Do engagement and behavioural mechanisms underpin the effectiveness of the Drink Less app?

This is a process evaluation of a large UK-based randomised controlled trial (RCT) (n = 5602) evaluating the effectiveness of recommending an alcohol reduction app, Drink Less, compared with usual digital care in reducing alcohol consumption in increasing and higher risk drinkers. The aim was to understand whether participants' engagement ('self-reported adherence') and behavioural characteristics were mechanisms of action underpinning the effectiveness of Drink Less. Self-reported adherence with both digital tools was over 70% (Drink Less: 78.0%, 95% CI = 77.6-78.4; usual digital care: 71.5%, 95% CI = 71.0-71.9). Self-reported adherence to the intervention (average causal mediation effect [ACME] = -0.250, 95% CI = -0.42, -0.11) and self-monitoring behaviour (ACME = -0.235, 95% CI = -0.44, -0.03) both partially mediated the effect of the intervention (versus comparator) on alcohol reduction. Following the recommendation (self-reported adherence) and the tracking (self-monitoring behaviour) feature of the Drink Less app appear to be important mechanisms of action for alcohol reduction among increasing and higher risk drinkers.

Evaluating the Acceptability of the Drink Less App and the National Health Service Alcohol Advice Web Page: Qualitative Interview Process Evaluation.

BACKGROUND: The extent to which interventions are perceived as acceptable to users impacts engagement and efficacy. OBJECTIVE: In this study, we evaluated the acceptability of (1) the smartphone app Drink Less (intervention) and (2) the National Health Service (NHS) alcohol advice web page (usual digital care and comparator) among adult drinkers in the United Kingdom participating in a randomized controlled trial evaluating the effectiveness of the Drink Less app. METHODS: A subsample of 26 increasing- and higher-risk drinkers (Alcohol Use Disorders Identification Test score≥8) assigned to the intervention group (Drink Less; n=14, 54%; female: n=10, 71%; age: 22-72 years; White: n=9, 64%) or usual digital care group (NHS alcohol advice web page; n=12, 46%; female: n=5, 42%; age: 23-68 years: White: n=9, 75%) took part in semistructured interviews. The interview questions were mapped on to the 7 facets of acceptability according to the Theoretical Framework of Acceptability: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs, and self-efficacy. Alongside these constructs, we also included a question on perceived personal relevance, which previous research has linked to acceptability and engagement. Framework and thematic analysis of data was undertaken. RESULTS: The Drink Less app was perceived as being ethical, easy, user-friendly, and effective for the period the app was used. Participants reported particularly liking the tracking and feedback sections of the app, which they reported increased personal relevance and which resulted in positive affect when achieving their goals. They reported no opportunity cost. Factors such as negative affect when not meeting goals and boredom led to disengagement in the longer term for some participants. The NHS alcohol advice web page was rated as being easy and user-friendly with no opportunity costs. However, the information presented was not perceived as being personally relevant or effective in changing drinking behavior. Most participants reported neutral or negative affect, most participants thought the alcohol advice web page was accessible, and some participants reported ethical concerns around the availability of suggested resources. Some participants reported that it had acted as a starting point or a signpost to other resources. Participants in both groups discussed motivation to change and contextual factors such as COVID-19 lockdowns, which influenced their perceived self-efficacy regardless of their assigned intervention. CONCLUSIONS: Drink Less appears to be an acceptable digital intervention among the recruited sample. The NHS alcohol advice web page was generally considered unacceptable as a stand-alone intervention among the recruited sample, although it may signpost and help people access other resources and interventions.

A data extraction template for the behaviour change intervention ontology.

Background: The Behaviour Change Intervention Ontology (BCIO) aims to improve the clarity, completeness and consistency of reporting within intervention descriptions and evidence synthesis. However, a recommended method for transparently annotating intervention evaluation reports using the BCIO does not currently exist. This study aimed to develop a data extraction template for annotating using the BCIO. Methods: The BCIO data extraction template was developed in four stages: i) scoping review of papers citing component ontologies within the BCIO, ii) development of a draft template, iii) piloting and revising the template, and iv) dissemination and maintenance of the template. Results: A prototype data extraction template using Microsoft Excel was developed based on BCIO annotations from 14 papers. The 'BCIO data extraction template v1' was produced following piloting and revision, incorporating a facility for user feedback. Discussion: This data extraction template provides a single, accessible resource to extract all necessary characteristics of behaviour change intervention scenarios. It can be used to annotate the presence of BCIO entities for evidence synthesis, including systematic reviews. In the future, we will update this template based on feedback from the community, additions of newly published ontologies within the BCIO, and revisions to existing ontologies.

Behaviour change interventions are often reported in an inconsistent and incomplete manner in study reports. This makes it difficult to build knowledge and predict outcomes. There is a need for a shared language to describe behaviour change interventions. This need was met using 'ontologies', which are classification systems that represent knowledge in a standardised way. The Behaviour Change Intervention Ontology (BCIO) has been developed to describe the different aspects of interventions in a way that is precise enough for computers as well as humans to 'read' study findings. The BCIO can be used to extract information from study reports for evidence synthesis, such as systematic literature reviews. To meet the need for a resource for annotating (coding) study reports according to the BCIO, we developed a data extraction template. The template was developed in four stages: i) reviewing existing papers using the BCIO, ii) development of a draft template, iii) piloting and revising the template, and iv) dissemination and maintenance of the template. The resulting resource is an accessible, easy-to-use template to assist with specifying the content of published papers reporting interventions and their evaluation. The template will be updated based on user feedback and future revisions to the BCIO.

Factors influencing uptake of protective behaviours by healthcare workers in England during the COVID-19 pandemic: A theory-based mixed-methods study.

BACKGROUND: Hospital infection control policies protect patients and healthcare workers (HCWs) and limit the spread of pathogens, but adherence to COVID-19 guidance varies. We examined hospital HCWs' enactment of social distancing and use of personal protective equipment (PPE) during the COVID-19 pandemic, factors influencing these behaviours, and acceptability and feasibility of strategies to increase social distancing. METHODS: An online, cross-sectional survey (n = 86) and semi-structured interviews (n = 22) with HCWs in two English hospitals during the first wave of the COVID-19 pandemic (May-December 2020). The Capability, Opportunity, Motivation (COM-B) model of behaviour change underpinned survey and topic guide questions. Spearman Rho correlations examined associations between COM-B domains and behaviours. Interviews were analysed using inductive and deductive thematic analysis. Potential strategies to improve social distancing were selected using the Behaviour Change Wheel and discussed in a stakeholder workshop (n = 8 participants). RESULTS: Social distancing enactment was low, with 85% of participants reporting very frequently or always being in close contact with others in communal areas. PPE use was high (88% very frequently or always using PPE in typical working day). Social distancing was associated with Physical Opportunity (e.g., size of physical space), Psychological Capability (e.g., clarity of guidance), and Social Opportunity (e.g., support from managers). Use of PPE was associated with Psychological Capability (e.g., training), Physical Opportunity (e.g., availability), Social Opportunity (e.g., impact on interactions with patients), and Reflective Motivation (e.g., beliefs that PPE is effective). Local champions and team competition were viewed as feasible strategies to improve social distancing. CONCLUSIONS: It is valuable to understand and compare the drivers of individual protective behaviours; when faced with the same level of perceived threat, PPE use was high whereas social distancing was rarely enacted. Identified influences represent targets for intervention strategies in response to future infectious disease outbreaks.

Linking measures to mechanisms of action in behavior change: A qualitative analysis of expert views.

RATIONALE: Testing mechanisms of action (MoAs) hypothesized to underlie behavior change can enhance intervention effectiveness. Rigorous measurement of putative mechanisms is critical to this effort, but measures are rarely validated with respect to target MoAs. OBJECTIVE: This study aimed to elucidate challenges of linking measures to putative MoAs and to identify priorities for future research. METHOD: This study was a systematic exploration of written comments by experts in behavioral intervention research and theories of behavior change (N = 20) capturing their opinions about a task querying whether self-report measures from the Science Of Behavior Change (SOBC) Measures Repository were related to a set of MoAs identified by the Human Behaviour Change Project (HBCP). RESULTS: Six themes were identified: 1) Study Value, 2) Measure Properties, 3) Mechanism Properties, 4) Miscellaneous Measure Concerns, 5) Conceptual Challenges, and 6) Approaches to Developing Measure-Mechanism Links. Experts noted challenges such as lack of measure validation, poor measure properties (e.g., double-barreled items), overly broad MoA definitions that limited their utility, lack of clarity around the term "related," and more. Nonetheless, experts expressed the importance of the exercise. Suggestions included developing and refining measures that are validate for assessing MoAs, clarifying and elaborating MoA definitions, and conducting further, more granular research. CONCLUSION: This systematic examination of expert comments highlights issues that need further investigation to advance behavioral science, specifically pertaining to identifying valid measures of MoAs in behavioral and process research. This study highlights the challenges and opportunities for future research on linking measures and MoA in behavioral science and subsequently enhancing the efficacy of behavioral interventions.

Effectiveness of a smartphone app (Drink Less) versus usual digital care for reducing alcohol consumption among increasing-and-higher-risk adult drinkers in the UK: a two-arm, parallel-group, double-blind, randomised controlled trial.

Background: Digital interventions, including apps and websites, can be effective for reducing alcohol consumption. However, many are not evidence- or theory-informed and have not been evaluated. We tested the effectiveness of the Drink Less app for reducing alcohol consumption compared with usual digital care in the UK. Methods: In this two-arm, parallel group, double-blind, randomised controlled trial, we enrolled increasing-and-higher-risk drinkers (AUDIT ≥ 8) in the UK, who were motivated to reduce their alcohol consumption and willing to use a digital intervention to do so, via online methods. Participants were randomly assigned (1:1), using an online algorithm, to receive a web link to download the Drink Less app (intervention) or to the NHS alcohol advice webpage (usual digital care). Researchers were masked to group allocation. Participants were followed up at one, three and six months. The primary outcome was self-reported weekly alcohol consumption at six months, adjusting for baseline consumption. The full analytic sample was used in most analyses, though missing data was treated in different ways. The primary, pre-registered intention-to-treat analysis assumed baseline-carried-forwards. Secondary pre-registered analyses also focused on the full analytic sample and used alternatives including multiple imputation and last observation carried forwards. This trial is registered with the ISRCTN registry, ISRCTN64052601. Findings: Between 07/13/2020 and 03/29/2022, 5602 people were randomly assigned to the Drink Less app (n = 2788) or comparator (n = 2814) groups. Six-month follow-up rates were 79% and 80%, respectively. The primary pre-registered conservative intention-to-treat approach assuming non-responders were drinking at baseline levels of consumption, found a non-significant greater reduction of 0.98 units in weekly alcohol consumption in the intervention group at 6-month follow-up (95% CI -2.67 to 0.70). The data were insensitive to detect the hypothesised effect (Bayes factor = 1.17). Data were not missing completely at random, with 6-month follow-up rates differing in terms of education, occupation, and income. We therefore conducted the pre-registered sensitivity analysis using multiple imputation, showing that the Drink Less app resulted in a 2.00-unit greater weekly reduction at 6-month follow-up compared with the NHS alcohol advice webpage (95% CI -3.76 to -0.24). Fewer than 0.1% of participants in both arms who responded to one, three or six-month follow-up reported adverse events linked to participation in the trial. Interpretation: The Drink Less app may be effective in reducing the alcohol consumption in increasing-and-higher-risk drinkers motivated to reduce their consumption. Funding: NIHR Public Health Research Programme.

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.

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.

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.

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.

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.

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.