One size doesn't fit all: methodological reflections in conducting community-based behavioural science research to tailor COVID-19 vaccination initiatives for public health priority populations.

BACKGROUND: Promoting the uptake of vaccination for infectious diseases such as COVID-19 remains a global challenge, necessitating collaborative efforts between public health units (PHUs) and communities. Applied behavioural science can play a crucial role in supporting PHUs' response by providing insights into human behaviour and informing tailored strategies to enhance vaccination uptake. Community engagement can help broaden the reach of behavioural science research by involving a more diverse range of populations and ensuring that strategies better represent the needs of specific communities. We developed and applied an approach to conducting community-based behavioural science research with ethnically and socioeconomically diverse populations to guide PHUs in tailoring their strategies to promote COVID-19 vaccination. This paper presents the community engagement methodology and the lessons learned in applying the methodology. METHODS: The community engagement methodology was developed based on integrated knowledge translation (iKT) and community-based participatory research (CBPR) principles. The study involved collaboration with PHUs and local communities in Ontario, Canada to identify priority groups for COVID-19 vaccination, understand factors influencing vaccine uptake and co-design strategies tailored to each community to promote vaccination. Community engagement was conducted across three large urban regions with individuals from Eastern European communities, African, Black, and Caribbean communities and low socioeconomic neighbourhoods. RESULTS: We developed and applied a seven-step methodology for conducting community-based behavioural science research: (1) aligning goals with system-level partners; (2) engaging with PHUs to understand priorities; (3) understanding community strengths and dynamics; (4) building relationships with each community; (5) establishing partnerships (community advisory groups); (6) involving community members in the research process; and (7) feeding back and interpreting research findings. Research partnerships were successfully established with members of prioritized communities, enabling recruitment of participants for theory-informed behavioural science interviews, interpretation of findings, and co-design of targeted recommendations for each PHU to improve COVID-19 vaccination uptake. Lessons learned include the importance of cultural sensitivity and awareness of sociopolitical context in tailoring community engagement, being agile to address the diverse and evolving priorities of PHUs, and building trust to achieve effective community engagement. CONCLUSION: Effective community engagement in behavioural science research can lead to more inclusive and representative research. The community engagement approach developed and applied in this study acknowledges the diversity of communities, recognizes the central role of PHUs, and can help in addressing complex public health challenges.

Methodological Insights on Recruitment and Retention From a Remote Randomized Controlled Trial Examining the Effectiveness of an Alcohol Reduction App: Descriptive Analysis Study.

BACKGROUND: Randomized controlled trials (RCTs) with no in-person contact (ie, remote) between researchers and participants offer savings in terms of cost and time but present unique challenges. OBJECTIVE: The goal of this study is to examine the differences between different forms of remote recruitment (eg, National Health Service [NHS] website, social media, and radio advertising) in the proportion of participants recruited, demographic diversity, follow-up rates, and cost. We also examine the cost per participant of sequential methods of follow-up (emails, phone calls, postal surveys, and postcards). Finally, our experience with broader issues around study advertising and participant deception is discussed. METHODS: We conducted a descriptive analysis of 5602 increasing-and-higher-risk drinkers (Alcohol Use Disorders Identification Test score ≥8), taking part in a 2-arm, parallel group, remote RCT with a 1:1 allocation, comparing the intervention (Drink Less app) with usual digital care (NHS alcohol advice web page). Participants were recruited between July 2020 and March 2022 and compensated with gift vouchers of up to £36 (a currency exchange rate of £1=US $1.26988 is applicable) for completing follow-up surveys, with 4 stages of follow-up: email reminders, phone calls, postal survey, and postcard. RESULTS: The three main recruitment methods were advertisements on (1) social media (2483/5602, 44.32%), (2) the NHS website (1961/5602, 35.01%), and (3) radio and newspapers (745/5602, 13.3%), with the remaining methods of recruitment accounting 7.37% (413/5602) of the sample. The overall recruitment cost per participant varied from £0 to £11.01. Costs were greater when recruiting participants who were men (£0-£28.85), from an ethnic minority group (£0-£303.81), and more disadvantaged (£0-£49.12). Targeted approaches were useful for recruiting more men but less useful in achieving diversity in ethnicity and socioeconomic status. Follow-up at 6 months was 79.58% (4458/5602). Of those who responded, 92.4% (4119/4458) responded by email. Each additional stage of follow-up resulted in an additional 2-3 percentage points of the overall sample being followed up, although phone calls, postal surveys, and postcards were more resource intensive than email reminders. CONCLUSIONS: For remote RCTs, researchers could benefit from using a range of recruitment methods and cost-targeted approaches to achieve demographic diversity. Automated emails with substantial financial incentives for prompt completion can achieve good follow-up rates, and sequential, offline follow-up options, such as phone calls and postal surveys, can further increase follow-up rates but are comparatively expensive. We also make broader recommendations focused on striking the right balance when designing remote RCTs. Careful planning, ongoing maintenance, and dynamic decision-making are required throughout a trial to balance the competing demands of participation among those eligible, deceptive participation among those who are not eligible, and ensuring no postrandomization bias is introduced by data-checking protocols.

Tailoring CONSORT-SPI to improve the reporting of smoking cessation intervention trials: An expert consensus study.

BACKGROUND AND AIMS: Inadequate reporting of smoking cessation intervention trials is common and leads to significant challenges for researchers. The aim of this study was to tailor CONSORT (Consolidated Standards of Reporting Trials)-SPI (Social and Psychological Interventions) guidelines to improve reporting of trials of behavioural interventions to promote smoking cessation. METHOD: Informed by missing data from the IC-SMOKE (Intervention and Comparison group support provided in SMOKing cEssation) systematic review project, this study used a multi-stage Delphi process to examine which items could be added or modified to improve the reporting of smoking cessation trials. The first stage involved an on-line survey of 17 international experts in smoking cessation and trial methodology voting on the importance of items for inclusion in the updated guidelines. This was followed by a face-to-face expert consensus meeting attended by 15 of these experts, where the final inclusion and exclusion of new items and modifications were agreed upon. A nine-point Likert scale was used to establish consensus, with suggested modifications requiring agreement of 75% or more. Disagreements in the first stage were presented again at the second stage for discussion and a second round of voting. Only items which reached the threshold for agreement were included. RESULTS: The experts agreed on the inclusion of 10 new items and the specification of 12 existing items. This included modifications that could apply to trials more widely (e.g. the rationale for the comparator), but also modifications that were very specific to smoking cessation trials (e.g. the reporting of smoking cessation outcomes). CONCLUSIONS: A Delphi study has developed a modified CONSORT-SPI guideline (CONSORT-SPI-SMOKE) to improve the reporting of trials of behavioural interventions to promote smoking cessation.

Factors associated with wearing a facemask in shops in England following removal of a legal requirement to do so during the COVID-19 pandemic.

OBJECTIVES: We aimed to identify psychological factors associated with the use of facemasks in shops in England following removal of legal requirements to do so, and to compare associations with and without legal restrictions. DESIGN: Repeated cross-sectional online surveys (n ≈ 2000 adults) between August 2020 and April 2022 (68,716 responses from 45,682 participants) using quota sampling. METHODS: The outcome measure was whether those who had visited a shop for essentials in the previous seven days reported always having worn a facemask versus sometimes or not at all. Psychological predictor variables included worry, perceived risk and severity of COVID-19 and the perceived effectiveness of facemasks. Socio-demographic variables and measures of clinical vulnerability were also measured. For the period following removal of legal restrictions, multivariable regression was used to assess associations between the primary outcome variable and predictors adjusting for socio-demographic and clinical vulnerability measures. The analysis was repeated including interactions between psychological predictors and presence versus absence of legal restrictions. RESULTS: Worry about COVID-19, beliefs about risks and severity of COVID-19 and effectiveness of facemasks were substantially and independently associated with the use of facemasks. Removal of legal obligations to wear facemasks was associated with a 25% decrease in wearing facemasks and stronger associations between psychological predictors and wearing facemasks. CONCLUSIONS: Legal obligations increase rates of wearing a facemask. Psychological factors associated with wearing a facemask could be targets for interventions aiming to alter rates of wearing a facemask. These interventions may be more effective when there are no legal obligations to wear a face covering in place.

Pioneer of human behaviour change science to deliver Wooldridge Lecture.

The 56th annual Wooldridge Memorial Lecture will be delivered at BVA Congress 2023 by Professor Susan Michie, pioneer of groundbreaking research exploring how influencing people's actions can have a positive impact on health and sustainability.

Bot or Not? Detecting and Managing Participant Deception When Conducting Digital Research Remotely: Case Study of a Randomized Controlled Trial.

BACKGROUND: Evaluating digital interventions using remote methods enables the recruitment of large numbers of participants relatively conveniently and cheaply compared with in-person methods. However, conducting research remotely based on participant self-report with little verification is open to automated "bots" and participant deception. OBJECTIVE: This paper uses a case study of a remotely conducted trial of an alcohol reduction app to highlight and discuss (1) the issues with participant deception affecting remote research trials with financial compensation; and (2) the importance of rigorous data management to detect and address these issues. METHODS: We recruited participants on the internet from July 2020 to March 2022 for a randomized controlled trial (n=5602) evaluating the effectiveness of an alcohol reduction app, Drink Less. Follow-up occurred at 3 time points, with financial compensation offered (up to £36 [US $39.23]). Address authentication and telephone verification were used to detect 2 kinds of deception: "bots," that is, automated responses generated in clusters; and manual participant deception, that is, participants providing false information. RESULTS: Of the 1142 participants who enrolled in the first 2 months of recruitment, 75.6% (n=863) of them were identified as bots during data screening. As a result, a CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) was added, and after this, no more bots were identified. Manual participant deception occurred throughout the study. Of the 5956 participants (excluding bots) who enrolled in the study, 298 (5%) were identified as false participants. The extent of this decreased from 110 in November 2020, to a negligible level by February 2022 including a number of months with 0. The decline occurred after we added further screening questions such as attention checks, removed the prominence of financial compensation from social media advertising, and added an additional requirement to provide a mobile phone number for identity verification. CONCLUSIONS: Data management protocols are necessary to detect automated bots and manual participant deception in remotely conducted trials. Bots and manual deception can be minimized by adding a CAPTCHA, attention checks, a requirement to provide a phone number for identity verification, and not prominently advertising financial compensation on social media. TRIAL REGISTRATION: ISRCTN Number ISRCTN64052601; https://doi.org/10.1186/ISRCTN64052601.

The Behaviour Change Technique Ontology: Transforming the Behaviour Change Technique Taxonomy v1.

Background: The Behaviour Change Technique Taxonomy v1 (BCTTv1) specifies the potentially active content of behaviour change interventions. Evaluation of BCTTv1 showed the need to extend it into a formal ontology, improve its labels and definitions, add BCTs and subdivide existing BCTs. We aimed to develop a Behaviour Change Technique Ontology (BCTO) that would meet these needs. Methods: The BCTO was developed by: (1) collating and synthesising feedback from multiple sources; (2) extracting information from published studies and classification systems; (3) multiple iterations of reviewing and refining entities, and their labels, definitions and relationships; (4) refining the ontology via expert stakeholder review of its comprehensiveness and clarity; (5) testing whether researchers could reliably apply the ontology to identify BCTs in intervention reports; and (6) making it available online and creating a machine-readable version. Results: Initially there were 282 proposed changes to BCTTv1. Following first-round review, 19 BCTs were split into two or more BCTs, 27 new BCTs were added and 26 BCTs were moved into a different group, giving 161 BCTs hierarchically organised into 12 logically defined higher-level groups in up to five hierarchical levels. Following expert stakeholder review, the refined ontology had 247 BCTs hierarchically organised into 20 higher-level groups. Independent annotations of intervention evaluation reports by researchers familiar and unfamiliar with the ontology resulted in good levels of inter-rater reliability (0.82 and 0.79, respectively). Following revision informed by this exercise, 34 BCTs were added, resulting in a final version of the BCTO containing 281 BCTs organised into 20 higher-level groups over five hierarchical levels. Discussion: The BCT Ontology provides a standard terminology and comprehensive classification system for the content of behaviour change interventions that can be reliably used to describe interventions.

New living evidence resource of human and non-human studies for early intervention and research prioritisation in anxiety, depression and psychosis.

In anxiety, depression and psychosis, there has been frustratingly slow progress in developing novel therapies that make a substantial difference in practice, as well as in predicting which treatments will work for whom and in what contexts. To intervene early in the process and deliver optimal care to patients, we need to understand the underlying mechanisms of mental health conditions, develop safe and effective interventions that target these mechanisms, and improve our capabilities in timely diagnosis and reliable prediction of symptom trajectories. Better synthesis of existing evidence is one way to reduce waste and improve efficiency in research towards these ends. Living systematic reviews produce rigorous, up-to-date and informative evidence summaries that are particularly important where research is emerging rapidly, current evidence is uncertain and new findings might change policy or practice. Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis (GALENOS) aims to tackle the challenges of mental health science research by cataloguing and evaluating the full spectrum of relevant scientific research including both human and preclinical studies. GALENOS will also allow the mental health community-including patients, carers, clinicians, researchers and funders-to better identify the research questions that most urgently need to be answered. By creating open-access datasets and outputs in a state-of-the-art online resource, GALENOS will help identify promising signals early in the research process. This will accelerate translation from discovery science into effective new interventions for anxiety, depression and psychosis, ready to be translated in clinical practice across the world.

Estimating the true effectiveness of smoking cessation interventions under variable comparator conditions: A systematic review and meta-regression.

BACKGROUND AND AIMS: Behavioural smoking cessation trials have used comparators that vary considerably between trials. Although some previous meta-analyses made attempts to account for variability in comparators, these relied on subsets of trials and incomplete data on comparators. This study aimed to estimate the relative effectiveness of (individual) smoking cessation interventions while accounting for variability in comparators using comprehensive data on experimental and comparator interventions. METHODS: A systematic review and meta-regression was conducted including 172 randomised controlled trials with at least 6 months follow-up and biochemically verified smoking cessation. Authors were contacted to obtain unpublished information. This information was coded in terms of active content and attributes of the study population and methods. Meta-regression was used to create a model predicting smoking cessation outcomes. This model was used to re-estimate intervention effects, as if all interventions have been evaluated against the same comparators. Outcome measures included log odds of smoking cessation for the meta-regression models and smoking cessation differences and ratios to compare relative effectiveness. RESULTS: The meta-regression model predicted smoking cessation rates well (pseudo R2 = 0.44). Standardising the comparator had substantial impact on conclusions regarding the (relative) effectiveness of trials and types of intervention. Compared with a 'no support comparator', self-help was 1.33 times (95% CI = 1.16-1.49), brief physician advice 1.61 times (95% CI = 1.31-1.90), nurse individual counselling 1.76 times (95% CI = 1.62-1.90), psychologist individual counselling 2.04 times (95% CI = 1.95-2.15) and group psychologist interventions 2.06 times (95% CI = 1.92-2.20) more effective. Notably, more elaborate experimental interventions (e.g. psychologist counselling) were typically compared with more elaborate comparators, masking their effectiveness. CONCLUSIONS: Comparator variability and underreporting of comparators obscures the interpretation, comparison and generalisability of behavioural smoking cessation trials. Comparator variability should, therefore, be taken into account when interpreting and synthesising evidence from trials. Otherwise, policymakers, practitioners and researchers may draw incorrect conclusions about the (cost) effectiveness of smoking cessation interventions and their constituent components.

Reducing touching eyes, nose and mouth ('T-zone') to reduce the spread of infectious disease: A prospective study of motivational, volitional and non-reflective predictors.

BACKGROUND: The route into the body for many pathogens is through the eyes, nose and mouth (i.e., the 'T-zone') via inhalation or fomite-based transfer during face touching. It is important to understand factors that are associated with touching the T-zone to inform preventive strategies. PURPOSE: To identify theory-informed predictors of intention to reduce facial 'T-zone' touching and self-reported 'T-zone' touching. METHODS: We conducted a nationally representative prospective questionnaire study of Canadians. Respondents were randomized to answer questions about touching their eyes, nose, or mouth with a questionnaire assessing 11 factors from an augmented Health Action Process Approach at baseline: intention, outcome expectancies, risk perception, individual severity, self-efficacy, action planning, coping planning, social support, automaticity, goal facilitation and stability of context. At 2-week follow-up, we assessed HAPA-based indicators of self-regulatory activities (awareness of standards, effort, self-monitoring) and self-reported behaviour (primary dependent variable). RESULTS: Of 656 Canadian adults recruited, 569 responded to follow-up (87% response rate). Across all areas of the 'T-zone', outcome expectancy was the strongest predictor of intention to reduce facial 'T-zone' touching, while self-efficacy was a significant predictor for only the eyes and mouth. Automaticity was the strongest predictor of behaviour at the 2-week follow-up. No sociodemographic or psychological factors predicted behaviour, with the exception of self-efficacy, which negatively predicted eye touching. CONCLUSION: Findings suggest that focusing on reflective processes may increase intention to reduce 'T-zone' touching, while reducing actual 'T-zone' touching may require strategies that address the automatic nature of this behaviour.

Public health and social measures during health emergencies such as the COVID-19 pandemic: An initial framework to conceptualize and classify measures.

Background: Public health and social measures (PHSM) intend to reduce the transmission of infectious diseases and to reduce the burden on health systems, economies and societies. During the COVID-19 pandemic, PHSM have been selected, combined and implemented in a variable manner and inconsistently categorized in policy trackers. This paper presents an initial conceptual framework depicting how PHSM operate in a complex system, enabling a wide-reaching description of these measures and their intended and unintended outcomes. Methods: In a multi-stage development process, we combined (i) a complexity perspective and systems thinking; (ii) literature on existing COVID-19 PHSM frameworks, taxonomies and policy trackers; (iii) expert input and (iv) application to school and international travel measures. Results: The initial framework reflects our current understanding of how PHSM are intended to achieve transmission-related outcomes in a complex system, offering visualizations, definitions and worked examples. First, PHSM operate through two basic mechanisms, that is, reducing contacts and/or making contacts safer. Second, PHSM are defined not only by the measures themselves but by their stringency and application to specific populations and settings. Third, PHSM are critically influenced by contextual factors. The framework provides a tool for structured thinking and further development, rather than a ready-to-use tool for practice. Conclusions: This conceptual framework seeks to facilitate coordinated, interdisciplinary research on PHSM effectiveness, impact and implementation; enable consistent, coherent PHSM monitoring and evaluation; and contribute to evidence-informed decision-making on PHSM implementation, adaptation and de-implementation. We expect this framework to be modified and refined over time.

Knowledge of Self-Isolation Rules in the UK for Those Who Have Symptoms of COVID-19: A Repeated Cross-Sectional Survey Study.

OBJECTIVES: To investigate knowledge of self-isolation rules and factors associated with knowledge. METHODS: Repeated cross-sectional online surveys (n ≈ 2000 UK adults) between 9 November 2020 and 16 February 2022 (78,573 responses from 51,881 participants). We computed a composite measure of knowledge of self-isolation rules and investigated associations between knowledge and survey wave, socio-demographic characteristics (age, gender, UK nation, index of multiple deprivation), trust in government, and participants' belief that they had received enough information about self-isolation. RESULTS: In total, 87.9% (95% CI 87.7% to 88.1%, n = 67,288/76,562) of participants knew that if they had symptoms of COVID-19 they should 'self-isolate'. However, only 62.8% (n = 48,058/76,562, 95% CI 62.4% to 63.1%) knew the main rules regarding what that meant. Younger people had less knowledge than older people, and men had less knowledge than women. Knowledge was lower in people living in England versus in Scotland, Wales, and Northern Ireland. The pattern of association between knowledge and trust in government was unclear. Knowledge was lower in people living in a more deprived area and those who did not believe they had enough information about self-isolation. Knowledge was lower in December 2020 to January 2021, compared with before and after this period. CONCLUSIONS: Approximately 63% of UK adults between November 2020 and February 2022 appeared to know the main rules regarding self-isolation if symptomatic with COVID-19. Knowledge was lower in younger than older people, men than women, those living in England compared with Scotland, Wales or Northern Ireland, and those living in more deprived areas.

Practitioner and digitally delivered interventions for reducing hazardous and harmful alcohol consumption in people not seeking alcohol treatment: a systematic review and network meta-analysis.

AIM: To compare the effectiveness of practitioner versus digitally delivered interventions for reducing hazardous and harmful alcohol consumption. DESIGN: Systematic review and network meta-analysis comprising comprehensive search for randomised controlled trials, robust screening and selection methods and appraisal with the Cochrane Risk of Bias tool. Network meta-analyses were conducted in Stata using random effects, frequentist models. The confidence in network meta-analysis (CINeMA) tool was used to assess confidence in effect sizes. SETTING: Online or community or health settings where the intervention was immediately accessible without referral. PARTICIPANTS: Non treatment-seeking hazardous or harmful drinkers. MEASUREMENTS: Primary outcome was mean difference in alcohol consumption (g/wk); secondary outcome was number of single high intensity drinking episodes. Baseline consumption was analysed as a covariate. FINDINGS: Of 201 included trials (94 753 participants), 152 reported a consumption outcome that could be converted to grams/week; 104 reported number of single high intensity drinking episodes. At 1 and 6 months, practitioner delivered interventions reduced consumption more than digitally delivered interventions (1 month: -23 g/wk (95% CI, -43 to -2); 6 months: -14 g/wk [95% CI, -25 to -3]). At 12 months there was no evidence of difference between practitioner and digitally delivered interventions (-6 g/wk [95% CI, -24 to 12]). There was no evidence of a difference in single high intensity drinking episodes between practitioner and digitally delivered interventions at any time point. Effect sizes were small, but could impact across a population with relatively high prevalence of hazardous and harmful drinking. Heterogeneity was a concern. Some inconsistency was indicated at 1 and 6 months, but little evidence was apparent at 12 months. CONCLUSION: Practitioner delivered interventions for reducing hazardous and harmful alcohol consumption are more effective than digitally delivered interventions up to 6 months; at 12 months there is no evidence of a difference.

Linking measures to mechanisms of action: An expert opinion study.

OBJECTIVE: This study sought to integrate the NIH Science of Behaviour Change (SOBC) measures repository comprising measures of putative mechanisms with mechanisms of action (MoA) identified by the Human Behaviour-Change Project (HBCP). DESIGN: Participants were 30 international experts recruited from professional networks and societies. In three anonymous virtual rounds, experts established consensus on hypothesized links between 26 MoAs and 44 self-report measures. METHODS: In Round 1, experts completed a survey rating agreement with 84 pre-identified measure-MoA links and suggested new links. In Round 2, experts discussed 10 links in an online forum, including pre-identified links with <50% agreement and new links suggested by 20-50% of experts. In Round 3, experts completed a survey rating all links eligible for discussion in Round 2. RESULTS: Twenty-seven experts completed Round 1, 23 completed Round 2 and 18 completed Round 3. In Round 1, 82 of 84 pre-identified links reached >50% agreement and 14 new links were suggested by >50% of experts. In Round 2, experts discussed measure-MoA links and measurement quality. In Round 3, 71 of 96 links reached ≥50% agreement. A total of 167 links reached >50% expert agreement, 33 of which reached ≥90% agreement. CONCLUSION: By identifying putative mechanisms (HBCP) for the 44 self-report measures (SOBC), this study advances the cumulation of scientific results and interoperability of resources to facilitate process research.

Evaluation of a complex intervention for prisoners with common mental health problems, near to and after release: the Engager randomised controlled trial.

BACKGROUND: Many male prisoners have significant mental health problems, including anxiety and depression. High proportions struggle with homelessness and substance misuse. AIMS: This study aims to evaluate whether the Engager intervention improves mental health outcomes following release. METHOD: The design is a parallel randomised superiority trial that was conducted in the North West and South West of England (ISRCTN11707331). Men serving a prison sentence of 2 years or less were individually allocated 1:1 to either the intervention (Engager plus usual care) or usual care alone. Engager included psychological and practical support in prison, on release and for 3-5 months in the community. The primary outcome was the Clinical Outcomes in Routine Evaluation Outcome Measure (CORE-OM), 6 months after release. Primary analysis compared groups based on intention-to-treat (ITT). RESULTS: In total, 280 men were randomised out of the 396 who were potentially eligible and agreed to participate; 105 did not meet the mental health inclusion criteria. There was no mean difference in the ITT complete case analysis between groups (92 in each arm) for change in the CORE-OM score (1.1, 95% CI -1.1 to 3.2, P = 0.325) or secondary analyses. There were no consistent clinically significant between-group differences for secondary outcomes. Full delivery was not achieved, with 77% (108/140) receiving community-based contact. CONCLUSIONS: Engager is the first trial of a collaborative care intervention adapted for prison leavers. The intervention was not shown to be effective using standard outcome measures. Further testing of different support strategies for prison with mental health problems is needed.

An ontology of mechanisms of action in behaviour change interventions.

Background: Behaviour change interventions influence behaviour through causal processes called "mechanisms of action" (MoAs). Reports of such interventions and their evaluations often use inconsistent or ambiguous terminology, creating problems for searching, evidence synthesis and theory development. This inconsistency includes the reporting of MoAs. An ontology can help address these challenges by serving as a classification system that labels and defines MoAs and their relationships. The aim of this study was to develop an ontology of MoAs of behaviour change interventions. Methods: To develop the MoA Ontology, we (1) defined the ontology's scope; (2) identified, labelled and defined the ontology's entities; (3) refined the ontology by annotating (i.e., coding) MoAs in intervention reports; (4) refined the ontology via stakeholder review of the ontology's comprehensiveness and clarity; (5) tested whether researchers could reliably apply the ontology to annotate MoAs in intervention evaluation reports; (6) refined the relationships between entities; (7) reviewed the alignment of the MoA Ontology with other relevant ontologies, (8) reviewed the ontology's alignment with the Theories and Techniques Tool; and (9) published a machine-readable version of the ontology. Results: An MoA was defined as "a process that is causally active in the relationship between a behaviour change intervention scenario and its outcome behaviour". We created an initial MoA Ontology with 261 entities through Steps 2-5. Inter-rater reliability for annotating study reports using these entities was α=0.68 ("acceptable") for researchers familiar with the ontology and α=0.47 for researchers unfamiliar with it. As a result of additional revisions (Steps 6-8), 21 further entities were added to the ontology resulting in 282 entities organised in seven hierarchical levels. Conclusions: The MoA Ontology extensively captures MoAs of behaviour change interventions. The ontology can serve as a controlled vocabulary for MoAs to consistently describe and synthesise evidence about MoAs across diverse sources.