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Background of The Study – Examples and Writing Guide

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Background of The Study

Definition:

Background of the study refers to the context, circumstances, and history that led to the research problem or topic being studied. It provides the reader with a comprehensive understanding of the subject matter and the significance of the study.

The background of the study usually includes a discussion of the relevant literature, the gap in knowledge or understanding, and the research questions or hypotheses to be addressed. It also highlights the importance of the research topic and its potential contributions to the field. A well-written background of the study sets the stage for the research and helps the reader to appreciate the need for the study and its potential significance.

How to Write Background of The Study

Here are some steps to help you write the background of the study:

Identify the Research Problem

Start by identifying the research problem you are trying to address. This problem should be significant and relevant to your field of study.

Provide Context

Once you have identified the research problem, provide some context. This could include the historical, social, or political context of the problem.

Review Literature

Conduct a thorough review of the existing literature on the topic. This will help you understand what has been studied and what gaps exist in the current research.

Identify Research Gap

Based on your literature review, identify the gap in knowledge or understanding that your research aims to address. This gap will be the focus of your research question or hypothesis.

State Objectives

Clearly state the objectives of your research . These should be specific, measurable, achievable, relevant, and time-bound (SMART).

Discuss Significance

Explain the significance of your research. This could include its potential impact on theory , practice, policy, or society.

Finally, summarize the key points of the background of the study. This will help the reader understand the research problem, its context, and its significance.

How to Write Background of The Study in Proposal

The background of the study is an essential part of any proposal as it sets the stage for the research project and provides the context and justification for why the research is needed. Here are the steps to write a compelling background of the study in your proposal:

• Identify the problem: Clearly state the research problem or gap in the current knowledge that you intend to address through your research.
• Provide context: Provide a brief overview of the research area and highlight its significance in the field.
• Review literature: Summarize the relevant literature related to the research problem and provide a critical evaluation of the current state of knowledge.
• Identify gaps : Identify the gaps or limitations in the existing literature and explain how your research will contribute to filling these gaps.
• Justify the study : Explain why your research is important and what practical or theoretical contributions it can make to the field.
• Highlight objectives: Clearly state the objectives of the study and how they relate to the research problem.
• Discuss methodology: Provide an overview of the methodology you will use to collect and analyze data, and explain why it is appropriate for the research problem.
• Conclude : Summarize the key points of the background of the study and explain how they support your research proposal.

How to Write Background of The Study In Thesis

The background of the study is a critical component of a thesis as it provides context for the research problem, rationale for conducting the study, and the significance of the research. Here are some steps to help you write a strong background of the study:

• Identify the research problem : Start by identifying the research problem that your thesis is addressing. What is the issue that you are trying to solve or explore? Be specific and concise in your problem statement.
• Review the literature: Conduct a thorough review of the relevant literature on the topic. This should include scholarly articles, books, and other sources that are directly related to your research question.
• I dentify gaps in the literature: After reviewing the literature, identify any gaps in the existing research. What questions remain unanswered? What areas have not been explored? This will help you to establish the need for your research.
• Establish the significance of the research: Clearly state the significance of your research. Why is it important to address this research problem? What are the potential implications of your research? How will it contribute to the field?
• Provide an overview of the research design: Provide an overview of the research design and methodology that you will be using in your study. This should include a brief explanation of the research approach, data collection methods, and data analysis techniques.
• State the research objectives and research questions: Clearly state the research objectives and research questions that your study aims to answer. These should be specific, measurable, achievable, relevant, and time-bound.
• Summarize the chapter: Summarize the chapter by highlighting the key points and linking them back to the research problem, significance of the study, and research questions.

How to Write Background of The Study in Research Paper

Here are the steps to write the background of the study in a research paper:

• Identify the research problem: Start by identifying the research problem that your study aims to address. This can be a particular issue, a gap in the literature, or a need for further investigation.
• Conduct a literature review: Conduct a thorough literature review to gather information on the topic, identify existing studies, and understand the current state of research. This will help you identify the gap in the literature that your study aims to fill.
• Explain the significance of the study: Explain why your study is important and why it is necessary. This can include the potential impact on the field, the importance to society, or the need to address a particular issue.
• Provide context: Provide context for the research problem by discussing the broader social, economic, or political context that the study is situated in. This can help the reader understand the relevance of the study and its potential implications.
• State the research questions and objectives: State the research questions and objectives that your study aims to address. This will help the reader understand the scope of the study and its purpose.
• Summarize the methodology : Briefly summarize the methodology you used to conduct the study, including the data collection and analysis methods. This can help the reader understand how the study was conducted and its reliability.

Examples of Background of The Study

Here are some examples of the background of the study:

Problem : The prevalence of obesity among children in the United States has reached alarming levels, with nearly one in five children classified as obese.

Significance : Obesity in childhood is associated with numerous negative health outcomes, including increased risk of type 2 diabetes, cardiovascular disease, and certain cancers.

Gap in knowledge : Despite efforts to address the obesity epidemic, rates continue to rise. There is a need for effective interventions that target the unique needs of children and their families.

Problem : The use of antibiotics in agriculture has contributed to the development of antibiotic-resistant bacteria, which poses a significant threat to human health.

Significance : Antibiotic-resistant infections are responsible for thousands of deaths each year and are a major public health concern.

Gap in knowledge: While there is a growing body of research on the use of antibiotics in agriculture, there is still much to be learned about the mechanisms of resistance and the most effective strategies for reducing antibiotic use.

Edxample 3:

Problem : Many low-income communities lack access to healthy food options, leading to high rates of food insecurity and diet-related diseases.

Significance : Poor nutrition is a major contributor to chronic diseases such as obesity, type 2 diabetes, and cardiovascular disease.

Gap in knowledge : While there have been efforts to address food insecurity, there is a need for more research on the barriers to accessing healthy food in low-income communities and effective strategies for increasing access.

Examples of Background of The Study In Research

Here are some real-life examples of how the background of the study can be written in different fields of study:

Example 1 : “There has been a significant increase in the incidence of diabetes in recent years. This has led to an increased demand for effective diabetes management strategies. The purpose of this study is to evaluate the effectiveness of a new diabetes management program in improving patient outcomes.”

Example 2 : “The use of social media has become increasingly prevalent in modern society. Despite its popularity, little is known about the effects of social media use on mental health. This study aims to investigate the relationship between social media use and mental health in young adults.”

Example 3: “Despite significant advancements in cancer treatment, the survival rate for patients with pancreatic cancer remains low. The purpose of this study is to identify potential biomarkers that can be used to improve early detection and treatment of pancreatic cancer.”

Examples of Background of The Study in Proposal

Here are some real-time examples of the background of the study in a proposal:

Example 1 : The prevalence of mental health issues among university students has been increasing over the past decade. This study aims to investigate the causes and impacts of mental health issues on academic performance and wellbeing.

Example 2 : Climate change is a global issue that has significant implications for agriculture in developing countries. This study aims to examine the adaptive capacity of smallholder farmers to climate change and identify effective strategies to enhance their resilience.

Example 3 : The use of social media in political campaigns has become increasingly common in recent years. This study aims to analyze the effectiveness of social media campaigns in mobilizing young voters and influencing their voting behavior.

Example 4 : Employee turnover is a major challenge for organizations, especially in the service sector. This study aims to identify the key factors that influence employee turnover in the hospitality industry and explore effective strategies for reducing turnover rates.

Examples of Background of The Study in Thesis

Here are some real-time examples of the background of the study in the thesis:

Example 1 : “Women’s participation in the workforce has increased significantly over the past few decades. However, women continue to be underrepresented in leadership positions, particularly in male-dominated industries such as technology. This study aims to examine the factors that contribute to the underrepresentation of women in leadership roles in the technology industry, with a focus on organizational culture and gender bias.”

Example 2 : “Mental health is a critical component of overall health and well-being. Despite increased awareness of the importance of mental health, there are still significant gaps in access to mental health services, particularly in low-income and rural communities. This study aims to evaluate the effectiveness of a community-based mental health intervention in improving mental health outcomes in underserved populations.”

Example 3: “The use of technology in education has become increasingly widespread, with many schools adopting online learning platforms and digital resources. However, there is limited research on the impact of technology on student learning outcomes and engagement. This study aims to explore the relationship between technology use and academic achievement among middle school students, as well as the factors that mediate this relationship.”

Examples of Background of The Study in Research Paper

Here are some examples of how the background of the study can be written in various fields:

Example 1: The prevalence of obesity has been on the rise globally, with the World Health Organization reporting that approximately 650 million adults were obese in 2016. Obesity is a major risk factor for several chronic diseases such as diabetes, cardiovascular diseases, and cancer. In recent years, several interventions have been proposed to address this issue, including lifestyle changes, pharmacotherapy, and bariatric surgery. However, there is a lack of consensus on the most effective intervention for obesity management. This study aims to investigate the efficacy of different interventions for obesity management and identify the most effective one.

Example 2: Antibiotic resistance has become a major public health threat worldwide. Infections caused by antibiotic-resistant bacteria are associated with longer hospital stays, higher healthcare costs, and increased mortality. The inappropriate use of antibiotics is one of the main factors contributing to the development of antibiotic resistance. Despite numerous efforts to promote the rational use of antibiotics, studies have shown that many healthcare providers continue to prescribe antibiotics inappropriately. This study aims to explore the factors influencing healthcare providers’ prescribing behavior and identify strategies to improve antibiotic prescribing practices.

Example 3: Social media has become an integral part of modern communication, with millions of people worldwide using platforms such as Facebook, Twitter, and Instagram. Social media has several advantages, including facilitating communication, connecting people, and disseminating information. However, social media use has also been associated with several negative outcomes, including cyberbullying, addiction, and mental health problems. This study aims to investigate the impact of social media use on mental health and identify the factors that mediate this relationship.

Purpose of Background of The Study

The primary purpose of the background of the study is to help the reader understand the rationale for the research by presenting the historical, theoretical, and empirical background of the problem.

More specifically, the background of the study aims to:

• Provide a clear understanding of the research problem and its context.
• Identify the gap in knowledge that the study intends to fill.
• Establish the significance of the research problem and its potential contribution to the field.
• Highlight the key concepts, theories, and research findings related to the problem.
• Provide a rationale for the research questions or hypotheses and the research design.
• Identify the limitations and scope of the study.

When to Write Background of The Study

The background of the study should be written early on in the research process, ideally before the research design is finalized and data collection begins. This allows the researcher to clearly articulate the rationale for the study and establish a strong foundation for the research.

The background of the study typically comes after the introduction but before the literature review section. It should provide an overview of the research problem and its context, and also introduce the key concepts, theories, and research findings related to the problem.

Writing the background of the study early on in the research process also helps to identify potential gaps in knowledge and areas for further investigation, which can guide the development of the research questions or hypotheses and the research design. By establishing the significance of the research problem and its potential contribution to the field, the background of the study can also help to justify the research and secure funding or support from stakeholders.

Advantage of Background of The Study

The background of the study has several advantages, including:

• Provides context: The background of the study provides context for the research problem by highlighting the historical, theoretical, and empirical background of the problem. This allows the reader to understand the research problem in its broader context and appreciate its significance.
• Identifies gaps in knowledge: By reviewing the existing literature related to the research problem, the background of the study can identify gaps in knowledge that the study intends to fill. This helps to establish the novelty and originality of the research and its potential contribution to the field.
• Justifies the research : The background of the study helps to justify the research by demonstrating its significance and potential impact. This can be useful in securing funding or support for the research.
• Guides the research design: The background of the study can guide the development of the research questions or hypotheses and the research design by identifying key concepts, theories, and research findings related to the problem. This ensures that the research is grounded in existing knowledge and is designed to address the research problem effectively.
• Establishes credibility: By demonstrating the researcher’s knowledge of the field and the research problem, the background of the study can establish the researcher’s credibility and expertise, which can enhance the trustworthiness and validity of the research.

Disadvantages of Background of The Study

Some Disadvantages of Background of The Study are as follows:

• Time-consuming : Writing a comprehensive background of the study can be time-consuming, especially if the research problem is complex and multifaceted. This can delay the research process and impact the timeline for completing the study.
• Repetitive: The background of the study can sometimes be repetitive, as it often involves summarizing existing research and theories related to the research problem. This can be tedious for the reader and may make the section less engaging.
• Limitations of existing research: The background of the study can reveal the limitations of existing research related to the problem. This can create challenges for the researcher in developing research questions or hypotheses that address the gaps in knowledge identified in the background of the study.
• Bias : The researcher’s biases and perspectives can influence the content and tone of the background of the study. This can impact the reader’s perception of the research problem and may influence the validity of the research.
• Accessibility: Accessing and reviewing the literature related to the research problem can be challenging, especially if the researcher does not have access to a comprehensive database or if the literature is not available in the researcher’s language. This can limit the depth and scope of the background of the study.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to Write an Effective Background of the Study: A Comprehensive Guide

Table of Contents

The background of the study in a research paper offers a clear context, highlighting why the research is essential and the problem it aims to address.

As a researcher, this foundational section is essential for you to chart the course of your study, Moreover, it allows readers to understand the importance and path of your research.

Whether in academic communities or to the general public, a well-articulated background aids in communicating the essence of the research effectively.

While it may seem straightforward, crafting an effective background requires a blend of clarity, precision, and relevance. Therefore, this article aims to be your guide, offering insights into:

• Understanding the concept of the background of the study.
• Learning how to craft a compelling background effectively.
• Identifying and sidestepping common pitfalls in writing the background.
• Exploring practical examples that bring the theory to life.
• Enhancing both your writing and reading of academic papers.

Keeping these compelling insights in mind, let's delve deeper into the details of the empirical background of the study, exploring its definition, distinctions, and the art of writing it effectively.

What is the background of the study?

The background of the study is placed at the beginning of a research paper. It provides the context, circumstances, and history that led to the research problem or topic being explored.

It offers readers a snapshot of the existing knowledge on the topic and the reasons that spurred your current research.

When crafting the background of your study, consider the following questions.

• What's the context of your research?
• Which previous research will you refer to?
• Are there any knowledge gaps in the existing relevant literature?
• How will you justify the need for your current research?
• Have you concisely presented the research question or problem?

In a typical research paper structure, after presenting the background, the introduction section follows. The introduction delves deeper into the specific objectives of the research and often outlines the structure or main points that the paper will cover.

Together, they create a cohesive starting point, ensuring readers are well-equipped to understand the subsequent sections of the research paper.

While the background of the study and the introduction section of the research manuscript may seem similar and sometimes even overlap, each serves a unique purpose in the research narrative.

Difference between background and introduction

A well-written background of the study and introduction are preliminary sections of a research paper and serve distinct purposes.

Here’s a detailed tabular comparison between the two of them.

What is the relevance of the background of the study?

It is necessary for you to provide your readers with the background of your research. Without this, readers may grapple with questions such as: Why was this specific research topic chosen? What led to this decision? Why is this study relevant? Is it worth their time?

Such uncertainties can deter them from fully engaging with your study, leading to the rejection of your research paper. Additionally, this can diminish its impact in the academic community, and reduce its potential for real-world application or policy influence .

To address these concerns and offer clarity, the background section plays a pivotal role in research papers.

The background of the study in research is important as it:

• Provides context: It offers readers a clear picture of the existing knowledge, helping them understand where the current research fits in.
• Highlights relevance: By detailing the reasons for the research, it underscores the study's significance and its potential impact.
• Guides the narrative: The background shapes the narrative flow of the paper, ensuring a logical progression from what's known to what the research aims to uncover.
• Enhances engagement: A well-crafted background piques the reader's interest, encouraging them to delve deeper into the research paper.
• Aids in comprehension: By setting the scenario, it aids readers in better grasping the research objectives, methodologies, and findings.

How to write the background of the study in a research paper?

The journey of presenting a compelling argument begins with the background study. This section holds the power to either captivate or lose the reader's interest.

An effectively written background not only provides context but also sets the tone for the entire research paper. It's the bridge that connects a broad topic to a specific research question, guiding readers through the logic behind the study.

But how does one craft a background of the study that resonates, informs, and engages?

Here, we’ll discuss how to write an impactful background study, ensuring your research stands out and captures the attention it deserves.

Identify the research problem

The first step is to start pinpointing the specific issue or gap you're addressing. This should be a significant and relevant problem in your field.

A well-defined problem is specific, relevant, and significant to your field. It should resonate with both experts and readers.

Here’s more on how to write an effective research problem .

Provide context

Here, you need to provide a broader perspective, illustrating how your research aligns with or contributes to the overarching context or the wider field of study. A comprehensive context is grounded in facts, offers multiple perspectives, and is relatable.

In addition to stating facts, you should weave a story that connects key concepts from the past, present, and potential future research. For instance, consider the following approach.

• Offer a brief history of the topic, highlighting major milestones or turning points that have shaped the current landscape.
• Discuss contemporary developments or current trends that provide relevant information to your research problem. This could include technological advancements, policy changes, or shifts in societal attitudes.
• Highlight the views of different stakeholders. For a topic like sustainable agriculture, this could mean discussing the perspectives of farmers, environmentalists, policymakers, and consumers.
• If relevant, compare and contrast global trends with local conditions and circumstances. This can offer readers a more holistic understanding of the topic.

Literature review

For this step, you’ll deep dive into the existing literature on the same topic. It's where you explore what scholars, researchers, and experts have already discovered or discussed about your topic.

Conducting a thorough literature review isn't just a recap of past works. To elevate its efficacy, it's essential to analyze the methods, outcomes, and intricacies of prior research work, demonstrating a thorough engagement with the existing body of knowledge.

• Instead of merely listing past research study, delve into their methodologies, findings, and limitations. Highlight groundbreaking studies and those that had contrasting results.
• Try to identify patterns. Look for recurring themes or trends in the literature. Are there common conclusions or contentious points?
• The next step would be to connect the dots. Show how different pieces of research relate to each other. This can help in understanding the evolution of thought on the topic.

By showcasing what's already known, you can better highlight the background of the study in research.

Highlight the research gap

This step involves identifying the unexplored areas or unanswered questions in the existing literature. Your research seeks to address these gaps, providing new insights or answers.

A clear research gap shows you've thoroughly engaged with existing literature and found an area that needs further exploration.

How can you efficiently highlight the research gap?

• Find the overlooked areas. Point out topics or angles that haven't been adequately addressed.
• Highlight questions that have emerged due to recent developments or changing circumstances.
• Identify areas where insights from other fields might be beneficial but haven't been explored yet.

State your objectives

Here, it’s all about laying out your game plan — What do you hope to achieve with your research? You need to mention a clear objective that’s specific, actionable, and directly tied to the research gap.

How to state your objectives?

• List the primary questions guiding your research.
• If applicable, state any hypotheses or predictions you aim to test.
• Specify what you hope to achieve, whether it's new insights, solutions, or methodologies.

Discuss the significance

This step describes your 'why'. Why is your research important? What broader implications does it have?

The significance of “why” should be both theoretical (adding to the existing literature) and practical (having real-world implications).

How do we effectively discuss the significance?

• Discuss how your research adds to the existing body of knowledge.
• Highlight how your findings could be applied in real-world scenarios, from policy changes to on-ground practices.
• Point out how your research could pave the way for further studies or open up new areas of exploration.

Summarize your points

A concise summary acts as a bridge, smoothly transitioning readers from the background to the main body of the paper. This step is a brief recap, ensuring that readers have grasped the foundational concepts.

How to summarize your study?

• Revisit the key points discussed, from the research problem to its significance.
• Prepare the reader for the subsequent sections, ensuring they understand the research's direction.

Include examples for better understanding

Research and come up with real-world or hypothetical examples to clarify complex concepts or to illustrate the practical applications of your research. Relevant examples make abstract ideas tangible, aiding comprehension.

How to include an effective example of the background of the study?

• Use past events or scenarios to explain concepts.
• Craft potential scenarios to demonstrate the implications of your findings.
• Use comparisons to simplify complex ideas, making them more relatable.

Crafting a compelling background of the study in research is about striking the right balance between providing essential context, showcasing your comprehensive understanding of the existing literature, and highlighting the unique value of your research .

While writing the background of the study, keep your readers at the forefront of your mind. Every piece of information, every example, and every objective should be geared toward helping them understand and appreciate your research.

How to avoid mistakes in the background of the study in research?

To write a well-crafted background of the study, you should be aware of the following potential research pitfalls .

• Stay away from ambiguity. Always assume that your reader might not be familiar with intricate details about your topic.
• Avoid discussing unrelated themes. Stick to what's directly relevant to your research problem.
• Ensure your background is well-organized. Information should flow logically, making it easy for readers to follow.
• While it's vital to provide context, avoid overwhelming the reader with excessive details that might not be directly relevant to your research problem.
• Ensure you've covered the most significant and relevant studies i` n your field. Overlooking key pieces of literature can make your background seem incomplete.
• Aim for a balanced presentation of facts, and avoid showing overt bias or presenting only one side of an argument.
• While academic paper often involves specialized terms, ensure they're adequately explained or use simpler alternatives when possible.
• Every claim or piece of information taken from existing literature should be appropriately cited. Failing to do so can lead to issues of plagiarism.
• Avoid making the background too lengthy. While thoroughness is appreciated, it should not come at the expense of losing the reader's interest. Maybe prefer to keep it to one-two paragraphs long.
• Especially in rapidly evolving fields, it's crucial to ensure that your literature review section is up-to-date and includes the latest research.

Example of an effective background of the study

Let's consider a topic: "The Impact of Online Learning on Student Performance." The ideal background of the study section for this topic would be as follows.

In the last decade, the rise of the internet has revolutionized many sectors, including education. Online learning platforms, once a supplementary educational tool, have now become a primary mode of instruction for many institutions worldwide. With the recent global events, such as the COVID-19 pandemic, there has been a rapid shift from traditional classroom learning to online modes, making it imperative to understand its effects on student performance.

Previous studies have explored various facets of online learning, from its accessibility to its flexibility. However, there is a growing need to assess its direct impact on student outcomes. While some educators advocate for its benefits, citing the convenience and vast resources available, others express concerns about potential drawbacks, such as reduced student engagement and the challenges of self-discipline.

This research aims to delve deeper into this debate, evaluating the true impact of online learning on student performance.

Why is this example considered as an effective background section of a research paper?

This background section example effectively sets the context by highlighting the rise of online learning and its increased relevance due to recent global events. It references prior research on the topic, indicating a foundation built on existing knowledge.

By presenting both the potential advantages and concerns of online learning, it establishes a balanced view, leading to the clear purpose of the study: to evaluate the true impact of online learning on student performance.

As we've explored, writing an effective background of the study in research requires clarity, precision, and a keen understanding of both the broader landscape and the specific details of your topic.

From identifying the research problem, providing context, reviewing existing literature to highlighting research gaps and stating objectives, each step is pivotal in shaping the narrative of your research. And while there are best practices to follow, it's equally crucial to be aware of the pitfalls to avoid.

Remember, writing or refining the background of your study is essential to engage your readers, familiarize them with the research context, and set the ground for the insights your research project will unveil.

Drawing from all the important details, insights and guidance shared, you're now in a strong position to craft a background of the study that not only informs but also engages and resonates with your readers.

Now that you've a clear understanding of what the background of the study aims to achieve, the natural progression is to delve into the next crucial component — write an effective introduction section of a research paper. Read here .

Frequently Asked Questions

The background of the study should include a clear context for the research, references to relevant previous studies, identification of knowledge gaps, justification for the current research, a concise overview of the research problem or question, and an indication of the study's significance or potential impact.

The background of the study is written to provide readers with a clear understanding of the context, significance, and rationale behind the research. It offers a snapshot of existing knowledge on the topic, highlights the relevance of the study, and sets the stage for the research questions and objectives. It ensures that readers can grasp the importance of the research and its place within the broader field of study.

The background of the study is a section in a research paper that provides context, circumstances, and history leading to the research problem or topic being explored. It presents existing knowledge on the topic and outlines the reasons that spurred the current research, helping readers understand the research's foundation and its significance in the broader academic landscape.

The number of paragraphs in the background of the study can vary based on the complexity of the topic and the depth of the context required. Typically, it might range from 3 to 5 paragraphs, but in more detailed or complex research papers, it could be longer. The key is to ensure that all relevant information is presented clearly and concisely, without unnecessary repetition.

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What is the Background of a Study and How Should it be Written?

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Table of Contents

The background of a study is one of the most important components of a research paper. The quality of the background determines whether the reader will be interested in the rest of the study. Thus, to ensure that the audience is invested in reading the entire research paper, it is important to write an appealing and effective background. So, what constitutes the background of a study, and how must it be written?

What is the background of a study?

The background of a study is the first section of the paper and establishes the context underlying the research. It contains the rationale, the key problem statement, and a brief overview of research questions that are addressed in the rest of the paper. The background forms the crux of the study because it introduces an unaware audience to the research and its importance in a clear and logical manner. At times, the background may even explore whether the study builds on or refutes findings from previous studies. Any relevant information that the readers need to know before delving into the paper should be made available to them in the background.

How is a background different from the introduction?

The introduction of your research paper is presented before the background. Let’s find out what factors differentiate the background from the introduction.

• The introduction only contains preliminary data about the research topic and does not state the purpose of the study. On the contrary, the background clarifies the importance of the study in detail.
• The introduction provides an overview of the research topic from a broader perspective, while the background provides a detailed understanding of the topic.
• The introduction should end with the mention of the research questions, aims, and objectives of the study. In contrast, the background follows no such format and only provides essential context to the study.

How should one write the background of a research paper?

The length and detail presented in the background varies for different research papers, depending on the complexity and novelty of the research topic. At times, a simple background suffices, even if the study is complex. Before writing and adding details in the background, take a note of these additional points:

• Start with a strong beginning: Begin the background by defining the research topic and then identify the target audience.
• Cover key components: Explain all theories, concepts, terms, and ideas that may feel unfamiliar to the target audience thoroughly.
• Take note of important prerequisites: Go through the relevant literature in detail. Take notes while reading and cite the sources.
• Maintain a balance: Make sure that the background is focused on important details, but also appeals to a broader audience.
• Include historical data: Current issues largely originate from historical events or findings. If the research borrows information from a historical context, add relevant data in the background.
• Explain novelty: If the research study or methodology is unique or novel, provide an explanation that helps to understand the research better.
• Increase engagement: To make the background engaging, build a story around the central theme of the research

Avoid these mistakes while writing the background:

• Ambiguity: Don’t be ambiguous. While writing, assume that the reader does not understand any intricate detail about your research.
• Unrelated themes: Steer clear from topics that are not related to the key aspects of your research topic.
• Poor organization: Do not place information without a structure. Make sure that the background reads in a chronological manner and organize the sub-sections so that it flows well.

Writing the background for a research paper should not be a daunting task. But directions to go about it can always help. At Elsevier Author Services we provide essential insights on how to write a high quality, appealing, and logically structured paper for publication, beginning with a robust background. For further queries, contact our experts now!

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Organizing Your Social Sciences Research Paper

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Background information identifies and describes the history and nature of a well-defined research problem with reference to contextualizing existing literature. The background information should indicate the root of the problem being studied, appropriate context of the problem in relation to theory, research, and/or practice , its scope, and the extent to which previous studies have successfully investigated the problem, noting, in particular, where gaps exist that your study attempts to address. Background information does not replace the literature review section of a research paper; it is intended to place the research problem within a specific context and an established plan for its solution.

Fitterling, Lori. Researching and Writing an Effective Background Section of a Research Paper. Kansas City University of Medicine & Biosciences; Creating a Research Paper: How to Write the Background to a Study. DurousseauElectricalInstitute.com; Background Information: Definition of Background Information. Literary Devices Definition and Examples of Literary Terms.

Importance of Having Enough Background Information

Background information expands upon the key points stated in the beginning of your introduction but is not intended to be the main focus of the paper. It generally supports the question, what is the most important information the reader needs to understand before continuing to read the paper? Sufficient background information helps the reader determine if you have a basic understanding of the research problem being investigated and promotes confidence in the overall quality of your analysis and findings. This information provides the reader with the essential context needed to conceptualize the research problem and its significance before moving on to a more thorough analysis of prior research.

Forms of contextualization included in background information can include describing one or more of the following:

• Cultural -- placed within the learned behavior of a specific group or groups of people.
• Economic -- of or relating to systems of production and management of material wealth and/or business activities.
• Gender -- located within the behavioral, cultural, or psychological traits typically associated with being self-identified as male, female, or other form of  gender expression.
• Historical -- the time in which something takes place or was created and how the condition of time influences how you interpret it.
• Interdisciplinary -- explanation of theories, concepts, ideas, or methodologies borrowed from other disciplines applied to the research problem rooted in a discipline other than the discipline where your paper resides.
• Philosophical -- clarification of the essential nature of being or of phenomena as it relates to the research problem.
• Physical/Spatial -- reflects the meaning of space around something and how that influences how it is understood.
• Political -- concerns the environment in which something is produced indicating it's public purpose or agenda.
• Social -- the environment of people that surrounds something's creation or intended audience, reflecting how the people associated with something use and interpret it.
• Temporal -- reflects issues or events of, relating to, or limited by time. Concerns past, present, or future contextualization and not just a historical past.

Background information can also include summaries of important research studies . This can be a particularly important element of providing background information if an innovative or groundbreaking study about the research problem laid a foundation for further research or there was a key study that is essential to understanding your arguments. The priority is to summarize for the reader what is known about the research problem before you conduct the analysis of prior research. This is accomplished with a general summary of the foundational research literature [with citations] that document findings that inform your study's overall aims and objectives.

NOTE : Research studies cited as part of the background information of your introduction should not include very specific, lengthy explanations. This should be discussed in greater detail in your literature review section. If you find a study requiring lengthy explanation, consider moving it to the literature review section.

ANOTHER NOTE : In some cases, your paper's introduction only needs to introduce the research problem, explain its significance, and then describe a road map for how you are going to address the problem; the background information basically forms the introduction part of your literature review. That said, while providing background information is not required, including it in the introduction is a way to highlight important contextual information that could otherwise be hidden or overlooked by the reader if placed in the literature review section.

Background of the Problem Section: What do you Need to Consider? Anonymous. Harvard University; Hopkins, Will G. How to Write a Research Paper. SPORTSCIENCE, Perspectives/Research Resources. Department of Physiology and School of Physical Education, University of Otago, 1999; Green, L. H. How to Write the Background/Introduction Section. Physics 499 Powerpoint slides. University of Illinois; Pyrczak, Fred. Writing Empirical Research Reports: A Basic Guide for Students of the Social and Behavioral Sciences . 8th edition. Glendale, CA: Pyrczak Publishing, 2014; Stevens, Kathleen C. “Can We Improve Reading by Teaching Background Information?.” Journal of Reading 25 (January 1982): 326-329; Woodall, W. Gill. Writing the Background and Significance Section. Senior Research Scientist and Professor of Communication. Center on Alcoholism, Substance Abuse, and Addictions. University of New Mexico.

Structure and Writing Style

Providing background information in the introduction of a research paper serves as a bridge that links the reader to the research problem . Precisely how long and in-depth this bridge should be is largely dependent upon how much information you think the reader will need to know in order to fully understand the problem being discussed and to appreciate why the issues you are investigating are important.

From another perspective, the length and detail of background information also depends on the degree to which you need to demonstrate to your professor how much you understand the research problem. Keep this in mind because providing pertinent background information can be an effective way to demonstrate that you have a clear grasp of key issues, debates, and concepts related to your overall study.

The structure and writing style of your background information can vary depending upon the complexity of your research and/or the nature of the assignment. However, in most cases it should be limited to only one to two paragraphs in your introduction.

Given this, here are some questions to consider while writing this part of your introduction :

• Are there concepts, terms, theories, or ideas that may be unfamiliar to the reader and, thus, require additional explanation?
• Are there historical elements that need to be explored in order to provide needed context, to highlight specific people, issues, or events, or to lay a foundation for understanding the emergence of a current issue or event?
• Are there theories, concepts, or ideas borrowed from other disciplines or academic traditions that may be unfamiliar to the reader and therefore require further explanation?
• Is there a key study or small set of studies that set the stage for understanding the topic and frames why it is important to conduct further research on the topic?
• Y our study uses a method of analysis never applied before;
• Your study investigates a very esoteric or complex research problem;
• Your study introduces new or unique variables that need to be taken into account ; or,
• Your study relies upon analyzing unique texts or documents, such as, archival materials or primary documents like diaries or personal letters that do not represent the established body of source literature on the topic?

Almost all introductions to a research problem require some contextualizing, but the scope and breadth of background information varies depending on your assumption about the reader's level of prior knowledge . However, despite this assessment, background information should be brief and succinct and sets the stage for the elaboration of critical points or in-depth discussion of key issues in the literature review section of your paper.

Writing Tip

Background Information vs. the Literature Review

Incorporating background information into the introduction is intended to provide the reader with critical information about the topic being studied, such as, highlighting and expanding upon foundational studies conducted in the past, describing important historical events that inform why and in what ways the research problem exists, defining key components of your study [concepts, people, places, phenomena] and/or placing the research problem within a particular context. Although introductory background information can often blend into the literature review portion of the paper, essential background information should not be considered a substitute for a comprehensive review and synthesis of relevant research literature.

Hart, Cris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage, 1998; Pyrczak, Fred. Writing Empirical Research Reports: A Basic Guide for Students of the Social and Behavioral Sciences . 8th edition. Glendale, CA: Pyrczak Publishing, 2014.

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• A Quick Guide to Experimental Design | 5 Steps & Examples

A Quick Guide to Experimental Design | 5 Steps & Examples

Published on 11 April 2022 by Rebecca Bevans . Revised on 5 December 2022.

Experiments are used to study causal relationships . You manipulate one or more independent variables and measure their effect on one or more dependent variables.

Experimental design means creating a set of procedures to systematically test a hypothesis . A good experimental design requires a strong understanding of the system you are studying. 

There are five key steps in designing an experiment:

• Consider your variables and how they are related
• Write a specific, testable hypothesis
• Design experimental treatments to manipulate your independent variable
• Assign subjects to groups, either between-subjects or within-subjects
• Plan how you will measure your dependent variable

For valid conclusions, you also need to select a representative sample and control any  extraneous variables that might influence your results. If if random assignment of participants to control and treatment groups is impossible, unethical, or highly difficult, consider an observational study instead.

Table of contents

Step 1: define your variables, step 2: write your hypothesis, step 3: design your experimental treatments, step 4: assign your subjects to treatment groups, step 5: measure your dependent variable, frequently asked questions about experimental design.

You should begin with a specific research question . We will work with two research question examples, one from health sciences and one from ecology:

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables .

Then you need to think about possible extraneous and confounding variables and consider how you might control  them in your experiment.

Finally, you can put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.

Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.

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Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

The next steps will describe how to design a controlled experiment . In a controlled experiment, you must be able to:

• Systematically and precisely manipulate the independent variable(s).
• Precisely measure the dependent variable(s).
• Control any potential confounding variables.

If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalised and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

• just slightly above the natural range for your study region.
• over a wider range of temperatures to mimic future warming.
• over an extreme range that is beyond any possible natural variation.

Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

• a categorical variable : either as binary (yes/no) or as levels of a factor (no phone use, low phone use, high phone use).
• a continuous variable (minutes of phone use measured every night).

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size : how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power , which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups . Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group , which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

• A completely randomised design vs a randomised block design .
• A between-subjects design vs a within-subjects design .

Randomisation

An experiment can be completely randomised or randomised within blocks (aka strata):

• In a completely randomised design , every subject is assigned to a treatment group at random.
• In a randomised block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

Sometimes randomisation isn’t practical or ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a quasi-experimental design .

Between-subjects vs within-subjects

In a between-subjects design (also known as an independent measures design or classic ANOVA design), individuals receive only one of the possible levels of an experimental treatment.

In medical or social research, you might also use matched pairs within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions.

In a within-subjects design (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured.

Within-subjects or repeated measures can also refer to an experimental design where an effect emerges over time, and individual responses are measured over time in order to measure this effect as it emerges.

Counterbalancing (randomising or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

Finally, you need to decide how you’ll collect data on your dependent variable outcomes. You should aim for reliable and valid measurements that minimise bias or error.

Some variables, like temperature, can be objectively measured with scientific instruments. Others may need to be operationalised to turn them into measurable observations.

• Ask participants to record what time they go to sleep and get up each day.
• Ask participants to wear a sleep tracker.

How precisely you measure your dependent variable also affects the kinds of statistical analysis you can use on your data.

Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

• A testable hypothesis
• One or more independent variables that you will manipulate
• One or more dependent variables that you will measure

When designing the experiment, first decide:

• How your variable(s) will be manipulated
• How you will control for any potential confounding or lurking variables
• How many subjects you will include
• How you will assign treatments to your subjects

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word ‘between’ means that you’re comparing different conditions between groups, while the word ‘within’ means you’re comparing different conditions within the same group.

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Rebecca Bevans

Chapter 10 Experimental Research

Experimental research, often considered to be the “gold standard” in research designs, is one of the most rigorous of all research designs. In this design, one or more independent variables are manipulated by the researcher (as treatments), subjects are randomly assigned to different treatment levels (random assignment), and the results of the treatments on outcomes (dependent variables) are observed. The unique strength of experimental research is its internal validity (causality) due to its ability to link cause and effect through treatment manipulation, while controlling for the spurious effect of extraneous variable.

Experimental research is best suited for explanatory research (rather than for descriptive or exploratory research), where the goal of the study is to examine cause-effect relationships. It also works well for research that involves a relatively limited and well-defined set of independent variables that can either be manipulated or controlled. Experimental research can be conducted in laboratory or field settings. Laboratory experiments , conducted in laboratory (artificial) settings, tend to be high in internal validity, but this comes at the cost of low external validity (generalizability), because the artificial (laboratory) setting in which the study is conducted may not reflect the real world. Field experiments , conducted in field settings such as in a real organization, and high in both internal and external validity. But such experiments are relatively rare, because of the difficulties associated with manipulating treatments and controlling for extraneous effects in a field setting.

Experimental research can be grouped into two broad categories: true experimental designs and quasi-experimental designs. Both designs require treatment manipulation, but while true experiments also require random assignment, quasi-experiments do not. Sometimes, we also refer to non-experimental research, which is not really a research design, but an all-inclusive term that includes all types of research that do not employ treatment manipulation or random assignment, such as survey research, observational research, and correlational studies.

Basic Concepts

Treatment and control groups. In experimental research, some subjects are administered one or more experimental stimulus called a treatment (the treatment group ) while other subjects are not given such a stimulus (the control group ). The treatment may be considered successful if subjects in the treatment group rate more favorably on outcome variables than control group subjects. Multiple levels of experimental stimulus may be administered, in which case, there may be more than one treatment group. For example, in order to test the effects of a new drug intended to treat a certain medical condition like dementia, if a sample of dementia patients is randomly divided into three groups, with the first group receiving a high dosage of the drug, the second group receiving a low dosage, and the third group receives a placebo such as a sugar pill (control group), then the first two groups are experimental groups and the third group is a control group. After administering the drug for a period of time, if the condition of the experimental group subjects improved significantly more than the control group subjects, we can say that the drug is effective. We can also compare the conditions of the high and low dosage experimental groups to determine if the high dose is more effective than the low dose.

Treatment manipulation. Treatments are the unique feature of experimental research that sets this design apart from all other research methods. Treatment manipulation helps control for the “cause” in cause-effect relationships. Naturally, the validity of experimental research depends on how well the treatment was manipulated. Treatment manipulation must be checked using pretests and pilot tests prior to the experimental study. Any measurements conducted before the treatment is administered are called pretest measures , while those conducted after the treatment are posttest measures .

Random selection and assignment. Random selection is the process of randomly drawing a sample from a population or a sampling frame. This approach is typically employed in survey research, and assures that each unit in the population has a positive chance of being selected into the sample. Random assignment is however a process of randomly assigning subjects to experimental or control groups. This is a standard practice in true experimental research to ensure that treatment groups are similar (equivalent) to each other and to the control group, prior to treatment administration. Random selection is related to sampling, and is therefore, more closely related to the external validity (generalizability) of findings. However, random assignment is related to design, and is therefore most related to internal validity. It is possible to have both random selection and random assignment in well-designed experimental research, but quasi-experimental research involves neither random selection nor random assignment.

Threats to internal validity. Although experimental designs are considered more rigorous than other research methods in terms of the internal validity of their inferences (by virtue of their ability to control causes through treatment manipulation), they are not immune to internal validity threats. Some of these threats to internal validity are described below, within the context of a study of the impact of a special remedial math tutoring program for improving the math abilities of high school students.

• History threat is the possibility that the observed effects (dependent variables) are caused by extraneous or historical events rather than by the experimental treatment. For instance, students’ post-remedial math score improvement may have been caused by their preparation for a math exam at their school, rather than the remedial math program.
• Maturation threat refers to the possibility that observed effects are caused by natural maturation of subjects (e.g., a general improvement in their intellectual ability to understand complex concepts) rather than the experimental treatment.
• Testing threat is a threat in pre-post designs where subjects’ posttest responses are conditioned by their pretest responses. For instance, if students remember their answers from the pretest evaluation, they may tend to repeat them in the posttest exam. Not conducting a pretest can help avoid this threat.
• Instrumentation threat , which also occurs in pre-post designs, refers to the possibility that the difference between pretest and posttest scores is not due to the remedial math program, but due to changes in the administered test, such as the posttest having a higher or lower degree of difficulty than the pretest.
• Mortality threat refers to the possibility that subjects may be dropping out of the study at differential rates between the treatment and control groups due to a systematic reason, such that the dropouts were mostly students who scored low on the pretest. If the low-performing students drop out, the results of the posttest will be artificially inflated by the preponderance of high-performing students.
• Regression threat , also called a regression to the mean, refers to the statistical tendency of a group’s overall performance on a measure during a posttest to regress toward the mean of that measure rather than in the anticipated direction. For instance, if subjects scored high on a pretest, they will have a tendency to score lower on the posttest (closer to the mean) because their high scores (away from the mean) during the pretest was possibly a statistical aberration. This problem tends to be more prevalent in non-random samples and when the two measures are imperfectly correlated.

Two-Group Experimental Designs

The simplest true experimental designs are two group designs involving one treatment group and one control group, and are ideally suited for testing the effects of a single independent variable that can be manipulated as a treatment. The two basic two-group designs are the pretest-posttest control group design and the posttest-only control group design, while variations may include covariance designs. These designs are often depicted using a standardized design notation, where R represents random assignment of subjects to groups, X represents the treatment administered to the treatment group, and O represents pretest or posttest observations of the dependent variable (with different subscripts to distinguish between pretest and posttest observations of treatment and control groups).

Pretest-posttest control group design . In this design, subjects are randomly assigned to treatment and control groups, subjected to an initial (pretest) measurement of the dependent variables of interest, the treatment group is administered a treatment (representing the independent variable of interest), and the dependent variables measured again (posttest). The notation of this design is shown in Figure 10.1.

Figure 10.1. Pretest-posttest control group design

The effect E of the experimental treatment in the pretest posttest design is measured as the difference in the posttest and pretest scores between the treatment and control groups:

E = (O 2 – O 1 ) – (O 4 – O 3 )

Statistical analysis of this design involves a simple analysis of variance (ANOVA) between the treatment and control groups. The pretest posttest design handles several threats to internal validity, such as maturation, testing, and regression, since these threats can be expected to influence both treatment and control groups in a similar (random) manner. The selection threat is controlled via random assignment. However, additional threats to internal validity may exist. For instance, mortality can be a problem if there are differential dropout rates between the two groups, and the pretest measurement may bias the posttest measurement (especially if the pretest introduces unusual topics or content).

Posttest-only control group design . This design is a simpler version of the pretest-posttest design where pretest measurements are omitted. The design notation is shown in Figure 10.2.

Figure 10.2. Posttest only control group design.

The treatment effect is measured simply as the difference in the posttest scores between the two groups:

E = (O 1 – O 2 )

The appropriate statistical analysis of this design is also a two- group analysis of variance (ANOVA). The simplicity of this design makes it more attractive than the pretest-posttest design in terms of internal validity. This design controls for maturation, testing, regression, selection, and pretest-posttest interaction, though the mortality threat may continue to exist.

Covariance designs . Sometimes, measures of dependent variables may be influenced by extraneous variables called covariates . Covariates are those variables that are not of central interest to an experimental study, but should nevertheless be controlled in an experimental design in order to eliminate their potential effect on the dependent variable and therefore allow for a more accurate detection of the effects of the independent variables of interest. The experimental designs discussed earlier did not control for such covariates. A covariance design (also called a concomitant variable design) is a special type of pretest posttest control group design where the pretest measure is essentially a measurement of the covariates of interest rather than that of the dependent variables. The design notation is shown in Figure 10.3, where C represents the covariates:

Figure 10.3. Covariance design

Because the pretest measure is not a measurement of the dependent variable, but rather a covariate, the treatment effect is measured as the difference in the posttest scores between the treatment and control groups as:

Figure 10.4. 2 x 2 factorial design

Factorial designs can also be depicted using a design notation, such as that shown on the right panel of Figure 10.4. R represents random assignment of subjects to treatment groups, X represents the treatment groups themselves (the subscripts of X represents the level of each factor), and O represent observations of the dependent variable. Notice that the 2 x 2 factorial design will have four treatment groups, corresponding to the four combinations of the two levels of each factor. Correspondingly, the 2 x 3 design will have six treatment groups, and the 2 x 2 x 2 design will have eight treatment groups. As a rule of thumb, each cell in a factorial design should have a minimum sample size of 20 (this estimate is derived from Cohen’s power calculations based on medium effect sizes). So a 2 x 2 x 2 factorial design requires a minimum total sample size of 160 subjects, with at least 20 subjects in each cell. As you can see, the cost of data collection can increase substantially with more levels or factors in your factorial design. Sometimes, due to resource constraints, some cells in such factorial designs may not receive any treatment at all, which are called incomplete factorial designs . Such incomplete designs hurt our ability to draw inferences about the incomplete factors.

In a factorial design, a main effect is said to exist if the dependent variable shows a significant difference between multiple levels of one factor, at all levels of other factors. No change in the dependent variable across factor levels is the null case (baseline), from which main effects are evaluated. In the above example, you may see a main effect of instructional type, instructional time, or both on learning outcomes. An interaction effect exists when the effect of differences in one factor depends upon the level of a second factor. In our example, if the effect of instructional type on learning outcomes is greater for 3 hours/week of instructional time than for 1.5 hours/week, then we can say that there is an interaction effect between instructional type and instructional time on learning outcomes. Note that the presence of interaction effects dominate and make main effects irrelevant, and it is not meaningful to interpret main effects if interaction effects are significant.

Hybrid Experimental Designs

Hybrid designs are those that are formed by combining features of more established designs. Three such hybrid designs are randomized bocks design, Solomon four-group design, and switched replications design.

Randomized block design. This is a variation of the posttest-only or pretest-posttest control group design where the subject population can be grouped into relatively homogeneous subgroups (called blocks ) within which the experiment is replicated. For instance, if you want to replicate the same posttest-only design among university students and full -time working professionals (two homogeneous blocks), subjects in both blocks are randomly split between treatment group (receiving the same treatment) or control group (see Figure 10.5). The purpose of this design is to reduce the “noise” or variance in data that may be attributable to differences between the blocks so that the actual effect of interest can be detected more accurately.

Figure 10.5. Randomized blocks design.

Solomon four-group design . In this design, the sample is divided into two treatment groups and two control groups. One treatment group and one control group receive the pretest, and the other two groups do not. This design represents a combination of posttest-only and pretest-posttest control group design, and is intended to test for the potential biasing effect of pretest measurement on posttest measures that tends to occur in pretest-posttest designs but not in posttest only designs. The design notation is shown in Figure 10.6.

Figure 10.6. Solomon four-group design

Switched replication design . This is a two-group design implemented in two phases with three waves of measurement. The treatment group in the first phase serves as the control group in the second phase, and the control group in the first phase becomes the treatment group in the second phase, as illustrated in Figure 10.7. In other words, the original design is repeated or replicated temporally with treatment/control roles switched between the two groups. By the end of the study, all participants will have received the treatment either during the first or the second phase. This design is most feasible in organizational contexts where organizational programs (e.g., employee training) are implemented in a phased manner or are repeated at regular intervals.

Figure 10.7. Switched replication design.

Quasi-Experimental Designs

Quasi-experimental designs are almost identical to true experimental designs, but lacking one key ingredient: random assignment. For instance, one entire class section or one organization is used as the treatment group, while another section of the same class or a different organization in the same industry is used as the control group. This lack of random assignment potentially results in groups that are non-equivalent, such as one group possessing greater mastery of a certain content than the other group, say by virtue of having a better teacher in a previous semester, which introduces the possibility of selection bias . Quasi-experimental designs are therefore inferior to true experimental designs in interval validity due to the presence of a variety of selection related threats such as selection-maturation threat (the treatment and control groups maturing at different rates), selection-history threat (the treatment and control groups being differentially impact by extraneous or historical events), selection-regression threat (the treatment and control groups regressing toward the mean between pretest and posttest at different rates), selection-instrumentation threat (the treatment and control groups responding differently to the measurement), selection-testing (the treatment and control groups responding differently to the pretest), and selection-mortality (the treatment and control groups demonstrating differential dropout rates). Given these selection threats, it is generally preferable to avoid quasi-experimental designs to the greatest extent possible.

Many true experimental designs can be converted to quasi-experimental designs by omitting random assignment. For instance, the quasi-equivalent version of pretest-posttest control group design is called nonequivalent groups design (NEGD), as shown in Figure 10.8, with random assignment R replaced by non-equivalent (non-random) assignment N . Likewise, the quasi -experimental version of switched replication design is called non-equivalent switched replication design (see Figure 10.9).

Figure 10.8. NEGD design.

Figure 10.9. Non-equivalent switched replication design.

In addition, there are quite a few unique non -equivalent designs without corresponding true experimental design cousins. Some of the more useful of these designs are discussed next.

Regression-discontinuity (RD) design . This is a non-equivalent pretest-posttest design where subjects are assigned to treatment or control group based on a cutoff score on a preprogram measure. For instance, patients who are severely ill may be assigned to a treatment group to test the efficacy of a new drug or treatment protocol and those who are mildly ill are assigned to the control group. In another example, students who are lagging behind on standardized test scores may be selected for a remedial curriculum program intended to improve their performance, while those who score high on such tests are not selected from the remedial program. The design notation can be represented as follows, where C represents the cutoff score:

Figure 10.10. RD design.

Because of the use of a cutoff score, it is possible that the observed results may be a function of the cutoff score rather than the treatment, which introduces a new threat to internal validity. However, using the cutoff score also ensures that limited or costly resources are distributed to people who need them the most rather than randomly across a population, while simultaneously allowing a quasi-experimental treatment. The control group scores in the RD design does not serve as a benchmark for comparing treatment group scores, given the systematic non-equivalence between the two groups. Rather, if there is no discontinuity between pretest and posttest scores in the control group, but such a discontinuity persists in the treatment group, then this discontinuity is viewed as evidence of the treatment effect.

Proxy pretest design . This design, shown in Figure 10.11, looks very similar to the standard NEGD (pretest-posttest) design, with one critical difference: the pretest score is collected after the treatment is administered. A typical application of this design is when a researcher is brought in to test the efficacy of a program (e.g., an educational program) after the program has already started and pretest data is not available. Under such circumstances, the best option for the researcher is often to use a different prerecorded measure, such as students’ grade point average before the start of the program, as a proxy for pretest data. A variation of the proxy pretest design is to use subjects’ posttest recollection of pretest data, which may be subject to recall bias, but nevertheless may provide a measure of perceived gain or change in the dependent variable.

Figure 10.11. Proxy pretest design.

Separate pretest-posttest samples design . This design is useful if it is not possible to collect pretest and posttest data from the same subjects for some reason. As shown in Figure 10.12, there are four groups in this design, but two groups come from a single non-equivalent group, while the other two groups come from a different non-equivalent group. For instance, you want to test customer satisfaction with a new online service that is implemented in one city but not in another. In this case, customers in the first city serve as the treatment group and those in the second city constitute the control group. If it is not possible to obtain pretest and posttest measures from the same customers, you can measure customer satisfaction at one point in time, implement the new service program, and measure customer satisfaction (with a different set of customers) after the program is implemented. Customer satisfaction is also measured in the control group at the same times as in the treatment group, but without the new program implementation. The design is not particularly strong, because you cannot examine the changes in any specific customer’s satisfaction score before and after the implementation, but you can only examine average customer satisfaction scores. Despite the lower internal validity, this design may still be a useful way of collecting quasi-experimental data when pretest and posttest data are not available from the same subjects.

Figure 10.12. Separate pretest-posttest samples design.

Nonequivalent dependent variable (NEDV) design . This is a single-group pre-post quasi-experimental design with two outcome measures, where one measure is theoretically expected to be influenced by the treatment and the other measure is not. For instance, if you are designing a new calculus curriculum for high school students, this curriculum is likely to influence students’ posttest calculus scores but not algebra scores. However, the posttest algebra scores may still vary due to extraneous factors such as history or maturation. Hence, the pre-post algebra scores can be used as a control measure, while that of pre-post calculus can be treated as the treatment measure. The design notation, shown in Figure 10.13, indicates the single group by a single N , followed by pretest O 1 and posttest O 2 for calculus and algebra for the same group of students. This design is weak in internal validity, but its advantage lies in not having to use a separate control group.

An interesting variation of the NEDV design is a pattern matching NEDV design , which employs multiple outcome variables and a theory that explains how much each variable will be affected by the treatment. The researcher can then examine if the theoretical prediction is matched in actual observations. This pattern-matching technique, based on the degree of correspondence between theoretical and observed patterns is a powerful way of alleviating internal validity concerns in the original NEDV design.

Figure 10.13. NEDV design.

Perils of Experimental Research

Experimental research is one of the most difficult of research designs, and should not be taken lightly. This type of research is often best with a multitude of methodological problems. First, though experimental research requires theories for framing hypotheses for testing, much of current experimental research is atheoretical. Without theories, the hypotheses being tested tend to be ad hoc, possibly illogical, and meaningless. Second, many of the measurement instruments used in experimental research are not tested for reliability and validity, and are incomparable across studies. Consequently, results generated using such instruments are also incomparable. Third, many experimental research use inappropriate research designs, such as irrelevant dependent variables, no interaction effects, no experimental controls, and non-equivalent stimulus across treatment groups. Findings from such studies tend to lack internal validity and are highly suspect. Fourth, the treatments (tasks) used in experimental research may be diverse, incomparable, and inconsistent across studies and sometimes inappropriate for the subject population. For instance, undergraduate student subjects are often asked to pretend that they are marketing managers and asked to perform a complex budget allocation task in which they have no experience or expertise. The use of such inappropriate tasks, introduces new threats to internal validity (i.e., subject’s performance may be an artifact of the content or difficulty of the task setting), generates findings that are non-interpretable and meaningless, and makes integration of findings across studies impossible.

The design of proper experimental treatments is a very important task in experimental design, because the treatment is the raison d’etre of the experimental method, and must never be rushed or neglected. To design an adequate and appropriate task, researchers should use prevalidated tasks if available, conduct treatment manipulation checks to check for the adequacy of such tasks (by debriefing subjects after performing the assigned task), conduct pilot tests (repeatedly, if necessary), and if doubt, using tasks that are simpler and familiar for the respondent sample than tasks that are complex or unfamiliar.

In summary, this chapter introduced key concepts in the experimental design research method and introduced a variety of true experimental and quasi-experimental designs. Although these designs vary widely in internal validity, designs with less internal validity should not be overlooked and may sometimes be useful under specific circumstances and empirical contingencies.

• Social Science Research: Principles, Methods, and Practices. Authored by : Anol Bhattacherjee. Provided by : University of South Florida. Located at : http://scholarcommons.usf.edu/oa_textbooks/3/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

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How to Write the Background of the Study in Research (Part 1)

Background of the Study in Research: Definition and the Core Elements it Contains

Before we embark on a detailed discussion on how to write the background of the study of your proposed research or thesis, it is important to first discuss its meaning and the core elements that it should contain. This is obviously because understanding the nature of the background of the study in research and knowing exactly what to include in it allow us to have both greater control and clear direction of the writing process.

So, what really is the background of the study and what are the core elements that it should contain?

The background of the study, which usually forms the first section of the introduction to a research paper or thesis, provides the overview of the study. In other words, it is that section of the research paper or thesis that establishes the context of the study. Its main function is to explain why the proposed research is important and essential to understanding the main aspects of the study.

The background of the study, therefore, is the section of the research paper or thesis that identifies the problem or gap of the study that needs to addressed and justifies the need for conducting the study. It also articulates the main goal of the study and the thesis statement, that is, the main claim or argument of the paper.

Given this brief understanding of the background of the study, we can anticipate what readers or thesis committee members expect from it. As we can see, the background of the study should contain the following major points:

1) brief discussion on what is known about the topic under investigation; 2) An articulation of the research gap or problem that needs to be addressed; 3) What the researcher would like to do or aim to achieve in the study ( research goal); 4) The thesis statement, that is, the main argument or contention of the paper (which also serves as the reason why the researcher would want to pursue the study); 5) The major significance or contribution of the study to a particular discipline; and 6) Depending on the nature of the study, an articulation of the hypothesis of the study.

Thus, when writing the background of the study, you should plan and structure it based on the major points just mentioned. With this, you will have a clear picture of the flow of the tasks that need to be completed in writing this section of your research or thesis proposal.

Now, how do you go about writing the background of the study in your proposed research or thesis?

The next lessons will address this question.

How to Write the Opening Paragraphs of the Background of the Study?

To begin with, let us assume that you already have conducted a preliminary research on your chosen topic, that is, you already have read a lot of literature and gathered relevant information for writing the background of your study. Let us also assume that you already have identified the gap of your proposed research and have already developed the research questions and thesis statement. If you have not yet identified the gap in your proposed research, you might as well go back to our lesson on how to identify a research gap.

So, we will just put together everything that you have researched into a background of the study (assuming, again, that you already have the necessary information). But in this lesson, let’s just focus on writing the opening paragraphs.

It is important to note at this point that there are different styles of writing the background of the study. Hence, what I will be sharing with you here is not just “the” only way of writing the background of the study. As a matter of fact, there is no “one-size-fits-all” style of writing this part of the research or thesis. At the end of the day, you are free to develop your own. However, whatever style it would be, it always starts with a plan which structures the writing process into stages or steps. The steps that I will share with below are just some of the most effective ways of writing the background of the study in research.

So, let’s begin.

It is always a good idea to begin the background of your study by giving an overview of your research topic. This may include providing a definition of the key concepts of your research or highlighting the main developments of the research topic.

Let us suppose that the topic of your study is the “lived experiences of students with mathematical anxiety”.

Here, you may start the background of your study with a discussion on the meaning, nature, and dynamics of the term “mathematical anxiety”. The reason for this is too obvious: “mathematical anxiety” is a highly technical term that is specific to mathematics. Hence, this term is not readily understandable to non-specialists in this field.

So, you may write the opening paragraph of your background of the study with this:

“Mathematical anxiety refers to the individual’s unpleasant emotional mood responses when confronted with a mathematical situation.”

Since you do not invent the definition of the term “mathematical anxiety”, then you need to provide a citation to the source of the material from which you are quoting. For example, you may now say:

“Mathematical anxiety refers to the individual’s unpleasant emotional mood responses when confronted with a mathematical situation (Eliot, 2020).”

And then you may proceed with the discussion on the nature and dynamics of the term “mathematical anxiety”. You may say:

“Lou (2019) specifically identifies some of the manifestations of this type of anxiety, which include, but not limited to, depression, helplessness, nervousness and fearfulness in doing mathematical and numerical tasks.”

After explaining to your readers the meaning, nature, and dynamics (as well as some historical development if you wish to) of the term “mathematical anxiety”, you may now proceed to showing the problem or gap of the study. As you may already know, the research gap is the problem that needs to be addressed in the study. This is important because no research activity is possible without the research gap.

Let us suppose that your research problem or gap is: “Mathematical anxiety can negatively affect not just the academic achievement of the students but also their future career plans and total well-being. Also, there are no known studies that deal with the mathematical anxiety of junior high school students in New Zealand.” With this, you may say:

“If left unchecked, as Shapiro (2019) claims, this problem will expand and create a total avoidance pattern on the part of the students, which can be expressed most visibly in the form of cutting classes and habitual absenteeism. As we can see, this will negatively affect the performance of students in mathematics. In fact, the study conducted by Luttenberger and Wimmer (2018) revealed that the outcomes of mathematical anxiety do not only negatively affect the students’ performance in math-related situations but also their future career as professionals. Without a doubt, therefore, mathematical anxiety is a recurring problem for many individuals which will negatively affect the academic success and future career of the student.”

Now that you already have both explained the meaning, nature, and dynamics of the term “mathematical anxiety” and articulated the gap of your proposed research, you may now state the main goal of your study. You may say:

“Hence, it is precisely in this context that the researcher aims to determine the lived experiences of those students with mathematical anxiety. In particular, this proposed thesis aims to determine the lived experiences of the junior high school students in New Zealand and identify the factors that caused them to become disinterested in mathematics.”

Please note that you should not end the first paragraph of your background of the study with the articulation of the research goal. You also need to articulate the “thesis statement”, which usually comes after the research goal. As is well known, the thesis statement is the statement of your argument or contention in the study. It is more of a personal argument or claim of the researcher, which specifically highlights the possible contribution of the study. For example, you may say:

“The researcher argues that there is a need to determine the lived experiences of these students with mathematical anxiety because knowing and understanding the difficulties and challenges that they have encountered will put the researcher in the best position to offer some alternatives to the problem. Indeed, it is only when we have performed some kind of a ‘diagnosis’ that we can offer practicable solutions to the problem. And in the case of the junior high school students in New Zealand who are having mathematical anxiety, determining their lived experiences as well as identifying the factors that caused them to become disinterested in mathematics are the very first steps in addressing the problem.”

If we combine the bits and pieces that we have written above, we can now come up with the opening paragraphs of your background of the study, which reads:

As we can see, we can find in the first paragraph 5 essential elements that must be articulated in the background of the study, namely:

1) A brief discussion on what is known about the topic under investigation; 2) An articulation of the research gap or problem that needs to be addressed; 3) What the researcher would like to do or aim to achieve in the study (research goal); 4) The thesis statement , that is, the main argument or claim of the paper; and 5) The major significance or contribution of the study to a particular discipline. So, that’s how you write the opening paragraphs of your background of the study. The next lesson will talk about writing the body of the background of the study.

How to Write the Body of the Background of the Study?

If we liken the background of the study to a sitting cat, then the opening paragraphs that we have completed in the previous lesson would just represent the head of the cat.

This means we still have to write the body (body of the cat) and the conclusion (tail). But how do we write the body of the background of the study? What should be its content?

Truly, this is one of the most difficult challenges that fledgling scholars faced. Because they are inexperienced researchers and didn’t know what to do next, they just wrote whatever they wished to write. Fortunately, this is relatively easy if they know the technique.

One of the best ways to write the body of the background of the study is to attack it from the vantage point of the research gap. If you recall, when we articulated the research gap in the opening paragraphs, we made a bold claim there, that is, there are junior high school students in New Zealand who are experiencing mathematical anxiety. Now, you have to remember that a “statement” remains an assumption until you can provide concrete proofs to it. This is what we call the “epistemological” aspect of research. As we may already know, epistemology is a specific branch of philosophy that deals with the validity of knowledge. And to validate knowledge is to provide concrete proofs to our statements. Hence, the reason why we need to provide proofs to our claim that there are indeed junior high school students in New Zealand who are experiencing mathematical anxiety is the obvious fact that if there are none, then we cannot proceed with our study. We have no one to interview with in the first. In short, we don’t have respondents.

The body of the background of the study, therefore, should be a presentation and articulation of the proofs to our claim that indeed there are junior high school students in New Zealand who are experiencing mathematical anxiety. Please note, however, that this idea is true only if you follow the style of writing the background of the study that I introduced in this course.

So, how do we do this?

One of the best ways to do this is to look for literature on mathematical anxiety among junior high school students in New Zealand and cite them here. However, if there are not enough literature on this topic in New Zealand, then we need to conduct initial interviews with these students or make actual classroom observations and record instances of mathematical anxiety among these students. But it is always a good idea if we combine literature review with interviews and actual observations.

Assuming you already have the data, then you may now proceed with the writing of the body of your background of the study. For example, you may say:

“According to records and based on the researcher’s firsthand experience with students in some junior high schools in New Zealand, indeed, there are students who lost interest in mathematics. For one, while checking the daily attendance and monitoring of the students, it was observed that some of them are not always attending classes in mathematics but are regularly attending the rest of the required subjects.”

After this sentence, you may insert some literature that will support this position. For example, you may say:

“As a matter of fact, this phenomenon is also observed in the work of Estonanto. In his study titled ‘Impact of Math Anxiety on Academic Performance in Pre-Calculus of Senior High School’, Estonanto (2019) found out that, inter alia, students with mathematical anxiety have the tendency to intentionally prioritize other subjects and commit habitual tardiness and absences.”

Then you may proceed saying:

“With this initial knowledge in mind, the researcher conducted initial interviews with some of these students. The researcher learned that one student did not regularly attend his math subject because he believed that he is not good in math and no matter how he listens to the topic he will not learn.”

Then you may say:

“Another student also mentioned that she was influenced by her friends’ perception that mathematics is hard; hence, she avoids the subject. Indeed, these are concrete proofs that there are some junior high school students in New Zealand who have mathematical anxiety. As already hinted, “disinterest” or the loss of interest in mathematics is one of the manifestations of a mathematical anxiety.”

If we combine what we have just written above, then we can have the first two paragraphs of the body of our background of the study. It reads:

“According to records and based on the researcher’s firsthand experience with students in some junior high schools in New Zealand, indeed there are students who lost interest in mathematics. For one, while checking the daily attendance and monitoring of the students, it was observed that some of them are not always attending classes in mathematics but are regularly attending the rest of the required subjects. As a matter of fact, this phenomenon is also observed in the work of Estonanto. In his study titled ‘Impact of Math Anxiety on Academic Performance in Pre-Calculus of Senior High School’, Estonanto (2019) found out that, inter alia, students with mathematical anxiety have the tendency to intentionally prioritize other subjects and commit habitual tardiness and absences.

With this initial knowledge in mind, the researcher conducted initial interviews with some of these students. The researcher learned that one student did not regularly attend his math subject because he believed that he is not good in math and no matter how he listens to the topic he will not learn. Another student also mentioned that she was influenced by her friends’ perception that mathematics is hard; hence, she avoids the subject. Indeed, these are concrete proofs that there are some junior high school students in New Zealand who have mathematical anxiety. As already hinted, “disinterest” or the loss of interest in mathematics is one of the manifestations of a mathematical anxiety.”

And then you need validate this observation by conducting another round of interview and observation in other schools. So, you may continue writing the body of the background of the study with this:

“To validate the information gathered from the initial interviews and observations, the researcher conducted another round of interview and observation with other junior high school students in New Zealand.”

“On the one hand, the researcher found out that during mathematics time some students felt uneasy; in fact, they showed a feeling of being tensed or anxious while working with numbers and mathematical problems. Some were even afraid to seat in front, while some students at the back were secretly playing with their mobile phones. These students also show remarkable apprehension during board works like trembling hands, nervous laughter, and the like.”

Then provide some literature that will support your position. You may say:

“As Finlayson (2017) corroborates, emotional symptoms of mathematical anxiety involve feeling of helplessness, lack of confidence, and being nervous for being put on the spot. It must be noted that these occasionally extreme emotional reactions are not triggered by provocative procedures. As a matter of fact, there are no personally sensitive questions or intentional manipulations of stress. The teacher simply asked a very simple question, like identifying the parts of a circle. Certainly, this observation also conforms with the study of Ashcraft (2016) when he mentions that students with mathematical anxiety show a negative attitude towards math and hold self-perceptions about their mathematical abilities.”

And then you proceed:

“On the other hand, when the class had their other subjects, the students show a feeling of excitement. They even hurried to seat in front and attentively participating in the class discussion without hesitation and without the feeling of being tensed or anxious. For sure, this is another concrete proof that there are junior high school students in New Zealand who have mathematical anxiety.”

To further prove the point that there indeed junior high school students in New Zealand who have mathematical anxiety, you may solicit observations from other math teachers. For instance, you may say:

“The researcher further verified if the problem is also happening in other sections and whether other mathematics teachers experienced the same observation that the researcher had. This validation or verification is important in establishing credibility of the claim (Buchbinder, 2016) and ensuring reliability and validity of the assertion (Morse et al., 2002). In this regard, the researcher attempted to open up the issue of math anxiety during the Departmentalized Learning Action Cell (LAC), a group discussion of educators per quarter, with the objective of ‘Teaching Strategies to Develop Critical Thinking of the Students’. During the session, one teacher corroborates the researcher’s observation that there are indeed junior high school students in New Zealand who have mathematical anxiety. The teacher pointed out that truly there were students who showed no extra effort in mathematics class in addition to the fact that some students really avoided the subject. In addition, another math teacher expressed her frustrations about these students who have mathematical anxiety. She quipped: “How can a teacher develop the critical thinking skills or ability of the students if in the first place these students show avoidance and disinterest in the subject?’.”

Again, if we combine what we have just written above, then we can now have the remaining parts of the body of the background of the study. It reads:

So, that’s how we write the body of the background of the study in research . Of course, you may add any relevant points which you think might amplify your content. What is important at this point is that you now have a clear idea of how to write the body of the background of the study.

How to Write the Concluding Part of the Background of the Study?

Since we have already completed the body of our background of the study in the previous lesson, we may now write the concluding paragraph (the tail of the cat). This is important because one of the rules of thumb in writing is that we always put a close to what we have started.

It is important to note that the conclusion of the background of the study is just a rehashing of the research gap and main goal of the study stated in the introductory paragraph, but framed differently. The purpose of this is just to emphasize, after presenting the justifications, what the study aims to attain and why it wants to do it. The conclusion, therefore, will look just like this:

“Given the above discussion, it is evident that there are indeed junior high school students in New Zealand who are experiencing mathematical anxiety. And as we can see, mathematical anxiety can negatively affect not just the academic achievement of the students but also their future career plans and total well-being. Again, it is for this reason that the researcher attempts to determine the lived experiences of those junior high school students in New Zealand who are experiencing a mathematical anxiety.”

If we combine all that we have written from the very beginning, the entire background of the study would now read:

If we analyze the background of the study that we have just completed, we can observe that in addition to the important elements that it should contain, it has also addressed other important elements that readers or thesis committee members expect from it.

On the one hand, it provides the researcher with a clear direction in the conduct of the study. As we can see, the background of the study that we have just completed enables us to move in the right direction with a strong focus as it has set clear goals and the reasons why we want to do it. Indeed, we now exactly know what to do next and how to write the rest of the research paper or thesis.

On the other hand, most researchers start their research with scattered ideas and usually get stuck with how to proceed further. But with a well-written background of the study, just as the one above, we have decluttered and organized our thoughts. We have also become aware of what have and have not been done in our area of study, as well as what we can significantly contribute in the already existing body of knowledge in this area of study.

Please note, however, as I already mentioned previously, that the model that I have just presented is only one of the many models available in textbooks and other sources. You are, of course, free to choose your own style of writing the background of the study. You may also consult your thesis supervisor for some guidance on how to attack the writing of your background of the study.

Lastly, and as you may already know, universities around the world have their own thesis formats. Hence, you should follow your university’s rules on the format and style in writing your research or thesis. What is important is that with the lessons that you learned in this course, you can now easily write the introductory part of your thesis, such as the background of the study.

Experimental Research Design — 6 mistakes you should never make!

Since school days’ students perform scientific experiments that provide results that define and prove the laws and theorems in science. These experiments are laid on a strong foundation of experimental research designs.

An experimental research design helps researchers execute their research objectives with more clarity and transparency.

In this article, we will not only discuss the key aspects of experimental research designs but also the issues to avoid and problems to resolve while designing your research study.

Table of Contents

What Is Experimental Research Design?

Experimental research design is a framework of protocols and procedures created to conduct experimental research with a scientific approach using two sets of variables. Herein, the first set of variables acts as a constant, used to measure the differences of the second set. The best example of experimental research methods is quantitative research .

Experimental research helps a researcher gather the necessary data for making better research decisions and determining the facts of a research study.

When Can a Researcher Conduct Experimental Research?

A researcher can conduct experimental research in the following situations —

• When time is an important factor in establishing a relationship between the cause and effect.
• When there is an invariable or never-changing behavior between the cause and effect.
• Finally, when the researcher wishes to understand the importance of the cause and effect.

Importance of Experimental Research Design

To publish significant results, choosing a quality research design forms the foundation to build the research study. Moreover, effective research design helps establish quality decision-making procedures, structures the research to lead to easier data analysis, and addresses the main research question. Therefore, it is essential to cater undivided attention and time to create an experimental research design before beginning the practical experiment.

By creating a research design, a researcher is also giving oneself time to organize the research, set up relevant boundaries for the study, and increase the reliability of the results. Through all these efforts, one could also avoid inconclusive results. If any part of the research design is flawed, it will reflect on the quality of the results derived.

Types of Experimental Research Designs

Based on the methods used to collect data in experimental studies, the experimental research designs are of three primary types:

1. Pre-experimental Research Design

A research study could conduct pre-experimental research design when a group or many groups are under observation after implementing factors of cause and effect of the research. The pre-experimental design will help researchers understand whether further investigation is necessary for the groups under observation.

Pre-experimental research is of three types —

• One-shot Case Study Research Design
• One-group Pretest-posttest Research Design
• Static-group Comparison

2. True Experimental Research Design

A true experimental research design relies on statistical analysis to prove or disprove a researcher’s hypothesis. It is one of the most accurate forms of research because it provides specific scientific evidence. Furthermore, out of all the types of experimental designs, only a true experimental design can establish a cause-effect relationship within a group. However, in a true experiment, a researcher must satisfy these three factors —

• There is a control group that is not subjected to changes and an experimental group that will experience the changed variables
• A variable that can be manipulated by the researcher
• Random distribution of the variables

This type of experimental research is commonly observed in the physical sciences.

3. Quasi-experimental Research Design

The word “Quasi” means similarity. A quasi-experimental design is similar to a true experimental design. However, the difference between the two is the assignment of the control group. In this research design, an independent variable is manipulated, but the participants of a group are not randomly assigned. This type of research design is used in field settings where random assignment is either irrelevant or not required.

The classification of the research subjects, conditions, or groups determines the type of research design to be used.

Advantages of Experimental Research

Experimental research allows you to test your idea in a controlled environment before taking the research to clinical trials. Moreover, it provides the best method to test your theory because of the following advantages:

• Researchers have firm control over variables to obtain results.
• The subject does not impact the effectiveness of experimental research. Anyone can implement it for research purposes.
• The results are specific.
• Post results analysis, research findings from the same dataset can be repurposed for similar research ideas.
• Researchers can identify the cause and effect of the hypothesis and further analyze this relationship to determine in-depth ideas.
• Experimental research makes an ideal starting point. The collected data could be used as a foundation to build new research ideas for further studies.

6 Mistakes to Avoid While Designing Your Research

There is no order to this list, and any one of these issues can seriously compromise the quality of your research. You could refer to the list as a checklist of what to avoid while designing your research.

1. Invalid Theoretical Framework

Usually, researchers miss out on checking if their hypothesis is logical to be tested. If your research design does not have basic assumptions or postulates, then it is fundamentally flawed and you need to rework on your research framework.

2. Inadequate Literature Study

Without a comprehensive research literature review , it is difficult to identify and fill the knowledge and information gaps. Furthermore, you need to clearly state how your research will contribute to the research field, either by adding value to the pertinent literature or challenging previous findings and assumptions.

3. Insufficient or Incorrect Statistical Analysis

Statistical results are one of the most trusted scientific evidence. The ultimate goal of a research experiment is to gain valid and sustainable evidence. Therefore, incorrect statistical analysis could affect the quality of any quantitative research.

4. Undefined Research Problem

This is one of the most basic aspects of research design. The research problem statement must be clear and to do that, you must set the framework for the development of research questions that address the core problems.

5. Research Limitations

Every study has some type of limitations . You should anticipate and incorporate those limitations into your conclusion, as well as the basic research design. Include a statement in your manuscript about any perceived limitations, and how you considered them while designing your experiment and drawing the conclusion.

6. Ethical Implications

The most important yet less talked about topic is the ethical issue. Your research design must include ways to minimize any risk for your participants and also address the research problem or question at hand. If you cannot manage the ethical norms along with your research study, your research objectives and validity could be questioned.

Experimental Research Design Example

In an experimental design, a researcher gathers plant samples and then randomly assigns half the samples to photosynthesize in sunlight and the other half to be kept in a dark box without sunlight, while controlling all the other variables (nutrients, water, soil, etc.)

By comparing their outcomes in biochemical tests, the researcher can confirm that the changes in the plants were due to the sunlight and not the other variables.

Experimental research is often the final form of a study conducted in the research process which is considered to provide conclusive and specific results. But it is not meant for every research. It involves a lot of resources, time, and money and is not easy to conduct, unless a foundation of research is built. Yet it is widely used in research institutes and commercial industries, for its most conclusive results in the scientific approach.

Have you worked on research designs? How was your experience creating an experimental design? What difficulties did you face? Do write to us or comment below and share your insights on experimental research designs!

Frequently Asked Questions

Randomization is important in an experimental research because it ensures unbiased results of the experiment. It also measures the cause-effect relationship on a particular group of interest.

Experimental research design lay the foundation of a research and structures the research to establish quality decision making process.

There are 3 types of experimental research designs. These are pre-experimental research design, true experimental research design, and quasi experimental research design.

The difference between an experimental and a quasi-experimental design are: 1. The assignment of the control group in quasi experimental research is non-random, unlike true experimental design, which is randomly assigned. 2. Experimental research group always has a control group; on the other hand, it may not be always present in quasi experimental research.

Experimental research establishes a cause-effect relationship by testing a theory or hypothesis using experimental groups or control variables. In contrast, descriptive research describes a study or a topic by defining the variables under it and answering the questions related to the same.

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• How to Write a Research Proposal | Examples & Templates

How to Write a Research Proposal | Examples & Templates

Published on October 12, 2022 by Shona McCombes and Tegan George. Revised on November 21, 2023.

A research proposal describes what you will investigate, why it’s important, and how you will conduct your research.

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

Introduction

Literature review.

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Table of contents

Research proposal purpose, research proposal examples, research design and methods, contribution to knowledge, research schedule, other interesting articles, frequently asked questions about research proposals.

Academics often have to write research proposals to get funding for their projects. As a student, you might have to write a research proposal as part of a grad school application , or prior to starting your thesis or dissertation .

In addition to helping you figure out what your research can look like, a proposal can also serve to demonstrate why your project is worth pursuing to a funder, educational institution, or supervisor.

Research proposal length

The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.

One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.

Download our research proposal template

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Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We’ve included a few for you below.

• Example research proposal #1: “A Conceptual Framework for Scheduling Constraint Management”
• Example research proposal #2: “Medical Students as Mediators of Change in Tobacco Use”

Like your dissertation or thesis, the proposal will usually have a title page that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.

Your introduction should:

• Introduce your topic
• Give necessary background and context
• Outline your  problem statement  and research questions

To guide your introduction , include information about:

• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights your research will contribute
• Why you believe this research is worth doing

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have already done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or synthesize prior scholarship

Following the literature review, restate your main  objectives . This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Last but not least, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use our free APA citation generator .

Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.

Here’s an example schedule to help you get started. You can also download a template at the button below.

Download our research schedule template

If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.

Make sure to check what type of costs the funding body will agree to cover. For each item, include:

• Cost : exactly how much money do you need?
• Justification : why is this cost necessary to complete the research?
• Source : how did you calculate the amount?

To determine your budget, think about:

• Travel costs : do you need to go somewhere to collect your data? How will you get there, and how much time will you need? What will you do there (e.g., interviews, archival research)?
• Materials : do you need access to any tools or technologies?
• Help : do you need to hire any research assistants for the project? What will they do, and how much will you pay them?

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

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.

A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.

A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.

All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.

Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

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How to Write the Rationale of the Study in Research (Examples)

What is the Rationale of the Study?

The rationale of the study is the justification for taking on a given study. It explains the reason the study was conducted or should be conducted. This means the study rationale should explain to the reader or examiner why the study is/was necessary. It is also sometimes called the “purpose” or “justification” of a study. While this is not difficult to grasp in itself, you might wonder how the rationale of the study is different from your research question or from the statement of the problem of your study, and how it fits into the rest of your thesis or research paper. 

The rationale of the study links the background of the study to your specific research question and justifies the need for the latter on the basis of the former. In brief, you first provide and discuss existing data on the topic, and then you tell the reader, based on the background evidence you just presented, where you identified gaps or issues and why you think it is important to address those. The problem statement, lastly, is the formulation of the specific research question you choose to investigate, following logically from your rationale, and the approach you are planning to use to do that.

Table of Contents:

How to write a rationale for a research paper , how do you justify the need for a research study.

• Study Rationale Example: Where Does It Go In Your Paper?

The basis for writing a research rationale is preliminary data or a clear description of an observation. If you are doing basic/theoretical research, then a literature review will help you identify gaps in current knowledge. In applied/practical research, you base your rationale on an existing issue with a certain process (e.g., vaccine proof registration) or practice (e.g., patient treatment) that is well documented and needs to be addressed. By presenting the reader with earlier evidence or observations, you can (and have to) convince them that you are not just repeating what other people have already done or said and that your ideas are not coming out of thin air. 

Once you have explained where you are coming from, you should justify the need for doing additional research–this is essentially the rationale of your study. Finally, when you have convinced the reader of the purpose of your work, you can end your introduction section with the statement of the problem of your research that contains clear aims and objectives and also briefly describes (and justifies) your methodological approach. 

When is the Rationale for Research Written?

The author can present the study rationale both before and after the research is conducted. 

• Before conducting research : The study rationale is a central component of the research proposal . It represents the plan of your work, constructed before the study is actually executed.
• Once research has been conducted : After the study is completed, the rationale is presented in a research article or  PhD dissertation  to explain why you focused on this specific research question. When writing the study rationale for this purpose, the author should link the rationale of the research to the aims and outcomes of the study.

What to Include in the Study Rationale

Although every study rationale is different and discusses different specific elements of a study’s method or approach, there are some elements that should be included to write a good rationale. Make sure to touch on the following:

• A summary of conclusions from your review of the relevant literature
• What is currently unknown (gaps in knowledge)
• Inconclusive or contested results  from previous studies on the same or similar topic
• The necessity to improve or build on previous research, such as to improve methodology or utilize newer techniques and/or technologies

There are different types of limitations that you can use to justify the need for your study. In applied/practical research, the justification for investigating something is always that an existing process/practice has a problem or is not satisfactory. Let’s say, for example, that people in a certain country/city/community commonly complain about hospital care on weekends (not enough staff, not enough attention, no decisions being made), but you looked into it and realized that nobody ever investigated whether these perceived problems are actually based on objective shortages/non-availabilities of care or whether the lower numbers of patients who are treated during weekends are commensurate with the provided services.

In this case, “lack of data” is your justification for digging deeper into the problem. Or, if it is obvious that there is a shortage of staff and provided services on weekends, you could decide to investigate which of the usual procedures are skipped during weekends as a result and what the negative consequences are. 

In basic/theoretical research, lack of knowledge is of course a common and accepted justification for additional research—but make sure that it is not your only motivation. “Nobody has ever done this” is only a convincing reason for a study if you explain to the reader why you think we should know more about this specific phenomenon. If there is earlier research but you think it has limitations, then those can usually be classified into “methodological”, “contextual”, and “conceptual” limitations. To identify such limitations, you can ask specific questions and let those questions guide you when you explain to the reader why your study was necessary:

Methodological limitations

• Did earlier studies try but failed to measure/identify a specific phenomenon?
• Was earlier research based on incorrect conceptualizations of variables?
• Were earlier studies based on questionable operationalizations of key concepts?
• Did earlier studies use questionable or inappropriate research designs?

Contextual limitations

• Have recent changes in the studied problem made previous studies irrelevant?
• Are you studying a new/particular context that previous findings do not apply to?

Conceptual limitations

• Do previous findings only make sense within a specific framework or ideology?

Study Rationale Examples

Let’s look at an example from one of our earlier articles on the statement of the problem to clarify how your rationale fits into your introduction section. This is a very short introduction for a practical research study on the challenges of online learning. Your introduction might be much longer (especially the context/background section), and this example does not contain any sources (which you will have to provide for all claims you make and all earlier studies you cite)—but please pay attention to how the background presentation , rationale, and problem statement blend into each other in a logical way so that the reader can follow and has no reason to question your motivation or the foundation of your research.

Background presentation

Since the beginning of the Covid pandemic, most educational institutions around the world have transitioned to a fully online study model, at least during peak times of infections and social distancing measures. This transition has not been easy and even two years into the pandemic, problems with online teaching and studying persist (reference needed) . 

While the increasing gap between those with access to technology and equipment and those without access has been determined to be one of the main challenges (reference needed) , others claim that online learning offers more opportunities for many students by breaking down barriers of location and distance (reference needed) .  

Rationale of the study

Since teachers and students cannot wait for circumstances to go back to normal, the measures that schools and universities have implemented during the last two years, their advantages and disadvantages, and the impact of those measures on students’ progress, satisfaction, and well-being need to be understood so that improvements can be made and demographics that have been left behind can receive the support they need as soon as possible.

Statement of the problem

To identify what changes in the learning environment were considered the most challenging and how those changes relate to a variety of student outcome measures, we conducted surveys and interviews among teachers and students at ten institutions of higher education in four different major cities, two in the US (New York and Chicago), one in South Korea (Seoul), and one in the UK (London). Responses were analyzed with a focus on different student demographics and how they might have been affected differently by the current situation.

How long is a study rationale?

In a research article bound for journal publication, your rationale should not be longer than a few sentences (no longer than one brief paragraph). A  dissertation or thesis  usually allows for a longer description; depending on the length and nature of your document, this could be up to a couple of paragraphs in length. A completely novel or unconventional approach might warrant a longer and more detailed justification than an approach that slightly deviates from well-established methods and approaches.

Consider Using Professional Academic Editing Services

Now that you know how to write the rationale of the study for a research proposal or paper, you should make use of our free AI grammar checker , Wordvice AI, or receive professional academic proofreading services from Wordvice, including research paper editing services and manuscript editing services to polish your submitted research documents.

You can also find many more articles, for example on writing the other parts of your research paper , on choosing a title , or on making sure you understand and adhere to the author instructions before you submit to a journal, on the Wordvice academic resources pages.

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Original research article, learning scientific observation with worked examples in a digital learning environment.

• 1 Department Educational Sciences, Chair for Formal and Informal Learning, Technical University Munich School of Social Sciences and Technology, Munich, Germany
• 2 Aquatic Systems Biology Unit, TUM School of Life Sciences, Technical University of Munich, Freising, Germany

Science education often aims to increase learners’ acquisition of fundamental principles, such as learning the basic steps of scientific methods. Worked examples (WE) have proven particularly useful for supporting the development of such cognitive schemas and successive actions in order to avoid using up more cognitive resources than are necessary. Therefore, we investigated the extent to which heuristic WE are beneficial for supporting the acquisition of a basic scientific methodological skill—conducting scientific observation. The current study has a one-factorial, quasi-experimental, comparative research design and was conducted as a field experiment. Sixty two students of a German University learned about scientific observation steps during a course on applying a fluvial audit, in which several sections of a river were classified based on specific morphological characteristics. In the two experimental groups scientific observation was supported either via faded WE or via non-faded WE both presented as short videos. The control group did not receive support via WE. We assessed factual and applied knowledge acquisition regarding scientific observation, motivational aspects and cognitive load. The results suggest that WE promoted knowledge application: Learners from both experimental groups were able to perform the individual steps of scientific observation more accurately. Fading of WE did not show any additional advantage compared to the non-faded version in this regard. Furthermore, the descriptive results reveal higher motivation and reduced extraneous cognitive load within the experimental groups, but none of these differences were statistically significant. Our findings add to existing evidence that WE may be useful to establish scientific competences.

1 Introduction

Learning in science education frequently involves the acquisition of basic principles or generalities, whether of domain-specific topics (e.g., applying a mathematical multiplication rule) or of rather universal scientific methodologies (e.g., performing the steps of scientific observation) ( Lunetta et al., 2007 ). Previous research has shown that worked examples (WE) can be considered particularly useful for developing such cognitive schemata during learning to avoid using more cognitive resources than necessary for learning successive actions ( Renkl et al., 2004 ; Renkl, 2017 ). WE consist of the presentation of a problem, consecutive solution steps and the solution itself. This is especially advantageous in initial cognitive skill acquisition, i.e., for novice learners with low prior knowledge ( Kalyuga et al., 2001 ). With growing knowledge, fading WE can lead from example-based learning to independent problem-solving ( Renkl et al., 2002 ). Preliminary work has shown the advantage of WE in specific STEM domains like mathematics ( Booth et al., 2015 ; Barbieri et al., 2021 ), but less studies have investigated their impact on the acquisition of basic scientific competencies that involve heuristic problem-solving processes (scientific argumentation, Schworm and Renkl, 2007 ; Hefter et al., 2014 ; Koenen et al., 2017 ). In the realm of natural sciences, various basic scientific methodologies are employed to acquire knowledge, such as experimentation or scientific observation ( Wellnitz and Mayer, 2013 ). During the pursuit of knowledge through scientific inquiry activities, learners may encounter several challenges and difficulties. Similar to the hurdles faced in experimentation, where understanding the criteria for appropriate experimental design, including the development, measurement, and evaluation of results, is crucial ( Sirum and Humburg, 2011 ; Brownell et al., 2014 ; Dasgupta et al., 2014 ; Deane et al., 2014 ), scientific observation additionally presents its own set of issues. In scientific observation, e.g., the acquisition of new insights may be somewhat incidental due to spontaneous and uncoordinated observations ( Jensen, 2014 ). To address these challenges, it is crucial to provide instructional support, including the use of WE, particularly when observations are carried out in a more self-directed manner.

For this reason, the aim of the present study was to determine the usefulness of digitally presented WE to support the acquisition of a basic scientific methodological skill—conducting scientific observations—using a digital learning environment. In this regard, this study examined the effects of different forms of digitally presented WE (non-faded vs. faded) on students’ cognitive and motivational outcomes and compared them to a control group without WE. Furthermore, the combined perspective of factual and applied knowledge, as well as motivational and cognitive aspects, represent further value added to the study.

2 Theoretical background

2.1 worked examples.

WE have been commonly used in the fields of STEM education (science, technology, engineering, and mathematics) ( Booth et al., 2015 ). They consist of a problem statement, the steps to solve the problem, and the solution itself ( Atkinson et al., 2000 ; Renkl et al., 2002 ; Renkl, 2014 ). The success of WE can be explained by their impact on cognitive load (CL) during learning, based on assumptions from Cognitive Load Theory ( Sweller, 2006 ).

Learning with WE is considered time-efficient, effective, and superior to problem-based learning (presentation of the problem without demonstration of solution steps) when it comes to knowledge acquisition and transfer (WE-effect, Atkinson et al., 2000 ; Van Gog et al., 2011 ). Especially WE can help by reducing the extraneous load (presentation and design of the learning material) and, in turn, can lead to an increase in germane load (effort of the learner to understand the learning material) ( Paas et al., 2003 ; Renkl, 2014 ). With regard to intrinsic load (difficulty and complexity of the learning material), it is still controversially discussed if it can be altered by instructional design, e.g., WE ( Gerjets et al., 2004 ). WE have a positive effect on learning and knowledge transfer, especially for novices, as the step-by-step presentation of the solution requires less extraneous mental effort compared to problem-based learning ( Sweller et al., 1998 ; Atkinson et al., 2000 ; Bokosmaty et al., 2015 ). With growing knowledge, WE can lose their advantages (due to the expertise-reversal effect), and scaffolding learning via faded WE might be more successful for knowledge gain and transfer ( Renkl, 2014 ). Faded WE are similar to complete WE, but fade out solution steps as knowledge and competencies grow. Faded WE enhance near-knowledge transfer and reduce errors compared to non-faded WE ( Renkl et al., 2000 ).

In addition, the reduction of intrinsic and extraneous CL by WE also has an impact on learner motivation, such as interest ( Van Gog and Paas, 2006 ). Um et al. (2012) showed that there is a strong positive correlation between germane CL and the motivational aspects of learning, like satisfaction and emotion. Gupta (2019) mentions a positive correlation between CL and interest. Van Harsel et al. (2019) found that WE positively affect learning motivation, while no such effect was found for problem-solving. Furthermore, learning with WE increases the learners’ belief in their competence in completing a task. In addition, fading WE can lead to higher motivation for more experienced learners, while non-faded WE can be particularly motivating for learners without prior knowledge ( Paas et al., 2005 ). In general, fundamental motivational aspects during the learning process, such as situational interest ( Lewalter and Knogler, 2014 ) or motivation-relevant experiences, like basic needs, are influenced by learning environments. At the same time, their use also depends on motivational characteristics of the learning process, such as self-determined motivation ( Deci and Ryan, 2012 ). Therefore, we assume that learning with WE as a relevant component of a learning environment might also influence situational interest and basic needs.

2.1.1 Presentation of worked examples

WE are frequently used in digital learning scenarios ( Renkl, 2014 ). When designing WE, the application via digital learning media can be helpful, as their content can be presented in different ways (video, audio, text, and images), tailored to the needs of the learners, so that individual use is possible according to their own prior knowledge or learning pace ( Mayer, 2001 ). Also, digital media can present relevant information in a timely, motivating, appealing and individualized way and support learning in an effective and needs-oriented way ( Mayer, 2001 ). The advantages of using digital media in designing WE have already been shown in previous studies. Dart et al. (2020) presented WE as short videos (WEV). They report that the use of WEV leads to increased student satisfaction and more positive attitudes. Approximately 90% of the students indicated an active learning approach when learning with the WEV. Furthermore, the results show that students improved their content knowledge through WEV and that they found WEV useful for other courses as well.

Another study ( Kay and Edwards, 2012 ) presented WE as video podcasts. Here, the advantages of WE regarding self-determined learning in terms of learning location, learning time, and learning speed were shown. Learning performance improved significantly after use. The step-by-step, easy-to-understand explanations, the diagrams, and the ability to determine the learning pace by oneself were seen as beneficial.

Multimedia WE can also be enhanced with self-explanation prompts ( Berthold et al., 2009 ). Learning from WE with self-explanation prompts was shown to be superior to other learning methods, such as hypertext learning and observational learning.

In addition to presenting WE in different medial ways, WE can also comprise different content domains.

2.1.2 Content and context of worked examples

Regarding the content of WE, algorithmic and heuristic WE, as well as single-content and double-content WE, can be distinguished ( Reiss et al., 2008 ; Koenen et al., 2017 ; Renkl, 2017 ). Algorithmic WE are traditionally used in the very structured mathematical–physical field. Here, an algorithm with very specific solution steps is to learn, for example, in probability calculation ( Koenen et al., 2017 ). In this study, however, we focus on heuristic double-content WE. Heuristic WE in science education comprise fundamental scientific working methods, e.g., conducting experiments ( Koenen et al., 2017 ). Furthermore, double-content WE contain two learning domains that are relevant for the learning process: (1) the learning domain describes the primarily to be learned abstract process or concept, e.g., scientific methodologies like observation (see section 2.2), while (2) the exemplifying domain consists of the content that is necessary to teach this process or concept, e.g., mapping of river structure ( Renkl et al., 2009 ).

Depending on the WE content to be learned, it may be necessary for learning to take place in different settings. This can be in a formal or informal learning setting or a non-formal field setting. In this study, the focus is on learning scientific observation (learning domain) through river structure mapping (exemplary domain), which takes place with the support of digital media in a formal (university) setting, but in an informal context (nature).

2.2 Scientific observation

Scientific observation is fundamental to all scientific activities and disciplines ( Kohlhauf et al., 2011 ). Scientific observation must be clearly distinguished from everyday observation, where observation is purely a matter of noticing and describing specific characteristics ( Chinn and Malhotra, 2001 ). In contrast to this everyday observation, scientific observation as a method of knowledge acquisition can be described as a rather complex activity, defined as the theory-based, systematic and selective perception of concrete systems and processes without any fundamental manipulation ( Wellnitz and Mayer, 2013 ). Wellnitz and Mayer (2013) described the scientific observation process via six steps: (1) formulation of the research question (s), (2) deduction of the null hypothesis and the alternative hypothesis, (3) planning of the research design, (4) conducting the observation, (5) analyzing the data, and (6) answering the research question(s) on this basis. Only through reliable and qualified observation, valid data can be obtained that provide solid scientific evidence ( Wellnitz and Mayer, 2013 ).

Since observation activities are not trivial and learners often observe without generating new knowledge or connecting their observations to scientific explanations and thoughts, it is important to provide support at the related cognitive level, so that observation activities can be conducted in a structured way according to pre-defined criteria ( Ford, 2005 ; Eberbach and Crowley, 2009 ). Especially during field-learning experiences, scientific observation is often spontaneous and uncoordinated, whereby random discoveries result in knowledge gain ( Jensen, 2014 ).

To promote successful observing in rather unstructured settings like field trips, instructional support for the observation process seems useful. To guide observation activities, digitally presented WE seem to be an appropriate way to introduce learners to the individual steps of scientific observation using concrete examples.

2.3 Research questions and hypothesis

The present study investigates the effect of digitally presented double-content WE that supports the mapping of a small Bavarian river by demonstrating the steps of scientific observation. In this analysis, we focus on the learning domain of the WE and do not investigate the exemplifying domain in detail. Distinct ways of integrating WE in the digital learning environment (faded WE vs. non-faded WE) are compared with each other and with a control group (no WE). The aim is to examine to what extent differences between those conditions exist with regard to (RQ1) learners’ competence acquisition [acquisition of factual knowledge about the scientific observation method (quantitative data) and practical application of the scientific observation method (quantified qualitative data)], (RQ2) learners’ motivation (situational interest and basic needs), and (RQ3) CL. It is assumed that (Hypothesis 1), the integration of WE (faded and non-faded) leads to significantly higher competence acquisition (factual and applied knowledge), significantly higher motivation and significantly lower extraneous CL as well as higher germane CL during the learning process compared to a learning environment without WE. No differences between the conditions are expected regarding intrinsic CL. Furthermore, it is assumed (Hypothesis 2) that the integration of faded WE leads to significantly higher competence acquisition, significantly higher motivation, and lower extraneous CL as well as higher germane CL during the learning processes compared to non-faded WE. No differences between the conditions are expected with regard to intrinsic CL.

The study took place during the field trips of a university course on the application of a fluvial audit (FA) using the German working aid for mapping the morphology of rivers and their floodplains ( Bayerisches Landesamt für Umwelt, 2019 ). FA is the leading fluvial geomorphological tool for application to data collection contiguously along all watercourses of interest ( Walker et al., 2007 ). It is widely used because it is a key example of environmental conservation and monitoring that needs to be taught to students of selected study programs; thus, knowing about the most effective ways of learning is of high practical relevance.

3.1 Sample and design

3.1.1 sample.

The study was conducted with 62 science students and doctoral students of a German University (age M  = 24.03 years; SD  = 4.20; 36 females; 26 males). A total of 37 participants had already conducted a scientific observation and would rate their knowledge in this regard at a medium level ( M  = 3.32 out of 5; SD  = 0.88). Seven participants had already conducted an FA and would rate their knowledge in this regard at a medium level ( M  = 3.14 out of 5; SD  = 0.90). A total of 25 participants had no experience at all. Two participants had to be excluded from the sample afterward because no posttest results were available.

3.1.2 Design

The study has a 1-factorial quasi-experimental comparative research design and is conducted as a field experiment using a pre/posttest design. Participants were randomly assigned to one of three conditions: no WE ( n  = 20), faded WE ( n  = 20), and non-faded WE ( n  = 20).

3.2 Implementation and material

3.2.1 implementation.

The study started with an online kick-off meeting where two lecturers informed all students within an hour about the basics regarding the assessment of the structural integrity of the study river and the course of the field trip days to conduct an FA. Afterward, within 2 weeks, students self-studied via Moodle the FA following the German standard method according to the scoresheets of Bayerisches Landesamt für Umwelt (2019) . This independent preparation using the online presented documents was a necessary prerequisite for participation in the field days and was checked in the pre-testing. The preparatory online documents included six short videos and four PDF files on the content, guidance on the German protocol of the FA, general information on river landscapes, information about anthropogenic changes in stream morphology and the scoresheets for applying the FA. In these sheets, the river and its floodplain are subdivided into sections of 100 m in length. Each of these sections is evaluated by assessing 21 habitat factors related to flow characteristics and structural variability. The findings are then transferred into a scoring system for the description of structural integrity from 1 (natural) to 7 (highly modified). Habitat factors have a decisive influence on the living conditions of animals and plants in and around rivers. They included, e.g., variability in water depth, stream width, substratum diversity, or diversity of flow velocities.

3.2.2 Materials

On the field trip days, participants were handed a tablet and a paper-based FA worksheet (last accessed 21st September 2022). 1 This four-page assessment sheet was accompanied by a digital learning environment presented on Moodle that instructed the participants on mapping the water body structure and guided the scientific observation method. All three Moodle courses were identical in structure and design; the only difference was the implementation of the WE. Below, the course without WE are described first. The other two courses have an identical structure, but contain additional WE in the form of learning videos.

3.2.3 No worked example

After a short welcome and introduction to the course navigation, the FA started with the description of a short hypothetical scenario: Participants should take the role of an employee of an urban planning office that assesses the ecomorphological status of a small river near a Bavarian city. The river was divided into five sections that had to be mapped separately. The course was structured accordingly. At the beginning of each section, participants had to formulate and write down a research question, and according to hypotheses regarding the ecomorphological status of the river’s section, they had to collect data in this regard via the mapping sheet and then evaluate their data and draw a conclusion. Since this course serves as a control group, no WE videos supporting the scientific observation method were integrated. The layout of the course is structured like a book, where it is not possible to scroll back. This is important insofar as the participants do not have the possibility to revisit information in order to keep the conditions comparable as well as distinguishable.

3.2.4 Non-faded worked example

In the course with no-faded WE, three instructional videos are shown for each of the five sections. In each of the three videos, two steps of the scientific observation method are presented so that, finally, all six steps of scientific observation are demonstrated. The mapping of the first section starts after the general introduction (as described above) with the instruction to work on the first two steps of scientific observation: the formulation of a research question and hypotheses. To support this, a video of about 4 min explains the features of scientific sound research questions and hypotheses. To this aim, a practical example, including explanations and tips, is given regarding the formulation of research questions and hypotheses for this section (e.g., “To what extent does the building development and the closeness of the path to the water body have an influence on the structure of the water body?” Alternative hypothesis: It is assumed that the housing development and the closeness of the path to the water body have a negative influence on the water body structure. Null hypothesis: It is assumed that the housing development and the closeness of the path to the watercourse have no negative influence on the watercourse structure.). Participants should now formulate their own research questions and hypotheses, write them down in a text field at the end of the page, and then skip to the next page. The next two steps of scientific observation, planning and conducting, are explained in a short 4-min video. To this aim, a practical example including explanations and tips is given regarding planning and conducting scientific for this section (e.g., “It’s best to go through each evaluation category carefully one by one that way you are sure not to forget anything!”). Now, participants were asked to collect data for the first section using their paper-based FA worksheet. Participants individually surveyed the river and reported their results in the mapping sheet by ticking the respective boxes in it. After collecting this data, they returned to the digital learning environment to learn how to use these data by studying the last two steps of scientific observation, evaluation, and conclusion. The third 4-min video explained how to evaluate and interpret collected data. For this purpose, a practical example with explanations and tips is given regarding evaluating and interpreting data for this section (e.g., “What were the individual points that led to the assessment? Have there been points that were weighted more than others? Remember the introduction video!”). At the end of the page, participants could answer their before-stated research questions and hypotheses by evaluating their collected data and drawing a conclusion. This brings participants to the end of the first mapping section. Afterward, the cycle begins again with the second section of the river that has to be mapped. Again, participants had to conduct the steps of scientific observation, guided by WE videos, explaining the steps in slightly different wording or with different examples. A total of five sections are mapped, in which the structure of the learning environment and the videos follow the same procedure.

3.2.5 Faded worked example

The digital learning environment with the faded WE follow the same structure as the version with the non-faded WE. However, in this version, the information in the WE videos is successively reduced. In the first section, all three videos are identical to the version with the non-faded WE. In the second section, faded content was presented as follows: the tip at the end was omitted in all three videos. In the third section, the tip and the practical example were omitted. In the fourth and fifth sections, no more videos were presented, only the work instructions.

3.3 Procedure

The data collection took place on four continuous days on the university campus, with a maximum group size of 15 participants on each day. The students were randomly assigned to one of the three conditions (no WE vs. faded WE vs. non-faded WE). After a short introduction to the procedure, the participants were handed the paper-based FA worksheet and one tablet per person. Students scanned the QR code on the first page of the worksheet that opened the pretest questionnaire, which took about 20 min to complete. After completing the questionnaire, the group walked for about 15 min to the nearby small river that was to be mapped. Upon arrival, there was first a short introduction to the digital learning environment and a check that the login (via university account on Moodle) worked. During the next 4 h, the participants individually mapped five segments of the river using the cartography worksheet. They were guided through the steps of scientific observation using the digital learning environment on the tablet. The results of their scientific observation were logged within the digital learning environment. At the end of the digital learning environment, participants were directed to the posttest via a link. After completing the test, the tablets and mapping sheets were returned. Overall, the study took about 5 h per group each day.

3.4 Instruments

In the pretest, sociodemographic data (age and gender), the study domain and the number of study semesters were collected. Additionally, the previous scientific observation experience and the estimation of one’s own ability in this regard were assessed. For example, it was asked whether scientific observation had already been conducted and, if so, how the abilities were rated on a 5-point scale from very low to very high. Preparation for the FA on the basis of the learning material was assessed: Participants were asked whether they had studied all six videos and all four PDF documents, with the response options not at all, partially, and completely. Furthermore, a factual knowledge test about scientific observation and questions about self-determination theory was administered. The posttest used the same knowledge test, and additional questions on basic needs, situational interest, measures of CL and questions about the usefulness of the WE. All scales were presented online, and participants reached the questionnaire via QR code.

3.4.1 Scientific observation competence acquisition

For the factual knowledge (quantitative assessment of the scientific observation competence), a single-choice knowledge test with 12 questions was developed and used as pre- and posttest with a maximum score of 12 points. It assesses the learners’ knowledge of the scientific observation method regarding the steps of scientific observation, e.g., formulating research questions and hypotheses or developing a research design. The questions are based on Wahser (2008 , adapted by Koenen, 2014 ) and adapted to scientific observation: “Although you are sure that you have conducted the scientific observation correctly, an unexpected result turns up. What conclusion can you draw?” Each question has four answer options (one of which is correct) and, in addition, one “I do not know” option.

For the applied knowledge (quantified qualitative assessment of the scientific observation competence), students’ scientific observations written in the digital learning environment were analyzed. A coding scheme was used with the following codes: 0 = insufficient (text field is empty or includes only insufficient key points), 1 = sufficient (a research question and no hypotheses or research question and inappropriate hypotheses are stated), 2 = comprehensive (research question and appropriate hypothesis or research question and hypotheses are stated, but, e.g., incorrect null hypothesis), 3 = very comprehensive (correct research question, hypothesis and null hypothesis are stated). One example of a very comprehensive answer regarding the research question and hypothesis is: To what extent does the lack of riparian vegetation have an impact on water body structure? Hypothesis: The lack of shore vegetation has a negative influence on the water body structure. Null hypothesis: The lack of shore vegetation has no influence on the water body structure. Afterward, a sum score was calculated for each participant. Five times, a research question and hypotheses (steps 1 and 2 in the observation process) had to be formulated (5 × max. 3 points = 15 points), and five times, the research questions and hypotheses had to be answered (steps 5 and 6 in the observation process: evaluation and conclusion) (5 × max. 3 points = 15 points). Overall, participants could reach up to 30 points. Since the observation and evaluation criteria in data collection and analysis were strongly predetermined by the scoresheet, steps 3 and 4 of the observation process (planning and conducting) were not included in the analysis.

All 600 cases (60 participants, each 10 responses to code) were coded by the first author. For verification, 240 cases (24 randomly selected participants, eight from each course) were cross-coded by an external coder. In 206 of the coded cases, the raters agreed. The cases in which the raters did not agree were discussed together, and a solution was found. This results in Cohen’s κ = 0.858, indicating a high to very high level of agreement. This indicates that the category system is clearly formulated and that the individual units of analysis could be correctly assigned.

3.4.2 Self-determination index

For the calculation of the self-determination index (SDI-index), Thomas and Müller (2011) scale for self-determination was used in the pretest. The scale consists of four subscales: intrinsic motivation (five items; e.g., I engage with the workshop content because I enjoy it; reliability of alpha = 0.87), identified motivation (four items; e.g., I engage with the workshop content because it gives me more options when choosing a career; alpha = 0.84), introjected motivation (five items; e.g., I engage with the workshop content because otherwise I would have a guilty feeling; alpha = 0.79), and external motivation (three items, e.g., I engage with the workshop content because I simply have to learn it; alpha = 0.74). Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree. To calculate the SDI-index, the sum of the self-determined regulation styles (intrinsic and identified) is subtracted from the sum of the external regulation styles (introjected and external), where intrinsic and external regulation are scored two times ( Thomas and Müller, 2011 ).

3.4.3 Motivation

Basic needs were measured in the posttest with the scale by Willems and Lewalter (2011) . The scale consists of three subscales: perceived competence (four items; e.g., during the workshop, I felt that I could meet the requirements; alpha = 0.90), perceived autonomy (five items; e.g., during the workshop, I felt that I had a lot of freedom; alpha = 0.75), and perceived autonomy regarding personal wishes and goals (APWG) (four items; e.g., during the workshop, I felt that the workshop was how I wish it would be; alpha = 0.93). We added all three subscales to one overall basic needs scale (alpha = 0.90). Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

Situational interest was measured in the posttest with the 12-item scale by Lewalter and Knogler (2014 ; Knogler et al., 2015 ; Lewalter, 2020 ; alpha = 0.84). The scale consists of two subscales: catch (six items; e.g., I found the workshop exciting; alpha = 0.81) and hold (six items; e.g., I would like to learn more about parts of the workshop; alpha = 0.80). Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

3.4.4 Cognitive load

In the posttest, CL was used to examine the mental load during the learning process. The intrinsic CL (three items; e.g., this task was very complex; alpha = 0.70) and extraneous CL (three items; e.g., in this task, it is difficult to identify the most important information; alpha = 0.61) are measured with the scales from Klepsch et al. (2017) . The germane CL (two items; e.g., the learning session contained elements that supported me to better understand the learning material; alpha = 0.72) is measured with the scale from Leppink et al. (2013) . Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

3.4.5 Attitudes toward worked examples

To measure how effective participants rated the WE, we used two scales related to the WE videos as instructional support. The first scale from Renkl (2001) relates to the usefulness of WE. The scale consists of four items (e.g., the explanations were helpful; alpha = 0.71). Two items were recoded because they were formulated negatively. The second scale is from Wachsmuth (2020) and relates to the participant’s evaluation of the WE. The scale consists of nine items (e.g., I always did what was explained in the learning videos; alpha = 0.76). Four items were recoded because they were formulated negatively. Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

3.5 Data analysis

An ANOVA was used to calculate if the variable’s prior knowledge and SDI index differed between the three groups. However, as no significant differences between the conditions were found [prior factual knowledge: F (2, 59) = 0.15, p  = 0.865, η 2  = 0.00 self-determination index: F (2, 59) = 0.19, p  = 0.829, η 2  = 0.00], they were not included as covariates in subsequent analyses.

Furthermore, a repeated measure, one-way analysis of variance (ANOVA), was conducted to compare the three treatment groups (no WE vs. faded WE vs. non-faded WE) regarding the increase in factual knowledge about the scientific observation method from pretest to posttest.

A MANOVA (multivariate analysis) was calculated with the three groups (no WE vs. non-faded WE vs. faded WE) as a fixed factor and the dependent variables being the practical application of the scientific observation method (first research question), situational interest, basic needs (second research question), and CL (third research question).

Additionally, to determine differences in applied knowledge even among the three groups, Bonferroni-adjusted post-hoc analyses were conducted.

The descriptive statistics between the three groups in terms of prior factual knowledge about the scientific observation method and the self-determination index are shown in Table 1 . The descriptive statistics revealed only small, non-significant differences between the three groups in terms of factual knowledge.

Table 1 . Means (standard deviations) of factual knowledge tests (pre- and posttest) and self-determination index for the three different groups.

The results of the ANOVA revealed that the overall increase in factual knowledge from pre- to posttest just misses significance [ F (1, 57) = 3.68, p  = 0.060, η 2  = 0 0.06]. Furthermore, no significant differences between the groups were found regarding the acquisition of factual knowledge from pre- to posttest [ F (2, 57) = 2.93, p  = 0.062, η 2  = 0.09].

An analysis of the descriptive statistics showed that the largest differences between the groups were found in applied knowledge (qualitative evaluation) and extraneous load (see Table 2 ).

Table 2 . Means (standard deviations) of dependent variables with the three different groups.

Results of the MANOVA revealed significant overall differences between the three groups [ F (12, 106) = 2.59, p  = 0.005, η 2  = 0.23]. Significant effects were found for the application of knowledge [ F (2, 57) = 13.26, p  = <0.001, η 2  = 0.32]. Extraneous CL just missed significance [ F (2, 57) = 2.68, p  = 0.065, η 2  = 0.09]. There were no significant effects for situational interest [ F (2, 57) = 0.44, p  = 0.644, η 2  = 0.02], basic needs [ F (2, 57) = 1.22, p  = 0.302, η 2  = 0.04], germane CL [ F (2, 57) = 2.68, p  = 0.077, η 2  = 0.09], and intrinsic CL [ F (2, 57) = 0.28, p  = 0.757, η 2  = 0.01].

Bonferroni-adjusted post hoc analysis revealed that the group without WE had significantly lower scores in the evaluation of the applied knowledge than the group with non-faded WE ( p  = <0.001, M diff  = −8.90, 95% CI [−13.47, −4.33]) and then the group with faded WE ( p  = <0.001, M diff  = −7.40, 95% CI [−11.97, −2.83]). No difference was found between the groups with faded and non-faded WE ( p  = 1.00, M diff  = −1.50, 95% CI [−6.07, 3.07]).

The descriptive statistics regarding the perceived usefulness of WE and participants’ evaluation of the WE revealed that the group with the faded WE rated usefulness slightly higher than the participants with non-faded WE and also reported a more positive evaluation. However, the results of a MANOVA revealed no significant overall differences [ F (2, 37) = 0.32, p  = 0.732, η 2  = 0 0.02] (see Table 3 ).

Table 3 . Means (standard deviations) of dependent variables with the three different groups.

5 Discussion

This study investigated the use of WE to support students’ acquisition of science observation. Below, the research questions are answered, and the implications and limitations of the study are discussed.

5.1 Results on factual and applied knowledge

In terms of knowledge gain (RQ1), our findings revealed no significant differences in participants’ results of the factual knowledge test both across all three groups and specifically between the two experimental groups. These results are in contradiction with related literature where WE had a positive impact on knowledge acquisition ( Renkl, 2014 ) and faded WE are considered to be more effective in knowledge acquisition and transfer, in contrast to non-faded WE ( Renkl et al., 2000 ; Renkl, 2014 ). A limitation of the study is the fact that the participants already scored very high on the pretest, so participation in the intervention would likely not yield significant knowledge gains due to ceiling effects ( Staus et al., 2021 ). Yet, nearly half of the students reported being novices in the field prior to the study, suggesting that the difficulty of some test items might have been too low. Here, it would be important to revise the factual knowledge test, e.g., the difficulty of the distractors in further study.

Nevertheless, with regard to application knowledge, the results revealed large significant differences: Participants of the two experimental groups performed better in conducting scientific observation steps than participants of the control group. In the experimental groups, the non-faded WE group performed better than the faded WE group. However, the absence of significant differences between the two experimental groups suggests that faded and non-faded WE used as double-content WE are suitable to teach applied knowledge about scientific observation in the learning domain ( Koenen, 2014 ). Furthermore, our results differ from the findings of Renkl et al. (2000) , in which the faded version led to the highest knowledge transfer. Despite the fact that the non-faded WE performed best in our study, the faded version of the WE was also appropriate to improve learning, confirming the findings of Renkl (2014) and Hesser and Gregory (2015) .

5.2 Results on learners’ motivation

Regarding participants’ motivation (RQ2; situational interest and basic needs), no significant differences were found across all three groups or between the two experimental groups. However, descriptive results reveal slightly higher motivation in the two experimental groups than in the control group. In this regard, our results confirm existing literature on a descriptive level showing that WE lead to higher learning-relevant motivation ( Paas et al., 2005 ; Van Harsel et al., 2019 ). Additionally, both experimental groups rated the usefulness of the WE as high and reported a positive evaluation of the WE. Therefore, we assume that even non-faded WE do not lead to over-instruction. Regarding the descriptive tendency, a larger sample might yield significant results and detect even small effects in future investigations. However, because this study also focused on comprehensive qualitative data analysis, it was not possible to evaluate a larger sample in this study.

5.3 Results on cognitive load

Finally, CL did not vary significantly across all three groups (RQ3). However, differences in extraneous CL just slightly missed significance. In descriptive values, the control group reported the highest extrinsic and lowest germane CL. The faded WE group showed the lowest extrinsic CL and a similar germane CL as the non-faded WE group. These results are consistent with Paas et al. (2003) and Renkl (2014) , reporting that WE can help to reduce the extraneous CL and, in return, lead to an increase in germane CL. Again, these differences were just above the significance level, and it would be advantageous to retest with a larger sample to detect even small effects.

Taken together, our results only partially confirm H1: the integration of WE (both faded and non-faded WE) led to a higher acquisition of application knowledge than the control group without WE, but higher factual knowledge was not found. Furthermore, higher motivation or different CL was found on a descriptive level only. The control group provided the basis for comparison with the treatment in order to investigate if there is an effect at all and, if so, how large the effect is. This is an important point to assess whether the effort of implementing WE is justified. Additionally, regarding H2, our results reveal no significant differences between the two WE conditions. We assume that the high complexity of the FA could play a role in this regard, which might be hard to handle, especially for beginners, so learners could benefit from support throughout (i.e., non-faded WE).

In addition to the limitations already mentioned, it must be noted that only one exemplary topic was investigated, and the sample only consisted of students. Since only the learning domain of the double-content WE was investigated, the exemplifying domain could also be analyzed, or further variables like motivation could be included in further studies. Furthermore, the influence of learners’ prior knowledge on learning with WE could be investigated, as studies have found that WE are particularly beneficial in the initial acquisition of cognitive skills ( Kalyuga et al., 2001 ).

6 Conclusion

Overall, the results of the current study suggest a beneficial role for WE in supporting the application of scientific observation steps. A major implication of these findings is that both faded and non-faded WE should be considered, as no general advantage of faded WE over non-faded WE was found. This information can be used to develop targeted interventions aimed at the support of scientific observation skills.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical approval was not required for the study involving human participants in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants in accordance with the national legislation and the institutional requirements.

Author contributions

ML: Writing – original draft. SM: Writing – review & editing. JP: Writing – review & editing. JG: Writing – review & editing. DL: Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2024.1293516/full#supplementary-material

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Keywords: digital media, worked examples, scientific observation, motivation, cognitive load

Citation: Lechner M, Moser S, Pander J, Geist J and Lewalter D (2024) Learning scientific observation with worked examples in a digital learning environment. Front. Educ . 9:1293516. doi: 10.3389/feduc.2024.1293516

Received: 13 September 2023; Accepted: 29 February 2024; Published: 18 March 2024.

Reviewed by:

Copyright © 2024 Lechner, Moser, Pander, Geist and Lewalter. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Miriam Lechner, [email protected]

• Open access
• Published: 26 March 2024

Sourdough bread as nutritional intervention tool for improvement of cognitive dysfunction in diabetic rats

• Doha A. Mohamed   ORCID: orcid.org/0000-0003-0606-9378 1 ,
• Karem Fouda   ORCID: orcid.org/0000-0001-7018-4202 1 ,
• Hoda B. Mabrok   ORCID: orcid.org/0000-0002-3839-0062 1 ,
• Marwa E. El-Shamarka   ORCID: orcid.org/0000-0002-9752-6556 2 &
• Ibrahim M. Hamed   ORCID: orcid.org/0000-0002-1995-4811 1  

BMC Nutrition volume  10 , Article number:  53 ( 2024 ) Cite this article

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The current research targeted to study the impact of nutritional intervention by two sourdough breads in improvement of cognitive dysfunction in diabetic rats.

Type-2 diabetes was induced in rats by Streptozotocin-Nicotinamide (STZ-NC). Diabetic rats were fed on balanced diet or balanced diet containing 20% of sourdough bread I or II for a month. Lipid profile, oxidative stress, inflammatory markers and cognitive functions were assessed in all rats. Gene expression of brain-derived neurotrophic factor (BDNF) and nuclear respiratory factor 2 (NRF-2) were assessed in hippocampal tissue, while expression of phosphoenol pyruvate carboxy kinase (PEPCK), and glucose transporter 2 (GLUT2) genes were evaluated in hepatic tissue. Chemical composition and fatty acids profile were evaluated in the prepared sourdough bread.

Sourdough bread II showed higher content of phenolic compounds, fat, fiber and carbohydrates. Fatty acids profile revealed that sourdough bread I was higher in saturated fatty acids (16.08%), while sourdough bread sample II was higher in unsaturated fatty acids (79.33%). Sourdough bread I or II feeding rats’ showed significant improvement in hyperglycemia, oxidative stress markers, inflammatory markers, lipid profile, liver and kidney functions in association with improvement in cognitive function. Gene expression of BDNF and NRF2 in hippocampal tissue were increased significantly, while hepatic GLUT2 and PEPCK gene expression were down-regulated in diabetic given sourdough bread I or II.

Sourdough bread II was superior in all the studied parameters. The anti-diabetic effect and protection from cognitive dysfunction of sourdough bread samples may be ascribed to the occurrence of dietary fibers, phenolic compounds, and polyunsaturated fatty acids.

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Diabetes mellitus is considered as one of the non-communicable disease affecting globally 537 million of people and this number rise to 783 million by 2045 [ 1 ]. People older than 65 years accounted about 19% of diabetic patients, while diabetic patients ranged from 65 to 99 years estimated 123 million globally [ 2 ]. The prevalence of Alzheimer’s disease (AD) is elevated in diabetic patients (65%) than normal subjects [ 3 ]. Type2-diabetes (T2D) causes brain oxidative stress, insulin resistance, and cognitive dysfunction [ 2 , 4 ]. Glucose intolerance, insulin resistance and impaired insulin excretion are the main linkage between T2D and AD [ 5 ]. Due to the conjunction of the reasons for T2D and AD a new name is created, which is Type 3 diabetes referring to AD as form of AD diabetes that especially involve the brain [ 6 ]. According to World Health Organization (WHO) T2D is consider as risk factor for dementia [ 7 ]. Consequently, diabetes and its disorders must be controlled for AD prevention [ 5 ]. Brain-derived neurotrophic factor (BDNF) is a neurotrophic factor act as neurotransmitter mediator, stimulates neuron regeneration, connection, decrease liver gluconeogenesis and promote liver insulin signal transduction [ 8 ]. Nuclear factor erythroid 2-related factor 2 (Nrf2) regulate BDNF, suppressed oxidative stress, decrease expression of genes related to gluconeogenesis such as GLUT2 and increase cellular glucose uptake [ 9 ]. Injection of insulin as treatment for diabetes induces neurotrophic factors (BDNF) in hippocampus which has an improving effect on memory performance of Morris water maze test [ 10 ]. Insulin impact on cognition may be mediated through glucose metabolism regulation in cortex and hippocampus region which responsible for learning and memory in brain. This action is mediated by elevation in glucose transporter genes (GLUTs) and glucose uptake [ 11 ]. Shi et al. [ 12 ] reported that a natural food additive called trilobatin has anti-diabetic effect through activation of IRD-1/GLUT2 pathway and NRF2/ARE pathway. Hence, producing a novel food product has an effect on glucose transporter signaling as well as NRF2 signaling might serve as a promising candidate for treatment of diabetic and prevent from cognition dysfunction.

Conventional sourdough starter is an old dough fermenting factor made by blending flour and water, put up with spontaneous fermentation through yeast and lactic acid bacteria (LAB). Sourdough enhance bread quality by prolongation of shelf life, augmented loaf volume, retard staling, enhance sensory characteristics, and increased nutritional value [ 13 , 14 , 15 ]. Conventional sourdough breads have proven health beneficial effects such as lowering of risks related to colorectal cancer, obesity, cardiovascular diseases and diabetes. The sourdoughs used in bread production usually contain a wide range of probiotics which give more beneficial activities towards human health [ 16 ]. Sourdough fermentation has been shown reduction in glycaemic index of baked products and enhances phytochemical content and increases the availability of minerals through reduction of anti-nutritional factors [ 17 ]. Fibers, polyphenols and polyunsaturated fatty acids have prebiotic properties and play an important role in improving cognitive performance in animal models through influence on biochemical pathways such as brain derived neurotropic factor [ 18 , 19 ]. Thus, nutritional intervention by fermented foods in form of sourdough bread containing plant food ingredients rich in phytochemicals (phenolic compounds, polyphenols and flavonoids) and phytonutrients (polyunsaturated fatty acids and fibers) may be a good strategy in treatment of type 2 diabetes and its complication in cognitive function impairment. The goal of the current investigation was preparation of two sourdough bread formulae and evaluation of their hypoglycaemic effect in type-2 diabetes induced in rats by Streptozotocin/Nicotinamide (STZ/NC). The impact of diabetes in biochemical parameters, molecular and behavioural parameters were assessed in all rats. Chemical analysis and fatty acids profile of the prepared sourdough bread were evaluated.

Plant materials

All material were purchased from local market (Cairo, Egypt) including sesame seeds, quinoa seeds, chickpea seeds, lupin seeds, whole wheat flour, wheat germ, oat, sunflower oil, sesame oil, yeast, salt and yoghurt.

Male rats of Sprague Dawley of average body weight 154.4 g were used in the current research. Animals were purchased from the National Research Centre Animal house. During the study, the animals were given clean water and normal laboratory feeds ad-libitum . All animals were housed individually in cages. The animal procedures were done according to our institutional research and ethics committee and in line with the ethical guideline for animal care and use for scientific purposes developed by the National Research Centre, Egypt (19176).

Animal’s diets

Three types of diet were designed and fed to animals during the entire study term (Table 1 ). AIN-93 vitamin and salt mixture were prepared according to Reeves et al. [ 20 ]. The prepared two sourdough bread samples were dehydrated and crush into powder prior their addition to the diet.

Preparation of sourdough

Liquid sourdough starter (LTSS) was prepared through fermentation of whole wheat flour and water in equal ratios according to the methods of Rózyło et al. [ 22 ] and Couch [ 23 ]. Twenty –four hour after incubation at 34 °C, of the preferment’s was refreshed each 7h/day with whole wheat flour and water till mature. Moreover, the mature sourdough starter was identified through the emergence of bubbles, the evanescence of the rotten milk smell, the emergence of a sweet smell, and a doubling in volume. So, sourdough was readiness for using in bread preparation.

Preparation, proximate analysis, phenolic compounds content and fatty acids profile of sourdough bread samples

Two sourdough (I and II) were intended. Bread I ingredients were sesame seeds, quinoa seeds, chickpea seeds (soaked, boiled and dried), sesame oil, yeast, yoghurt, salt and flour of whole wheat. Bread II was consisted of lupin seeds (soaked, boiled and dried), oat, wheat germ, sunflower seeds, yeast, yoghurt, salt and flour of whole wheat.

Sourdough was mixed with the dried ingredients of powder mixture of bread I and II in a spiral type KM400 dough mixer (Kenwood Havant, Hampshire, UK) for 10 min, temperature of dough after mixing was 25 ℃. Dough was incubated for 30 min at 35 ◦C. Bread samples were baked in oven for 45 min at 200 ± 10 ℃ after 30 min of incubation. After cooling to ambient temperature, proximate composition of bread samples were analyzed [ 21 ]. Folin-Ciocalteu reagent was used in the estimation of total phenolic content and the results were represented as gallic acid equivalents (GAE) in mg/100g sample[ 24 ]. The results were expressed as mean ± SD for three replicates. Fatty acids methyl esters were prepared according to AOAC [ 21 ] was used for preparation of methyl esters of fatty acids of the formulated sourdough bread for GLC analysis of fatty acids. Fatty acids methyl ester were identified and estimated of the executed using the condition utilized in Moha––med et al. [ 25 ].

Induction of experimental diabetes

Freshly prepared streptozotocin (STZ) (60 mg/kg BW) were intraperitoneally (ip) injected in rats after 15 min from nicotinamide (NA) (ip 110 mg/kg BW) administration [ 26 ]. Fasting blood glucose was measured after 72 h after injection of STZ-NA for proven of T2D in rats (values above 200 mg/dl).

Study protocol

Twenty-four rats were split into four groups (6 rats in group) as follows:

Group1: Normal control rats, Group 2: diabetic control rats (DC), Group 3: diabetic rats fed on balanced diet containing 20% sourdough bread I and Group (4) diabetic rats fed on balanced diet containing 20% sourdough bread II. Rats in groups one and two were rats fed on balanced diet all the experimental period. The impact of diabetes on cognitive functions was assessed in rats through behavioural assessment (MWM, Y-maze, and new object recognition). Throughout the research, food intake and body weight were observed weekly. After five weeks all nutritional parameters (total food intake, body weight gain and feed efficiency ratio) were evaluated.

Rat’s anesthesia for collection of plasma and tissues samples

After overnight fasting, rats were anesthetized with peritoneal injection of 6.6 mg/kg Ketamin and 0.3 mg/ kg of Xylazine. Cardiac puncture blood samples were obtained and centrifuged for plasma extraction. Plasma were detached from all blood samples for estimation of blood glucose [ 27 ], insulin (ELISA kit, Catalogue # SL0373Ra Sunlong ® ), malondialdehyde (MDA) [ 28 ], catalase [ 29 ], C-reactive protein (CRP) (ELISA kit, Catalogue # SL0202Ra Sunlong ® ), tumour necrosis factor-α (TNF-α) (ELISA kit, Catalogue # SL0722Ra, Sunlong ® ). Functions of liver (AST and ALT) and kidney (urea and creatinine) were evaluated using colorimetric kits. Plasma lipid profile was determined (total cholesterol, triglycerides, HDL-cholesterol and LDL-cholesterol) using colorimetric kits. Ratios of T-Ch/HDL-Ch and TGs/HDL-Ch were calculated. Functions of liver (AST and ALT) and kidney (urea and creatinine) were evaluated using colorimetric kits. Plasma lipid profile was determined (total cholesterol, triglycerides, HDL-cholesterol and LDL-cholesterol) using colorimetric kits. Ratios of T-Ch/HDL-Ch and TGs/HDL-Ch were calculated. Consequently, the rats were sacrificed by decapitation under guillotine consisting of a metal frame and a sharp blade, and being operated by one hand. After decapitation of animals, the liver and brain samples were dissected for gene expression analysis.

Gene expression of BDNF, NRF2, GLUT2 and PEPCK

PureLink®RNA Mini kit (Ambion®Life-technologies TM ) was used to isolate total RNA from frozen hippocampus and liver tissue according to the manufacturer’s guidelines. Total RNA levels and RNA purity were measured using Nanodrop-spectrophotometer. RevertAid first strand cDNA synthesis kit (ThermoFisher® invitrogen TM ) was used to synthesize cDNA from RNA (1.5µg) according to the manufacturer’s guidelines.

Real-time PCR was performed with a Rotor-Gene® MDx instrument. The reaction mixture of 25 µl was contained cDNA (1 µl), master mix (SYBR-Green®PCR master mix, ThermoFisher® invitrogen TM ) and primer pairs (0.25 µM). The sequence of primer pairs used for Brain-derived neurotrophic factor (BDNF) (Gene ID: 116901726), Nuclear respiratory factor 2 (NRF-2) (Gene ID: 116901536), Phosphoenol pyruvate carboxy kinase (PEPCK) (Gene ID:116902279), and Glucose transporter 2 (GLUT2) (Gene ID:116896985) genes expression determination were presented in Table 2 . The protocol for the reaction of PCR used as follow: 2 min at 50°C thereafter 10 min at 95°C subsequently 45 cycles consist of 20 Sec at 95°C, 60 Sec at 60°C, 30 Sec at 72°C then melting curve programme. The target genes relative expressions were calculated using the method of delta CT [ 30 ] and it was normalized to the expression of the house-keeping-gene glyceraldhyde-3-phosthate dehydrogenase (GAPDH) (Gene ID:116884019).

The impact of diabetes on cognitive functions (behavioural assessment)

Three behavioural tests were evaluated in the diabetic rats. These tests were y-maze test, which estimates short memory [ 35 ] , Morris water maze (MWM), which assesses the learning capacity and visuo-spatial memory of animals [ 36 ] and the object recognition test, which test long-term memory (LTM) and evaluate cognition[ 37 ]. All behavioural assessment tests were carried according to the methods of Mohamed et al. [ 38 ].

Statistical analysis

SPSS v26 statistical programme was used to analyse the data, one-way ANOVA with Tukey multiple comparison test was performed to evaluate whether the means are statistically different. The results of bread samples analysis were statistical analysed using Student’s t-test. Normal distributions of values were test by Kolmogorov-Smirnov normality test. Differences were considered significant at p≤0.05.

Table 3 represented the chemical composition and fatty acids profile of the two sourdough bread samples. The results revealed that both bread samples I and II contain similar content of protein (13.24% and 13.14%, respectively) and ash (1.75% and 1.76%, respectively). Sourdough bread I showed higher content of fat (13.97%) compared to sourdough bread II (7.49%), while sourdough bread II presented high fiber (5.66%) and carbohydrates (71.96%) content compared to sourdough bread I. Total phenolic compounds were presented in sourdough bread I and II by 636.4 and 976 mg GAE/100g sample. GC analysis of fatty acids methyl esters of the studied bread samples revealed that sourdough bread I and II contain palmitic acid was the main saturated fatty acid presents in both samples and appeared by 16.08% and 11.65%, respectively. Linoleic acid ω-6 (38.14%) was the major unsaturated fatty acid present in sourdough bread I, while linolenic acid ω-3 (39.71%) was the major unsaturated fatty acid present in sourdough bread II. Oleic acid was present in sourdough bread I and II by 15.82% and 17.87%, respectively. Sourdough bread I (16.08%) was higher in saturated fatty acids compared with sourdough bread II (11.65%), while sourdough bread II (79.33%) was higher in unsaturated fatty acids compared with sourdough bread I (53.65%).

Table 4 showed plasma levels of glucose, insulin, oxidative stress and inflammatory markers of different experimental groups. The results revealed that plasma levels of glucose were elevated (163.4%) significantly in diabetic control rats compared with normal. Plasma levels of insulin were reduced significantly in diabetic control rats compared with normal by 39.6%. Elevation of plasma glucose and reduction of plasma insulin in diabetic control rats are indicator to success of STZ as a model in induction of diabetes in rats. Rats feeding on balanced diet containing sourdough bread I or II noticed significant reduction in plasma glucose levels compared with diabetic control by 56.8% and 58.2%, respectively. Rats’ groups feeding on balanced diet containing sourdough bread I or II recorded significant elevation in plasma levels of insulin by 43% and 56%, respectively. Plasma MDA as indicator of lipid peroxidation was elevated significantly in diabetic control (118.6%) rats compared with normal rats, while plasma catalase as indicator to antioxidant status reduced significantly in diabetic rats (51.1%) in comparison to normal control rats. Elevation in plasma MDA in association with reduction of catalase is indicator to elevation of oxidative stress status in diabetic rats. Plasma TNF-α and CRP as inflammatory markers recorded significant elevation in diabetic control when compared with normal rats by 114% and 100%, respectively. Diabetic rats feeding on balanced diet containing sourdough bread I or II showed significant reduction in plasma levels of oxidative stress (MDA & catalase) and inflammatory markers (TNF-α and CRP) with different degrees.

Table 5 showed plasma lipid profile, liver and kidney functions of normal and different diabetic rats groups. The results revealed that diabetic control group showed significant elevation in plasma levels of total cholesterol (78.5%), triglycerides (69.9%), LDL-cholesterol (218.3%) in association with reduction of HDL-cholesterol levels (22.6%) when compared with normal rats. The atherogenic ratio total cholesterol/HDL-cholesterol elevated significantly by 129.5% in the rats of diabetic control. Noteworthy raise were witnessed in liver (AST and ALT) and kidney (urea and creatinine) functions of diabetic control rats compared with normal rats. Feeding diabetic rats on balanced diet containing sourdough bread I or II improved plasma lipid profile with different degrees. AST and ALT as indicator to liver function were retarded to normal levels in rats feeding on balanced diet containing sourdough bread I or II. Also plasma urea and creatinine as kidney function indicator recorded significant reduction with different degrees compared with diabetic control in rats’ groups feeding on balanced diet containing sourdough bread I or II.

Table 6 indicated parameters of nutritional evaluation of different investigational groups. Rats of diabetic control revealed meaningful decrease in the gain of body weight and the ratio of food efficiency compared with all the studied rats groups, while the remained nutritional parameters and relative liver weight showed non-significant changes. The gain of body weight, final weight of the body, and liver relative weight of rats feeding on balanced diet containing sourdough bread I or II showed non-significant changes compared with normal rats group.

The mRNA gene expression of BDNF and NRF2 in hippocampal tissue (Fig. 1 ) were significantly ( p < 0.001) down-regulated in diabetic control rats compared to normal control rats by 86% and 58%, respectively. Feeding on balanced diet containing sourdough bread I and II significantly increased the levels of BDNF ( p < 0.01) gene expression by 2.6 and 2.9 fold changes, respectively. The mRNA levels of NRF2 were significantly elevated by sourdough bread I and II by 29 and 32%, respectively.

The mRNA gene expression of BDNF and NRF2 in hippocampal tissue and GLUT2 and PEPCK in liver tissue of different experimental rats. The mRNA expression is normalized with housekeeping gene (GAPDH), values are representing as means± SE. Similar letters mean non-significant difference within groups at P ≤0.05

Hepatic GLUT2 and PEPCK gene expression (Fig. 1 ) were significantly ( p < 0.001) up-regulated in rats of diabetic-control in comparison with rats of normal group (Fig. 1 ). Feeding on balanced diet containing sourdough bread I and II significantly ( p < 0.001) decreased the levels of GLUT2 and PEPCK gene expression. Sourdough bread I and II I and II down-regulated GLUT2 gene expression by 8.5 and 8 fold-change, respectively. Sourdough bread I and II down-regulated PEPCK gene expression by 8.5 and 7 fold-change, respectively.

Behavioural studies

The impact of diabetes in cognitive functions was evaluated through studying the different behavioural tests of all diabetic rats compared to normal rats. Diabetes leads to cognitive dysfunction as clarified in the investigated behavioural tests (water maze test, Y maze test and novel object recognition).

Y–maze test

Short-term memory is evaluated by Y-maze test. Diabetes leads to significant decreased in the percentage change seen in the diabetic control by 10.75% (Fig. 2 ) from those noticed in the normal rats. Feeding on balanced diet containing sourdough bread II showed significant elevation in percentage change in comparison to the diabetic control, while diet containing sourdough bread I showed non-significant elevation compared with diabetic control. However, the changes were still lower than that witnessed in the normal control.

Y-maze test of normal and diabetic groups. Similar letters mean non-significant difference within groups at P ≤0.05

The Morris water maze test (MWM)

The MWM is applied to reconnoitre the spatial signal learning and memory of mice. The average of each group of the two trials that held in the same day was recorded and taken. On the first day, rat in all groups took the full 60 s fixed for the test to attain the platform. From the second day to the fifth day, normal rats and rats feeding on balanced diet containing both sourdough bread samples began to reveal considerable amelioration in comparison to diabetic control rats.

Impact of diabetes and sourdough bread samples on the time spent in the target quadrant during the probe test

The average time consumed in the target quadrant for rats feeding on balanced diet containing sourdough bread I and II increased by 6 seconds in comparison to that noted in the group of diabetic control (Fig. 3 ). However, it was yet considerably shorter than that relate to the normal group.

Morris water maze of normal and diabetic groups. Similar letters mean non-significant difference within groups at P ≤0.05

The Novel object recognition test

NOR test investigates non-spatial memory (long-term remembrance and cognition). The period diabetic control rats, as well as rats feeding on balanced diet containing sourdough bread I spent exploring the new object was significantly lower from the time used by normal rats discovering the novel object (Fig. 4 ), while rats feeding on balanced diet containing sourdough bread II; spent considerably shorter time in discovering the new object from the time consumed by normal group.

Time spent with new object recognition of normal and diabetic groups. Similar letters mean non-significant difference within groups at P ≤0.05

In the present research the impact of diabetes which induced in male rats through injection with Streptozotocin-Nicotinamide (STZ-NC) on biochemical parameters, gene expression and cognitive functions were evaluated. In the present study male rats were used in the model of diabetes due to their sensitivity to cognitive dysfunction as risk factor of diabetes [ 39 ].

Our results revealed that insulin was reduced in association with elevation of glucose levels, which proven the induction of type-2 diabetes in rats (Table 4 ). Reduction of insulin will cause hyperglycaemia [ 40 ]. Insulin is responsible for regulation of enzymes that metabolized carbohydrate to maintain blood glucose level. Hyperglycemia is associated with the impairment in insulin excretion with extreme hepatic glycogenolysis and gluconeogenesis; and reduction uptake of glucose by the tissues [ 41 ]. Feeding rats on diet containing sourdough bread I or II showed significant elevation of insulin and reduction of glucose, which proven the anti-diabetic effect of the prepared fermented sourdough bread. It was reported previously that sourdough fermentation has been shown reduction in glycaemic index of baked products and enhances phytochemical content and increases the availability of minerals through reduction of anti-nutritional factors [ 17 ].

It was reported previously a considerable correlation between diabetes complication and elevation of blood glucose. Hyperglycaemia induces oxidative stress through imbalance between free radicals and antioxidant defence [ 42 ]. So, lipid peroxidation (MDA) is an indicator of oxidative stress, which measured in the current research. In models of diabetes in animals, MDA plasma level and catalase activity increased and decreased meaningfully due to hyperglycaemia and oxidative stress induction as shown in the current research. The present results proved that CRP and TNF-α as inflammatory makers elevated significantly in diabetic rats. Diabetic rats feeding on balanced diet containing fermented bakery product I or II exhibited significant reduction in CRP and TNF-α as inflammatory makers with variable degrees. Diabetes mellitus is considered as inflammatory disease due to presence of cytokines such as interleukin (IL)-6 and TNF-α which rose in the blood of diabetic patients [ 43 ].

Hyperglycemia induced neuronal and axon injury through rose of oxidative stress in the nervous system [ 44 ]. Natural or chemical drugs have improvement effects on histopathology and renal function markers. Renal dysfunction is one of diabetes complication. So any treatment reduce hyperglycemia may be effective in reducing renal dysfunction [ 45 ].

The present study indicated that feeding rats on sourdough bread I or II showed significant improvement of plasma lipid profile (Table 5 ). Fermentation of food materials is a biochemical operation by microorganisms, which presenting different organoleptic characteristic and elevates nutritional value. Consuming fermented foods is linked, with a broad range of dietary supplements beneficial effect such as antioxidant, neuroprotective, anti-inflammatory, immune-modulatory, and hypocholesterolemic properties [ 46 ].

Brain-derived neurotrophic factor (BDNF) supports the survival and differentiation of embryonic neurons and controls various neural processes in development and adulthood, including growth, differentiation, survival, synaptic formation, function, and plasticity [ 47 , 48 ]. Gene expression of BDNF alteration is contributed to many disorder and diseases such as epilepsy, depression, Parkinson and Alzheimer [ 49 , 50 , 51 , 52 , 53 ]. BDNF plays a role in glucose metabolism and may play pathogenetic roles in type-2 diabetes [ 54 ]. BDNF ameliorate of hyperglycemia by improving hepatic insulin resistance in diabetes models in animal [ 55 ]. Nuclear factor erythroid 2-related factor 2 (Nrf2) regulates anti-inflammatory and antioxidant responses [ 56 , 57 ]. Nrf2 regulates BDNF transcriptions [ 58 ]. Activation of BDNF by transcription factor Nrf2 contributes to antidepressant-like actions in rodents [ 59 , 60 ]. Studies suggested that lack of Nrf2 may impair both type I and II diabetes [ 61 , 62 ]. Nrf2 deficient animals showed deteriorated diabetic symptoms and complications in many  in vivo  models [ 63 ]. Nrf2 activation ameliorate insulin sensitivity in diabetic patients by suppression of oxidative stress, decrease expression of genes related to gluconeogenesis, reduced weight gain and raise skeletal muscle oxygen exhaustion, and ATP output, as well as increase cellular glucose uptake [ 9 ].

GLUT2 is an insulin-independent trans-membrane carrier protein which facilitated glucose movement across cell membranes [ 64 ]. PEPCK also called PCK1 is the first rate-limiting enzyme of gluconeogenesis (catalyses the conversion of oxaloacetate to phosphoenolpyruvate) [ 65 ]. Up-regulation of GLUT2 and PEPCK expression increased the hepatic glucose production and leads to hyperglycaemia and development of diabetes [ 66 ]. The activation of Nrf2 decreases the level of expression of GLUT2 and reactive oxygen species [ 67 ]. Overexpression of PEPCK revoked the expression of the nuclear translocation of Nrf2 [ 68 ]. In our study; fermented bakery products I and II increased the levels of Nrf2 and BDNF and inhibited glucose production by decreasing the levels of GLUT2 and PEPCK gene expression.

Fermentation of food materials is a biochemical operation by microorganisms, which presenting different organoleptic characteristic and elevates nutritional value [ 69 ]. Fermented foods are now considered as “super-foods” for their functional health-enhancer activities [ 46 ]. The valuable effects of fermented foods for brain and cognitive function was reported previously [ 70 , 71 , 72 , 73 ].

The compounds resulted by fermentation of food boost their neuroprotective effects by raising their bioavailability by intestinal absorption and exploitation of the consumed nutrients within the body [ 74 , 75 ] . Short-chain fatty acids (SCFA) positively effectiveness the host metabolism and play essential role in the CNS [ 76 ]. Microbiota may be contributing in the management of absorption of phytochemicals and improves their activities as antioxidant and anti-inflammatory [ 77 , 78 ]. Probobiotic supplementation possessed alleviation in memory dysfunction and neuroinflammation through their activities as anti-inflammatory and antioxidant; via lipopolysaccharides-induced suppression of acetylcholeinesterase [ 79 ].

Nutritional intervention is the best efficient way to moderating the gut microbiota. Dietary supplements influence the gut microbial composition and directly affect neural functioning in both the ENS and CNS [ 80 , 81 ]. Diet containing fruits and vegetables as source of antioxidants, probiotics, flaxseed, nuts and fish as source of omega-3 polyunsaturated fatty acids has been shown to alleviate inflammation of the neuron and reduce the chance of cognitive dysfunction and finally AD [ 82 , 83 ].

In the present study sourdough bread samples I and II containing fibers as shown from the proximate analysis (Table 3 ), polyunsaturated fatty acids (Table 3 ) and phenolic compounds (Table 3 ). Fibers, phenolic compounds and polyunsaturated fatty acids have prebiotic properties and play an important role in improving cognitive performance in animal models through influence on biochemical pathways such as brain derived neurotropic factor [ 18 , 19 ]. Linolenic acid (ALA) (C18:3, ω-3), which is present in both prepared bread samples (Table 3 ); when consumed is metabolized to EPA (20:5 ω-3) and DHA (22:6 ω-3) by series of desaturation and elongation reactions. EPA (20:5 ω-3) and DHA (22:6 ω-3) are essential PUFA and are important component of cell membranes. Both EPA and DHA reportedly have neuroprotective effects via mechanisms such as suppression of inflammation, regulation of neurogenesis, and protection against oxidative stress [ 84 ]. Omega-3 fatty acids significantly induce neovasculogenesis in high glucose-mediated endothelial progenitor cells in type-2 diabetes. Also they are effective in diabetic retinopathy via suppression of angiogenesis [ 85 ].

The outcomes of the present research could support the WHO guidelines about the effect of diabetes on increasing cognitive dysfunction incidence. The studied sourdough breads samples were effectively improved diabetes status in diabetic rats and also reduced the retardation in cognitive function due to diabetes. Sourdough bread II was superior to Sourdough bread I. The anti-diabetic effect and protection from cognitive dysfunction of sourdough bread samples may be ascribed to the occurrence of dietary fibers, phenolic compounds, and polyunsaturated fatty acids.

Availability of data and materials

The data that support the findings of this study are available from corresponding author but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of corresponding author. All the relevant data found in the study are available in the article.

Abbreviations

Alzheimer’s disease

Analysis of variance

Brain-derived neurotrophic factor

C-reactive protein

Glucose transporter 2

Malondialdehyde

Nuclear respiratory factor 2

Phosphoenol pyruvate carboxy kinase

• Streptozotocin-Nicotinamide

Type2-diabetes

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The authors acknowledge the NRC, Egypt for funding this research through the research project No. 12050203.

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Doha A. Mohamed, Karem Fouda, Hoda B. Mabrok & Ibrahim M. Hamed

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DAM was the main researcher, designed the study, analysis all ELISA analysis, prepared, analysed the sourdough bread and prepared the manuscript. KF performed the animal experiment and analysis plasma colorimetric analysis and enter data on the excel sheet. HBM evaluated all PCR, gene expression study, performed statistical data analysis and contribute in the preparation of the manuscript. MEE studied the behavioural assessment. IMH prepared all raw materials, contribute in preparation of the sourdough bread, and contribute in preparation of the manuscript. All authors read and approved the final manuscript.

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Mohamed, D.A., Fouda, K., Mabrok, H.B. et al. Sourdough bread as nutritional intervention tool for improvement of cognitive dysfunction in diabetic rats. BMC Nutr 10 , 53 (2024). https://doi.org/10.1186/s40795-024-00861-x

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The effects of individual music therapy in nursing home residents with dementia to improve general well-being: study protocol of a randomized controlled trial

• Vanusa M. Baroni Caramel   ORCID: orcid.org/0000-0002-1921-0951 1 , 2 ,
• Jenny T. van der Steen   ORCID: orcid.org/0000-0002-9063-7501 3 , 4 ,
• Annemieke C. Vink   ORCID: orcid.org/0000-0003-4242-4314 5 ,
• Sarah I. M. Janus   ORCID: orcid.org/0000-0003-0419-4407 1 ,
• Jos W. R. Twisk   ORCID: orcid.org/0000-0001-9617-1020 6 ,
• Erik J. A. Scherder   ORCID: orcid.org/0000-0003-1203-3208 2 &
• Sytse U. Zuidema   ORCID: orcid.org/0000-0002-4991-9507 1  

BMC Geriatrics volume  24 , Article number:  290 ( 2024 ) Cite this article

Metrics details

Dementia is often associated with Neuropsychiatric Symptoms (NPS) such as agitation, depression, hallucinations, anxiety, that can cause distress for the resident with dementia in long-term care settings and can impose emotional burden on the environment. NPS are often treated with psychotropic drugs, which, however, frequently cause side effects. Alternatively, non-pharmacological interventions can improve well-being and maintain an optimal quality of life (QoL) of those living with dementia. Other QoL related outcomes, such as pain, discomfort and sleep disruption are relevant outcomes in music trials as well. Music therapy is a non-pharmacological intervention that can reduce NPS and improve well-being, and its associated symptoms in dementia.

The research will be conducted at eight nursing home facilities of a health care organization in the Netherlands. A sample size of 30 in each group (experimental and control group) is required, totalling 60 residents increased to 80 when considering expected drop out to follow up. The participants in the intervention group receive 30 min of individual music therapy (MT) in their own room by a music therapist twice a week for 12 weeks. The participants in the control group will receive 30 min of individual attention in their own room by a volunteer twice a week for 12 weeks. Assessments will be done at baseline, 6 weeks and 12 weeks. An independent observer, blinded for the intervention or control condition, will assess directly observed well-being (primary outcome) and pain (secondary outcome) before and after the sessions. Nurses will assess other secondary outcomes unblinded, i.e., perceived quality of life and NPS, both assessed with validated scales. The sleep duration will be indirectly assessed by a wrist device called MotionWatch. Information about psychotropic drug use will be derived from electronic medical chart review.

The main purpose of this study is to assess the effects of individual music therapy on directly observed well-being controlled for individual attention in nursing home residents with dementia with NPS. The outcomes refer to both short-term and long-term effects consistent with therapeutic goals of care for a longer term. We hope to overcome limitations of previous study designs such as not blinded designs and music facilitators that were not only music therapists but also occupational therapists and nurses. This study should lead to more focused recommendations for practice and further research into non-pharmacological interventions in dementia such as music therapy.

Trial registration

The trial is registered at the International Clinical Trials Registry Platform (ICTRP) search portal in the Netherlands Trial Registration number NL7708, registration date 04-05-2019.

Peer Review reports

Introduction

Background and rationale.

Dementia is a common disease and in 2021, the World Health Organization estimated that around 55 million people have dementia worldwide [ 1 ]. Dementia is a neurodegenerative syndrome characterized by a progressive deterioration of cognitive function, in particular memory but other cognitive domains such as language, praxis, visual perception and most notably executive functions are also often affected [ 2 ]. Personality and behavior changes, together with a decline in the ability to perform activities of daily living, may result in a loss of independence. The personality and behavioral changes are often reflected in Neuropsychiatric Symptoms (NPS). More specifically, NPS may express itself in, for example, agitation, disinhibition, irritability, delusions, hallucinations, depression, anxiety and apathy. These symptoms are ubiquitous in nursing home patients with dementia, with overall rates of more than 80% [ 3 ].

As there are no curative treatments for dementia yet, it is important to focus on interventions that may have beneficial effects on well-being and maintain an optimal quality of life. Quality of life is defined by the WHO as “individuals’ perceptions of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” [ 4 ]. Well-being is defined in terms of a state of equilibrium existing between personal resources and life challenges that, when achieved, gives rise to positive emotions and psychological health [ 5 ]. The constructs of QoL and well-being have often been used inter-changeably in dementia research [ 6 ].

There is a growing consensus that quality of life is an important outcome for assessing the effectiveness of interventions for dementia in clinical trials even though it concerns a multidimensional construct influenced by a variety of factors [ 7 , 8 ]. An observational study in 288 nursing home residents with dementia, showed that NPS such as agitation and depression were particularly strong predictors of poor QoL [ 9 ]. These results underline the growing awareness that NPS independently decreases QoL in moderate and severe stages of dementia [ 9 ]. Pain is highly prevalent in nursing home residents [ 10 , 11 ] and can also cause NPS and influences their quality of life directly [ 12 ]. Nursing home residents with severe cognitive impairment who have difficulty expressing pain may manifest it through agitation, aggression, or withdrawal [ 10 ]. Pain in dementia may express itself also through vocalizations (e.g., crying, screaming, noisy breathing), specific facial expressions (e.g. grimacing) and body language such as restless behaviour [ 13 , 14 ].

Another factor that may reduce QoL of people with dementia is a deterioration of sleep quality. Sleep disturbances include poor sleep efficiency and increased night awakenings. Petrovsky [ 15 ] used domains of Lawton’s framework for quality of life in persons with dementia to synthesize current knowledge on the association between sleep disruption and quality of life in persons with dementia. Sleep disruption was negatively associated with all of four QoL domains (physical functioning, social/behavioral functioning, emotional well-being and cognitive function). In sum, neuropsychiatric symptoms, in relation to or provoked by pain and sleep disturbances, reduces QoL in people with dementia.

Consequently, the question arises if adequate strategies are available for treating this triad of symptoms, i.e. NPS, pain, and sleep disturbances, and hence, improving QoL, in people with dementia. NPS are often treated pharmacologically with psychotropic drugs, which frequently cause unwanted side effects, such as somnolence and extrapyramidal symptoms [ 16 ]. Psychosocial interventions, however, may obviate the indication for antipsychotic drug prescriptions [ 17 ]. Moreover, therapies such as validation, reminiscence, psychomotor therapy, multisensory stimulation and music therapy can increase QoL of people with dementia and their caregivers [ 18 ]. Sikkes et al. reviewed the evidence and found that various non-pharmacologic treatments such as music therapy effectively improve behavior [ 19 ].

Music therapy is a non-pharmacological intervention which is used as a treatment for NPS in patients with dementia [ 20 , 21 , 22 ]. In the USA, music therapy is defined by the American Music Therapy Association (AMTA) as “the clinical and evidence-based use of music interventions within a therapeutic relationship to accomplish individualized goals by a credentialed professional who has completed an approved music therapy program” [ 23 ]. This definition of music therapy and the accompanying AMTA Standards of Practice recommend an individualized treatment process, including referral, building a therapeutic relationship, assessment, observation, targeting individualized goals and objectives, treatment planning, protocol selection and implementation, termination and evaluation [ 24 ]. The number of studies examining the effects of music therapy for people with dementia has increased over time [ 25 ]. A Cochrane review in 2011 [ 26 ] included 10 studies mostly of poor quality and could not draw firm conclusions about the effects of music therapy in the treatment of behavioral, social, cognitive and emotional problems of older people with dementia. In an update of the Cochrane review [ 27 ] twenty-two studies were included. The results from the review suggest that music therapy may also improve emotional well-being including quality of life. However, outcomes could be based on recall or direct observation, and not all outcomes are assessed blinded. The results of the review further suggest that providing institutionalized people with dementia with at least five sessions of a music-based therapeutic intervention might reduce NPS. Moreover, individual therapy, compared with group therapy, had larger effects on behavioral outcomes (agitation, aggression and overall behavioral problems).

Indeed, music therapy can be offered via individual treatment, as well as through a group approach [ 28 ]. The group approach benefits engagement and social interaction but in advanced stages of dementia, individual music therapy can better reach the residents with communicative limitations. Personalized interventions with music or music therapy may be a predictor of success [ 20 ].

In 2010, we conducted a randomized pilot study on individual music therapy in a nursing home in the Netherlands. The intervention group received individual music therapy from a qualified music therapist who used a person-centered approach. The results pointed to possible reduction of NPS in patients who received individual music therapy compared to patients in the control condition who received usual care [ 29 ]. The sample size of the pilot study was very small and the outcome assessments were not blinded. Sakamoto [ 30 ] conducted an RCT in 2013 with blinded outcome assessment and individual intervention sessions carried out by music facilitators. The study indicated that interactive individualized interventions reduce stress and increase relaxation in individuals with severe dementia immediately after the intervention.

The main purpose of the present study is to build on the earlier pilot study with an improved design, in which we blindly assess the effects of individual music therapy delivered by an accredited music therapist on directly observed well-being and related outcomes such as NPS, agitation, depression, quality of life and pain controlled for individual attention in nursing home residents with dementia who also have NPS.

Trial design

The design involves an individual randomized controlled trial (RCT) employing longitudinal repeated measurements in nursing home residents with dementia and NPS. The study is single blinded. The research assistant who assesses the primary outcome well-being and the secondary outcome pain through observation does not know whether residents participate in the experimental group or the control group. The music therapist and the patients themselves cannot be blinded to the condition they are assigned to. Nursing staff that performs the measurements as part of the secondary outcomes is not blinded either. The research takes place at eight nursing homes facilities of a health care organization in the Netherlands. Music therapy is provided in 30-minutes sessions, twice a week for 12 weeks, in their own room. The control group receives a ‘social’ visit with individual attention with the same frequency and of the same duration.

A process evaluation is performed according to an approach developed by Saunders [ 31 ], using components from Linnan and Steckler’s [ 32 ]. The process evaluation is based on mixed methods, collecting quantitative and qualitative data. Qualitative data collection comprises a focus group discussion with participants of health care professionals to evaluate barriers and facilitators influencing the implementation of research protocol. Quantitative data is gathered with questionnaires about reach, dose delivered, dose received, fidelity, recruitment and participant engagement. Quantitative data is gathered with questionnaires at 1, 2, 6 and 12 weeks after the baseline assessment completed by music therapists (intervention) or attendants (control). The questionnaires include items about participation in the sessions, fidelity, dose, engagement and about levels of implementation. Nurses and a research assistant will fill a questionnaire at the end of treatment to evaluate the process of implementation. Quantitative data will be analyzed with descriptive statistics.

Study setting

The study population consist of a sample of residents with dementia and NPS, residing on psychogeriatric units in one of eight nursing homes facilities of a health care organization (Amstelring) in the Netherlands.

Participants’ eligibility

Inclusion criteria.

First, potentially eligible participants of psychogeriatric units in eight nursing homes are screened for eligibility according to the following criteria:

Candidate has a charted diagnosis of dementia, which is in general according to Diagnostic and Statistical Manual of Mental Disorders IV criteria (American psychiatric association, 2001).

Display a clinically relevant NPS measured with the Neuropsychiatric Inventory Nursing Home Version (NPI-NH) [ 33 , 34 ] with the Frequency X Severity item score for at least one individual item rated 4 (Wood, 2000 [ 35 ]; Margallo, 2001 [ 36 ], Zuidema, 2007 [ 3 ], Zuidema, 2010 [ 37 ].

Exclusion criteria

Candidate having received individual music therapy before or having participated in a music therapy group in the past 3 months.

Candidate has major comorbid psychiatric diagnosis (i.e., schizophrenia, psychosis, anxiety disorder). Due to an overlap between depression and dementia [ 38 ], candidate participants with a history of depression will not be excluded.

Candidate has a hearing impairment that hampers the listening to music at a moderately volume. We use item 1a of the Severe Dual Sensory Loss in old age screening tool (SDSL) [ 39 ]. SDSL was found a valid and reliable tool [ 40 ].

Demographic variables

Demographic variables such as age and gender will be assessed at baseline from the electronical medical chart review.

At baseline, nurses will register whether the resident has any background in music with questions about their experiences with music before entering the nursing home. The relatives of participants are asked closed-ended questions if the participant:

Has no experience with music in the past.

Played an instrument before or was involved in singing activities or made music in some other way.

Has served as a professional musician.

Material and procedure

Intervention.

The participants of the intervention group (music therapy) receive 30 min of individual music therapy twice a week for 12 weeks in their own room. Music therapists use music experiences to promote health [ 41 ]. In this trial, music therapy consists of individual active music therapy sessions with also receptive techniques. Individual music therapy implies a one-to-one contact between the music therapist and the patient using a person-centered approach. Receptive and active music therapy are often combined [ 42 ]. Receptive therapeutic interventions consist of listening to music by the therapist who sings, plays, or selects recorded music for the recipients. In active music therapy, recipients are actively involved in the music-making, for instance by playing on small instruments. The participants may be encouraged to participate in musical improvisation with instruments or voices, movements activities or singing.

To determine the precise content of the intervention and to standardize procedures amongst all music therapists of Amstelring we conducted a focus group with 7 music therapists working at the nursing home facilities of Amstelring. We used a group interview because reaching a consensus is best achieved in a group setting. The focus group established a therapy protocol that comprised six steps for this study purpose:

All participating music therapists are employed by the nursing home organization. The music therapists are qualified and credentialed professionals by the federations for music therapy in the Netherlands (NVvMT), indicating that they have all been trained at an acknowledged and certified music therapy study program.

The music therapist will ask, before the start, the participant or a legal representative about the musical preferences of the participant with a questionnaire (Gerdner, 2010 [ 43 ], Raven-de Vries, 2018 [ 44 ]). Based on this information, the music therapist will develop an individual music therapy session for the participants.

Music therapists start each session trying to connect with the patient by eye contact, calling the name or giving a hand, to build trust.

Music therapists use an observation list between 4 and 6 weeks. This observation list is based on the improvisational music therapy guideline of Kurstjens [ 45 ] and has been used to identify which important musical elements are of help in the approach of the problem.

The music therapists will adapt the therapy continuously to needs and wishes of the participants. Participants receive an individual session tailored to the musical preferences of the participant.

The participant will be invited to make a choice out of different musical instruments such as a guitar, keyboard, drums, maracas, etc. The therapist will aim at using active techniques mainly, for example improvisation where participants will try to play the instruments, sing together, clap the hands, move the body or face with the music. Also, receptive techniques will be used such as listening to live or pre-recorded music. The music therapist provides a safe environment, in which the participant can experience contact, interaction, atonement, structure and a natural finishing of the session.

In case of refusal of the session of adverse reactions such as fatigue or traumatic memory during the sessions, music therapists inform the researcher (VMBC). The music therapists then stop immediately. Music therapists fill in questionnaires at 1, 2, 6 and 12 weeks after the intervention starts to gather information for the process evaluation. During the Covid-19 outbreak, the music therapists (intervention group) use gloves and face masks during the sessions.

Control condition

The control group receives 30 min of individual attention twice a week for 12 weeks with no therapeutic basis. Individual attention will take place through a social visit, during which an attendant will drink coffee or tea with the participant. The individual attention will be given in the resident’s room by one attendant, who will have a conversation with the participant, drink coffee without an intervention goal such as cognitive training and without any musical intervention. The person who is doing the social visits is an informal care support company employee or volunteer. The attendants are students who work for an informal care support company and had a workshop about dementia. This is on top of the regular usual care delivered. The attendant starts every session by trying to connect with the patient via eye contact, calling his/her name or giving a hand, to build trust.

The attendants from the informal care support company or care support volunteer who provide the individual attention report attended sessions in the participants forms. In case of refusal of the session, the attendants inform the researcher (VMBC). The individual attention will then stop immediately. Attendants fill in questionnaires at 1, 2, 6 and 12 weeks after the individual attention starts to gather information for the process evaluation. During the Covid-19 outbreak, the attendants (control group) use gloves and face masks through the sessions.

Primary outcome measure

Observed well-being is the primary outcome measure rather than multidimensional quality of life with proxy estimation of domain ratings based on recall. Lawton has most extensively explored the concept of QoL concerning dementia and described QoL in dementia in terms of four sectors: psychological well-being, behavioral competence, objective environment (response to surroundings) and perceived QoL [ 46 , 47 , 48 ]. Jonker et al. reviewed conceptual developments in QoL research concerning dementia and based on the dimensions presented by Lawton, they identified psychological well-being as the core dimension of QoL of patients with dementia. Patients with severe dementia cannot always self-report their psychological well-being [ 49 ] but indicators of wellbeing of persons with dementia can be observed with validated instruments. We assess well-being with an objective observational instrument−the Discomfort Scale - Dementia of Alzheimer Type (DS-DAT) where discomfort is defined as a negative emotional and/or physical state subject to variation in magnitude in response to internal or environmental conditions. It is a scale for direct observation of behavior of a patient and is applicable also in later phases of dementia [ 50 ]. The Dutch translation is characterized by a good reliability (Hoogendoorn. 2001) [ 51 ] and validity (van der Steen, 2002) [ 52 , 53 ]. The scale consists of 9 items measuring 7 negative and 2 positive items regarding vocalization, breathing, facial expression, and body movements. The nine 4-point items are summed for a total score ranging from 0 (no observed discomfort) to 27 (highest possible level of observed discomfort). Well-being will be assessed by a blinded research assistant at baseline (T0), six weeks (T1) and twelve weeks (T2). Well-being is assessed during 5 min before and after the music therapy sessions or individual attention sessions. The research assistant will be trained in using the DS-DAT trough an instructional video and practice completion of the DS-DAT with videotaped patients. Feedback is provided against the scores of the scale’s developer (Dr Hurley) who had rated the patient video clips.

Secondary outcomes measures

Secondary outcomes are also assessed in all /participating residents and include pain, quality of life, neuropsychiatric symptoms (agitation, anxiety, symptoms of depression), quality of sleep and psychotropic drug use.

Pain will be assessed by a blinded research assistant at baseline, six weeks and twelve weeks during 2 min before and after the intervention session or individual attention with the PAIC-15 (Pain Assessment in Impaired Cognition) [ 54 , 55 ] which is an observational assessment instrument that lists 15 items and uses scores from 0 to 3 for each item. PAIC-15 comprises three domains: facial expression, body movements and verbalizations/vocalizations. Each domain has 5 items and the total score is the sum of all items, ranging from 0 to 45. The research assistant will be trained in using the PAIC-15.

Quality of life will be rated by non-blinded nurses at baseline (T0), at six weeks (T1) and at twelve weeks (T2) with the Quality of Life in Late-Stage Dementia Scale (QUALID) [ 56 ] that can be used with late-stage dementia patients in institutional settings and has been designed for proxy-rating by nurses. Responses reflect patient behavior over the past seven days. The QUALID consists of eleven items that are short and simple and is characterized by a good reliability and validity and the Dutch translation was a valid measure for quality of life in patients with advanced dementia [ 57 ]. The total score is the sum of all items, ranging from 11 to 55. Lower scores indicate a higher quality of life.

Neuropsychiatric symptoms (NPS) will be assessed by non-blinded nurses at baseline (T0), at six weeks (T1) and at twelve weeks (T2) with the Neuropsychiatric Inventory Nursing Home Version (NPI-NH), a scale originally developed by Cummings [ 33 , 34 ] to assess NPS in outpatients with dementia. The nursing home version was developed for use of professional caregivers in institutions and proved to be valid and reliable for trained nursing staff [ 58 , 59 ]. The NPI-NH is the only nursing home instrument to assess NPS that occurred in the past four weeks that has been translated into Dutch [ 60 ]. The NPI is a structured interview that includes 12 neuropsychiatric symptoms: delusions, hallucinations, agitation, depression, anxiety, euphoria, apathy, disinhibition, irritability, aberrant motor behavior, night-time disturbances and appetite/eating change. Frequency (F) and severity (S) of each symptom are rated on a four (1–4) and three (1–3) point scale respectively. A separate score can be calculated for each symptom by multiplying the frequency and severity (FxS score), resulting values range from zero to 12 for each symptom. Summing all FxS scores results in a total score that ranges from 0 to 144. Interview also includes a caregiver distress questions using a 5-point scale.

Agitation and aggression will be assessed by non-blinded nurses at baseline (T0), 6 weeks (T1) and 12 weeks (T2) using the caregiver rated questionnaire Cohen-Mansfield Agitation Inventory (CMAI). This instrument, developed by Cohen-Mansfield and Billig [ 61 ] and validated by Miller [ 62 ] is an instrument that specifically addresses agitation or aggression that has been translated into Dutch. The Dutch translation of the CMAI (CMAI-D) has been validated by De Jonghe [ 63 ] and rated agitated behaviors occurred during last two weeks. The frequency of each symptom is rated on a seven-point scale (1–7) ranging from ‘never’ to ‘several times an hour’. Summing all symptom scores results in a total score that ranges from 29 to 203.

Depression will be rated by non-blinded nurses at baseline (T0), at six weeks (T1) and twelve weeks (T2) with the Cornell Scale for Depression in Dementia (CSDD) [ 64 ], which has good internal consistency [ 65 ]. Responses reflect symptoms of depression in the week before. The CSDD is a 19-item instrument, with scores for each item ranging from 0 to 2 (total score range 0–38). The CSDD has been translated into Dutch [ 66 ].

Physical activity : rest-activity data will be collected by a MotionWatch (CamNtech Ltd, Cambridge, UK). The MotionWatch measures the arm movements of the participant; based on these movements, the rest-activity and physical activity are determined. It quantifies accelerations due to motor activity of the arm and integrates these over I-minute periods. The MotionWatch has the size and shape of a watch, is worn on the dominant wrist. The participants will be asked to wear the MotionWatch twenty-four hours a day for 1 week in the week before the intervention starts (T0) and the week directly after the last intervention session (T2). Nurses are asked to temporarily take off the MotionWatch when the participant takes a shower, performs another activity in which the MotionWatch could be exposed to too much water. Nurses will report the time that devices are taken off. Five parameters are calculated: Interdaily Stability (IS), Intradaily Variability (IV), Relative Amplitude (RA), most active period of 10 h and least active period of five hours. First, the IS variable that quantifies the strength of coupling between the rest-activity rhythm and supposedly stable Zeitgebers (e.g., meals) is calculated. IV, which quantifies the fragmentation of the rhythm, that is, the frequency and extent of transitions between rest and activity. RA quantifies the difference between the main activity (day) and rest (night) periods. The parameter of 10 most active hours (M10) is used to determine the amount of physical activity. The parameter (L5) are least active periods of five hours to determine rest activity.

Data on chronic psychotropic drug use will be derived from the electronic medical chart. Psychotropic drugs will be categorized into antipsychotics, anxiolytics, hypnotics, antidepressants and anti-dementia drugs according to the Anatomical Therapeutic Classification (ATC) system.

Any attrition or adverse effects of the interventions will be documented. The interventions will be discontinued if, in consultation with the physician or psychologists, harmful effects are observed and are expected to continue with exposure to any of the two interventions.

The nurses will determine the stage of dementia, measured with the Global Deterioration Scale (GDS) [ 67 , 68 ] at baseline. The DS describes seven stages: ‘no global impairment’ (1), ‘very mild cognitive decline’ (2), ‘mild cognitive decline’ (3), ‘moderate cognitive decline’ (4), ‘moderately severe’ (5), ‘severe’ (6) and ‘very severe global impairment’ (7).

Participants timeline

All eligible residents for whom consent have been provided will be randomly allocated to the intervention group (individual music therapy) or control group (individual attention). Randomization will take place with a statistician using randomization software. The outcomes variables are measured at baseline (T0) one week before individual attention of music therapy starts (pre-treatment), after 6 weeks of intervention (T1) and after 12 weeks of intervention (T2). Figure  1 shows the participant’s flow.

Participant flow: T0 baseline data collection, T1 follow up assessment at 6 weeks and T2 the follow up after 12 weeks. Participants who are lost to follow-up at the T2 assessment can still be included in the analyses, due to the use of mixed models analyses

Measurements (DS-DAT and PAIC-15) will be done at baseline T0, just shortly before (T1a and T2a) and shortly after the intervention (T1b and T2b); to assess overall effects, cumulative and immediate effects ( see Table  1 ). An independent research assistant performs the blinded direct observations and complies the primary outcome well-being (measured with the DS-DAT) and secondary outcome pain (measured with the PAIC-15). The nursing staff will complete the unblinding observations scales concerning the various stages of dementia at baseline T0 and they will fill in the unblinding questionnaires about QoL, NPS, agitation and symptoms of depression at T1b and T2b.

Data prescription records concerning medication use, among which psychotropic drugs, will be extracted from the electronic medical charts by VMBC, physician employed by the participating organization.

Sample size

The sample size calculation is based on the study’s primary outcome measure, the Discomfort Scale – Dementia of Alzheimer type (DS-DAT) [ 51 ] for F-tests ANOVA repeated measures. To determine the sample size required to assess relevant effects, we used data from the Cochrane review on music-based therapeutic interventions [ 27 ]; the effect size for emotional well-being and quality of life (SMD 0.32, 95%CI 0.02 to 0.62). The correlation between multiple assessments of the DS-DAT was calculated with the data of Schalkwijk et al. [ 57 ] as 0.6. Using a type I error of 0.05, a power of 0.80, two follow-up measurements and 2 groups, a sample size of 30 in each group is required, totaling 60 participants to achieve 0.81 power. According to the availability of music therapists we estimated that the study would take approximately 3 years. The mortality rate in the nursing home setting is high. Moore [ 58 ] stated that the length of stay in long-term care facilities in Europe countries is almost 2 years. It is estimated that about a one third (20 of 60 residents) may die or will be lost to follow up for other reasons during the study period, so we need to enroll a total of around 70 till 80 residents for this study.

Recruitment

First, the medical staff is informed about the goal and procedure of the study. Second, the medical staff (physicians) of each psychogeriatric unit of the eight nursing homes selects eligible residents with dementia and NPS who have a referral for individual music therapy. Third the researcher provides an information letter with informed consent form to competent residents and to legal representatives of non-competent residents. After informed consent or proxy informed consent has been given and the participant has been recruited, the participants are randomly allocated to the intervention group (individual music therapy) or control group (individual attention).

Assignment of interventions

Participants will be randomly assigned to either the control or the experimental group with a 1:1 allocation as per a computer-generated randomisation schedule. Randomization is performed by a statistician who is not involved in carrying out the study in the facilities, using randomization software.

The study is single blinded, i.e. that the therapist and the patients themselves are not blinded. Trained research assistants who are blinded to intervention assignment, conduct the well-being (primary outcome) and pain (secondary outcome) measurements. The nursing staff completes the scales concerning the stage of dementia, QoL, NPS, agitation and symptoms of depression. Blinding to these measurements is not possible because these measurements require familiarity with the person’s usual behavior in the previous week(s). The nursing staff who complete the questionnaires are not blinded to intervention assignment, but they are not informed about the hypothesis and specific research questions.

Data analysis

Immediate effects are defined as the difference in change between outcomes 15 min before and after the intervention sessions. Cumulative effects are effects over time not including those immediately after the session (i.e., built-up effect over time and measured before the session in order not to include possible immediate effects of the session). Overall effects are effects over time including those immediately after the session. Immediate, cumulative and overall effects are analyzed with mixed model analysis to consider the dependency of the repeated observations within the patient.

For the immediate effects, the outcome will be the post-test (T1b, T2b) and adjustment will be made for the pre-test (T1a, T2a). For the cumulative effect, the outcome will be the pre-test and an adjustment will be made for the baseline. For overall effects, the outcome will be post-test and adjustment will be made for the baseline.

For all treatment effects, effects at the different time-points will be analyzed by adding a time x treatment interaction to the mixed model analysis. Furthermore, both crude and adjusted (adjustments for gender, age, cognitive deterioration and for medication use, which will be added as a time-dependent covariate) will be performed. In the mixed-model analysis, we will also evaluate whether an adjustment for the correlated observations within facilities is necessary. There is no need to impute missing data because mixed models can handle missing assessments.

In explorative post-hoc analysis we will evaluate whether the intervention effects will be different for patients with a musical background by adding the interaction between the intervention variable and presence of musical background.

Sleep quality data of the MotionWatch (CamNtech Ltd, Cambridge, UK) will be analyzed with Motionware software version 1.2.1. Five parameters will be calculated: Interdaily stability, Intradaily variability, Relative Amplitude, most active period of 10 h and least active period of five hours. The 5 parameters will be analyzed with linear regression analyses with the values measured after the intervention period as outcome with an adjustment for the baseline vale of particular outcome.

Study monitoring

This clinical trial does not involve a high-risk intervention. We do not expect adverse events or significant unintended effects of the intervention. However, the participants of this study are vulnerable subjects and monitoring, and quality assurance will be necessary according to national legislation (WMO). The Department of anesthesiology (an independent department of UMCG) will be responsible for the data monitoring.

Over recent decades, the care offered in nursing homes has expanded to include various types of psychosocial interventions such as music therapy, validation, gentle care, psychomotor therapy and movement activation [ 69 ]. Music therapy is a non-pharmacological intervention which is also used as a treatment for NPS in patients with dementia and can improve quality of life [ 70 ].

Quality of life (QoL) is a multi-dimensional concept that includes well-being and has objective and subjective effects [ 49 , 50 , 51 ]. Psychological well-being is considered to be the central indicator for QoL of patients with dementia [ 52 ]. This study aims to show if individual music therapy leads to improved well-being of nursing home residents with dementia and NPS. NPS result in a lower QoL for people with dementia and their caregivers and affect the quality of the relationship with the caregivers [ 71 ]. Efforts aiming at preventing low or decreasing well-being and QoL at any stage of dementia should, therefore, target the factors associated with lower QoL such as psychotropic drug use [ 17 ], NPS [ 9 ], pain [ 10 ] and sleep disturbances [ 15 ] as well as keeping a person-centered approach open to the individual perceptions of QoL [ 71 ]. Music-based interventions can be effective in alleviating the NPS of dementia, such as agitation, depression, and anxiety [ 72 , 73 , 74 ]. Recently, a systematic review concluded that non-pharmacological interventions such as music therapy show a positive impact on pain [ 75 ]. Further, a recent review of 8 studies identified 6 studies showing a positive effect of music interventions on sleep outcomes. There were decreases in nighttime sleep disturbance, increases in daytime alertness, and improvements in sleep quality [ 76 ].

Further, in patients unable to self-report, directly observed well-being is an expression of their emotional and physical state an important indicator of comfort and quality of life, in addition to impressions of quality of life assessed over a specific time window such as the previous week. Quality of life is an important outcome of different care approaches, including palliative care. Improving quality of life and maximizing comfort are goals of palliative care in dementia [ 77 ]. With this design and specific analyses, we can ensure blinding and allow estimation of short and long-term effects.

Participants receive either individual music therapy or a social visit for individual attention, in their own room. This is because the room represents a safe place for the resident. Moving residents to another room may lead unnecessary to more restless behavior during the already short duration of the therapy session.

Research often lacks methodological rigor and continues to produce mixed results. A recent Cochrane review [ 27 ] included 22 studies with 1097 randomized participants to assess the effects of music-based therapeutic interventions for people with dementia. This review showed modest positive effects in meta-analyses of 9 studies on emotional well-being and quality of life of interventions that included group and individual interventions. Only seven studies out of the 22 studies received individual music therapy treatment. Sensitivity analyses indicated that the SMDs for individual therapy were similar to those for the main analyses with individual and group therapy, except for behavioral problems (both agitation or aggression and overall), for which SMDs for individual therapy were clearly larger. In this Cochrane review, many studies did not used blinded outcome assessment. We use blinded assessment for the primary outcome (well-being) and one of the secondary outcome (pain) but possible limitations of this study will be the unblinded assessment of secondary outcomes (with the QUALID, NPI-NH, CMAI, CSDD) assessed by nurses of the department.

During the Covid-19 outbreak, the music therapists (intervention group) and the attendants (control group) used gloves and mouth masks through the sessions that may complicate the relation between participants and music therapists or attendants. Residents who participate in the study during Covid-19 period might receive substandard quality sessions because of the difficulties in the verbal and non-verbal contact. Sensitivity analysis will be done to examine whether this period with wearing of face masks and gloves yields a negative effect on treatment outcome, compared to the period before (or after) the outbreak of COVID-19.

The present study aims to make a next step in the field of music therapy and address the limitations of earlier research by including a larger number of participants and investigating if individual music therapy influences well-being of people with dementia and on NPS and other outcomes. Major strengths of the current study design are, first, the blinded primary outcome assessments and second, the comparison between intervention group with the control group receiving enhanced usual care to rule out effects of extra individual attention. The residents of the intervention group receive individual music therapy from qualified and certified music therapists with knowledge and skills that are clinically relevant to personalized care delivery. This study will help to clarify the effects of individual music therapy in dementia care.

Data availability

The handling of personal data is conducted according to the EU General Data Protection Regulation and the Dutch Act of Implementation of the General Data Protection Regulation (in Dutch: AVG, UAVG).

Abbreviations

• Neuropsychiatric symptoms
• Music therapy

American Music Therapy Association

Dutch association of music therapists:DS-DAT:Discomfort Scale - Dementia of Alzheimer Type

Pain Assessment in Impaired Cognition

Quality of Life in Late-Stage Dementia Scale

Neuropsychiatric Inventory Nursing Home Version

Cohen-Mansfield Agitation Inventory

Cornell Scale for Depression in Dementia

Global Deterioration scale

Medical research involving human subjects act

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Acknowledgements

The authors want to acknowledge the nursing home residents who voluntarily participated in this study. We thank all the music therapists and nurses of Amstelring who contributed to this study. We thank the research assistant Marianne Pruis who did all the blinded observations.

Amstelring Care Institution (RVB U-9109-2019 IB/RR/lw) support this study. This study has also Alzheimer Nederland as subsiding party (Project number: WE.09-2018-06). The funders had no role in the study design, data collection and analysis of data.

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Vanusa M. Baroni Caramel, Sarah I. M. Janus & Sytse U. Zuidema

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Vanusa M. Baroni Caramel & Erik J. A. Scherder

Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands

Jenny T. van der Steen

Department of Primary and Community Care, Radboud university medical center, Nijmegen, The Netherlands

Department of Music Therapy, ArtEZ University of The Arts, Academy of Music, Enschede, The Netherlands

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“This study was conducted according to the guidelines laid down in the declaration of Helsinki. Ethical approval was obtained from the Medical Ethics Review Board of the university medical center of Groningen (UMCG) in the context of the Medical Research Involving Human Subjects Act (WMO). The review board reference number is METc 2019/021. An informed (proxy) consent is obtained for all participants. Participation in the study will be voluntary. Participants or legal representatives can withdraw consent at any time. Any attrition or adverse effects of the intervention or control group will be documented. In addition to sessions immediately stopped in the case of adverse reactions, the interventions will be discontinued if, in consultation with the physician or psychologists, harmful effects are observed and are expected to continue with exposure to any of the two interventions. The trial is registered at the International Clinical Trials Registry Platform (ICTRP) search Trial Registration number NL 7708 ( https://trialsearch.who.int/Trial2.aspx?TrialID=NL7708) ” in the Ethics approval and consent to participate section.

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Baroni Caramel, V.M., van der Steen, J.T., Vink, A.C. et al. The effects of individual music therapy in nursing home residents with dementia to improve general well-being: study protocol of a randomized controlled trial. BMC Geriatr 24 , 290 (2024). https://doi.org/10.1186/s12877-024-04863-z

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DOI : https://doi.org/10.1186/s12877-024-04863-z

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• Quality of life
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• Nursing homes

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Applications of Large Language Models in Psychiatry: A Systematic Review.

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Background: With their unmatched ability to interpret and engage with human language and context, large language models (LLMs) hint at the potential to bridge AI and human cognitive processes. This review explores the current application of LLMs, such as ChatGPT, in the field of psychiatry. Methods: We followed PRISMA guidelines and searched through PubMed, Embase, Web of Science, and Scopus, up until March 2024. Results: From 771 retrieved articles, we included 16 that directly examine LLMs' use in psychiatry. LLMs, particularly ChatGPT and GPT-4, showed diverse applications in clinical reasoning, social media, and education within psychiatry. They can assist in diagnosing mental health issues, managing depression, evaluating suicide risk, and supporting education in the field. However, our review also points out their limitations, such as difficulties with complex cases and potential underestimation of suicide risks. Conclusion: Early research in psychiatry reveals LLMs' versatile applications, from diagnostic support to educational roles. Given the rapid pace of advancement, future investigations are poised to explore the extent to which these models might redefine traditional roles in mental health care.

Competing Interest Statement

The authors have declared no competing interest.

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This study did not receive any funding

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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