Project description:BackgroundDigital harm-reduction interventions typically focus on people with severe drug-use problems, yet these interventions have moderate effectiveness on drug-users with lower levels of risk of harm. The difference in effectiveness may be explained by differences in behavioural patterns between the two groupings. Harnessing behavioural theories to understand what is at the core of drug-use behaviours and mapping the content of new interventions, may improve upon the effectiveness of interventions for lower-risk drug-users. To the best of our knowledge, this is the first study to systematically apply the Behaviour Change Wheel (BCW) approach to understand the components, influencing capabilities, opportunities, and motivations (COM-B) of higher education students to change their drug-use behaviors. It is also the first study which identifies specific patterns of behaviours that are more responsive to harm reduction practices through the use of the Theoretical Domain Framework (TDF).MethodsWe employed an explanatory sequential mix-method design. We first conducted an on-line survey and a Delphi exercise to understand the factors influencing COM-B components of higher education students to change their drug-use. Subsequently, we mapped all evidence onto the COM-B components and the TDF domains to identify clusters of behaviours to target for change, using a pattern-based discourse analysis. Finally, a series of multidisciplinary group meetings identified the intervention functions-the means by which the intervention change targeted behaviours and the Behavioural Change Techniques (BCTs) involved using the behaviour change technique taxonomy (v.1).ResultsTwenty-nine BCTs relevant to harm-reduction practices were identified and mapped across five intervention functions (education, modelling, persuasion, incentivization, and training) and five policy categories (communication/marketing, guidelines, regulation, service provision, and environmental/social planning). These BCTs were distributed across eight identified saturated clusters of behaviours MyUSE intervention attempts to change.ConclusionsThe BCTs, identified, will inform the development of a digitally delivered behaviour change intervention that focuses on increasing mindful decision-making with respect to drug-use and promotes alternatives to drug-use activities. The findings can also inform implementation scientists in applying context-specific harm-reduction practices in higher education. We present examples of how the eight identified clusters of target behaviours are mapped across the COM-B components and the TDF, along with suggestions of implementation practices for harm reduction at student population level.

Project description:BackgroundImproving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations.MethodsA systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity.ResultsNineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a 'behaviour system' involving three essential conditions: capability, opportunity, and motivation (what we term the 'COM-B system'). This forms the hub of a 'behaviour change wheel' (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health's 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence's guidance on reducing obesity.ConclusionsInterventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions.

Project description:BackgroundAudit and feedback (A&F) is among the most widely used implementation strategies, providing healthcare professionals with summaries of their practice performance to prompt behaviour change and optimize care. Wide variability in effectiveness of A&F has spurred efforts to explore why some A&F interventions are more effective than others. Unpacking the variability of the content of A&F interventions in terms of their component behaviours change techniques (BCTs) may help advance our understanding of how A&F works best. This study aimed to systematically specify BCTs in A&F interventions targeting healthcare professional practice change.MethodsWe conducted a directed content analysis of intervention descriptions in 287 randomized trials included in an ongoing Cochrane systematic review update of A&F interventions (searched up to June 2020). Three trained researchers identified and categorized BCTs in all trial arms (treatment & control/comparator) using the 93-item BCT Taxonomy version 1. The original BCT definitions and examples in the taxonomy were adapted to include A&F-specific decision rules and examples. Two additional BCTs ('Education (unspecified)' and 'Feedback (unspecified)') were added, such that 95 BCTs were considered for coding.ResultsIn total, 47/95 BCTs (49%) were identified across 360 treatment arms at least once (median = 5.0, IQR = 2.3, range = 129 per arm). The most common BCTs were 'Feedback on behaviour' (present 89% of the time; e.g. feedback on drug prescribing), 'Instruction on how to perform the behaviour' (71%; e.g. issuing a clinical guideline), 'Social comparison' (52%; e.g. feedback on performance of peers), 'Credible source' (41%; e.g. endorsements from respected professional body), and 'Education (unspecified)' (31%; e.g. giving a lecture to staff). A total of 130/287 (45%) control/comparator arms contained at least one BCT (median = 2.0, IQR = 3.0, range = 0-15 per arm), of which the most common were identical to those identified in treatment arms.ConclusionsA&F interventions to improve healthcare professional practice include a moderate range of BCTs, focusing predominantly on providing behavioural feedback, sharing guidelines, peer comparison data, education, and leveraging credible sources. We encourage the use of our A&F-specific list of BCTs to improve knowledge of what is being delivered in A&F interventions. Our study provides a basis for exploring which BCTs are associated with intervention effectiveness.Trial registrationsN/A.

Project description:BackgroundPilot/feasibility studies play an important role in the development and refinement of behavioral interventions by providing information about feasibility, acceptability, and potential efficacy. Despite their importance and wide-spread use, the approaches taken by behavioral scientists to scale-up early-stage studies to larger-scale trials has received little attention. The aim of our study was to understand the role that pilot studies play in the development and execution of larger-scale trials.MethodsWe conducted interviews with childhood obesity researchers who had published pilot behavioral interventions and larger-scale trials of the same or similar interventions. Questions were asked about the role of pilot studies in developing larger-scale trials and the challenges encountered when scaling-up an intervention based upon pilot findings. Data were coded and analyzed using an inductive analytic approach to identify themes.ResultsTwenty-four interventionists (54% women, 37-70 years old, mean 20 years since terminal degree) completed a total of 148 pilot studies across their careers (mean 6.4, range 1-20), of which 59% were scaled-up. Scaling was described as resource intensive and pilot work was considered essential to successfully competing for funding by 63% of the sample (n = 15). When asked to define a high-quality pilot study, interventionists described studies that allowed them to evaluate two independent factors: components of their intervention (e.g., acceptability, feasibility) and study parameters (e.g., sample size, measures). Interventionists expressed that more process implementation measures, different study designs, and additional iterations could improve decisions to scale-up. Most agreed that pilot studies were likely to produce inflated estimates of potential efficacy though only nine interventionists provided potential solutions for decreasing inflated measures of efficacy. Suggested major causes of inflated effects included high levels of oversight in pilot studies (e.g., researcher support), reliance on subjective measures, and utilizing convenience or highly motivated samples. Potential solutions included designing pilots for real-world implementation, only conducting randomized controlled pilot studies, and pre-registering pilot studies.ConclusionsPilot studies purposes are multifaceted and deemed essential to obtaining funding for larger-scale trials. Clarifying the form and function of preliminary, early-stage research may enhance the productive utilization of early-stage studies and reduced drops in efficacy when transitioning to larger scale studies.

Project description:BackgroundIn the coming years, major governance changes in the form of policy directives and regulations will catalyse major top-down change with respect to animal health on European farms in an effort to combat the OneHealth threat of antimicrobial resistance. This top-down approach must be met with bottom-up strategies to ensure target actors (namely, farmers and vets) are supported and motivated to change their practices, thus, avoiding unintended consequences of forced change. Although much behavioural research has explored the factors influencing antimicrobial practices on farms, a gap exists translating these findings into evidence-based behaviour change interventions that can be put into practice. The current study aims to fill this gap. It provides insights into identifying, understanding, and changing the behaviours of farmers and veterinarians with respect to the responsible use of antimicrobials in farming.ResultsThrough an inter-disciplinary and multi-actor approach, the study combines scientific knowledge from the behavioural sciences and animal health sciences, coupled with tacit knowledge from a co-design, participatory approach to recommend seven behaviour change interventions that can help to support good practices amongst farmers and vets, with respect to animal health, and reduce the use of antimicrobials on farms. The behaviour change interventions include message framing; OneHealth awareness campaign; specialised communications training; on-farm visual prompts and tools; social support strategies (for both farmers and vets); and antimicrobial use monitoring. The study details each intervention with respect to their evidence base and scientific concept, grounded in behavioural science, along with stakeholder feedback on design and delivery of the interventions.ConclusionsThese behaviour change interventions can be taken, adapted, and put into practice by the agri-food community to support good animal health practices and responsible antimicrobial use on farms.

Project description:BackgroundBlinding is an established approach in clinical trials which aims to minimise the risk of performance and detection bias. There is little empirical evidence to guide UK clinical trials units (CTUs) about the practice of blinding statisticians. Guidelines recommend that statisticians remain blinded to allocation prior to the final analysis. As these guidelines are not based on empirical evidence, this study undertook a qualitative investigation relating to when and how statisticians should be blinded in clinical trials.MethodsData were collected through online focus groups with various stakeholders who work in the delivery and oversight of clinical trials. Recordings of the focus groups were transcribed verbatim and thematic analysis was used to analyse the transcripts.ResultsThirty-seven participants from 19 CTUs participated in one of six focus groups. Four main themes were identified, namely statistical models of work, factors affecting the decision to blind statisticians, benefits of blinding/not blinding statisticians and practicalities. Factors influencing the decision to blind the statistician included available resources, study design and types of intervention and outcomes and analysis. Although blinding of the statistician is perceived as a desirable mitigation against bias, there was uncertainty about the extent to which an unblinded statistician might impart bias. Instead, in most cases, the insight that the statistician offers was deemed more important to delivery of a trial than the risk of bias they may introduce if unblinded. Blinding of statisticians was only considered achievable with the appropriate resource and staffing, which were not always available. In many cases, a standard approach to blinding was therefore considered unrealistic and impractical; hence the need for a proportionate risk assessment approach identifying possible mitigations.ConclusionsThere was wide variation in practice between UK CTUs regarding the blinding of trial statisticians. A risk assessment approach would enable CTUs to identify risks associated with unblinded statisticians conducting the final analysis and alternative mitigation strategies. The findings of this study will be used to design guidance and a tool to support this risk assessment process.

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Recording harms in randomised controlled trials of behaviour change interventions: a qualitative study of UK clinical trials units and NIHR trial investigators

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