or waiting times and predicting interruptions. Intelligent resource optimization may include various key variables (e.g., the maximized lifespan of a radiation scanner) [ 48 ]. Optimized device utilization reduces the time periods when the device is not utilized, and thus, losses are made.

Optimized organizational capacities are possible due to AI applications breaking up static key performance indicators and finding more dynamic measuring approaches for the required workflow changes (E5, E10). The utilization of capacities in hospitals relies on various known and unknown parameters, which are often interdependent [ 80 ]. AI applications can detect and optimize these dependencies to manage capacity. An example is the optimization of clinical occupancy in the hospital (use case CA3), which has a strong impact on cost. E5 adds that the integration of AI applications may increase the reliability of planning HC resources since they can predict capacity trends from historical occupancy rates. Optimized planning of capacities can prevent capacities from remaining unused and fixed costs from being offset by no revenue.

Unleashing personnel capabilities is enabled by AI applications performing analytical and administrative tasks, relieving caregivers’ workload (E8, E10, E11). E7 validates that “our conviction is […] that administrational tasks generate the greatest added value and benefit for doctors and caregivers.” Administrative tasks include the creation of case summaries (use case CA4) or automated de-identification of private health information in electronic health records (use case BR2) [ 54 ]. E8 says that resource optimization enables “more time for direct contact with patients.”

Knowledge discovery

Knowledge discovery follows the business objectives that increase perception and access to novel and previously unrevealed information. AI applications might synthesize and contextualize medical knowledge to create uniform or equalized semantics of information (E5, E11). This semantics enables a translation of knowledge for specific users.

Detection of similarities is enabled by AI applications identifying entities with similar features. AI applications can screen complex and nonlinear databases to identify reoccurring patterns without any a priori understanding of the data (E3). These similarities generate valuable knowledge, which can be applied to enhance scientific research processes such as drug development (use case BR1). In drug development, AI applications can facilitate ligand-based screening to detect new active molecules based on similarities compared with already existing molecular properties. This increases the effectiveness of drug design and reduces risks in clinical trials [ 6 ].

Exploration of new correlations is facilitated by AI applications identifying relationships in data. In diagnostics, AI applications can analyze facial photographs to accurately identify genotype–phenotype correlations and, thus, increase the detection rate of rare diseases (use case DD7). E8 states the potential of AI applications in the field of knowledge discovery: “Well, if you are researching in any medical area, then everybody aims to understand and describe phenomena because science always demands a certain causation.” However, it is crucial to develop transparent and intelligible inferences that are comprehensible for HC professionals and researchers. Exploring new correlations improves diagnoses of rare diseases and ensures earlier treatment.

After describing each business objective and value proposition, we summarize the AI use cases’ contributions to the value propositions in Table  3 .

By revealing 15 business objectives that translate into six value propositions, we contribute to the academic discourse on the value creation of AI (e.g. [ 81 ] and provide prescriptive knowledge on AI applications' value propositions in the HC domain. Our discourse also emphasizes that our findings are not only relevant to the field of value creation research but can also be helpful for adoption research. The value propositions we have identified can be a good starting point to accelerate the adoption of AI in HC, as the understanding of potential value propositions that we foster could mitigate some of the current obstacles to the adoption of AI applications in HC. For example, our findings may help to mitigate the obstacle “added value”, which is presented in the study by Hennrich et al.38 [ 38 ] as users’ concerns that AI might create more burden than benefits.

Further, we deliver valuable implications for practice and provide a comprehensive picture of how organizations in the context of HC can achieve business value with AI applications from a managerial level, which has been missing until now. We guide HC organizations in evaluating their AI applications or those of the competition to assess AI investment decisions and align their AI application portfolio toward an overarching strategy. These results will foster the adoption of AI applications as HC organizations can now understand how they can unfold AI applications’ capabilities into business value. In case a hospital’s major strategy is to reduce patient risks due to limited personal capacities, it might be beneficial for them to invest in AI applications that reduce side effects by calculating medication dosages (use case T2). If an HC organization currently faces issues with overcrowded emergency rooms, the HC organization might acquire AI applications that increase information delivery and help patients decide if and when they should visit the hospital (use case T3) to increase patients’ self-management and, in turn, improve triage. Besides, our findings also offer valuable insights for AI developers. Addressing issues such as transparency and the alignment of AI applications with the needs of HC professionals is crucial. Adapting AI solutions to the specific requirements of the HC sector ensures responsible integration and thus the realization of the expected values.

A closer look at the current challenges in the HC sector reveals that new solutions to mitigate them and improve value creation are needed. Given that a nurse, for example, dedicates a substantial 25% of their working hours to administrative tasks [ 17 ], the rationale behind the respondents’ (E7) recognition of “the greatest added value” in utilizing AI applications for administrative purposes becomes evident. The potential of AI applications in streamlining administrative tasks lies in creating additional time for meaningful patient interactions. Acknowledging the significant impact of the doctor-patient interpersonal relationship on both the patient’s well-being and the processes of diagnosis and healing, as elucidated by Buck et al. [ 82 ] in their interview study, the physicians interviewed emphasized that the mere presence of the doctor in the same room often alleviates the patient’s problems. Consequently, it becomes apparent that the intangible value of AI applications plays a crucial role in the context of HC and is an important factor in the investment decision as to where an AI application should be deployed.

The interviews also indicate that the special context of the HC sector leads to concerns regarding the use of AI applications. For example, one interviewee emphasized a fundamental characteristic of medical staff by pointing out that physicians have a natural desire to understand all phenomena (E8). AI applications, however, are currently struggling with the challenge of transparency. This challenge is described by the so-called black box problem, a phenomenon that makes it impossible to decipher the underlying algorithms that lead to a particular recommendation [ 37 ]. The lack of transparency and the resulting lack of intervention options for medical staff can lead to incorrect decisions by the AI application, which may cause considerable damage. Aware of these risks, physicians are currently struggling with trust issues in AI applications [ 72 ]. The numerous opportunities for value creation through AI applications in HC are offset by the significant risk of causing considerable harm to patients if the technology is not yet fully mature. Ultimately, it remains essential to keep in mind that there are many ethical questions to be answered [ 83 ], and AI applications are still facing many obstacles [ 38 ] that must be overcome in order to realize the expected values and avoid serious harm. One important first step in mitigating the obstacles is disseminating the concerns and risks to relevant stakeholders, emphasizing the urgency for collaborative scientific and public monitoring efforts [ 84 ]. However, keeping these obstacles in mind, by providing prescriptive knowledge, we enhance the understanding of AI’s value creation paths in the HC industry and thus help to drive AI integration forward. For example, looking at the value proposition risk reduced patient care , we demonstrate that this value proposition is determined by four business objectives: precise decision support , detection of misconduct, reduction of side effects, and reduction of invasiveness . Similarly, the AI application’s capability to analyze data more accurately in diagnosis (use case DD1) enables the business objective precise decision support , thereby reducing risks in patient care. Another mechanism can be seen, for example, considering the business objective task execution , which leads to the value proposition process acceleration . The ability of AI applications to rapidly analyze large amounts of data and recognize patterns in biomedical research (use case BR1) allows a faster drug development process.

Further research

By investigating the value creation mechanism of AI applications for HC organizations, we not only make an important contribution to research and practice but also create a valuable foundation for future studies. While we have systematically identified the relations between the business objectives and value propositions, further research is needed to investigate how the business objectives themselves are determined. While the examination of AI capabilities was not the primary research focus, we found first evidence in the use cases that indicates AI technology’s unique capabilities (e.g., to make diagnoses accurate, faster, and more objective) that foster one or several business objectives (e.g., rapid task execution, precise decision support) and unlock one or several value propositions (e.g., Risk-reduced patient care, process acceleration ). In subsequent research, we aim to integrate these into the value creation mechanism by identifying which specific AI capabilities drive business objectives, thereby advancing the understanding of how AI applications in HC create value propositions.

Limitations

This study is subject to certain limitations of methodological and conceptual nature. First, while our methodological approach covers an in-depth analysis of 21 AI use cases, extending the sample of AI use cases would foster the generalizability of the results. This is especially important regarding the latest developments on generative AI and its newcoming use cases. However, our results demonstrate that these AI use cases already provide rich information to derive 15 business objectives, which translate into six value propositions. Second, while many papers assume the potential of AI applications to create value propositions, only a few papers explicitly focus on the value creation and capture mechanisms. To compensate for this paucity of appropriate papers, we used 11 expert interviews to enrich and evaluate the results. Besides, these interviews ensured the practical relevance and reliability of the derived results. Third, we acknowledge limitations of conceptual nature. Our study predominantly takes an optimistic perspective on AI applications in medicine. While we discuss the potential benefits and value propositions in detail, it is important to emphasize that there are still significant barriers and risks currently associated with AI applications that need to be addressed before the identified values can be realized. Furthermore, our investigation is limited because we derive the expected value of AI applications without having extensive real-world use cases to evaluate. It is important to emphasize that our findings are preliminary, and critical reassessment will be essential as the broader implementation of AI applications in medical practice progresses. These limitations emphasize the need for ongoing research and monitoring to understand the true value of AI applications in HC fully.

Conclusions

This study aimed to investigate how AI applications can create value for HC organizations. After elaborating on a diverse and comprehensive set of AI use cases, we are confident that AI applications can create value by making HC, among others, more precise, individualized, self-determined, faster, resource-optimized, and data insight-driven. Especially with regard to the mounting challenges of the industry, such as the aging population and the resulting increase in HC professionals’ workloads, the integration of AI applications and the expected benefits have become more critical than ever. Based on the systematic literature review and expert interviews, we derived 15 business objectives that translate into the following six value propositions that describe how HC organizations can capture the value of AI applications: risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery .

By presenting and discussing our results, we enhance the understanding of how HC organizations can unlock AI applications’ value proposition. We provide HC organizations with valuable insights to help them strategically assess their AI applications as well as those deployed by competitors at a management level. Our goal is to facilitate informed decision-making regarding AI investments and enable HC organizations to align their AI application portfolios with a comprehensive and overarching strategy. However, even if various value proposition-creating scenarios exist, AI applications are not yet fully mature in every area or ready for widespread use. Ultimately, it remains essential to take a critical look at which AI applications can be used for which task at which point in time to achieve the promised value. Nonetheless, we are confident that we can shed more light on the value proposition-capturing mechanism and, therefore, support AI application adoption in HC.

Availability of data and materials

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Artificial Intelligence

Machine Learning

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JH initially composed the introduction, background, and discussion sections; PH contributed to the analysis design, supported data analysis, and critically reviewed the manuscript; ER conducted data collection and analysis and produced the initial draft of the methodology section; NU edited and critically reviewed the manuscript and provided guidance. All authors read and approved the final manuscript.

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Hennrich, J., Ritz, E., Hofmann, P. et al. Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study. BMC Health Serv Res 24 , 420 (2024). https://doi.org/10.1186/s12913-024-10894-4

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Received : 26 October 2023

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DOI : https://doi.org/10.1186/s12913-024-10894-4

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