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Published on: January 28, 2014
Using the behaviour change wheel approach to optimize self-sampling packs for sexually transmitted infection and
Paul Flowers1, Gabriele Vojt2, Maria Pothoulaki2
1School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK.
Purpose:
This paper describes the process of optimizing a widely offered intervention-self-sampling packs for sexually transmitted infections (STIs) and blood borne viruses (BBVs). We drew upon the behaviour change wheel (BCW) approach, incorporating the theoretical domains framework (TDF) and the behaviour change technique taxonomy (BCTTv1) to systematically specify potential intervention components that may optimize the packs.
Methods:
A BCW analysis built upon prior thematic analyses of qualitative data collected through focus groups and interviews with members of the public and people recruited from sexual health clinics in Glasgow and London (n = 56). Salient barriers and facilitators to specific sequential behavioural domains associated with the wider behavioural system of pack use were subjected to further analyses, coding them in relation to the TDF, the BCW's intervention functions, and finally specifying potential optimisation using behaviour change techniques (BCTs).
Results:
Our TDF analysis suggested that across the overall behavioural system of pack use, the most important theoretical domains were 'beliefs about consequences' and 'memory, attention and decision-making'. BCW analysis on the overall pack suggested useful intervention functions should focus on 'environmental restructuring', 'persuasion', 'enablement', 'education' and 'modelling'. Specific ways of optimizing the intervention were also described in relation to potentially useful BCTs.
Conclusions:
Through a detailed behavioural analysis and the TDF and wider BCW approach built on earlier qualitative work, we provide a systematic approach to optimizing an existing intervention. The approach enabled the specification of highly specific, evidence-based, and theoretically informed recommendations for intervention optimization.
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