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.

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.

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.

Acceptability and facilitators of and barriers to point-of-care HIV testing in a homeless-focused service in Gloucestershire: a qualitative evaluation.

OBJECTIVES: Late HIV diagnosis increases the risks of onward transmission, morbidity and mortality. Rapid point-of-care testing (POCT) reaches people who have never been tested and people living with HIV who are undiagnosed. This study explored the acceptability and feasibility of HIV POCT from the perspectives of service providers and users. METHODS: A pilot study introduced HIV POCT to one service in Gloucestershire, England. Eleven semi-structured interviews with service users and a focus group with three service providers were conducted. The Theoretical Framework of Acceptability and the Theoretical Domains Framework were used to design the topic guide and analysis. RESULTS: Acceptability of HIV POCT was high. Seven facilitators were identified (e.g. understanding the test purpose and process), alongside two potential barriers, one relevant to service providers and users (anxiety) and the other to service users (stigma). CONCLUSIONS: To maximize the benefits of implementation of HIV POCT, health care providers require appropriate training and supervision to offer and administer POCT.

Engagement with protective behaviours in the UK during the COVID-19 pandemic: a series of cross-sectional surveys (the COVID-19 rapid survey of adherence to interventions and responses [CORSAIR] study).

BACKGROUND: Behaviour is key to suppressing the COVID-19 pandemic. Maintaining behaviour change can be difficult. We investigated engagement with hand cleaning, reducing the number of outings, and wearing a face covering over the course of the pandemic. METHODS: We used a series of 64 cross-sectional surveys between 10 February 2020 and 20 January 2022 (n ≈ 2000 per wave). Surveys investigated uptake of hand cleaning behaviours, out of home activity (England only, n ≈ 1700 per wave) and wearing a face covering (England only, restricted to those who reported going out shopping in the last week, n ≈ 1400 per wave). RESULTS: Reported hand cleaning has been high throughout the pandemic period (85 to 90% of participants consistently reporting washing their hands thoroughly and regularly with soap and water frequently or very frequently). Out of home activity has mirrored the easing and re-introduction of restrictive measures. Total number of outings were higher in the second national lockdown than in the first and third lockdowns. Wearing a face covering increased steadily between April to August 2020, plateauing until the end of measurement in May 2021, with approximately 80% of those who had been out shopping in the previous week reporting wearing a face covering frequently or very frequently. CONCLUSIONS: Engagement with protective behaviours increased at the start of the pandemic and has remained high since. The greatest variations in behaviour reflected changes to Government rules. Despite the duration of restrictions, people have continued to adopt personal protective behaviours that were intended to prevent the spread of COVID-19.

Conversational Agents in Health Care: Scoping Review of Their Behavior Change Techniques and Underpinning Theory.

BACKGROUND: Conversational agents (CAs) are increasingly used in health care to deliver behavior change interventions. Their evaluation often includes categorizing the behavior change techniques (BCTs) using a classification system of which the BCT Taxonomy v1 (BCTTv1) is one of the most common. Previous studies have presented descriptive summaries of behavior change interventions delivered by CAs, but no in-depth study reporting the use of BCTs in these interventions has been published to date. OBJECTIVE: This review aims to describe behavior change interventions delivered by CAs and to identify the BCTs and theories guiding their design. METHODS: We searched PubMed, Embase, Cochrane's Central Register of Controlled Trials, and the first 10 pages of Google and Google Scholar in April 2021. We included primary, experimental studies evaluating a behavior change intervention delivered by a CA. BCTs coding followed the BCTTv1. Two independent reviewers selected the studies and extracted the data. Descriptive analysis and frequent itemset mining to identify BCT clusters were performed. RESULTS: We included 47 studies reporting on mental health (n=19, 40%), chronic disorders (n=14, 30%), and lifestyle change (n=14, 30%) interventions. There were 20/47 embodied CAs (43%) and 27/47 CAs (57%) represented a female character. Most CAs were rule based (34/47, 72%). Experimental interventions included 63 BCTs, (mean 9 BCTs; range 2-21 BCTs), while comparisons included 32 BCTs (mean 2 BCTs; range 2-17 BCTs). Most interventions included BCTs 4.1 "Instruction on how to perform a behavior" (34/47, 72%), 3.3 "Social support" (emotional; 27/47, 57%), and 1.2 "Problem solving" (24/47, 51%). A total of 12/47 studies (26%) were informed by a behavior change theory, mainly the Transtheoretical Model and the Social Cognitive Theory. Studies using the same behavior change theory included different BCTs. CONCLUSIONS: There is a need for the more explicit use of behavior change theories and improved reporting of BCTs in CA interventions to enhance the analysis of intervention effectiveness and improve the reproducibility of research.

A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers.

The COVID-19 pandemic has brought the combined disciplines of public health, infectious disease and policy modelling squarely into the spotlight. Never before have decisions regarding public health measures and their impacts been such a topic of international deliberation, from the level of individuals and communities through to global leaders. Nor have models-developed at rapid pace and often in the absence of complete information-ever been so central to the decision-making process. However, after nearly 3 years of experience with modelling, policy-makers need to be more confident about which models will be most helpful to support them when taking public health decisions, and modellers need to better understand the factors that will lead to successful model adoption and utilization. We present a three-stage framework for achieving these ends.

Community Occupational Therapy for people with dementia and family carers (COTiD-UK) versus treatment as usual (Valuing Active Life in Dementia [VALID]) study: A single-blind, randomised controlled trial.

BACKGROUND: We aimed to estimate the clinical effectiveness of Community Occupational Therapy for people with dementia and family carers-UK version (Community Occupational Therapy in Dementia-UK version [COTiD-UK]) relative to treatment as usual (TAU). We hypothesised that COTiD-UK would improve the ability of people with dementia to perform activities of daily living (ADL), and family carers' sense of competence, compared with TAU. METHODS AND FINDINGS: The study design was a multicentre, 2-arm, parallel-group, assessor-masked, individually randomised controlled trial (RCT) with internal pilot. It was conducted in 15 sites across England from September 2014 to January 2018. People with a diagnosis of mild to moderate dementia living in their own home were recruited in pairs with a family carer who provided domestic or personal support for at least 4 hours per week. Pairs were randomised to either receive COTiD-UK, which comprised 10 hours of occupational therapy delivered over 10 weeks in the person with dementia's home or TAU, which comprised the usual local service provision that may or may not include standard occupational therapy. The primary outcome was the Bristol Activities of Daily Living Scale (BADLS) score at 26 weeks. Secondary outcomes for the person with dementia included the following: the BADLS scores at 52 and 78 weeks, cognition, quality of life, and mood; and for the family carer: sense of competence and mood; plus the number of social contacts and leisure activities for both partners. Participants were analysed by treatment allocated. A total of 468 pairs were recruited: people with dementia ranged from 55 to 97 years with a mean age of 78.6 and family carers ranged from 29 to 94 with a mean of 69.1 years. Of the people with dementia, 74.8% were married and 19.2% lived alone. Of the family carers, 72.6% were spouses, and 22.2% were adult children. On randomisation, 249 pairs were assigned to COTiD-UK (62% people with dementia and 23% carers were male) and 219 to TAU (52% people with dementia and 32% carers were male). At the 26 weeks follow-up, data were available for 364 pairs (77.8%). The BADLS score at 26 weeks did not differ significantly between groups (adjusted mean difference estimate 0.35, 95% CI -0.81 to 1.51; p = 0.55). Secondary outcomes did not differ between the groups. In total, 91% of the activity-based goals set by the pairs taking part in the COTiD-UK intervention were fully or partially achieved by the final COTiD-UK session. Study limitations include the following: Intervention fidelity was moderate but varied across and within sites, and the reliance on primarily proxy data focused on measuring the level of functional or cognitive impairment which may not truly reflect the actual performance and views of the person living with dementia. CONCLUSIONS: Providing community occupational therapy as delivered in this study did not improve ADL performance, cognition, quality of life, or mood in people with dementia nor sense of competence or mood in family carers. Future research should consider measuring person-centred outcomes that are more meaningful and closely aligned to participants' priorities, such as goal achievement or the quantity and quality of activity engagement and participation. TRIAL REGISTRATION: Current Controlled Trials ISRCTN10748953.

The DAFNEplus programme for sustained type 1 diabetes self management: Intervention development using the Behaviour Change Wheel.

AIMS: Self-management programmes for type 1 diabetes, such as the UK's Dose Adjustment for Normal Eating (DAFNE), improve short-term clinical outcomes but difficulties maintaining behavioural changes attenuate long-term impact. This study used the Behaviour Change Wheel (BCW) framework to revise the DAFNE intervention to support sustained behaviour change. METHODS: A four-step method was based on the BCW intervention development approach: (1) Identifying self-management behaviours and barriers/enablers to maintain them via stakeholder consultation and evidence synthesis, and mapping barriers/enablers to the Capability, Opportunity, Motivation-Behaviour (COM-B) model. (2) Specifying behaviour change techniques (BCTs) in the existing DAFNE intervention using the Behaviour Change Techniques Taxonomy (BCTTv1). (3) Identifying additional BCTs to target the barriers/enablers using the BCW and BCTTv1. (4) Parallel stakeholder consultation to generate recommendations for intervention revision. Revised materials were co-designed by stakeholders (diabetologists, psychologists, specialist nurses and dieticians). RESULTS: In all, 34 barriers and 5 enablers to sustaining self-management post-DAFNE were identified. The existing DAFNE intervention contained 24 BCTs, which partially addressed the enablers. In all, 27 BCTs were added, including 'Habit formation', 'Credible source' and 'Conserving mental resources'. In total, 15 stakeholder-agreed recommendations for content and delivery were incorporated into the final DAFNEplus intervention, comprising three co-designed components: (1) face-to-face group learning course, (2) individual structured follow-up sessions and (3) technological support, including blood glucose data management. CONCLUSIONS: This method provided a systematic approach to specifying and revising a behaviour change intervention incorporating stakeholder input. The revised DAFNEplus intervention aims to support the maintenance of behavioural changes by targeting barriers and enablers to sustaining self-management behaviours.

Informing the research agenda for optimizing audit and feedback interventions: results of a prioritization exercise.

BACKGROUND: Audit and feedback (A&F) interventions are one of the most common approaches for implementing evidence-based practices. A key barrier to more effective A&F interventions is the lack of a theory-guided approach to the accumulation of evidence. Recent interviews with theory experts identified 313 theory-informed hypotheses, spread across 30 themes, about how to create more effective A&F interventions. In the current survey, we sought to elicit from stakeholders which hypotheses were most likely to advance the field if studied further. METHODS: From the list of 313, three members of the research team identified 216 that were clear and distinguishable enough for prioritization. A web-based survey was then sent to 211 A&F intervention stakeholders asking them to choose up to 50 'priority' hypotheses following the header "A&F interventions will be more effective if…". Analyses included frequencies of endorsement of the individual hypotheses and themes into which they were grouped. RESULTS: 68 of the 211 invited participants responded to the survey. Seven hypotheses were chosen by > 50% of respondents, including A&F interventions will be more effective… "if feedback is provided by a trusted source"; "if recipients are involved in the design/development of the feedback intervention"; "if recommendations related to the feedback are based on good quality evidence"; "if the behaviour is under the control of the recipient"; "if it addresses barriers and facilitators (drivers) to behaviour change"; "if it suggests clear action plans"; and "if target/goal/optimal rates are clear and explicit". The most endorsed theme was Recipient Priorities (four hypotheses were chosen 92 times as a 'priority' hypotheses). CONCLUSIONS: This work determined a set of hypotheses thought by respondents to be to be most likely to advance the field through future A&F intervention research. This work can inform a coordinated research agenda that may more efficiently lead to more effective A&F interventions.

Incidence, healthcare-seeking behaviours, antibiotic use and natural history of common infection syndromes in England: results from the Bug Watch community cohort study.

BACKGROUND: Better information on the typical course and management of acute common infections in the community could inform antibiotic stewardship campaigns. We aimed to investigate the incidence, management, and natural history of a range of infection syndromes (respiratory, gastrointestinal, mouth/dental, skin/soft tissue, urinary tract, and eye). METHODS: Bug Watch was an online prospective community cohort study of the general population in England (2018-2019) with weekly symptom reporting for 6 months. We combined symptom reports into infection syndromes, calculated incidence rates, described the proportion leading to healthcare-seeking behaviours and antibiotic use, and estimated duration and severity. RESULTS: The cohort comprised 873 individuals with 23,111 person-weeks follow-up. The mean age was 54 years and 528 (60%) were female. We identified 1422 infection syndromes, comprising 40,590 symptom reports. The incidence of respiratory tract infection syndromes was two per person year; for all other categories it was less than one. 194/1422 (14%) syndromes led to GP (or dentist) consultation and 136/1422 (10%) to antibiotic use. Symptoms usually resolved within a week and the third day was the most severe. CONCLUSIONS: Most people reported managing their symptoms without medical consultation. Interventions encouraging safe self-management across a range of acute infection syndromes could decrease pressure on primary healthcare services and support targets for reducing antibiotic prescribing.

The impact of celebrity influence and national media coverage on users of an alcohol reduction app: a natural experiment.

BACKGROUND: Smartphone apps are increasingly used for health-related behaviour change and people discover apps through different sources. However, it is unclear whether users differ by mode of app discovery. Drink Less is an alcohol reduction app that received national media coverage in the UK caused by celebrity influence (a male TV and radio national broadcaster, aged 51). Our aim was to compare users who discovered the app before and after this coverage. METHODS: A natural experiment assessing the impact of media coverage of Drink Less on users' socio-demographic and drinking characteristics, app engagement levels, and extent of alcohol reduction. The study period was from 17th May 2017 to 23rd January 2019, with media coverage starting on 21st August 2018. Users were 18 years or over, based in the UK and interested in drinking less. Interrupted time series analyses using Generalised Additive Mixed Models were conducted for each outcome variable aggregated at the weekly level. RESULTS: In 66 weeks prior to the media coverage, 8617 users downloaded the app and 18,959 in 23 weeks afterwards. There was a significant step-level increase in users' mean age (B = 8.17, p < .001) and a decrease in the percentage of female users (B = -27.71, p < .001), though these effects dissipated non-linearly over time. No effect of media coverage was detected on employment type or on the percentage of at-risk drinkers, though the mean Alcohol Use Disorders Identification Test score was lower after the media coverage (B = -1.43, p = .031). There was a step-level increase in app engagement - number of sessions (B = 3.45, p = .038) and number of days used (B = 2.30, p = .005) - which continued to increase over time following quadratic trends. CONCLUSIONS: Celebrity influence leading to national media coverage in the UK of the Drink Less app was associated with more people downloading the app who were male, older and engaged with the app; and did not appear to impact employment inequality.

Reducing expectations for antibiotics in primary care: a randomised experiment to test the response to fear-based messages about antimicrobial resistance.

BACKGROUND: To reduce inappropriate antibiotic use, public health campaigns often provide fear-based information about antimicrobial resistance (AMR). Meta-analyses have found that fear-based campaigns in other contexts are likely to be ineffective unless respondents feel confident they can carry out the recommended behaviour ('self-efficacy'). This study aimed to test the likely impact of fear-based messages, with and without empowering self-efficacy elements, on patient consultations/antibiotic requests for influenza-like illnesses, using a randomised design. METHODS: We hypothesised that fear-based messages containing empowering information about self-management without antibiotics would be more effective than fear alone, particularly in a pre-specified subgroup with low AMR awareness. Four thousand respondents from an online panel, representative of UK adults, were randomised to receive three different messages about antibiotic use and AMR, designed to induce fear about AMR to varying degrees. Two messages (one 'strong-fear', one 'mild-fear') also contained empowering information regarding influenza-like symptoms being easily self-managed without antibiotics. The main outcome measures were self-reported effect of information on likelihood of visiting a doctor and requesting antibiotics, for influenza-like illness, analysed separately according to whether or not the AMR information was 'very/somewhat new' to respondents, pre-specified based on a previous (non-randomised) survey. RESULTS: The 'fear-only' message was 'very/somewhat new' to 285/1000 (28.5%) respondents, 'mild-fear-plus-empowerment' to 336/1500 (22.4%), and 'strong-fear-plus-empowerment' to 388/1500 (25.9%) (p = 0.002). Of those for whom the respective information was 'very/somewhat new', only those given the 'strong-fear-plus-empowerment' message said they would be less likely to request antibiotics if they visited a doctor for an influenza-like illness (p < 0.0001; 182/388 (46.9%) 'much less likely'/'less likely', versus 116/336 (34.5%) with 'mild-fear-plus-empowerment' versus 85/285 (29.8%) with 'fear-alone'). Those for whom the respective information was not 'very/somewhat new' said they would be less likely to request antibiotics for influenza-like illness (p < 0.0001) across all messages (interaction p < 0.0001 versus 'very/somewhat new' subgroup). The three messages had analogous self-reported effects on likelihood of visiting a doctor and in subgroups defined by believing antibiotics would 'definitely/probably' help an influenza-like illness. Results were reproduced in an independent randomised survey (additional 4000 adults). CONCLUSIONS: Fear could be effective in public campaigns to reduce inappropriate antibiotic use, but should be combined with messages empowering patients to self-manage symptoms effectively without antibiotics.

Artificial Intelligence and Behavioral Science Through the Looking Glass: Challenges for Real-World Application.

BACKGROUND: Artificial Intelligence (AI) is transforming the process of scientific research. AI, coupled with availability of large datasets and increasing computational power, is accelerating progress in areas such as genetics, climate change and astronomy [NeurIPS 2019 Workshop Tackling Climate Change with Machine Learning, Vancouver, Canada; Hausen R, Robertson BE. Morpheus: A deep learning framework for the pixel-level analysis of astronomical image data. Astrophys J Suppl Ser. 2020;248:20; Dias R, Torkamani A. AI in clinical and genomic diagnostics. Genome Med. 2019;11:70.]. The application of AI in behavioral science is still in its infancy and realizing the promise of AI requires adapting current practices. PURPOSES: By using AI to synthesize and interpret behavior change intervention evaluation report findings at a scale beyond human capability, the HBCP seeks to improve the efficiency and effectiveness of research activities. We explore challenges facing AI adoption in behavioral science through the lens of lessons learned during the Human Behaviour-Change Project (HBCP). METHODS: The project used an iterative cycle of development and testing of AI algorithms. Using a corpus of published research reports of randomized controlled trials of behavioral interventions, behavioral science experts annotated occurrences of interventions and outcomes. AI algorithms were trained to recognize natural language patterns associated with interventions and outcomes from the expert human annotations. Once trained, the AI algorithms were used to predict outcomes for interventions that were checked by behavioral scientists. RESULTS: Intervention reports contain many items of information needing to be extracted and these are expressed in hugely variable and idiosyncratic language used in research reports to convey information makes developing algorithms to extract all the information with near perfect accuracy impractical. However, statistical matching algorithms combined with advanced machine learning approaches created reasonably accurate outcome predictions from incomplete data. CONCLUSIONS: AI holds promise for achieving the goal of predicting outcomes of behavior change interventions, based on information that is automatically extracted from intervention evaluation reports. This information can be used to train knowledge systems using machine learning and reasoning algorithms.

Do Combinations of Behavior Change Techniques That Occur Frequently in Interventions Reflect Underlying Theory?

BACKGROUND: Behavioral interventions typically include multiple behavior change techniques (BCTs). The theory informing the selection of BCTs for an intervention may be stated explicitly or remain unreported, thus impeding the identification of links between theory and behavior change outcomes. PURPOSE: This study aimed to identify groups of BCTs commonly occurring together in behavior change interventions and examine whether behavior change theories underlying these groups could be identified. METHODS: The study involved three phases: (a) a factor analysis to identify groups of co-occurring BCTs from 277 behavior change intervention reports; (b) examining expert consensus (n = 25) about links between BCT groups and behavioral theories; (c) a comparison of the expert-linked theories with theories explicitly mentioned by authors of the 277 intervention reports. RESULTS: Five groups of co-occurring BCTs (range: 3-13 BCTs per group) were identified through factor analysis. Experts agreed on five links (≥80% of experts), comprising three BCT groups and five behavior change theories. Four of the five BCT group-theory links agreed by experts were also stated by study authors in intervention reports using similar groups of BCTs. CONCLUSIONS: It is possible to identify groups of BCTs frequently used together in interventions. Experts made shared inferences about behavior change theory underlying these BCT groups, suggesting that it may be possible to propose a theoretical basis for interventions where authors do not explicitly put forward a theory. These results advance our understanding of theory use in multicomponent interventions and build the evidence base for further understanding theory-based intervention development and evaluation.

Developing strategies to improve fidelity of delivery of, and engagement with, a complex intervention to improve independence in dementia: a mixed methods study.

BACKGROUND: It is important to evaluate fidelity of delivery and engagement during feasibility trials. However, there is little guidance on how to systematically develop strategies to improve implementation if problems arise. We aimed to: 1) Assess fidelity of delivery and engagement, 2) Identify factors influencing fidelity of delivery and engagement, and 3) Develop strategies to improve fidelity of delivery of, and engagement with, a complex intervention to improve independence in dementia, within a feasibility trial. METHODS: A mixed methods evaluation of an intervention that aimed to improve independence in dementia. To assess fidelity of delivery and engagement, observation and self-report methods were used: 60% of audio-recorded intervention sessions were transcribed and reliably rated for fidelity. Providers (n = 12) and people with dementia/supporters (n = 34) were asked to complete checklists after each session. Descriptive statistics were used to analyse the data. To identify factors influencing fidelity and engagement, one-to-one semi-structured interviews were conducted with providers (n = 8), people with dementia (n = 7) and supporters (n = 7). Thematic analysis and content analysis were used to analyse data. To develop strategies, we followed four steps proposed by the authors of the Behaviour Change Wheel (1. Understanding the behaviour, 2. Identifying intervention functions, 3. Specifying intervention content, 4. Identifying mode of delivery). RESULTS: Researcher ratings indicated moderate fidelity and provider/participant ratings indicated high fidelity of delivery. Knowledge, providers' attributes, ease of adaptation of the intervention in relation to participants' needs and logistical considerations influenced fidelity. We developed four strategies to improve fidelity of delivery of PRIDE: 1) showing a video, 2) giving an instruction sheet, 3) giving time to practice and 4) providing continued support. Participants reported high levels of engagement. Participants' attributes, capability and opportunity influenced engagement. We developed four strategies to improve engagement with PRIDE: 1) a session summary document, 2) clear instructions, 3) time to practice activity and 4) providing regular compulsory telephone support. CONCLUSION: Fidelity of delivery and engagement are complex behaviours. This manuscript provides an example of how the Behaviour Change Wheel can be used during a feasibility trial to systematically develop strategies to improve implementation of complex interventions.

Exploratory Analyses of the Popularity and Efficacy of Four Behavioral Methods of Gradual Smoking Cessation.

INTRODUCTION: Around half of smokers attempt to stop by cutting-down first. Evidence suggests that this results in similar quit rates to abrupt quitting. Evidence for the effectiveness and popularity of different gradual cessation methods is sparse. METHODS: Secondary, exploratory, analyses of a randomized trial of gradual versus abrupt smoking cessation. Gradual participants (N = 342) chose between four methods of cutting-down over 2 weeks: cutting-out the easiest cigarettes first (HR-E); cutting-out the most difficult cigarettes first (HR-D); smoking on an increasing time schedule (SR); and not smoking during particular periods (SFP). Nicotine replacement therapy and behavioral support were provided before and after quit day. We used logistic and linear regression modeling to test whether the method chosen was associated with smoking reduction, quit attempts, and abstinence, while adjusting for potential confounders. RESULTS: Participants were on average 49 years old, smoked 20 cigarettes per day, and had a Fagerstrom Test for Cigarette Dependence score of 6. 14.9% (51/342) chose HR-E, 2.1% (7/342) HR-D, 46.2% (158/342) SFP, and 36.8% (126/342) SR. We found no evidence of adjusted or unadjusted associations between method and successful 75% reduction in cigarette consumption, reduction in percentage cigarettes per day or exhaled carbon monoxide, quit attempts, or abstinence at 4-week or 6-month follow-up. CONCLUSIONS: Future research and practice could focus more heavily on the SR and SFP methods as these appeared notably more popular than HR. There was substantial imprecision in the efficacy data, which should be treated with caution; however, none of the gradual cessation methods showed clear evidence of being more efficacious than others. IMPLICATIONS: There is evidence that people who would like to quit smoking gradually should be supported to do so. However, as this is relatively new thinking and there is large potential for variation in methods, guidance on the best way to offer support is sparse. This article is an exploratory analysis of the popularity and efficacy of various methods in an attempt to move the topic forward and inform the implementation of gradual smoking cessation methods in practice. The identified popularity of some methods over others signposts directions for future research.

Interventions to improve appropriate antibiotic prescribing in long-term care facilities: a systematic review.

BACKGROUND: Overuse of antibiotics has contributed to antimicrobial resistance; a growing public health threat. In long-term care facilities, levels of inappropriate prescribing are as high as 75%. Numerous interventions targeting long-term care facilities' antimicrobial stewardship have been reported with varying, and largely unexplained, effects. Therefore, this review aimed to apply behavioural science frameworks to specify the component behaviour change techniques of stewardship interventions in long-term care facilities and identify those components associated with improved outcomes. METHOD: A systematic review (CRD42018103803) was conducted through electronic database searches. Two behavioural science frameworks, the Behaviour Change Wheel and Behaviour Change Technique Taxonomy were used to classify intervention descriptions into intervention types and component behaviour change techniques used. Study design and outcome heterogeneity prevented meta-analysis and meta-regression. Interventions were categorised as 'very promising' (all outcomes statistically significant), 'quite promising' (some outcomes statistically significant), or 'not promising' (no outcomes statistically significant). 'Promise ratios' (PR) were calculated for identified intervention types and behaviour change techniques by dividing the number of (very or quite) promising interventions featuring the intervention type or behaviour change technique by the number of interventions featuring the intervention type or behaviour change technique that were not promising. Promising intervention types and behaviour change techniques were defined as those with a PR ≥ 2. RESULTS: Twenty studies (of19 interventions) were included. Seven interventions (37%) were 'very promising', eight 'quite promising' (42%) and four 'not promising' (21%). Most promising intervention types were 'persuasion' (n = 12; promise ratio (PR) = 5.0), 'enablement' (n = 16; PR = 4.33) and 'education' (n = 19; PR = 3.75). Most promising behaviour change techniques were 'feedback on behaviour' (n = 9; PR = 8.0) and 'restructuring the social environment' (e.g. staff role changes; n = 8; PR = 7.0). CONCLUSION: Systematic identification of the active ingredients of antimicrobial stewardship in long-term care facilities was facilitated through the application of behavioural science frameworks. Incorporating environmental restructuring and performance feedback may be promising intervention strategies for antimicrobial stewardship interventions within long-term care facilities.

Influences on NHS Health Check behaviours: a systematic review.

BACKGROUND: National Health Service Health Checks were introduced in 2009 to reduce cardiovascular disease (CVD) risks and events. Since then, national evaluations have highlighted the need to maximise the programme's impact by improving coverage and outputs. To address these challenges it is important to understand the extent to which positive behaviours are influenced across the NHS Health Check pathway and encourage the promotion or minimisation of behavioural facilitators and barriers respectively. This study applied behavioural science frameworks to: i) identify behaviours and actors relevant to uptake, delivery and follow up of NHS Health Checks and influences on these behaviours and; ii) signpost to example intervention content. METHODS: A systematic review of studies reporting behaviours related to NHS Health Check-related behaviours of patients, health care professionals (HCPs) and commissioners. Influences on behaviours were coded using theory-based models: COM-B and Theoretical Domains Framework (TDF). Potential intervention types and behaviour change techniques (BCTs) were suggested to target key influences. RESULTS: We identified 37 studies reporting nine behaviours and influences for eight of these. The most frequently identified influences were physical opportunity including HCPs having space and time to deliver NHS Health Checks and patients having money to adhere to recommendations to change diet and physical activity. Other key influences were motivational, such as beliefs about consequences about the value of NHS Health Checks and behaviour change, and social, such as influences of others on behaviour change. The following techniques are suggested for websites or smartphone apps: Adding objects to the environment, e.g. provide HCPs with electronic schedules to guide timely delivery of Health Checks to target physical opportunity, Social support (unspecified), e.g. include text suggesting patients to ask a colleague to agree in advance to join them in taking the 'healthy option' lunch at work; Information about health consequences, e.g. quotes and/or videos from patients talking about the health benefits of changes they have made. CONCLUSIONS: Through the application of behavioural science we identified key behaviours and their influences which informed recommendations for intervention content. To ascertain the extent to which this reflects existing interventions we recommend a review of relevant evidence.

Antibiotic prescribing in UK care homes 2016-2017: retrospective cohort study of linked data.

BACKGROUND: Older people living in care homes are particularly susceptible to infections and antibiotics are therefore used frequently for this population. However, there is limited information on antibiotic prescribing in this setting. This study aimed to investigate the frequency, patterns and risk factors for antibiotic prescribing in a large chain of UK care homes. METHODS: Retrospective cohort study of administrative data from a large chain of UK care homes (resident and care home-level) linked to individual-level pharmacy data. Residents aged 65 years or older between 1 January 2016 and 31 December 2017 were included. Antibiotics were classified by type and as new or repeated prescriptions. Rates of antibiotic prescribing were calculated and modelled using multilevel negative binomial regression. RESULTS: 13,487 residents of 135 homes were included. The median age was 85; 63% residents were female. 28,689 antibiotic prescriptions were dispensed, the majority were penicillins (11,327, 39%), sulfonamides and trimethoprim (5818, 20%), or other antibacterials (4665, 16%). 8433 (30%) were repeat prescriptions. The crude rate of antibiotic prescriptions was 2.68 per resident year (95% confidence interval (CI) 2.64-2.71). Increased antibiotic prescribing was associated with residents requiring more medical assistance (adjusted incidence rate ratio for nursing opposed to residential care 1.21, 95% CI 1.13-1.30). Prescribing rates varied widely by care home but there were no significant associations with the care home-level characteristics available in routine data. CONCLUSIONS: Rates of antibiotic prescribing in care homes are high and there is substantial variation between homes. Further research is needed to understand the drivers of this variation to enable development of effective stewardship approaches that target the influences of prescribing.