qualitative research analysis course

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Qualitative Data Analysis

This course provides an applied approach to qualitative data analysis through the lens of multiple methods and methodologies.

About this Course

The analysis of qualitative research data is a fundamental yet multifaceted process that requires careful attention to the unique qualities of qualitative research design. This course provides an applied, phenomenological approach to qualitative data analysis. It is designed for an interdisciplinary audience with examples taken from the nonprofit, commercial, and government sectors in the health and social sciences.

Undergraduate/graduate students, research staff, and IRB members in particular may find this course meaningful as an introduction to qualitative research methods.

Course Preview:

Language Availability: English

Suggested Audiences: Faculty, IRB Chairs, IRB Members, Research Staff, Undergraduate and Graduate Students

Organizational Subscription Price: $675 per year/per site for government and non-profit organizations; $750 per year/per site for for-profit organizations Independent Learner Price: $99 per person

Course Content

" role="button"> introduction to qualitative data analysis.

This module discusses the data analysis considerations shared by all qualitative methods and approaches this course covers. This includes the basic qualitative data analysis process and tools and the rigorous and ethical approaches to qualitative data analysis that apply across methods.

Recommended Use: Required ID (Language): 20971 (English) Author(s): Margaret R. Roller, MA - Roller Research

" role="button"> In-Depth Interview Method

This module begins with an overview of the basic in-depth interview method and its variations. This provides the foundation for the core discussions concerning the distinctive aspects of the in-depth interview method that affect qualitative data analysis, including quality and ethical considerations.

Recommended Use: Supplemental ID (Language): 20972 (English) Author(s): Margaret R. Roller, MA - Roller Research

" role="button"> Focus Group Discussion Method

To provide a basis for the core discussions, this module begins with an overview of the fundamentals of the focus group method and its variations. This provides an understanding of the distinctive aspects of the focus group method that affect qualitative data analysis, including quality and ethical considerations.

Recommended Use: Supplemental ID (Language): 20973 (English) Author(s): Margaret R. Roller, MA - Roller Research

" role="button"> Ethnography

Understanding the ethnographic approach and its variations is important to the discussion of data analysis. For this reason, the module begins with an overview of ethnographic research and the distinctive aspects of ethnography that affect qualitative data analysis, including quality and ethical considerations.

Recommended Use: Supplemental ID (Language): 20974 (English) Author(s): Margaret R. Roller, MA - Roller Research

" role="button"> Narrative Research

This module provides an overview of narrative research and its variations. It provides an overview of narrative research, which serves as a foundation for the core discussions concerning the distinctive aspects of the narrative research approach that affect qualitative data analysis. The module concludes with a discussion of quality and ethical considerations.

Recommended Use: Supplemental ID (Language): 20975 (English) Author(s): Margaret R. Roller, MA - Roller Research

" role="button"> Case Study Research

Case study research and its variations are examined at the start of this module. Then, distinctive aspects of case study research that affect qualitative data analysis are explored, including quality and ethical considerations.

Recommended Use: Supplemental ID (Language): 20976 (English) Author(s): Margaret R. Roller, MA - Roller Research

" role="button"> Qualitative Content Analysis Method

This module reviews the basic Qualitative Content Analysis (QCA) method and its variations. It also discusses the distinctive aspects of the QCA method that affect qualitative data analysis and the quality and ethical considerations that QCA presents.

Recommended Use: Supplemental ID (Language): 20977 (English) Author(s): Margaret R. Roller, MA - Roller Research

Who should take the Qualitative Data Analysis course?

The suggested audience includes students, faculty, and staff that want to learn more about the basics of qualitative data analysis and one or more of the discussed methods.

How long does it take to complete the Qualitative Data Analysis course?

This course consists of one required module and six supplemental modules. All learners should complete module 1 and then complete the supplemental modules as needed (20-30 minutes each).

" role="button"> Why should an organization subscribe to this course?

Organizational subscriptions provide access to the organization's affiliated members. This allows organizations to train individuals across the organization on how to properly conduct qualitative data analysis.

" role="button"> What are the standard recommendations for learner groups?

This course is designed such that learners should complete the first module and then any following method modules as needed.

" role="button"> Is this course eligible for continuing medical education credits?

This course does not currently have CE/CME credits available.

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• Study with us
• Short Courses in Qualitative Research Methods
• Introduction to Analysing Qualitative Data

Study with us:

• Introduction to Qualitative Research Methods
• Introduction to doing Qualitative Interviews
• Introduction to conversation analysis and health care encounters
• Learning with the book: an introduction to qualitative research methods for health research

This course will provide you with a good introduction to qualitative data analysis. Our expert tutors will support you to develop and practice your analysis skills using a combination of online lectures, group discussions, and practical online workshops.

This two-day online course introduces the principles and practice of qualitative data analysis, with emphasis on thematic analysis.

Over two days our approachable and research-active experts will show that analysis is achievable though an accessible step-by-step process, and will provide de-identified data for you to work with. Day one begins by looking at organising data (coding categorising and theme development); day two explores 'finding a story' and developing your analysis to translate to a research paper or thesis chapter. 

We aim to support those who are planning to undertake or manage qualitative research using in-depth or semi-structured interviews or qualitative observational data, and support those who have already collected qualitative data which they are unsure how to analyse. The thematic analysis approach used is also applicable to other kinds of qualitative data including observation, diaries, and other text sources. While the course is aimed at the needs of health and care professionals, researchers, academics and postgraduate students, the skills developed here apply to many settings  - please ask us if you are unsure whether Analysing Qualitative Data is the course for you.

COURSE DELIVERY

Please note that some of the teaching sessions for this online course will involve you participating in live, interactive Zoom sessions, which will fall between the hours of  09:00 and 17:00 UK time . We are very happy to welcome bookings wherever you are internationally, but please make sure that you are able to attend video calls between these hours. 

The course will include:

• Expert-led lectures (a mixture of live and pre-recorded) on the principles of qualitative data analysis, with emphasis on thematic analysis
• Demonstrations and small group work to develop skills in coding and categorising qualitative data and in data interpretation
• Practical online exercises considering how to conduct and recognise 'good quality' qualitative analysis
• Expert feedback to support your learning and understanding

Learning outcomes

Learning Outcomes

By the end of the course participants will:

• Have an understanding of the principles of qualitative data analysis with emphasis on thematic analysis
• Have gained practical experience of coding, categorising, and conceptualising qualitative data or qualitative observational data using a thematic analysis approach

We provide:

• Access to the online learning platform (CANVAS)
• Online access to slides and materials
• De-identified data for you to work on whilst developing your skills
• Experienced, approachable tutors who are research-active

Online course

Date: 11-12 March 2024

Course details:

Course fee: £750 Duration: 2 days Total places: 24 Venue: Online Course

If you have any questions and queries please   email us

“Fantastic teaching, great content, personal insight / experiences, putting it into practice and great to meet so many other people involved in qual research... Excellent course!”

“It has been a real privilege to attend a course led by such high quality, high calibre speakers – sharing the theory but intertwined with the reality of their own experiences and interests and passions.”

"A highlight was realising how far I’d come and how much I’d learned! Feeling inspired to try out what I’ve learned, thank you”

COURSE TUTORS

Lisa Hinton

Catherine Pope

Sue Ziebland

and expert tutors from the  Medical Sociology & Health Experiences Research Group  team 

Oxford Qualitative Courses

This highly-regarded programme is delivered in online and face to face formats to suit a range of learners.  We use a mixture of lectures and small group work, delivered by our team of qualitative researchers from the University of Oxford’s  Medical Sociology and Health Experiences Research Group . Our group has run these successful courses for almost twenty years alongside active involvement in qualitative research on a variety of different topics, ranging from studies of personal experiences of health conditions and of healthcare practice, to evaluations of organisational change. Our group also includes qualitative methodologists at the forefront of developing qualitative methods including conversation analysis and evidence synthesis.

Findings from our group’s research on patient experiences, together with supported video, audio and text extracts, have been compiled to form the multi-award winning  heathtalk.org   website and its sister site socialcaretalk.org . Our portfolio of research and expertise informs current local, national and international healthcare policy and research. 

The syllabuses of our qualitative courses draw on a wide range of expertise from within our research group, including the disciplinary areas of medical sociology, anthropology, and public policy. 

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Our courses are popular and often sell-out quickly. To receive a bulletin of upcoming course dates, please  register here .

Got a question? Contact us:

Our friendly team are on-hand to answer your questions and queries. 

Email:  [email protected]

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Qualitative Research

The Odum Institute provides ongoing consulting services and short courses on qualitative research and related software. Qualitative research is a social scientific method for collecting textual, visual, or audio data.

Consultations & Guest Lectures

Consultations.

If you have questions regarding research design, data collection, strategies for analysis, and options for reporting findings , please contact Paul Mihas using the information provided below. Paul can also provide consultations on deductive, inductive, and abductive perspectives that inform qualitative research.

Paul can help you through any of the stages of your project, including the early stages of developing research questions and proposal writing, such as: Designing a study, data collection, analysis, developing research products .

Assistant Director of Qualitative and Mixed Methods Research

Guest lectures.

Time permitting, Paul is also available to give guest lectures on various qualitative research topics at classes and meetings. If you would like to schedule a guest lecture on a qualitative research topic, please contact Paul Mihas directly or visit our guest lecture page .

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Qualitative Research Traditions

• Generic qualitative
• Thematic qualitative research
• Phenomenology
• Ethnography
• Narrative Analysis
• Grounded Theory

Mixed Methods

Paul can also assist if you are conducting a study combining or connecting qualitative and quantitative data. Please visit our mixed methods page for more information.

Project Planning, Data Collection and Analysis

As part of a fee-based service , the Odum Institute offers project-based design and analysis using strategies customized for each project’s needs. These range from evaluation projects to multi-year research studies. Assistant Director Paul Mihas, with the assistance of graduate students, can help with:

• Research design
• Developing interview and focus group guides
• Conducting data collection
• Data analysis using specialized software
• Final reports

Dissertation & Master’s Thesis Assistance

If you would like Paul Mihas to provide feedback regarding a master’s thesis or dissertation proposal or draft of a chapter, please feel free to contact him at [email protected] .

Qualitative Data Analysis Software

The Odum Institute provides specialized computer programs that provide tools for mixed methods analyses; these include QSR NVivo, ATLAS.ti, MAXQDA, and a web-based program, Dedoose .

Odum offers short courses on these programs as well as consultations regarding their use. Please see the current Institute short course schedule or contact Paul Mihas to arrange a customized presentation for graduate or undergraduate classes or other special audiences.

QRS NVivo is a software program for coding and analyzing textual and multimedia data . It also allows researchers to construct diagrams (“mind maps” and “concept maps”) of codes and transcripts and automatically generates comparison diagrams to assess differences between codes or transcripts.

Its analytical strengths include:

• Cluster analysis of transcripts and multidimensional matrix analysis of codes
• Quantitative variables for “mixing” quantitative and qualitative data.

ATLAS.ti , a program for analyzing textual and multimedia data , allows users to analyze data based on codes and analytical memos . The software also allows users to create diagrams of transcripts, quotations, memos, and codes and to create links between these “objects” in diagrams.

The query tool lets users ask complex questions of their data, including Boolean searches or queries based on demographics. A co-occurrence table allows researchers to review conceptual intersections of codes. A joint-display matrix allows users to combine qualitative codes and quantitative variables.

MAXQDA is a qualitative analysis software package that helps researchers code textual, audio, or video data and analyze coded segments .

The software also allows users to merge qualitative and quantitative analysis by exporting and importing variables to and from SPSS and Excel. The software includes a mixed methods set of tools for generating tables that “mix” the qualitative codes and quantitative variables. A memo-writing feature allows users to add reflective writing to their analytic process.

A content analysis feature allows researchers to create a special dictionary of keywords. Intercoder reliability features are also available.

Dedoose is a web-based application for analyzing qualitative and mixed methods research with text, images, audio, videos, and spreadsheet data . The program provides numerous user-friendly charts for making sense of mixed methods studies.

Learning Opportunities

Qualitative research summer intensive:.

The Odum Institute has joined ResearchTalk, Inc. , in presenting the Qualitative Research Summer Intensive , a five-day qualitative research professional development course series, offered annually in July. The intensive includes courses on qualitative traditions, research design, data collection, analysis, and innovative strategies in the field.

Examples & Resources

Consultants at the Odum Institute have authored several online articles regarding specific qualitative methods. For more information, please visit the Sage website regarding learning to use:

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Phenomenological analysis jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });, analyze written text jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });, narrative analysis jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });, build a codebook jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });, charmazian grounded theory jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });, visual analysis jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });, analyze oral discourse jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });, instrument development jquery(document).ready(function(){ jquery('.osc_tooltip').tooltip({ template:'' }).on('shown.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'false'); }).on('hidden.bs.tooltip', function(){ jquery( '.tooltip.oscitas-bootstrap-container' ).attr( 'aria-hidden', 'true'); }); });.

The Qualitative Research Resources Page from the UNC Health Sciences Library is also an excellent resource for information on qualitative research methods.

Qualitative Research Certificate

Graduate Certificate

The Qualitative Research Certificate consists of four three-credit hour courses (12 credit hours) developed to prepare students and professionals to understand a broad and in-depth knowledge of qualitative research approaches and to conduct qualitative research studies.

Over recent years, qualitative research has been increasingly conducted and influential in educational research across disciplines.

The Qualitative Research Certificate within the College of Education at Purdue University requires students to obtain a minimum grade of B for each course while also maintaining an overall GPA of 3.0/4.0. This certificate program accepts applications from Purdue University graduate students from any Purdue West Lafayette graduate programs.

This residential program has rolling admission. Applications must be fully complete and submitted (including all required materials) and all application fees paid prior to the deadline in order for applications to be considered and reviewed. For a list of all required materials for this program application, please see the “Admissions” tab below.

July 1 is the deadline for Fall applications.

November 15 is the deadline for Spring applications.

March 15 is the deadline for Summer applications.

This program does not lead to licensure in the state of Indiana or elsewhere. Contact the College of Education Office of Teacher Education and Licensure (OTEL) at [email protected] before continuing with program application if you have questions regarding licensure or contact your state Department of Education about how this program may translate to licensure in your state of residence.

Application Instructions for the Qualitative Research Certificate from the Office of Graduate Studies :

In addition to a submitted application (and any applicable application fees paid), the following materials are required for admission consideration, and all completed materials must be submitted by the application deadline in order for an application to be considered complete and forwarded on to faculty and the Purdue Graduate School for review.

Here are the materials required for this application:

• Official, current Purdue transcripts
• Graduate School Form 18 for Dual Enrolled students. Please upload this form with your application with your signature and information only. Our office will obtain the necessary faculty signatures.
• Academic Statement of Purpose
• Personal History Statement

We encourage prospective students submit an application early, even if not all required materials are uploaded. Applications are not forwarded on for faculty review until all required materials are uploaded.

When submitting your application for this program, please select the following options:

• Select a Campus: Purdue West Lafayette (PWL)
• Select your proposed graduate major: Curriculum and Instruction
• Please select an Area of Interest: Curriculum Studies
• Please select a Degree Objective: Qualitative Research Graduate Certificate
• Primary Course Delivery: Residential

Program Requirements

Required courses.

• EDCI 61500:  Qualitative Research Methods in Education (3 cr.) A course providing an introduction to qualitative research methods in education.
• EDCI 61600:  Qualitative Data Collection and Analysis in Educational Research (3 cr.) A course focused on collection and analysis of qualitative data
• Elective #1:  with focus on qualitative methods (3 cr.)
• Elective #2:  with focus on qualitative methods (3 cr.)
• CAND 99100: Candidate (Must be registered as a candidate for graduation to receive the Certificate) Candidate registration should be completed through the Office of Graduate Studies when registering for the final course. Student must contact the office directly at [email protected] . Failure to register properly will result in a delay of being awarded the certificate
• EDCI 567: Action Research in Science Education
• EDCI 59100: Research in International Contexts
• EDCI 591: Technology for Qualitative Research
• EDCI 612: Literacy Research Methodologies
• ANTH 605: Seminar in Ethnographic Analysis
• COM 584: Historical/Critical Research in Communication
• HDFS 679: Qualitative Research on Families
• TECH 697: Qualitative Research Methods in Technology Studies
• WGSS 680: Feminist Theory
• WGSS 682: Issues in Feminist Research and Methodology
• Other elective courses may be approved (before completing) by the faculty advisor in the home department in conjunction with the Qualitative Research Certificate coordinator in the Dept. of Curriculum and Instruction

APPLICATION PROCEDURE

Course Content Information or Blackboard: Contact Dr. Stephanie Zywicki Course Registration, payment, drops/withdraws, and removing holds: [email protected] Career accounts: ITaP (765) 494-4000

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Qualitative Research: Design, Implementation and Methods

DESIGN X440.2

Get an introduction to what qualitative research is, the types of qualitative research methods, the appropriate situations to apply qualitative methods, and how to conduct your own qualitative research. You learn to build a research protocol and use various techniques to design, conduct, analyze and present an informative research study.

At the end of the course, you are expected to conduct your own qualitative research study . To that end, you develop a research plan based on the given situation, collect data using qualitative methodologies , engage with various techniques for coding and analyzing qualitative data effectively, and present the data and insights in a manner that is best aligned with the goals of the research.

Prerequisites: None.

Course Outline

Course Objectives

• Understand what constitutes qualitative research, how it differs from quantitative research and when to apply qualitative research methods
• Identify and formulate appropriate qualitative research plans
• Apply qualitative research data collection techniques
• Develop coding schemes for analysis of qualitative data
• Present qualitative data to inform and influence

What You Learn

• Developing qualitative research questions
• Building a research protocol
• Observing, listening and probing: the core skills of a qualitative researcher
• Qualitative sampling and participant recruitment
• Understanding an overview of the qualitative data analysis process
• Communicating your findings, from summary to interpretation
• Presenting qualitative results

How You Learn

We are online! All of the design classes are conducted online and include video classes, mentor-led learning and peer-to-peer support through our student online platform, Canvas. 

• Reading assignments
• Quizzes at instructor’s discretion
• Small-group activities
• Homework assignments
• Capstone project

Is This Course Right for You?

This course is intended for students in the Professional Program in User Experience (UX) Design , or anybody interested in obtaining skills in qualitative research. You do not need preexisting research experience for this course. Our experienced instructors provide practical information, leverage their qualitative research skills and monitor your development along with peer-to-peer support on our student online platform.

Summer 2024 enrollment opens on March 18!

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Short courses

Qualitative Research Methods in Health

• 10am - 1pm each day

Cost: £1,500

Book a place.

Please email [email protected]  if you wish to apply for this course. The next course will start on 3 October 2024

This course aims to equip you with the knowledge and skills to understand, design and conduct high quality qualitative research.

The course will help you:

• gain a clear understanding of the principles of qualitative research
• practise skills including interviewing, running a focus group, data analysis, and developing and presenting a research protocol

This course will be delivered online over 10 Thursday mornings from 3 October to 12 December.

This course is run by researchers from the UCL Centre for Excellence in Qualitative Research, within the Research Department of Primary Care and Population Health (PCPH).

Who it's for

This course is for: 

• Master's level students, PhD students and research staff who need to design and conduct a qualitative study
• those who wish to know how to assess the quality of qualitative research (e.g. funders, journal editors, ethical committee members etc.)

You don't need to have any previous experience of qualitative research, but you will need to do some preparation before each session.

Course content

Lead: Julia Bailey and Tom Witney

This workshop will help you understand the basis on which qualitative methodology is selected as a research approach.

• learn about the philosophical debates around qualitative research
• contrast qualitative and quantitative approaches
• discuss the place of qualitative research in health and medicine

You'll also critique a published paper of a qualitative study. This will help you reflect on a completed study and consider not only the methodological approach and selection of methods, but also practical aspects such as sampling, what counts as data, the position of the researcher, data analysis, and application of findings.

Learning objectives

By the end of this workshop you'll be able to:

• describe key features of qualitative research
• explain the rationale for key features of qualitative research design 
• know when qualitative or quantitative study designs are appropriate 
• understand how ‘theory’ is relevant for qualitative research

Leads: Harpreet Sihre and Silvie Cooper

On this workshop you'll learn about qualitative research interviewing techniques and developing topic guides.

You'll explore structured, semi-structured and in-depth interview methods and their application, using real world examples. However, the emphasis will be on semi-structured interview techniques.

You'll also learn about and discuss:

• the importance of different communication styles and researcher reflexivity
• practical issues such as structuring questions, building rapport and dealing with challenging interviews

You'll be encouraged to think of an area of research around which you'll structure and produce a topic guide for use in a practical session. You'll also get the opportunity to practice your newly developed interviewing skills.

As far as possible, the workshop is tailored towards research that those attending are planning/doing.

By the end of this workshop you'll be able to:

• describe and distinguish between structured, semi-structured and 'in-depth' interviewing
• formulate and construct a topic guide
• apply and evaluate some key interviewing skills

Lead: Tom Witney and Fiona Aspinal

This workshop will introduce you to focus groups - a key qualitative research method.

You'll learn about the:

• different stages of the research process where focus groups can be used
• types of research questions that lend themselves to this approach
• practicalities of sampling, convening and conducting focus groups, including issues to consider when researching sensitive topics

You'll also practise your communication and group facilitation skills.

You'll be encouraged to think of an area of research around which you'll structure and produce a topic guide for use in a practical session.

• explain when and how to use focus groups
• design a topic guide for a focus group study
• organise and facilitate a focus group

Leads: Nathan Davies and Fiona Stevenson

On this workshop you'll discuss a range of ways of conducting qualitative data analysis and the rationales for different approaches.

You'll be encouraged to critically reflect on how decisions made throughout research affect the type and extent of analysis possible. The importance of decisions about transcription are also stressed.

You'll consider the place of data management software in qualitative analysis. You won't be taught how to use particular software packages, but you'll discuss the advantages and disadvantages of using these.

You'll conduct a thematic analysis on a piece of data, and reflect on and consider the best approach for your own work.

Please note: this workshop does not provide training in the use of Computer Assisted Qualitative Data Analysis packages

• distinguish between different types of qualitative data analysis
• recognise the importance of decisions relating to transcribing, reflexivity, field notes, double coding and data management
• consider various approaches to analysis
• understand the principles and practicalities of conducting a basic thematic analysis
• evaluate the benefits of Computer Assisted Qualitative Data Analysis for your projects

Leads: Jane Wilcock and Stephanie Kumpunen

In this interactive workshop you'll plan your own qualitative study design.

You'll work on your own and in small and large groups, with an experienced tutor. You'll also have the opportunity for one-to-one and small group discussions and advice on qualitative study design.

The first day is spent planning your study in a structured way. On the second day you'll present your study design proposal to tutors and other students in small groups, and discuss research issues arising from the proposed studies.

• write clear research questions
• understand the principles of (and debates about) quality in qualitative research
• plan a qualitative research study, specifying the details of how a study will be carried out
• present a four-slide summary of your study design
• discuss the rationale for chosen study designs

Teaching and assessment

The course is highly interactive, involving a range of teaching techniques including group work, practical tasks and discussion.

It will be run with a mixture of synchronous, online learning (e.g. presentations, small group discussions) and asynchronous learning (pre-recorded videos, readings, preparatory writing/planning).

You'll receive help designing and planning your own qualitative research project. You'll then present your design proposals and receive feedback from course tutors and peers at the end of the course.

You'll be required to do some preparation before each session (reading and/or watching videos).

How to apply

To apply for this course you’ll need to complete a short application form.

Your application will be judged on your suitability for the course and how much you're likely to benefit. Priority will be given to people who are actively planning or conducting qualitative research.

Please email [email protected]  if you’d like to be added to the waiting list. When booking opens and there are spaces available for the course, you'll be emailed the application form.

Cancellation policy

Cancellations must be received in writing at least two weeks before the start of the event and will be subject to an administration charge of 20% of the course fee. Unfortunately, no refunds will be made within two weeks of the course date. Any refund will be made by UCL to you within 30 days of your cancellation and be paid to you in the same way as you paid for your order.

We reserve the right to cancel teaching if necessary and will, in such event, make a full refund of the registration fee. PCPH Events will not be liable for any additional incurred costs.

Further information

If you have any questions about the course content, please email Fiona Stevenson ( [email protected] ) or Julia Bailey ( [email protected] ).

For administrative queries, please contact Lynda Russell-Whitaker ( [email protected] ).

Course team

Julia Bailey - joint Course Director

Julia is an Associate Professor at the e-Health Unit at UCL and a sexual health speciality doctor in South East London. Her research interests include sexual health, e-Health, doctor-patient interaction, science communication and social science in medicine (qualitative methodologies). View Julia’s IRIS profile for more information about her work and publications.

Fiona Stevenson - joint Course Director

Fiona is a Professor of Medical Sociology and Co-Director of e-Health Unit at UCL. She’s currently Head of the Department of Primary Care and Population Health at UCL. Her research is broadly encompassed by the overarching theme of perceptions, communication and interactions about treatment. Her methodological expertise lies in qualitative methods, both in relation to thematic analysis of interviews and focus groups and conversation analysis of interactional data. She has expertise in conducting original research as well as implementing research findings into practice. View Fiona’s IRIS profile for more information about her work and publications.

Nathan Davies

Nathan is an Associate Professor and Alzheimer’s Society Fellow based in the Centre for Ageing Population Studies at UCL. His main research interests are in older adults, dementia, and supporting family carers. He's a qualitative researcher leading on several qualitative studies, which explore sensitive topics, including end of life care. In addition to experience of interviews, focus groups and various types of qualitative analysis, he has extensive experience of co-design, co-production and consensus-based methods. View Nathan’s IRIS profile for more information about his work and publications.

Jane Wilcock

Jane is a Senior Research Associate in the Centre for Ageing & Population Studies, UCL. Her main research interests are in dementia, ageing, emergent technologies and trials of complex interventions in primary care and community settings. A mixed-methods researcher, Jane has experience of a variety of study designs such as RCTs, interview and focus group studies, nominal group techniques and co-design of interventions. In addition, she is a methodology expert for the NIHR Research Design Service London. View Jane’s IRIS profile for more information about her work and publications.

Silvie Cooper

Silvie is a Lecturer (Teaching) in the Department of Applied Health Research at UCL. Her research interests include capacity building for health research, management of chronic pain, digital health, and patient education, using qualitative, mixed methods, and translational research approaches. Alongside her research, she designs and teaches on a variety of health and social science courses for undergraduates, postgraduates and professionals. Topics include research and evaluation methods, the social aspects of health and illness, and the impact of context, practice and policy on healthcare experiences. View Silvie’s IRIS profile for more information about her works and publications.

Harpreet Sihre

Harpreet formerly completed her PhD at the Institute of Applied Health Research, University of Birmingham, where she researched the lived experiences of South Asian women with severe postnatal psychiatric illnesses using Interpretative Phenomenological Analysis. She then worked at the Unit of Social and Community Psychiatry on an NIHR-funded study researching accessibility and acceptability of Perinatal Mental Health Services.

Harpreet’s research interests encompass mental health, perinatal mental health, access to services and equality, diversity and inclusion, using qualitative research methods. Harpreet has taught on both undergraduate and postgraduate courses, including small group teaching and lecturing at the University of Birmingham and Queen Mary University. View Harpreet’s IRIS profile for more information about her work and publications.

Tom is a Research Fellow at the department of  Primary Care and Population Health . He is a qualitative health researcher, with a particular interest in sexual health and relationship intimacy. His current work focuses on improving access to sexual health for trans and gender diverse people and supporting uptake of chlamydia retesting following a diagnosis. View Tom’s Iris profile for more information about his work and publications.

Fiona Aspinal

Fiona is based in the Department of Applied Health Research for the NIHR ARC North Thames as 'Senior Research Associate in Qualitative Methods Applied to Organisational Research in Health' where, as part of the ARC North Thames' Research Partnership Team, she helps to facilitate and support health and social care research with local, regional and national relevance. She is also the social care research lead for NIHR CRN North Thames.

Her areas of research interest are: Qualitative research and evaluation of complex health and social care interventions and organisations; The experience and outcomes of integrated care policy and practice for staff, service users and informal carers; Social and community health care for adults, including people with dementia; Social care research infrastructure/skills.

At UCL, in addition to the Qualitative Research Methods in Health short course, Fiona teaches on research methods and social science courses and modules, such as the BSc Population Health Sciences, the Medicine MBBS BSc and the Population Health MSc. She also supervises undergraduate and postgraduate students. View Fiona’s Iris profile for more information about her work and publications.

Stephanie Kumpunen

Stephanie is a THIS Institute Doctoral Fellow at UCL and a Senior Fellow in Health Policy at Nuffield Trust (a London-based health and care think tank). Her research focuses on the organisation of Primary Care and community-based health and care services.

Stephanie has led on a number of qualitative studies and mixed-methods evaluations. She has a particular interest in rapid qualitative approaches; namely rapid ethnographies that inform health and care service improvement. View Stephanie’s UCL profile for more information about her work and publications.

“The course is a really a great opportunity to read, reflect, discuss and share research, which is helpful for personal and professional development.” [Academic Clinical Fellow, Spring 2022]

“This session really helped me to organise my thoughts and put together a coherent plan for future research. It will make writing my protocol very easy!” [PhD Student, Spring 2022]

“It was such an excellent course. The information and materials provided were straight to the point and helpful, the working atmosphere was inspiring and constructive, and the tasks were interesting and activating. Thank you to all tutors!” [Clinical Research Programme Coordinator, Spring 2022]

“Great tutors, great reading material. It was very interesting to hear other peoples' experiences. Although this course was virtual, there were plenty of opportunities for interaction. I now have a better understanding and I am confident to run my study. I would recommend this course to anyone who wants an intro in qual research.” [Pre-Doctoral Research Fellow, 2021]

"I have a more clear understanding of the basics of qual methods, terminology and ways it may fit into my own research." [Researcher, 2019] 

Course information last modified: 22 Apr 2024, 13:33

Length and time commitment

• Time commitment: 10am - 1pm each day
• Course length: 10 weeks

Contact information

• Lynda Russell-Whitaker
• [email protected]

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10 free data analytics courses you can take online

Data analytics is the science of taking raw data, cleaning it, and analyzing it to inform conclusions and support decision making. From business to health care to social media, data analytics is changing the way organizations operate.

“It’s not hyperbole to say that data analytics has really taken over the world,” says Brian Caffo, professor of biostatistics at Johns Hopkins University’s Bloomberg School of Public Health and director of academic programs for the university’s Data Science and AI Institute. “Every domain has become increasingly quantitative to inform decision making.”

Berkeley's Data Science Master's

And this space isn’t slowing down anytime soon: The U.S. Bureau of Labor Statistics projects that employment for data scientists will grow 35% from 2022 to 2032, with 17,700 new job openings projected each year on average during that decade. 

Interested in becoming a data analyst? Below, we’ve compiled ten free data analytics courses to help give you a firmer grasp of this rapidly growing field.

A/B Testing  

About: This course covers the design and analysis of A/B tests, which are online experiments that compare two versions of content to see which one appeals to viewers more. A/B tests are used throughout the tech industry by companies like Amazon and Google. This course is offered through Udacity. 

Course length: Six self-paced modules

Who this course is for: Beginners

What you’ll learn: In this course you’ll learn about A/B testing, experiment ethics, how to choose metrics, design an experiment, and analyze results.

Prerequisites: None  

Data Analytics Short Course  

About: In this quick, five-tutorial course you’ll get a broad overview of data analytics. You’ll learn about the different types of roles in data analytics, a summary of the tools and skills you’ll need to develop, and a hands-on introduction to the field. This course is offered by CareerFoundry.

Course length: 75 minutes, divided into five 15-minute lessons

What you’ll learn: In this course you’ll get an introduction to data analytics. You’ll also analyze a real dataset to solve a business problem through data cleaning, visualizations, and garnering final insights.

Prerequisites: None 

Data Science: R Basics  

About: This program gives you a foundational knowledge of programming language R. Offered by HarvardX through the EdX platform, this course is offered for free; the paid version includes a credential. It’s the first of ten courses HarvardX offers as part of its Professional Certificate in Data Science.

Course length: Eight weeks, 1–2 hours per week

What you’ll learn: In this course you’ll learn basic R syntax and foundational R programming concepts, including data types, vectors arithmetic, and indexing. You’ll also perform operations that include sorting, data wrangling using dplyr, and making plots. 

“It’s the basics of how to wrangle, analyze, and visualize data in R,” says Dustin Tingley, Harvard University’s deputy vice provost for advances in learning and a professor of government in the school’s government department. “That gets you writing a little bit of code, but you’re not doing anything that heavy.”

Prerequisites: HarvardX recommends having an up-to-date browser to enable programming directly in a browser-based interface 

Fundamentals of Qualitative Research Methods  

About: This course will teach you the fundamentals of qualitative research methods. Qualitative research provides deeper insights into real-world problems that might not always be immediately evident. This course is offered through Yale University on YouTube.

Course length: 90 minutes spread out over six modules

What you’ll learn: In this course you’ll learn how qualitative research is a way to systematically collect, organize, and interpret information that is difficult to measure quantitatively. This includes developing qualitative research questions, gathering data through interviews and focus groups, and analyzing this data. 

“Qualitative research is the systematic, rigorous application of narratives and tools to better understand a complex phenomenon,” says Leslie Curry, a professor of public health and management at the Yale School of Public Health and a professor of management at the Yale School of Management. She adds that this approach can help understand flaws in large data sets. “It can be used as an adjunct to a lot of the really important work that’s happening in large data analysis.”

Getting and Cleaning Data  

About: This course covers the basic ways that data can be obtained and how that data can be cleaned to make it “tidy.” It will also teach you the components of a complete data set, such as raw data, codebooks, processing instructions, and processed data. This course is offered by Johns Hopkins University through Coursera, and is part of a 10-course Data Science Specialization series.

Course length: Four weeks, totaling approximately 19 hours

What you’ll learn: Through this course you’ll learn about common data storage systems, how to use R for text and date manipulation, how to use data cleaning basics to make data “tidy,” and how to obtain useable data from the web, application programming interfaces (APIs), and databases. 

“It’s the starting point” when it comes to data analysis, Caffo says. “Without a good data set that is cleaned and appropriate for use, you have nothing. You can talk all you want about doing models or whatnot—underlying that has to be the data to support it.”

Prerequisites: None

Introduction to Data Science with Python  

About: This course teaches you concepts and techniques to give you a foundational understanding of data science and machine learning. Offered by HarvardX through the EdX platform, this course can be taken for free. The paid version offers a credential.

Course length: Eight weeks, 3–4 hours a week

Who this course is for: Intermediate

What you’ll learn: This course will give you hands-on experience using Python to solve real data science challenges. You’ll use Python programming and coding for modeling, statistics, and storytelling. 

“It gets you up and running with the main workhorse tools of data analytics,” says Tingley. “It helps to set people up to take more advanced courses in things like machine learning and artificial intelligence.”

Prerequisites: None, but Tingley says having a basic background in high school-level algebra and basic probability is helpful. Some programming experience—particularly in Python—is recommended 

Introduction to Databases and SQL Querying  

About: In this course you’ll learn how to query a database, create tables and databases, and be proficient in basic SQL querying. This free course is offered through Udemy.

Course length: Two hours and 17 minutes

What you’ll learn: This course will acquaint you with the basic concepts of databases and queries. This course will walk you through setting up your environment, creating your first table, and writing your first query. By the course’s conclusion, you should be able to write simple queries related to dates, string manipulation, and aggregation.

Introduction to Data Analytics  

About: This course offers an introduction to data analysis, the role of a data analyst, and the various tools used for data analytics. This course is offered by IBM through Coursera.

Course length: Five modules totaling roughly 10 hours 

What you’ll learn: This course will teach you about data analytics and the different types of data structures, file formats, and sources of data. You’ll learn about the data analysis process, including collecting, wrangling, mining, and visualizing data. And you’ll learn about the different roles within the field of data analysis.

Learn to Code for Data Analysis  

About: This course will teach you how to write your own computer programs, access open data, clean and analyze data, and produce visualizations. You’ll code in Python, write analyses and do coding exercises using the Jupyter Notebooks platform. This course is offered through the United Kingdom’s Open University on its OpenLearn platform.

Course length: Eight weeks, totaling 24 hours

What you’ll learn: In this course you’ll learn basic programming and data analysis concepts, recognize open data sources, use a programming environment to develop programs, and write simple programs to analyze large datasets and produce results.

Prerequisites: A background in coding—especially Python—is helpful  

The Data Scientist’s Toolbox  

About: This course will give you an introduction to the main tools and concepts of data science. You will learn the ideas behind turning data into actionable knowledge and get an introduction to tools like version control, markdown, git, GitHub, R, and RStudio. This course is offered by Johns Hopkins University through Coursera, and is part of a 10-course Data Science Specialization series.

Course length: 18 hours

What you’ll learn: This course will teach you how to set up R, RStudio, GitHub, and other tools. You will learn essential study design concepts, as well as how to understand the data, problems, and tools that data analysts use. 

“That course is a very accessible introduction for anyone who wants to get started in this,” Caffo says. “It’s an overview that covers the full pipeline, from things like collecting and arranging data to asking good questions, all the way to creating a data deliverable.”

The takeaway  

From businesses estimating demand for their products to political campaigns figuring out where they should run advertisements to health care professionals running clinical trials to judge a drug’s efficacy, data analytics has a wide variety of applications. Getting a better understanding of the field on your own time can be done easily and freely. And the field is only growing.

“Just about every field is having a revolution in data analytics,” Caffo says. “In fields like medicine that have always been data driven, it’s become more data-driven.”

Syracuse University MS in Applied Data Science Online

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Earn Your Master’s in Data Science Online From SMU

Effectiveness of Psychosocial Skills Training and Community Mental Health Services: A Qualitative Research

• Original Paper
• Published: 22 April 2024

Cite this article

• Halil İbrahim Bilkay   ORCID: orcid.org/0000-0002-8231-960X 1 ,
• Burak Şirin   ORCID: orcid.org/0000-0002-8485-5756 2 &
• Nermin Gürhan   ORCID: orcid.org/0000-0002-3472-7115 2  

This study employs a phenomenological approach to investigate the experiences of individuals who access services at a community mental health center (CHMC) in Türkiye The aim of this study is to comprehend the experiences of individuals who participate in psychosocial skills training at the CHMC. Thematic analysis of data from sixteen in-depth interviews revealed three main themes and eight sub-themes. Functionality theme emphasizes the positive impact of CHMC services and training on daily life and social functioning. Effective Factors theme encompasses the elements that improve the effectiveness of CHMC services. Participants have provided suggestions for the content of the training under the theme of Recommendations. Study results show that CHMC services and psychosocial skills training benefit individuals' daily lives and functioning, but that opportunities for improvement exist. It is crucial to incorporate participant feedback, and further research should be conducted to investigate the effectiveness of these services in this area.

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The authors express gratitude to the staff of the mental health center for their support and assistance during the study, as well as to the participants who generously provided responses to the questions posed.

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Material preparation, data collection and analysis were performed by Halil İbrahim BİLKAY and Burak ŞİRİN. The first draft of the manuscript was written by Halil İbrahim BİLKAY and all authors commented on previous versions of the manuscript. Nermin GÜRHAN read and approved the final manuscript.

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Bilkay, H.İ., Şirin, B. & Gürhan, N. Effectiveness of Psychosocial Skills Training and Community Mental Health Services: A Qualitative Research. Community Ment Health J (2024). https://doi.org/10.1007/s10597-024-01278-3

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Exploring information needs among family caregivers of children with intellectual disability in a rural area of South Africa: a qualitative study

• Mantji Juliah Modula 1 &
• Mpho Grace Chipu 1  

BMC Public Health volume  24 , Article number:  1139 ( 2024 ) Cite this article

Metrics details

Globally, families experience challenges caring for and raising children with intellectual disability (ID). Family caregivers in rural states are mostly known for lacking support resources, including information on understanding the care of ID. Lack of adequate information on understanding of ID compromises the provision of life-long care and support of the children with ID’s physical, emotional, psychological and social developmental well-being. The study aimed to explore the information needs of family caregivers regarding the care of children with ID in rural areas of Limpopo Province, South Africa.

This qualitative explorative research conducted 16 in-depth individual interviews and one focus group discussion with ten family members. The participants shared their experiences of raising children with ID in rural communities. Inductive thematic analysis using Atlas Ti software categorised emerging themes and subthemes of this study from merged data sets on information needs regarding the care of children with ID among family caregivers.

The findings highlighted the need for information regarding ID care among family caregivers raising children with ID in the home environment. The information challenges experienced by family caregivers include caring for the challenging behaviour of children with ID and available support resources and services for the children and their families. These challenges impact the care and support required to meet the developmental needs of children with ID. Furthermore, inadequate information on ID among family caregivers in rural communities with a lack of resources restricts the children from accessing required support services.

Conclusions

Given the information challenges these families face on ID, the stakeholders must develop continuous training programmes that will equip, empower, and further monitor ID care and management among family caregivers to enhance care and the raising of children with dignity.

Peer Review reports

Intellectual disability (ID) diagnosis requires families as primary caregivers to support their children during the developmental stages of life. ID as a neurodevelopmental disorder limits intellectual functioning and adaptive behaviour during the developmental period of a child [ 1 ]. ID ranges from mild, moderate, severe and profound impairment. The diagnosis affects the child’s communication, cognitive and self-care skills development, leading to dependency support living [ 2 ]. Children with ID are prone to physical conditions, including obesity and constipation, often exposing them to misdiagnosis and underdiagnosis [ 3 ], limiting their access to healthcare services. Early diagnosis of ID enables early intervention and enhances acceptance of the child by the community [ 4 ].

Globally, ID affects approximately 2–3% of the general population [ 5 ], and the prevalence of children under five is 3.2% [ 6 ]. The incidence in low-income countries is 16.41/1000; in middle-income countries, it is 15.94/1000 persons, higher than in other countries, with approximately 9.21/1000 persons [ 4 ]. South Africa experiences a lack of data on the prevalence of ID and is further dependent on the census.

ID diagnosis generally increases the lifelong dependency of the children on their families regarding self-care and support to thrive. As a primary caregiver, every family is an environment where essential interpersonal experiences of a child’s development occur [ 7 ], including personality, behaviour, and attitudes. Even though families take the lead in raising these children, ID awareness and information among the carers has been a continued concern [ 8 ]. In addition, information created for childrearing may not benefit caregivers of children with ID [ 9 ]. In most cases, families of children with ID experience parenteral barriers, including limited knowledge related to a lack of resources or support [ 10 ].

Past research established that children with ID are more at risk of experiencing childhood problems than their peers without ID [ 11 ]. As most children with ID have a prevalence of developmental delay impacting their independence ability [ 12 ], their care requires information and understanding of ID. Past research has shown that adequate knowledge is measured through the caregiver’s confidence in a particular realm or topic to declare the knowing of what, how, when and why questions that inform one’s attitudes and further influence one’s behavioural changes [ 13 ].

Quality caregiving of a child with ID influences their developmental outcomes [ 14 ]. It is noteworthy that parents’ understanding of the capacity to care for children with ID is assessed based on their responses to the needs of such children [ 15 ]. Previous studies highlighted how the families were more reactive than proactive regarding caring for their children with ID, leading to social exclusion by their communities [ 16 ]. Although the need for training of parents raising children with ID has broadly been investigated successfully [ 17 ], exploring information needs on the care of ID among primary caregivers in rural areas has yet to be fully established.

South Africa surpassed an estimated population of 60 million, with more than 19 million people residing in rural jurisdictions. The country still needs improvement in service delivery problems, especially in rural states. The pastoral population’s life challenges are unique and mainly complex due to geographical and race/ethnicity characteristics [ 18 ]. Previous studies on the experiences of families of children with ID in the South African rural context revealed challenges related to poverty, poor education, and unemployment, including limited transport to access professional services and support systems for ID [ 19 , 20 , 21 , 22 ]. Furthermore, rural communities report low access to health services, including a scarcity of professionals and specialist care, exposing them to health risks resulting in shorter life expectancy [ 23 , 24 ].

Evidence from previous research established that the diagnosis of children with ID in rural areas is likely delayed due to geographic barriers to access services, causing health disparity for children compared to their peers in urban areas [ 25 ]. This delay prevents families from receiving information relevant to planning and managing the child’s care, which is considered a way of simplifying the processes of the professionals [ 26 ]. The family caregivers of children with ID require information including health specialists and rehabilitation services for their children, government support grants, networking and educational services [ 27 , 28 ]. The social model posits that the lack of information access experienced by caregivers of children with ID limits their parenting abilities and further impacts the support of the functioning level of their children [ 29 ]. The study aimed to explore the family caregivers’ information needs regarding understanding the care of children with ID in rural areas to fill the gaps in the caring and management challenges of ID in the home environment. Adequate information by families regarding the care of ID is vital in meeting the support needs of their children with ID in rural areas. These require comprehensive care, support, and rehabilitation for children and their families. The study’s objective was to explore and describe the information needs of family caregivers regarding the care of children with ID in rural areas of Limpopo Province, South Africa.

Study design

This qualitative explorative research helped the researcher facilitate data collection, analysis, and interpretation of the finding processes [ 30 ]. The approach enabled an unrestrained process that explored the participants’ information needs regarding the care of children with ID in a rural home environment. The focus group discussion and in-depth individual interviews allowed participants to share their experiences caring for and managing a child with ID in a rural community. The first researcher recruited participants, collected data, analysed, and wrote manuscripts. The second author reviewed the manuscript.

The researcher conducted the study in the Capricorn district municipality of Limpopo Province, which is approximately 80% rural and estimated at 5.8. million population [ 31 ]. The district is one of the five municipalities of the province and has a growing economic centre. It is known for providing better community services such as job opportunities, schooling, and health care facilities in the province. Thus, it attracts a high population density with a unique cultural heritage, diverse ethnicities, and five languages under 30 traditional authorities [ 31 , 32 ]. The district’s households in the rural community experience challenges regarding limited access to basic needs, including piped water, poor hygienic sanitation conditions and restricted access to health and education services. The high unemployment in this rural status contributed towards people migrating to other provinces for job opportunities, leaving most families to female and single-headed households [ 33 ].

Participants and sampling

The study sampled 26 families from different tribal authorities of Capricorn district with the core function of directly caring for and raising children with ID in home environments. The vulnerability of family caregivers resulted in some hiding their children from their communities due to social stigma related to ID diagnosis. The researcher recruited participants whose children were accessing education and health facilities in their communities through purposive and snowballing sampling strategies. The strategies assisted the researcher in reaching those families not known to community facilities, including schools and health care services, as their children were not utilising such services. The family caregivers recruited, invited, and introduced other families who were relatives or neighbours or encountered them at churches or community meetings and met inclusion criteria to the researcher [ 30 ]. Such families’ children were diagnosed with ID from hospitals in other provinces and private health care services. They did not use public services, fearing discrimination related to stigmatisation from their communities.

Eligibility criteria included any family caregiver above 18 years who was living and directly involved with raising children with ID and was voluntarily willing to share their experiences regarding caregiving informational needs in the rural home environment. Furthermore, the researcher’s judgement stayed instrumental in the selection of family caregivers whose children were of school-going age or over six years old, indicating that they were not recently diagnosed with ID. For most children at this age, healthcare professionals have already established their diagnosis of ID, as their developmental capabilities were able to be assessed with their peers at school. Furthermore, on this ground, the researcher’s opinion assumed that children were emotionally ready to express their feelings in their life circumstances. The researcher further believed such participants had adequate information to relate their experiences as primary family caregivers raising children with ID. The researcher excluded family caregivers of children with IDs less than 6 and above 19 years old and those family members who did not live with the children in a home environment.

The family caregivers were between 19 and 67 years old, and most left schooling at the secondary level. The sample comprised 16 mothers, one father, two grandparents (one grandfather and one grandmother), three aunts, two uncles and two guardians of the children with ID. Table  1 below indicates the participants’ demographic information and the profile of children with ID.

Most participants were females, 85%, showing that caring for children with ID was on their shoulders. Most men migrated to cities looking for jobs. Half of the participants left schooling before Grade 12, while few obtained tertiary qualifications. Participants indicated a need for more funds as a contributory factor for not proceeding to tertiary education. Most participants were unemployed at 61%. The interview guides helped the researcher to profile information about the children, including age, gender, and other health problems. In addition, the researcher asked participants for more details of medical treatment for those experiencing other health problems besides ID diagnosis. Participants reported their children with ID experiencing comorbidity problems, including speech and hearing, dental and epilepsy, requiring health care support. Female-headed households were at 38%, and single parents at 42%. Most children were males with fewer father figures. The ages of the children were between 6 and 17 years and mostly experienced speech problems at 37% and unattended dental issues, including missing teeth and tooth decay at 30%, requiring health care services. The dental problems were mainly related to the difficulty of the children with ID to identify and report their needs to their caregivers compared to their peers without ID.

Data collection

The researcher conducted 16 in-depth interviews followed by one focus group discussion of 10 family members raising children with ID in a home environment. The individual in-depth interviews enabled the asking of predetermined questions and focus group discussion triangulation to enhance the richness of data. The participants shared their experiences of caring for their children with ID in a rural environment with the first author. All family caregivers signed written consent to participate before the commencement of data collection. Observational field notes complemented capturing pertinent data not documented through the audio recorder, including the participants’ emotional expressions towards answering questions. Participants gave verbal consent for their narratives to be audio-recorded. The researcher maintained the anonymity and confidentiality of participants throughout the data collection process to protect their human dignity.

Semi-structured interview guides directed the interviews and focus group discussion to explore family caregivers’ experiences raising children with ID in rural communities. The researcher used professional assistance in translating interview guides into the Sepedi language, which is dominant in the district and understood by participants. The researcher was fluent in languages preferred by the participants. The interview guides for in-depth interviews and focus group discussion collected socio-demographic information under section A. The central question was asked about the experiences of raising a child with an intellectual disability, followed by probing questions. The guides enabled comparability amongst data sets of focus group discussions and in-depth individual interviews.

Data analysis

The researcher analysed data concurrently with the collection process. The inductive thematic data analysis with the assistance of the Atlas Ti software program followed qualitative analysis steps (Rubin & Rubin, 2012) [ 34 ] of familiarising oneself with data, generating initial codes, searching emerging themes, reviewing them, and naming their related and subthemes. Data analysis consolidated individual in-depth interviews and focus group discussion data. The first researcher (MJM) translated data into English and transcribed audio-recorded information from both data sets on an Excel Sheet. The researcher read written transcripts with written observational field notes to acquaint oneself with the collected data. The observational field notes maximised analysis in documenting participants’ emotional and psychological status attached to their narratives, further increasing reliability and validity. The researcher allocated various codes to participants according to associated themes. The researcher removed any information linking participants to data to ensure anonymity and confidentiality. Transcripts were loaded to Atlas Ti software to arrange similar codes using the coding manager. The Atlas Ti assisted the researcher in handling multiple overlapping codes without losing their contexts. The researcher conducted content analysis to determine themes and subcategories from frequently occurring styles and patterns in the participants’ narrative statements. Data from both participant groups were duly categorised and compared, including examination of any connections, regularities, variations and peculiarities. The researcher summarised information into meaningful units, presented in thick descriptions and quotes from the participants to demonstrate their authenticated voice in the context of supporting literature-based evidence [ 35 ]. The academic supervisor of the study confirmed the appropriateness of the findings.

The researcher comparably consolidated data analysed from 16 in-depth individual interviews and one focus group discussion of 10 female family caregivers raising children with ID. Table  1 presents the profiles of participants and their children with ID. The results revealed information needs regarding the care of children with ID among family caregivers in rural areas. Most families showed a quest for information regarding the care of children’s challenging behaviour and available resources to enable the caregiving of children with ID. The researcher allocated participants’ narrative numbers, such as Participant 1, age, relationship to the child and the type of interviews, to ensure their anonymity and confidentiality throughout the study. Table  2 presents the generated themes and subcategories of the results.

Caregiving of challenging behaviour of children with ID

This theme emerged during focus group discussion around their experiences of the challenging behaviour of children with ID. In addition, the in-depth individual interview responses on supporting families raising children with ID highlighted that most children display challenging behaviour, and most participants reported difficulties in handling them. Participants communicated the theme as a way to make sure that their children were always safe. The results showed the need for information to understand the care of their children’s challenging behaviour. Family caregivers needed information regarding impaired social interaction of the child, overprotectiveness and caretaking attachment toward their children with ID. The diagnosis of ID limits the intellectual adaptive behaviour of children with ID, including impaired social and emotional well-being that resulted in some family caregivers being overprotective and developing a caretaking attachment to approach and cope with the care of their children.

Impaired social interaction of the child

Some participants were concerned about their children’s poor social interaction challenges within and outside the home environments. Most children reported being more comfortable staying at home with familiar family members. The families found introducing these children to new faces, including their peers, difficult.

“My child doesn’t want to meet people outside the family members. He is more comfortable to stay home” (Participant 5, mother, 63 years, focus group). “ My child is having a problem refusing to be sent to the shop near home to buy bread, and he will tell you to send his younger sibling. We cannot force him ”. (Participant 16, mother, 54 years). “My child doesn’t want to go anywhere. He stays at home. He does not want to visit anywhere, even his sister. I even left him alone at home now” (Participant 12, mother, 43 years, individual interview).

Some families needed more information to understand that intervening in children’s behaviour can improve with regular medical help provided by professionals. However, some participants found it challenging to associate refusing to be sent or going anywhere outside the home with impaired social interaction, where the child experiences challenges meeting unfamiliar faces. In addition, participants believed that the children decide to stick to the family environment, including disobedience. In other instances, rejection by community members related to stigma can result in poor interaction of the children with ID with other community members outside the home.

Impaired emotional well-being of the child

The families highlighted the information to deal with different emotions and mood disorders displayed by their children with ID. Some participants indicated emotional dysregulation among the children with ID, contributing to their stress levels as family caregivers. Speech problems experienced by children with ID resulted in most children not being able to express their needs, thus leading them to display challenging behaviour, such as crying for attention.

“The child does not want to stay alone, but she needs attention. She will cry even when nothing is happening to her. I mean like crying unexpectedly. I need training on how to treat her properly” (Participant 23, father, 55 years, individual interview) . “I need more information on how to take care of the child. Especially to manage her when she is angry because of her strange behaviour. I will be happy if they can teach me so I don’t stress too much” (Participant 9, aunt, 42 years, focus group).

Participants believed that adequate information on the care of children with ID would help control and manage their children’s challenging behaviour. These will further reduce the caregiver’s stress level and increase their caregiving skills and self-efficacy towards the difficulties related to the conduct of their children with ID.

Overprotectiveness towards the child

Some families displayed and reported an overly protective approach towards their children with ID. Family caregivers gave individual attention to children more than other children at home. The families were concerned that their children with ID need more protection as they cannot stand for themselves. Participants showed the need for information to be able to treat their children equally.

“I must pay attention and listen to the child more than anyone in the family because he is not able to take care of himself.” (Participant 11, guardian, 27 years, individual interview). “I have other children besides him. I don’t have time for other children; I think I give more attention to him only; I need training to know how to treat other children because this causes conflict”. (Participant 1, mother, 44 years, focus group).

The delayed development of ID in self-care of the children resulted in dependency of the children on the care and support of family caregivers. However, some families felt that the children should not be treated like other children and care for the children more than their siblings. These could further contribute to the rejection of the child by siblings. Social stigma and lack of inclusiveness of the children with ID could contribute to the family caregivers feeling responsible for protecting their vulnerable children more than any other children. Thus, there is a dire need for information to enable family caregivers to provide care of children with ID without feeling guilty and neglecting the parental care of other children.

Caretaking attachment towards the child

Some families reported that children were close to their family members and felt more comfortable around their mothers as caregivers. However, some family members found it difficult to share the caretaking responsibility of the children with other persons willing to help.

“He refuses to sleep with his siblings. He cries to share a bed with me, and it is not easy because I am married” (Participant 13, mother, 35 years, individual interview). “I do not believe in taking the child to institutions like boarding. I think that the child will think that I don’t like him and have abandoned him” (Participant 16, mother, 54 years, individual interview).

Family caregivers communicated caretaking attachment to ensure that children receive full support related to their dependency on the family members’ care. Some felt responsible for providing care independently and needed more trust in other facilities with trained professionals to care for and manage their children with ID. Both children and family caregivers found it difficult to wean from caretaking attachment. However, some responses indicate that caring for a child with ID could bring intense bonding, impacting the family’s quality of life. These narratives highlight the need for professional family interventions.

Available child and family support services

The researcher generated this theme from both focus group discussions and in-depth individual interviews on responses around the available resources to care for and support the families caring for and raising children with ID. The results showed that family caregivers need information on services available for their support as primary caregivers and their children with ID. Support services enable caregivers raising children with ID to cope with the challenges and burdens of care.

Counselling services

This study found that most families needed information to access critical health and well-being services involving counselling as professional assistance in public institutions, which is provided free to such families. Some participants reported an inability to cope with the stress of meeting the needs of their children with ID, especially single parents who experienced difficulties meeting their children’s needs. However, they needed the information to access such support services.

One mother who separated from her husband displayed a dire need for counselling services to deal with caring challenges. Her narrative and observational field notes highlighted the frustration of dealing with her child’s care without her partner’s support. The result communicates the need for continuous counselling to enable ongoing support of parenting skills needed to care for the child with ID in a home environment.

“I was not coping and needed counselling for this matter. But did not know where to go for help.” (Participant 21, mother, 32 years, individual interview).

Some participants reported difficulties in dealing with the fact that their children were diagnosed with ID. The narratives indicate the information needed for counselling services to enable coping abilities.

“I just accepted, but at the beginning, I was not coping. I always take whatever is happening and take it very lightly. I still have unanswered questions. It is difficult to let it go” (Participant 10, mother, 45 years, focus group). “I am not sure of the services [counselling] provided to such families; what I know is that we do not have services for the children” (Participant 11, guardian, 27 years, individual interview).

Some participants believed that information on counselling services would enable them to access professional support for reducing stress levels and using adaptive coping mechanisms to deal with caring responsibilities. Mothers of children with ID mostly communicated the need for counselling services.

Social work services

The family caregivers needed access to information to understand the social workers’ services as a support system for their children’s needs. Some used these services for other family problems but less for raising children with ID. They needed information on collaborations between themselves and the social workers to support and provide care to their children with ID.

“ I consulted the social worker in 2012 when we had family issues. The social workers have never visited my child. I even asked them to visit my house, but they never came” (Participant 14, mother, 42 years, individual interview). “ We once decided to apply for him to be institutionalised but did not succeed ” (P articipant 25, uncle, 31 years, individual interview).

Some families were willing to institutionalise their children with ID for different reasons. However, they needed more information on the processes to follow. In most cases, such an institutionalisation process in South Africa is coordinated and finalised through social work services. The communicated evidence further showed the need for home visits by health professionals that will improve individualised family interventions on the information needed for the child’s care. Socio-demographic information revealed that most participants utilised the social work services when making applications for the children’s dependency grants but needed help to continue with the services for information regarding further assistance in the care of such children.

Psychological services

Some families were not coping with the diagnosis of their children with ID. The burden experienced by these families leads to some willing to end their lives to deal with the impact of raising a child with ID. One single mother of 5 children was emotional when sharing her experiences:

“I was frustrated and wanted to ingest poison and kill both my children. I felt the pain” (Participant 14, mother, 42 years, individual interview). “I feel emotional pain that he is like the way he is, not the same as other children” (Participant 18, mother, 50 years, individual interview).

The excerpts above show evidence of hopelessness related to the burden of raising a child with ID. The care burdens required psychological intervention services to assist the needy family caregivers. The observations on these parents displayed signs of emotional and psychological drains of raising a child with ID. The diagnosis of children with ID showed frustration, especially among mothers who experienced emotional and psychological impacts.

Health care services for children with ID

Most children experienced health-related challenges that required intervention in health services such as medical, dental, speech and hearing, and mental health services. Some families needed to utilise community facilities such as clinics to support their children’s basic needs with ID effectively. However, few participants reported taking their children to health care services. Stigmatisation resulted in some family caregivers not being at ease in seeking help to bring their children to health care professionals. However, services for such children are provided freely in South African public institutions.

“My child shuffles on the floor and cannot walk or sit. I took him [the child] to the church to receive healing. I think mental problems get different treatment from other diseases. I don’t know the services around us to help my child.” (Participant 20, mother, 47 years, individual interview). “I sometimes fail to understand what he wants, especially around people. I get frustrated because I do not understand the sign language that he is using. It is challenging to understand him. (Participant 1, mother, 44 years, focus group). “She lost most of her teeth, and it was difficult to save them. They started by decaying, and most of the time, she refused to chew hard food, complaining of pain. I didn’t take her to the hospital as the tooth fell without anyone removing it. Now, she eats eggs” (Participant 19, mother, 36 years, individual interview). “I wake up during the night when he is fitting. I can hear him struggling when I am asleep. I must make sure that everything is right with him. The child is not on treatment.” (Participant 6, mother, 42 years, focus group).

The evidence shows that some family caregivers needed information to understand the communication displayed by children with speech problems to respond to their basic needs. Such children require caregivers’ knowledge of primary sign language to facilitate training and rehabilitation of their developmental needs. Lack of adequate information on ID resulted in some families finding alternatives for medical care, such as spiritual and traditional care, for assistance with their children’s health challenges with ID. The dental problems comprised the nutrition of the children as they could not eat hard food, exposing the children to malnutrition.

The results evidenced that although South Africa provides free healthcare services to all citizens at primary healthcare facilities, access to specialised professionals still needs to be improved. Most children experienced health challenges, including epilepsy, physical impairment, speech and hearing problems and dental issues requiring special attention. The study indicates that disseminating information on available ID resources will empower families to provide needed care to their children.

Discussions

The study explored the information needs of family caregivers regarding the care of children with ID in rural home environments. The results established that most families as primary caregivers experienced information challenges regarding caring for their children’s challenging behaviour and the available support resources in their communities. Furthermore, the need for more information on social support structures in rural areas environment regarding the care and raising of children with ID restrains the inclusiveness of these children to participate in societal activities [ 36 ].

Family caregivers needed information to understand and handle challenging behaviour and grooming of their children to possible independence. In support, past research found that parents seek information on the care of their children with ID from professionals to cope with the burden [ 37 ]. On the other hand, research revealed that the knowledge of families of children on ID mostly depends on the type of information provided by the professionals educating them [ 38 ]. In line with the findings, the previous research found a lack of dissemination to family caregivers of children with disabilities in welfare information by the Indian government [ 39 ]. The results extend to prior studies that found information increasing, knowledge and understanding of the parents’ level of children with ID, further leading to self-advocacy in proactive decision-making on the care [ 40 ].

Previous research that resonates with this study found that knowledge is good if shared with caregivers who require it to meet the children’s developmental needs [ 41 ]. However, the empowerment of families of children with ID is mainly determined by their economic status and educational level [ 42 , 43 ]. In support, previous results indicate that the caregivers’ awareness of ID is allied to resilience ability, which mainly enhances the care of children with ID [ 44 ].

This study is congruent with the reflection that reported that caregivers found the behavioural needs of their children with ID challenging to fit into other environments and required expertise to handle them [ 45 ]. Behavioural challenges in ID may indicate the children need attention regarding stimulation, pain reduction, social escape and tangible reinforcement [ 46 ]. Some children presented with impaired social interaction with other family and community members. Similarly, it was revealed that children with ID have few interactions with other people and experience rejection or isolation [ 47 ]. This finding supports the study established that the environmental and social enablers, including inclusivity in activities by their communities, can determine the children’s social interaction [ 48 ]. Congruent with these findings, previous results found that information given to the family caregivers on the children’s behaviour, including emotional changes and aggression, improved their skills to handle the child and further increased feelings of competence and confidence [ 49 ].

Most family caregivers resorted to coping mechanisms that involve caretaking attachment and overprotective towards their children with ID. This finding resonates with the research that found that parents with less information on ID were inadequately involved in modelling behaviour that was adaptive to the development of their children with ID [ 50 ]. The study results support the finding that Australian children with ID experience emotional and behavioural problems challenging to their caregivers [ 51 ]. In addition, the conclusions aligned with the study, which found that in Spain, parents felt responsible for the happiness of their children and developed an overprotective approach towards their care [ 52 ]. Comparably, a caretaking attachment bond mainly develops between the child and caregiver based on love, interaction, and the child’s feeling more uncomfortable in the caregiver’s absence [ 53 ]. Hence, the overprotectiveness of children with ID sometimes makes it difficult for caregivers to combine their work life and the care of their children with ID [ 52 ]. However, a similar study revealed that households with extended family members share the care responsibilities for children with ID, reducing the caring burden [ 54 ].

The study highlighted the need for information to empower the family caregivers on the services available in the communities to offer them support, including counselling, social work, psychological care, and health care services for their children. The findings further resonate with the study, which reported that the caregivers of children with ID needed to be made aware of the support resources available to their health needs [ 25 ]. Most families with children with ID are highly vulnerable and require support interventions for their well-being [ 39 ]. This study highlights that family caregivers, primarily mothers, need information on counselling services to cope with the care challenges of raising their children with ID. In support of this finding, a study conducted in South Africa indicates that most children with developmental disorders were under the care of mothers who are primary caregivers [ 55 ]. Similar research established that counselling of families of children with ID decreases their stress levels, increases their self-esteem and further reduces the risk of disorders related to anxiety [ 56 ]. Furthermore, congruent with these findings, a study revealed that counselling was crucial in enabling family members to create a friendly, positive home environment for their children with ID [ 57 ].

The information needed for health care services included medical, dental, and speech challenges experienced by the children with ID. Some family caregivers reported their children presenting with dental problems such as loose and missing teeth. Comparable studies found that caregivers could identify the dental pain of their children with ID through salivation and putting hands in their mouths more often than their typical peers [ 58 ]. In addition, congruent with this finding, the speech of children with ID is more emotional and requires stimulation than their typical development peers [ 59 ]. In alignment with this finding, accessing appropriate professional services in rural Australia was challenging due to geographical distances [ 60 ]. In support, the study in South Africa revealed that public facilities experience a long list of bookings [ 61 , 62 ]. These reduce access to available rural support services and resources to cater for the needs of the children with ID and their families.

Suggestions and recommendations for practice

The study recommends prioritising the information needs of children with ID and their families to receive professional assistance. Policymakers should establish, support, and provide resources on awareness of ID within health and education facilities. Furthermore, the development of directive policies and regulations should strengthen the implementation of education and training programmes on ID awareness within societies. Collaboration of health care professionals and essential service providers, including teachers and educators in early childhood development centres and schools, should support the dissemination of information on ID to the public. In addition, the results recommend ID awareness campaigns and community education regarding the care of children with ID and the support of caregivers. Thus, training nurses, midwives, social workers, and other health professionals, including educators, is vital to enable them to provide ID awareness and train family caregivers. Training of available community healthcare workers and traditional and religious leaders on ID will equip them with the knowledge to be able to support the vulnerable family caregivers of children with ID. These will provide the families with continuous, valuable, updated information to help their children.

Furthermore, the study highly recommends collaborative professionals for training, empowerment, and providing psychoeducational interventions that will strengthen caregiver competence and confidence in ensuring continuity of the caregiving of children with ID from the home environments. Collaboration and coordination of educational facilities, social development, rehabilitation, and health care services will further enhance information on ID for the public. The study suggests that professionals should actively facilitate forming community support groups and home-based care services to interact and equip family caregivers with relevant information regarding ID awareness to reduce social stigma. Forming partnerships with family caregivers will strengthen information giving and access.

The study’s limitations involve data on the prevalence of children with ID in Limpopo Province that were not available. The study could not capture the experiences of family caregivers of children with ID not accessed through snowballing and known to community health care facilities. Fathers of the children with ID were less presented, limiting their narrative experiences on the caregiving of their children. The study has no information on professional facilities available for support services in rural communities.

This study provides insights into the information access and understanding of family caregivers of children with ID in rural areas of Limpopo Province. The study findings indicate the need for information access by these families to understand the care of their children with ID. The study shows the crucial responsibility of service providers to activate the information support system of caregivers raising children with ID in rural home environments. The findings of this research hope to inform the establishment of training programmes to improve ID information by empowering and enabling family caregivers in rural areas to improve understanding of the care of their children with ID. Training programmes that continuously update caregivers’ knowledge of ID play a critical role in enhancing self-efficacy and competency to support their children. The study supports stakeholders’ collaboration on ID awareness campaigns and opens more platforms to disseminate information and educate the public, including those in rural areas with fewer resources.

Data availability

The datasets used and analysed during the current study are available from the corresponding author upon reasonable request. The data are not publicly available due to information that could compromise the privacy of the research participants. Please write to [email protected].

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The authors would like to acknowledge O.N. Makhubela-Nkondo as a PhD supervisor of one of the authors.

The research received funding from the University of South Africa as PhD bursary.

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Modula MJ conceptualized the study, developed the protocol and interview checklist, conducted the interviews, transcribed the data, analysed and drafted the manuscript and accept personal accountability to the findings of the study. Chipu MG reviewed and aligned a draft of the manuscript to the journal.

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Modula, M.J., Chipu, M.G. Exploring information needs among family caregivers of children with intellectual disability in a rural area of South Africa: a qualitative study. BMC Public Health 24 , 1139 (2024). https://doi.org/10.1186/s12889-024-18606-7

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Empowering School Staff to Support Pupil Mental Health Through a Brief, Interactive Web-Based Training Program: Mixed Methods Study

Authors of this article:

Original Paper

• Emma Soneson 1, 2 , PhD   ; 
• Emma Howarth 3 , PhD   ; 
• Alison Weir 4, 5 , MA, MSc   ; 
• Peter B Jones 2 * , PhD   ; 
• Mina Fazel 1 * , DM  

1 Department of Psychiatry, University of Oxford, Oxford, United Kingdom

2 Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom

3 School of Psychology, University of East London, London, United Kingdom

4 Faculty of Education, University of Cambridge, Cambridge, United Kingdom

5 Howard Community Academy, Anglian Learning multi-academy trust, Bury St Edmunds, United Kingdom

*these authors contributed equally

Corresponding Author:

Emma Soneson, PhD

Department of Psychiatry

University of Oxford

Warneford Lane

Oxford, OX3 7JX

United Kingdom

Phone: 44 1865 613127

Email: [email protected]

Background: Schools in the United Kingdom and elsewhere are expected to protect and promote pupil mental health. However, many school staff members do not feel confident in identifying and responding to pupil mental health difficulties and report wanting additional training in this area.

Objective: We aimed to explore the feasibility of Kognito’s At-Risk for Elementary School Educators , a brief, interactive web-based training program that uses a simulation-based approach to improve school staff’s knowledge and skills in supporting pupil mental health.

Methods: We conducted a mixed methods, nonrandomized feasibility study of At-Risk for Elementary School Educators in 6 UK primary schools. Our outcomes were (1) school staff’s self-efficacy and preparedness to identify and respond to pupil mental health difficulties, (2) school staff’s identification of mental health difficulties and increased risk of mental health difficulties, (3) mental health support for identified pupils (including conversations about concerns, documentation of concerns, in-class and in-school support, and referral and access to specialist mental health services), and (4) the acceptability and practicality of the training. We assessed these outcomes using a series of questionnaires completed at baseline (T1), 1 week after the training (T2), and 3 months after the training (T3), as well as semistructured qualitative interviews. Following guidance for feasibility studies, we assessed quantitative outcomes across time points by comparing medians and IQRs and analyzed qualitative data using reflexive thematic analysis.

Results: A total of 108 teachers and teaching assistants (TAs) completed T1 questionnaires, 89 (82.4%) completed T2 questionnaires, and 70 (64.8%) completed T3 questionnaires; 54 (50%) completed all 3. Eight school staff members, including teachers, TAs, mental health leads, and senior leaders, participated in the interviews. School staff reported greater confidence and preparedness in identifying and responding to mental health difficulties after completing the training. The proportion of pupils whom they identified as having mental health difficulties or increased risk declined slightly over time (median T1 =10%; median T2 =10%; median T3 =7.4%), but findings suggested a slight increase in accuracy compared with a validated screening measure (the Strengths and Difficulties Questionnaire). In-school mental health support outcomes for identified pupils improved after the training, with increases in formal documentation and communication of concerns as well as provision of in-class and in-school support. Referrals and access to external mental health services remained constant. The qualitative findings indicated that school staff perceived the training as useful, practical, and acceptable.

Conclusions: The findings suggest that brief, interactive web-based training programs such as At-Risk for Elementary School Educators are a feasible means to improve the identification of and response to mental health difficulties in UK primary schools. Such training may help address the high prevalence of mental health difficulties in this age group by helping facilitate access to care and support.

Introduction

In recent years, there has been an increased emphasis on the role of schools in supporting children’s mental health [ 1 - 3 ]. This enhanced focus has been driven in large part by an apparent increase in mental health difficulties (including behavioral, social, and emotional difficulties) present in school-aged populations [ 4 - 6 ]—a concern that became increasingly prominent in the context of the COVID-19 pandemic and the associated school closures and social distancing measures [ 7 , 8 ]. There is also a growing recognition of the many unique advantages of using the school setting to promote and protect pupil mental health [ 9 ]. First, most lifetime disorders begin during the schooling years [ 10 ], which suggests that schools may be an ideal setting for early identification and intervention. Second, schools have access to most children, meaning that they are an important component of any public health approach to address child mental health difficulties [ 11 - 14 ]. Third, schools benefit from prolonged engagement with pupils, which can facilitate the implementation of mental health promotion and prevention strategies as well as support and interventions for pupils with identified mental health needs [ 12 ]. Finally, mental health support in schools is often more accessible to families than other types of support [ 15 ].

However, while school staff are increasingly expected to support children’s mental health [ 1 ], many do not feel prepared to do so [ 16 - 19 ] due in part to receiving limited training and supervision in this area [ 20 ]. Therefore, improving school staff’s confidence and preparedness are important considerations for supporting them in taking an expanded role in pupil mental health [ 21 ]. Most schools offer some form of mental health training [ 22 , 23 ], but many staff members believe that they could benefit from additional training [ 18 - 20 , 24 - 26 ]. One area where staff training may be particularly beneficial is the identification of and first response to pupils who have mental health difficulties or who are believed to be at increased risk of developing them. However, although there is evidence suggesting that school staff, parents, and practitioners see such training as an acceptable, feasible, and potentially useful way to support pupil mental health [ 20 , 27 - 29 ], empirical evidence for the effectiveness of such training is limited and focuses primarily on intermediate outcomes (eg, staff knowledge and confidence) rather than downstream outcomes (eg, accurate identification, access to support, and mental health outcomes) [ 30 , 31 ]. Furthermore, there are several potential barriers to implementing training programs in schools, including time, cost, and resource requirements [ 28 ].

At-Risk for Elementary School Educators : A Brief, Interactive Web-Based Training

Training programs that address these barriers may be beneficial for supporting schools in identifying and responding to pupil mental health difficulties. Brief, interactive web-based training programs are a particularly promising avenue as they have the potential to be more affordable, flexible, and scalable than other training formats. One such training is At-Risk for Elementary School Educators (hereinafter, At-Risk ), a virtual simulation-based program developed by the American company Kognito [ 32 ]. The program, which has been completed by >125,000 teachers in the United States, aims to improve pupil mental health by “[building] awareness, knowledge, and skills about mental health, and [preparing] users to lead real-life conversations with pupils, parents, and caregivers about their concerns and available support” [ 33 ].

The program addresses many common implementation barriers to school-based mental health training. For example, At-Risk only requires approximately 1 hour to complete, which is much shorter than many other available training programs [ 31 , 34 ]. This comparatively low time commitment may address the concern that training programs are overly time intensive and, thus, make the training more feasible for busy schools [ 28 , 34 , 35 ]. The web-based format of At-Risk may also address concerns about school-based mental health programs being resource intensive [ 28 ]. Nearly all school mental health training programs documented in the literature are face-to-face sessions led by external facilitators [ 34 , 36 ], with only a few examples of web-based training [ 37 - 39 ]. For schools with limited budgets, programs requiring external facilitators can prove unsustainable and have limited scalability. In terms of financial resources, the costs of At-Risk vary depending on the number of licenses purchased, but the maximum cost is approximately £22 (US $30) per user, a price point that is feasible for many UK schools. In the United States, there have been many examples of bulk purchases at the district or state level that have made the training even more affordable per teacher. In many areas, the training is even free at point of use due to state- or district-wide licensing agreements [ 40 ].

To date, 3 randomized studies have examined the effectiveness and acceptability of At-Risk among samples of American teachers [ 17 , 41 ] and teachers in training [ 42 ] across school years. Each study found high satisfaction ratings, with between 75% and 85% of participants rating the training as useful, well constructed, relevant, and easy to use, and nearly all (88%-95%) reporting that they would recommend it to colleagues. The training also improved teachers’ self-rated preparedness, self-efficacy, and likelihood of identifying and discussing concerns about pupils’ mental health and referring them to appropriate support when needed. These improvements were reflected in the teachers’ behaviors—compared with teachers in the control group , those who completed At-Risk self-reported significantly more helping behaviors (eg, identifying psychological distress, discussing concerns with pupils and parents, and consulting with parents about options for care and support) and gatekeeping behaviors (ie, connecting pupils with care and support) after the training and at 3 months after the training. The findings of these studies indicate that At-Risk may help improve teachers’ ability to identify and respond to pupil mental health needs and lead to positive behavior change in terms of discussing concerns and facilitating access to care and support.

At-Risk in a UK Context: Considerations for Transportability

These 3 studies suggest that At-Risk may be a promising intervention for improving children’s mental health; however, there is still much to be learned about the training’s effectiveness, feasibility, and acceptability. Furthermore, to date, no evaluation of the training has been conducted outside the United States. There is increasing focus on the influence of context on the effectiveness of complex interventions [ 43 - 48 ], and while some interventions have shown success in terms of transportability [ 48 ], other interventions that have evidence of effectiveness in one context have demonstrated null or even negative effects in another [ 46 ]. Furthermore, information that could inform “transportability” is often not collected as part of evaluations [ 44 ], making it difficult to determine the likelihood of success in a new setting.

There are many contextual differences between the United States and the United Kingdom that could mean that school-based interventions developed in one country may not translate well to the other. Cross-country differences in education systems and (mental) health services are particularly relevant to this study. Differences in the education system include the length and content of initial teacher training, the number and roles of teaching assistants (TAs), and school funding structures. There are also key differences in the structure and availability of school-based mental health provision. In the United States, schools often have staff whose sole or at least main responsibility is mental health, such as school psychologists. While these roles are becoming more common in the United Kingdom with the implementation of the Green Paper recommendations [ 1 ], in most UK primary schools, mental health is included within the broader roles of the special educational needs coordinator (SENCo) and pastoral team. Finally, differences in the wider health care systems across the countries also mean that the process and outcomes of external referrals to specialist mental health services vary across settings, another fact that may influence the transportability of school-based interventions such as At-Risk.

Given these uncertainties regarding intervention transportability, additional evaluation of At-Risk is needed to understand whether it is a potentially useful and feasible tool to improve the identification of and response to mental health difficulties in UK primary schools. To explore the potential value of the training in this new context, we conducted a mixed methods feasibility study of At-Risk in 6 UK primary schools covering pupils aged 4 to 11 years . We aimed to examine the influence of At-Risk on staff confidence and preparedness, identification of pupils with mental health difficulties or increased risk of developing mental health difficulties, mental health support outcomes for identified children, and intervention acceptability and practicality.

Study Design

We used a mixed methods, nonrandomized, pretest-posttest study design to explore the feasibility of At-Risk in UK primary schools. While feasibility studies are acknowledged as a key stage of intervention design and evaluation [ 49 , 50 ], there is no universally agreed-upon definition of a feasibility study [ 50 , 51 ]. Therefore, we focused on 3 criteria from the guidance by Bowen et al [ 52 ]: acceptability, practicality, and limited effectiveness testing.

Intervention: At-Risk for Elementary School Educators

At-Risk is a web-based training that is delivered individually and requires only a log-in and internet connection. Using a simulation-based teaching model, the training aims to (1) improve mental health awareness and knowledge, (2) empower users to approach pupils about what they have noticed, (3) impart skills to have meaningful conversations with pupils and parents, and (4) train users to refer pupils to further support. The diagram in Figure 1 illustrates how the training might lead to improved mental health outcomes for pupils.

The simulation begins with an introduction by a virtual coach, who defines and explains how to recognize the warning signs of psychological distress and specific mental health difficulties and provides guidance and practical advice for discussing and acting upon concerns. Users then practice 2 virtual scenarios. The first scenario involves a fifth-grade (UK Year 6; ages of 10-11 years) teacher speaking with the parent of a pupil showing signs of behavioral difficulties. The second involves a third-grade (UK Year 4; ages of 8-9 years) teacher speaking with a pupil showing signs of emotional difficulties. During the conversations, users choose what to say via drop-down menus organized into categories (eg, “bring up concerns” or “ask a question”) and phrases (eg, “Mia sometimes seems a little agitated in class”). Throughout the conversation, users receive feedback through a “comfort bar” (based on how the pupil or parent perceives the conversation), opportunities to “see” the thoughts of the pupil or parent, and suggestions from the virtual coach.

Importantly, there is no one “right” way to conduct the conversations, and several approaches can lead to a positive outcome. Throughout the conversation, users can “undo” actions to backtrack after receiving an undesirable response or to explore what the response would have been had they chosen another option. At the end of each conversation, the pupil or parent provides feedback on the conversation. The training finishes with a short segment on connecting pupils with further support.

For this feasibility study, we used an unmodified version of the training (ie, the standard training designed for American schools, not tailored to the UK context) provided free of cost by Kognito. The potential need for adaptation and tailoring was an important consideration that we explicitly examined as part of our exploration of the acceptability and practicality of At-Risk in this new setting.

Recruitment

We originally sought to purposively sample 5 primary schools from Cambridgeshire or Norfolk that (1) had a higher-than-average proportion of pupils eligible for free school meals or (2) were located in an area in the top tertile of deprivation as measured using the Index of Multiple Deprivation [ 53 ], which we calculated with the publicly available Schools, pupils and their characteristics data [ 54 ]. We emailed headteachers, SENCos, and mental health leads from 131 candidate schools in September and October 2019 about participating in the study. To increase recruitment, we contacted additional schools in January 2020 for a study start date of March 2020. However, the study was suspended in March 2020 due to the in-person school closures associated with the onset of the COVID-19 pandemic. As some of the participating schools dropped out due to the pandemic, we reopened recruitment for a January 2021 study start date. In this round, we did not restrict participation by the 2 deprivation criteria described previously (ie, free school meal eligibility and Index of Multiple Deprivation), so any UK-based mainstream primary school was eligible to participate. The January 2021 start date was again delayed by the pandemic, but there was no subsequent recruitment.

Teachers and TAs

Schools were responsible for recruiting individual teachers and TAs to participate in the training. We encouraged schools to invite all teachers and TAs to participate, but schools made a variety of decisions in this regard. Three schools (schools D, E, and F) had all staff complete the training during inset (in-service training) days or other designated times, 2 schools (schools A and C) had staff volunteer to participate, and 1 school (school B) selected 2 to 3 staff members in each year group to participate.

Measures and Materials

School characteristics.

The characteristics of the participating schools, including school type, school sex (ie, whether they were single or mixed sex), urbanicity, head count, area-level deprivation, level of free school meal eligibility, ethnic composition, and proportion of pupils with special educational needs, were obtained from publicly available data from the Department for Education [ 54 , 55 ].

Teacher and TA Identification Form

The purpose of the Teacher and TA Identification Form ( Multimedia Appendix 1 ) was to understand which pupils participants would identify as having mental health difficulties or an increased risk of developing mental health difficulties. As systematic reviews in this area have identified no suitable questionnaires [ 28 , 30 ], we developed a bespoke questionnaire, which was reviewed by a school staff advisory group to ensure accuracy and relevance. The questionnaire begins with instructions, including explanations and examples of what is meant by “mental health difficulties or risk for mental health difficulties.” Full definitions are provided in Multimedia Appendix 1 , but in brief, “mental health difficulties” are described as “behavioural and social-emotional problems” regardless of formal diagnosis, and “risk for mental health difficulties” is described as experiences that increase the chance of a child developing mental health difficulties in the future.

For all pupils in their class, participants first indicated whether they thought a pupil had mental health difficulties or increased risk. If yes, they answered 9 subsequent questions about mental health support outcomes. The first four outcomes were about communication of concerns, namely whether they had (1) formally documented their concerns with the school, (2) communicated concerns to the SENCo, pastoral care lead, or mental health lead, (3) communicated concerns to another member of the school staff, or (4) communicated concerns to the child or their parents. The next five outcomes pertained to the provision of mental health support, namely whether the pupil (5) received in-class support; (6) received in-school support or had an in-house support plan; (7) had documented social, emotional, and mental health (SEMH) status (a type of special educational need focused on mental health difficulties); (8) had been referred to external mental health services; or (9) had access to external mental health services.

Strengths and Difficulties Questionnaire

The teacher-report Strengths and Difficulties Questionnaire (SDQ) [ 56 - 59 ] served as the comparator for findings about teachers’ and TAs’ identification of pupils. The SDQ includes 25 positive and negative psychological attributes across 5 scales: emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship problems, and prosocial behavior. The first 4 scales add up to a Total Difficulties Score (0-40, with higher scores representing greater difficulties). The SDQ has demonstrated acceptable psychometric properties in primary school samples [ 60 ]. It is important to note that the SDQ is not an exact comparator as it measures a narrower concept than the Teacher and TA Identification Form (which also includes increased risk ). However, this comparison could potentially yield valuable information regarding feasibility .

Pre- and Posttraining Surveys

Kognito uses pre- and posttraining surveys to assess their training. These surveys (based on the validated Gatekeeper Behavior Scale [ 61 ]) explore teachers’ self-efficacy in identifying and responding to mental health difficulties and whether their attitudes, self-efficacy, or practice have changed since completing the At-Risk training. The posttraining survey also includes questions on perceptions of the training’s impact. We independently (ie, with no input from Kognito) reviewed the merits of these questionnaires and decided to use them in this study because (1) they covered relevant and useful concepts related to our aims and (2) using them increased comparability to the other 3 US-based studies of At-Risk . We slightly adapted the surveys to make them more relevant to the UK context ( Multimedia Appendix 2 ).

Interview Schedules

For the pretraining interviews with SENCos and mental health leads, we developed a topic guide about current practice ( Multimedia Appendix 3 ) with the specific purpose of creating Mental Health Resource Maps for each school (refer to the Procedures section). The main topics pertained to formal and informal procedures for when staff members suspect that a child might have mental health difficulties or increased risk, as well as the types of support available.

For the posttraining interviews with teachers, TAs, and strategic stakeholders (ie, those with key leadership roles, including senior leadership teams [SLTs], school governors, and SENCos and mental health leads), we developed 3 separate topic guides ( Multimedia Appendix 3 ), which were informed by our research questions, systematic reviews [ 28 , 30 ], and the Consolidated Framework for Implementation Research [ 62 , 63 ]. For teachers and TAs who completed At-Risk and strategic stakeholders, interview topics included the acceptability of the training, the practicality of implementing it in schools, the utility of further refinement and testing, possible harms associated with the training (if any), and suggestions for adaptations. For teachers and TAs who did not complete the training, topics included reasons for not completing it, barriers to acceptability and practicality, and suggestions for adaptations.

Interviews With SENCos and Mental Health Leads

We conducted a pretraining interview with each school’s SENCo or mental health lead to develop a “Mental Health Resource Map” with information on referral processes and available support. These maps served an ethical purpose by ensuring that pupils identified as potentially having mental health difficulties would have the best possible chance of being linked to care and support.

Completing At-Risk

Schools’ timelines for the study varied due to the pandemic and other commitments. School D completed the training in December 2020; school E completed the training in March 2021; schools B, C, and F completed the training in May 2021; and school A completed the training in June 2021. At baseline (T1), participants completed a Teacher and TA Identification Form and the pretraining survey. They then completed the At-Risk training. We encouraged schools to designate specific time for the training, which 3 schools (schools D, E, and F) did. One week after training (T2), participants were asked to complete a second Teacher and TA Identification Form and the posttraining survey. Three months after the training or at the end of the school year (whichever came first; T3), participants completed a third Teacher and TA Identification Form as well as SDQs for all pupils. All questionnaires were completed on the University of Cambridge Qualtrics platform (Qualtrics International Inc).

Feedback Provision

After T2, we provided all SENCos and mental health leads but not teachers or TAs with feedback regarding which children had been identified as having mental health difficulties or increased risk. After T3, we provided SDQ scores for each child as well as whole-class distributions (where available). This feedback was provided to ensure the ethical conduct of the study.

Interviews With Teachers, TAs, and Strategic Stakeholders

We aimed to recruit at least 3 teachers or TAs who completed the training per school, 3 to 5 teachers or TAs who had not completed the training across all schools, and up to 3 strategic stakeholders per school for posttraining semistructured interviews. Schools contacted staff members directly with an invitation to complete a virtual interview.

Quantitative Outcomes

Analytical samples.

For the main analysis, participants were included if they (1) completed at least the pretraining (T1) questionnaires and the training itself and (2) had what we judged to be a typical number of children they regularly worked with. For the latter criterion, given that the average UK primary school class size is approximately 27 to 28 pupils [ 64 ], we excluded teachers and TAs who worked with <10 children (as we suspected this would not be a random selection of pupils and would therefore influence aggregate identification rates) and those who worked with >60 children (as we believed that it would be difficult for a teacher or TA to know >2 classes’ worth of children well enough to make accurate judgments about their mental health).

Teacher and TA Self-Efficacy and Preparedness

To assess teachers’ and TAs’ preparedness, self-efficacy, and perceptions of training impact, we calculated the absolute and relative frequencies of responses to the pre- and posttraining surveys. Participants were eligible for inclusion in this analysis only if they had pretraining (T1) data.

Identification Outcomes

On the basis of the Teacher and TA Identification Forms, we calculated the number and percentage of pupils in each class whom teachers and TAs perceived as having mental health difficulties or increased risk at each time point. We summarized these across all participants using medians and IQRs.

We then calculated SDQ scores, which we compared with responses from the Teacher and TA Identification Form by calculating (1) the median and IQR for the percentage of children identified by participants who did not have elevated SDQ scores and (2) the median and IQR for the percentage of children with elevated SDQ scores who were not identified by participants. To be included in these analyses, participants had to have completed all 3 time points. For the first outcome, they had to have completed an SDQ for all children they identified in the Teacher and TA Identification Form . For the second outcome, they had to have completed SDQs for at least 80% of their class. Where it was possible to match pupil IDs between teachers and TAs, we pooled SDQ data such that, if one participant did not meet the inclusion criteria themselves, they could still be included if the SDQ data were available from another staff member working with the same children.

Mental Health Support Outcomes

Finally, for each time point, we calculated medians and IQRs for the proportion of identified children with each of the 9 mental health support outcomes (refer to the Teacher and TA Identification Form section for the outcomes) .

Sensitivity Analyses

We also conducted 2 post hoc sensitivity analyses. The first sensitivity analysis excluded all participants from school D. When we prepared feedback for school D (the first school to complete the training), we learned that most participants at the school had misinterpreted the Teacher and TA Identification Form. We edited the form and instructions accordingly to address this issue, but therefore, school D participants completed a slightly different form than the other schools. The second sensitivity analysis was a complete case analysis intended to explore observed differences in outcomes according to whether participants had completed all 3 time points. For the analysis of outcomes pertaining to preparedness, self-efficacy, and perceptions of training impact, we included all participants who completed the surveys at least at T1 and T2.

Statistical Analysis

For all quantitative outcomes, we focused on preliminary, descriptive comparisons across the 3 time points and did not perform any formal hypothesis testing. This aligns with established recommendations for feasibility studies, which generally lack the statistical power necessary for a clear interpretation of hypothesis-testing results [ 65 - 68 ]. We conducted all quantitative analyses in R (version 4.0.3; R Foundation for Statistical Computing) [ 69 ] except for the comparison of Teacher and TA Identification Forms and SDQ scores, for which we used Microsoft Excel (Microsoft Corp). We created all plots using the ggplot2 [ 70 ] and likert packages [ 71 ]. To score the SDQs, we used the freely available R code on the Youthinmind website [ 72 ].

Qualitative Outcomes

We considered 3 analysis approaches for the interview and qualitative questionnaire data: content analysis [ 73 ], framework analysis [ 74 ], and reflexive thematic analysis [ 75 , 76 ]. We initially decided to use content analysis for the survey comments and reflexive thematic analysis for the interviews; however, as we familiarized ourselves with the data, we realized that there was significant overlap between the survey comments and interviews and decided that analyzing them separately was not a useful distinction. As our main aim was to generate insights into the program and its future potential, we decided to use the 6-phase reflexive thematic analysis by Braun and Clarke [ 76 ] for all qualitative data due to its flexibility and ability to generate themes both inductively and deductively. ES developed the initial themes, and MF and EH helped clarify and enrich them. ES and MF worked together to name and refine the themes before the final write-up. We managed and coded all qualitative data in ATLAS.ti (version 9.1.3; ATLAS.ti Scientific Software Development GmbH) and additionally created manual thematic maps to better visualize and understand patterns between our data.

Ethical Considerations

This study was approved by the University of Cambridge Psychology Research Ethics Committee (PRE 2019.076). We obtained active informed consent from all teachers and TAs who took part in the study. We used an opt-out model for parental consent whereby parents received (directly from the schools via their preferred communication routes) an information sheet detailing study aims, procedures, how data would be used, and the right to opt their child out of participation. Parents had 2 weeks to opt their child out of the study by returning a hard copy of the opt-out form or emailing or calling the school. Schools kept track of all opt-outs and instructed teachers and TAs not to include these children in their forms. All quantitative data were collected using anonymous pupil and staff identifiers generated by the participating schools, and all qualitative data were deidentified before analysis, with identifiable information stored on secure servers at the University of Cambridge. Teachers and TAs received £20 (approximately US $28) vouchers for completing the training and questionnaires for at least 2 of the 3 time points and an additional £10 (approximately US $14) for taking part in an interview. School staff members who created the anonymous identifiers received £10 (approximately US $14) vouchers to thank them for their time.

Participants

A total of 6 schools participated in this study (Table S1 in Multimedia Appendix 4 [ 40 ]). Among these 6 schools, there were 4 (67%) from Cambridgeshire and 1 (17%) each from Greater London and Merseyside; 5 (83%) were located in urban areas and 1 (17%) was located in a rural area. All but 1 school (5/6, 83%) were situated in areas of above-average deprivation, and 50% (3/6) of the schools had a higher-than-average proportion of pupils eligible for free school meals. In total, 67% (4/6) of the schools had a high proportion of White pupils (>80%), and 33% (2/6) of the schools were more diverse, with approximately 20% of pupils from Black, Black British, Caribbean, or African backgrounds (school B) or Asian or Asian British backgrounds (school E).

A total of 108 teachers and TAs completed the T1 questionnaires and the training itself, 89 (82.4%) completed the T2 questionnaires, and 70 (64.8%) completed the T3 questionnaires ( Table 1 ), with 54 (50%) having completed all 3. After excluding those teachers and TAs who did not meet the inclusion criteria for the analyses, the final analytical samples were as follows:

• Main analysis of identification and mental health support outcomes: n=97 at T1, n=75 at T2, and n=57 at T3.
• Main analysis of preparedness, self-efficacy, and training impact outcomes: n=107 at T1 and n=83 at T2.
• Main analysis comparing identification outcomes with SDQ scores: n=28 and n=25 (refer to the following section).
• Complete case sensitivity analysis: n=51 at T1, T2, and T3.
• Sensitivity analysis excluding all teachers and TAs from school D: n=70 at T1, n=54 at T2, and n=41 at T3.

Compared with the 2019-2020 national workforce statistics for teachers and TAs working in state-funded nursery and primary schools [ 77 ], our sample had a similar proportion of women (81/89, 91% in our sample vs 90.9% nationally) and a slightly higher proportion of White staff members (82/89, 92% in our sample vs 90.5% nationally).

A total of 7.4% (8/108) of school staff members from 67% (4/6) of the schools completed an interview ( Table 2 ).

a N=89 because this information was collected only at T2.

b N NA =4 (number with missing data for this question).

c Percentages add up to >100 because some participants had multiple roles.

d SENCo: special educational needs coordinator.

e N NA =7 (number with missing data for this question).

a PSHE: Personal, Social, Health and Economic.

b SENCo: special educational needs coordinator.

c TA: teaching assistant.

d HLTA: higher-level teaching assistant.

Pretest-posttest changes suggested that participating in the training was beneficial for the staff and that they had positive perceptions of the training. Findings regarding preparedness ( Figure 2 ) suggest improvements across all domains of recognizing and acting upon concerns about pupils’ mental health, particularly in terms of using key communication strategies and working with parents. Findings regarding self-efficacy ( Figure 3 ) suggest that participants were more confident in their abilities to discuss their concerns about pupils’ mental health after the training than before. Again, the largest changes were observed in discussing concerns with parents and applying key communication strategies. Finally, findings regarding teachers’ and TAs’ perceptions of the impact of applying the skills of the training ( Figure 4 ) suggest that they were generally positive about the possible effects of the training on pupil outcomes (ie, attendance and academic success), teacher-pupil rapport, and the classroom environment. The results from the complete case analysis ( Multimedia Appendix 5 ) were nearly identical to those of the main analysis (all differences were ≤3 percentage points in magnitude).

In terms of how many pupils were identified as having mental health difficulties or increased risk, participants identified similar proportions of their pupils before and immediately after the training and then fewer over time. The median percentage of pupils whom participants believed had mental health difficulties or increased risk was 10% (IQR 6.7%-18.2%) at T1, 10% (IQR 4.5%-16.7%) at T2, and 7.4% (IQR 5.0%-16.7%) at T3. The directions of change were similar for both sensitivity analyses (whereby teachers and TAs identified fewer children over time), with slight differences. For the sensitivity analysis excluding school D ( Multimedia Appendix 6 ), the percentages were slightly (approximately 2 percentage points) higher. For the complete case analysis, the decrease was also notable 1 week after the training, decreasing from 10% (IQR 6.7%-17.3%) at T1 to 8% (IQR 3.9%-16.7%) at T2 and 7.4% (IQR 5.7%-16.7%) at T3.

In terms of the accuracy of identification, it seems that teachers and TAs became slightly more accurate over time in comparison to pupils’ SDQ scores (although it is important to acknowledge the limitations described in the Methods section regarding questionnaire comparability). The median percentage of children identified by participants who did not have elevated SDQ scores was 40% (IQR 0%-50%) at T1, 27.2% (IQR 0%-50%) at T2, and 25% (IQR 0%-50%) at T3. The median percentage of children with elevated SDQ scores who were not identified by participants was 68.8% (IQR 42.9%-87.5%) at T1, 66.7% (IQR 50%-88.2%) at T2, and 57.1% (IQR 33.3%-87.5%) at T3. In the sensitivity analysis excluding school D, the results were similar (typically within 5 percentage points); one small difference was that the median percentage of children identified by teachers and TAs who did not have elevated SDQ scores was 0% (IQR 0%-50%) at T2. The results of the complete case analysis were identical to those of the main analysis.

Overall, the findings suggest that the training may be beneficial for facilitating conversations and access to school-based support (but not external support) for pupils with identified mental health difficulties or increased risk. Figure 5 presents the findings for the 9 mental health support outcomes among identified children across the 3 study time points. As with before the training, there was typically a wide variation in outcomes.

A comparison across time points suggests that participants formally documented their concerns and spoke with the SENCo, pastoral lead, or mental health lead for a greater proportion of identified pupils after the training than before. For example, at T1, teachers and TAs documented concerns for a median of 50% (IQR 0%-100%) of identified pupils; this increased to 56.3% (IQR 4.2%-100%) at T2 and 75.7% (IQR 0%-100%) at T3. The equivalent statistics for speaking with the SENCo, pastoral lead, or mental health lead were a median of 66.7% (IQR 16.7%-100%) at T1, 75% (IQR 50.0%-100%) at T2, and 95.5% (IQR 50.0%-100%) at T3. There was no change in speaking with another staff member, but this was because nearly all participants did so across all time points. Finally, the percentage of pupils whom teachers and TAs spoke with (or whose parents they spoke with) also increased after the training, with a median of 33.3% (IQR 0%-87.5%) at T1, 61.9% (IQR 0%-100%) at T2, and 50% (IQR 0%-100%) at T3.

A comparison across time points also suggests increases in school-based support for identified children after the training compared with before. The median percentage of pupils identified by teachers and TAs who received in-class support increased from 75% (IQR 35.4%-100%) at T1 to 100% at T2 and T3 (IQR 50%-100% and 66.7%-100%, respectively). There was a more modest increase in the receipt of in-school support or in-house support plans, with a median of 40% (IQR 0%-71.4%) of identified pupils receiving them at T1 compared with 50% at T2 and T3 (IQR 3.6%-100% and 8.3%-81.4%, respectively). There was very little change in documented SEMH status or referral or access to specialist mental health services. For each of these outcomes, the median percentage of identified pupils was 0% across time points.

The findings from the sensitivity analyses were similar to those of the main analysis in terms of direction, although improvements across time in the complete case analysis ( Multimedia Appendix 5 ) tended to be more modest than for the main analysis.

Acceptability and Practicality

Quantitative findings.

Quantitative data from the posttraining survey showed that participants were generally positive about the training. Of the 83 participants who completed the survey, 53 (64%) rated it as “good” and 13 (16%) rated it as “very good.” An additional 17% (14/83) rated it as “fair,” 2% (2/83) rated it as “poor”, and 1% (1/83) as “very poor.” A total of 84% (70/83) of the teachers and TAs said that the scenarios in the training were relevant to them. Finally, most participants (74/83, 89%) would recommend the training to other educators.

Qualitative Findings

Qualitative data also suggested that school staff generally found the training practical and acceptable. We generated three themes from our survey and interview data:

• Individual fit: positive perceptions, self-efficacy, and change.
• Institutional fit: alignment with school values and context.
• Taking it forward: improvements and implementation.

Additional findings on possible harms are presented in Multimedia Appendix 7 .

Individual Fit: Positive Perceptions, Self-Efficacy, and Change

In general, participants perceived the program to be a “good fit” with their personal philosophies and practice. Regarding the training itself, many appreciated the included scenarios, particularly in terms of their relevance to their practice. The format of the training—primarily that it was web-based and required active role-play—was also viewed as useful, engaging, and novel and might have contributed to its perceived usefulness. For example, one teacher commented:

The interactive elements of the training were brilliant and something which I have never encountered before! [Survey respondent (SR) 56; school E]

One teacher and well-being lead described:

I think it definitely made you think. [...] you had to really think about what was being said and the response that you would give, reflecting back on sort of the knowledge that they’d given you beforehand, so I thought that was good. [Interviewee 1]

Other participants suggested that opportunities to practice skills during the training improved the likelihood of using those skills in day-to-day practice.

Participants also believed that they had learned a lot from the training, especially in terms of skills and strategies. These included but were not limited to the skills within the At-Risk “EASING” strategy (check your Emotions, Ask for permission, be Specific, use I statements, keep it Neutral, and show Genuine curiosity). Importantly, there was evidence that participants had also applied new skills. Several participants described having new conversations with pupils or parents facilitated by the skills and strategies from the training. For example, one teacher described:

It was that permission thing [...] I wanted to ask [a child] about his home life [...] and kind of he just cried and didn’t want to speak about it anymore, and then when I asked him if we were OK to talk about it, he said, “Actually no, because I think I’m going to cry again,” so then we left it. And then he came to me the following week, and [...] said, “Can we talk about it now?” [...] so actually me asking that, it was the wrong time for him to talk about it, he wasn’t ready, he would have just been emotional, and wouldn’t have been able to get his words out, and actually the week after, him coming to me and saying, “Can we have a little chat,” works perfectly [...] And now we’re more aware of his situation. [Interviewee 2]

This skill seems to have enabled this pupil to have this conversation with the teacher in a manner (in terms of time, place, and identified person) that suited him. Other participants provided similar examples, referencing how skills from the training had facilitated better outcomes.

However, it is important to note that the perceived usefulness of the training varied. Most notably, some participants indicated that their previous training or role made the training less impactful. Illustratively, when asked how the training had impacted their practice, one TA responded:

Having previously received similar training, due to my role, I do not have any recent cases where the training would have changed the way I carried out discussions. [SR 60; school E]

Institutional Fit: Alignment With School Values and Context

Sustainable school-based programs should also align with the values of the school more broadly. Participants often referenced the importance of schools’ prioritization of pupil mental health. For example, one teacher described:

[Mental health is] a conversation which is constantly ongoing and trying to constantly better our practices and make sure we’re looking after them as best as we can and spotting things as best we can as well. [Interviewee 3]

This description demonstrates how prioritizing mental health can promote the critical evaluation of related school practices as well as the additional provision of training opportunities. In many cases, support from the SLT led to formal recognition of pupil mental health within school policies or plans. One strategic stakeholder explained:

I think because our school have well-being and mental health as such a focus, SLT are very supportive of doing things like this and they’re very accommodating. So when I said we had the training and people were going to have to take part in the training, it was very flexible, although they had other ones lined up, they were quite happy to move things around to make things work. And I think, the fact it is such a priority in our school definitely makes that easier. [Interviewee 1]

In this school, mental health and well-being were one of three main school priorities. As indicated previously, direction setting from the SLT is key to ensuring momentum and impetus. However, as others noted, it is important that support from the SLT is genuine rather than being “just another tick box” (Interviewee 4) exercise.

Another facet of institutional fit pertained to the practical aspects of the training. Schools are time- and resource-limited settings, so mental health training needs to fit within this context. The format of At-Risk, especially its flexibility and relatively low time requirements, was viewed as beneficial, with comments such as “For the amount of time [...] I got a huge amount from it” (Interviewee 4). Others made direct comparisons with other training courses. For example, one higher-level TA had previously completed a 1-day, in-person training course with a similar purpose to that of At-Risk. While she preferred the in-person training, she listed the benefits of both types:

[In the in-person training] you can then query and question to your trainer, so you’ve got that interaction, so that obviously isn’t there, is it, on the computer one. [...] if I was looking from a management point of view, I would say, budgetary, I’m sure it’s cheaper [...] to use [At-Risk], not just cheaper as in [...] money, [...] but also cheaper in time [...] So probably if I was looking [...] with my management hat on, I would say the computer-based [training] would get the same message, or similar message, across for a wider audience for probably a cheaper cost. [Interviewee 7]

In terms of efficiency, this participant highlighted the favorable input-to-output ratio of At-Risk , which could allow more staff members to participate in training. This quote also highlights that schools could use At-Risk flexibly. For example, schools might assign staff members to different training programs based on their roles and previous experience, with more intensive, in-person training for staff members with more significant mental health roles and At-Risk for those with fewer responsibilities or less experience.

Taking It Forward: Improvements and Implementation

Participants offered key insights into how to take the training forward in terms of both changes to the training itself and how best to implement it, primarily by tailoring it to the UK context. In terms of language, there was some reference to the American accent, but more so, participants highlighted the need to adapt some of the terminology and signposting resources to reflect UK support systems. They also made suggestions about additional training that could be useful with different topics (such as bullying) and age groups (particularly for younger children).

In addition to improvements and adaptations to the training itself, participants illustrated the importance of implementation. A common theme was that, to maximize impact, the training should include follow-up discussions or live workshopping. One teacher suggested:

I think some kind of “live” element to conclude the training—to have a “real” person to ask questions to as part of a group video chat could have been useful. Also, maybe to ask advice about particular scenarios that we may have found ourselves in in the past. [SR 56; school E]

By facilitating greater engagement and critical thinking, a live element could enhance the impact of the training and potentially make At-Risk more acceptable to those who generally prefer face-to-face training. Participants indicated that someone internal, for example, the SENCo, would be best placed to lead a live element and would enable staff to practice role-playing based on situations and scenarios specific to each school.

There was also wide acknowledgment that any training had to lie within a strong support system. This began with having a clear referral pathway for identified concerns, which was viewed as important for facilitating access to support. In some cases, teachers and TAs were able to find new ways to support children after completing the training. However, in many cases, participants—and strategic stakeholders in particular—explained that support had not always been readily available. For example, one strategic stakeholder recounted what happened after the training:

A lot of them are people saying to me, “What are you going to do about it?” about different children. And I, because some of our support staff don’t know the sort of route for getting extra support, or they’re really shocked to find actually there’s nothing out there for these children...it’s about what we can do in school, and I think people have been really quite shocked about that. You know, they just presume I can make a phone call and these children will get face-to-face counselling. [Interviewee 5]

This shows the importance of embedding the training within a wider support system, including collaboration with external agencies. However, many interviewees referenced the systemic issues that schools face in helping pupils access specialist support, particularly in terms of the high thresholds and long waiting lists that exist for many external services. While schools may be able to provide beneficial support for children, particularly for those with lower-level difficulties, this indicates an ongoing area of need for schools and their pupils.

Summary of Findings

This study offers the first UK evidence for Kognito’s At-Risk for Elementary School Educators , extending findings from 3 US-based trials and providing needed evidence regarding the potential utility, acceptability, and practicality of brief, interactive web-based mental health training for school staff. Overall, the findings showed that At-Risk is a feasible means of improving the identification of and response to pupil mental health difficulties in UK primary schools. Quantitative findings showed that staff preparedness and self-efficacy in identifying and responding to mental health difficulties increased after the training. Identification rates did not increase (and, in fact, decreased at the 3-month follow-up), but there was some suggestion that teachers’ and TAs’ identification became slightly more accurate in comparison with SDQ scores. Crucially, for those pupils identified as having mental health difficulties or increased risk, in-school mental health support outcomes (ie, documentation or discussion of concerns, conversations with pupils and parents, and in-class and in-school support) increased after the training, but more “downstream” outcomes (ie, documented SEMH status and referral and access to external mental health services) did not. Qualitative findings indicated that participants generally found the training acceptable and practical, with many explaining how they intended to use or had already used the skills they learned to improve their practice. Participants also suggested several useful improvements for the training and its implementation, including making it more relevant to the United Kingdom, adding more scenarios, and including a live element in the implementation of the training.

Findings regarding confidence and preparedness reflect those of the 3 US-based studies of At-Risk [ 17 , 41 , 42 ] and the wider literature surrounding teacher mental health training [ 31 ]. In general, mental health training seems to be effective in improving staff confidence. For example, 2 Australian-based studies [ 37 , 78 ] found that secondary school teachers who completed training felt more confident discussing their concerns and helping pupils with their mental health. Another UK-based study of a psychoeducational training program to improve recognition of depression in secondary schools [ 79 ] found significant pretest-posttest improvements in teacher confidence in their knowledge of symptoms, ability to recognize symptoms, and knowledge about how to speak with pupils about their mental health. However, not all studies have shown an impact, with a prominent UK-based study of mental health first aid training finding no effect on educators’ confidence in helping pupils with their mental health [ 80 ].

The general decrease in the proportion of pupils identified as having mental health difficulties or increased risk stands in contrast to previous studies of At-Risk , which found that school staff identified significantly more pupils of concern after completing the training [ 17 , 41 ]. Evidence of the effect of other training programs on identification is extremely limited [ 30 , 31 , 36 ], and differences in context, training content and delivery, baseline knowledge, and outcome measurement make it difficult to compare findings across studies. Two vignette-based studies showed little effect of either mental health first aid [ 78 ] or psychoeducational [ 81 ] training on identification (although each study also reported high recognition of difficulties before the training), whereas studies focused on real-world identification have shown mixed results [ 79 , 82 ]. However, changes in the proportion of identified pupils must be contextualized within the accuracy of identification. There are consequences of both over- and underidentification [ 83 , 84 ], most notably in terms of inefficient allocation of limited mental health support resources. While comparison with the SDQ suggested that there was some improvement in terms of the accuracy of identification following the training, underidentification remained a substantial challenge, with between one-half and two-thirds of pupils with elevated SDQ scores remaining unidentified by teachers and TAs. The underidentification of children with mental health difficulties in educational settings, particularly for children with internalizing as opposed to externalizing problems [ 85 ], has been well documented in the literature [ 30 ], and it is likely that a combination of identification models is required to address this challenge [ 27 , 29 ].

Promisingly, the training appeared to be useful in terms of connecting pupils with care and support, an outcome not frequently measured in other studies [ 30 , 31 , 34 ]. First, the findings suggested that participants had conversations about or documented concerns for a greater proportion of identified pupils following the training, which reflects findings from previous studies of At-Risk [ 17 , 41 ]. This is a rather unique outcome in the literature as other training evaluations have found no difference between training and control groups in terms of conversations with pupils and colleagues [ 78 ]. Importantly, this study went beyond conversations to include outcomes pertaining to in-school and external support. The increases in in-class and in-school support for identified pupils reflect findings of the UK-based study by Kidger et al [ 80 ] of mental health first aid training and the Australian-based pilot study by Parker et al [ 37 ] of a web-based training program, each of which found a positive effect of the training on helping behaviors. Although in-class and in-school support seemed to increase following the training, it is notable that referrals and access to specialist services did not. There are several plausible explanations for this finding. For example, it is likely that school staff were already aware of children with the most severe mental health difficulties and were confident and able to support newly identified pupils—who might have had lower-level mental health difficulties—within the school setting. However, if the training did lead to the identification of children who might benefit from specialist care, there are many barriers to accessing such support (eg, availability and long waiting lists) that might have influenced these outcomes, as reflected in both the qualitative interviews and the wider literature [ 23 , 86 ].

In addition, quantitative and qualitative findings suggested that the program was a good fit for individuals and schools, which aligns with previous research on the acceptability and perceived need for mental health training for school staff [ 18 , 20 , 27 - 29 , 87 , 88 ]. The training’s format seemed to be a key contributor to its feasibility. With a few exceptions [ 37 , 39 , 89 ], the web-based simulation-based format of At-Risk is unique among training programs and is well aligned with teachers’ preferences. For example, in their focus group study of UK secondary school teachers, Shelemy et al [ 20 ] found that participants wanted engaging, interactive, and concise training that included practical strategies and illustrative case studies, all of which are central to At-Risk . While the authors found that teachers disagreed over the usefulness of web-based training, it is possible that these concerns would have decreased during the COVID-19 pandemic as staff became more accepting of web-based opportunities to learn.

Qualitative findings also demonstrated the importance of school context and culture, which have been highlighted in previous research [ 27 ]. In particular, participants noted the importance of school culture in adopting mental health interventions into regular practice. In their systematic review, Moore et al [ 90 ] identified school culture, values, and policies as key facilitators of sustaining mental health interventions. A related area of focus was support from the SLT. This support is a well-recognized factor contributing to intervention success and sustainability for several reasons, including these leaders’ practical role in communicating about interventions and allocating specific time and resources to them [ 43 , 90 , 91 ]. However, it is important to recognize that mental health training for school staff may be even more needed and impactful in schools where mental health is not as much of a priority.

Limitations

Our mixed methods approach, wide range of outcomes, and diverse sample of participating schools offer rich information regarding the feasibility of At-Risk in the United Kingdom. These strengths notwithstanding, there are also several limitations to consider when interpreting the findings. The nonrandomized design, while common for feasibility studies, prevents any conclusions regarding causality and also limits the exploration of other factors that may have influenced outcomes (eg, providing teachers and TAs with the Mental Health Resource Maps or SENCos and mental health leads with feedback on identified pupils). In terms of recruitment and retention, the study had 50% (54/108) attrition. Several factors may have influenced this, including the increased pressure on school staff due to the COVID-19 pandemic, the timing of the study within the school year, and the requirement to communicate with participants only via the study link person. While we tried to explore the effect of attrition through a complete case sensitivity analysis, we lacked important information on the characteristics of those who dropped out as this information was collected only at T2. Furthermore, we were only able to recruit 8 staff members for the posttraining interviews, which was far below our recruitment target. Low participation rates could again be due to several factors, including the impact of the COVID-19 pandemic or competing priorities. Of note, we were not able to recruit anyone who did not complete the training, any headteachers, or any staff from 2 of the schools (schools A and D). This could mean that we lack viewpoints that may be important for understanding the feasibility and utility of the training.

There were also limitations associated with the study measures. While the Teacher and TA Identification Form was informed by the literature and reviewed by our primary school staff advisory group, its validity and reliability are unknown. In addition, the questionnaire only measured mental health support outcomes for those pupils identified as having mental health difficulties or increased risk. Therefore, we do not have information on those who were not identified. The measure is also based on teacher and TA reports and so may not have complete information about all types of support that pupils receive. Another important limitation pertains to the comparator used to assess the identification outcomes. To understand the potential utility of the training program, it is important to have a robust comparator. While we chose to use the teacher-report SDQ, it would also have been interesting to compare identification outcomes with parent-rated mental health difficulties, particularly in light of the low interrater agreement of common measures of child mental health difficulties [ 92 ]. An even stronger comparator would be to assess the teacher and TA identification outcomes against a clinical interview; however, this was not feasible in this study.

Finally, at the time of writing, At-Risk is currently not available for use as Kognito restructures its offerings. This demonstrates a trend that unfortunately is a common occurrence in the field of mental health, whereby many evidence-based digital tools are not available to potential end users [ 93 ]. Nonetheless, the learnings from this feasibility study offer rich information on what type of content and format may be useful for training programs in this area and, as such, can support further development and evaluation in the field.

Implications for Practice

Studies have consistently demonstrated that school staff would appreciate additional training on how best to support pupil mental health [ 18 , 20 , 87 , 88 ]. However, to be scalable, such programs must be realistic in terms of time, cost, and resource requirements [ 28 , 90 , 91 ]. Contextualized within the wider literature on school-based mental health interventions, the findings from this study suggest that mental health training is a feasible option for upskilling school staff to identify and respond to pupil mental health difficulties. They further highlight several specific factors that might positively contribute to feasibility and scalability, many of which are reflected in the broader literature on mental health training [ 20 , 28 ]. For example, teachers and TAs appreciated that the training actively engaged them in learning and applying new skills and that it used realistic examples to demonstrate the real-world applicability of the training, whereas school leaders identified the relatively low time and cost requirements and flexibility as key factors that could make the training feasible for their school context.

However, this is not to say that there are no implementation barriers associated with At-Risk or similar training programs. While the resources required to implement At-Risk are relatively low compared with other training programs, they must still be considered within the context of other school priorities. As demonstrated in the interviews and the wider literature [ 3 , 43 , 90 , 91 ], support from school leadership is essential for securing the time and budget required to implement a training such as At-Risk , and in schools where mental health is not a priority, there are likely to be many barriers to implementation . Even in schools with strong support from the leadership team, it may be difficult to find the requisite budget, time, and human resources to devote to the training. Finally, as is the case with any school-based mental health intervention, it is important that schools do not take sole responsibility for pupils’ mental health. Active partnership between schools and mental health services is key to ensuring that schools feel empowered and supported in this role [ 21 , 90 , 94 ]. While the schools in this study worked hard to support pupils as best they could, interviewees expressed frustration about the difficulty of accessing external support for children who could benefit from it. This is not an uncommon theme in the wider literature surrounding school-based interventions [ 20 , 23 , 91 ] and is a key consideration for scaling up training programs.

Implications for Future Research

The promising findings of this study suggest that additional research is needed to explore the role of scalable mental health training in supporting schools to protect and promote children’s mental health. On the basis of gaps in the literature, particular areas of interest include training for primary school staff (as most are focused on secondary school staff), web-based training (as opposed to traditional time- and resource-intensive in-person training), and training that takes a “whole school approach” by including all school staff members (rather than only teachers). This final area is especially interesting as findings from this study and others [ 27 ] have highlighted stakeholders’ preference that training programs include all school staff members. While our study jointly analyzed findings for teachers and TAs, future research would do well to consider how the unique roles and perspectives of these professionals—as well as other staff members within the school setting—might influence outcomes. Furthermore, future research should be more inclusive about their choice of outcomes, as too often evaluations of school staff training programs have focused on intermediate outcomes such as knowledge or confidence [ 31 ] without considering more “downstream” outcomes such as access to support. Finally, as demonstrated in our study, there is great value in using mixed methods approaches and including information about wider issues of feasibility and implementation, and studies that take this broader lens can help identify programs that are scalable, sustainable, and effective.

Conclusions

School staff would welcome additional mental health training to enable them to respond to pupil mental health difficulties, but there are many barriers to implementing such training at scale. Therefore, training programs that have relatively low time and resource requirements have great potential to fulfill an unmet need in schools. This mixed methods feasibility study showed that At-Risk for Elementary School Educators —an example of a brief, interactive web-based training program—is a feasible means of empowering school staff to accurately identify and respond to pupil mental health difficulties and increased risk.

Acknowledgments

The authors would like to thank Professor Paul Ramchandani for his input in the design of this study, the Cambridge Mental Health in Schools Advisory Group for sharing their views and advice throughout the study, and the staff at the 6 schools that took part in this study for their time and effort. This study was funded by the UK Research and Innovation Emerging Minds network (grant ES/S004726/2), and the training was provided to the schools free of cost by Kognito. ES was funded by a Gates Cambridge Scholarship (grant OPP1144) for the duration of the study. MF is funded by the National Institute for Health and Care Research (NIHR) Oxford and Thames Valley Applied Research Collaboration at the Oxford Health National Health Service (NHS) Foundation Trust. PBJ is funded by the NIHR (grant 0616-20003). All research in the Cambridge Department of Psychiatry is supported by the NIHR Applied Research Collaboration East of England and the Cambridge Biomedical Research Centre at the Cambridgeshire and Peterborough NHS Foundation Trust. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health and Social Care, or the Bill & Melinda Gates Foundation.

Data Availability

The data sets generated during and analyzed during this study are not publicly available due to restrictions associated with our ethics approvals but are available from the corresponding author on reasonable request.

Conflicts of Interest

Kognito is a for-profit company. After reviewing their questionnaires on preparedness and self-efficacy and having found them rigorous and unbiased, we independently decided to include them as outcomes in our study. Kognito had no role in the study design, analysis, or publication. PBJ was a scientific advisory board member for MSD. All other authors declare no other conflicts of interest.

Teacher and Teaching Assistant Identification Form.

Kognito pre- and posttraining surveys.

Interview topic guides.

School characteristics.

Results from complete case sensitivity analysis.

Results from the sensitivity analysis excluding school D.

Quantitative and qualitative findings pertaining to the potential harms of At-Risk.

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Abbreviations

Edited by T Leung; submitted 24.02.23; peer-reviewed by E Widnall, B Fernandes, J Burns, K Cohen; comments to author 27.08.23; accepted 01.03.24; published 23.04.24.

©Emma Soneson, Emma Howarth, Alison Weir, Peter B Jones, Mina Fazel. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.04.2024.

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