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Abstract

Background
Meeting global health challenges requires effective behaviour change interventions (BCIs). This depends on advancing the science of behaviour change which, in turn, depends on accurate intervention reporting. Current reporting often lacks detail, preventing accurate replication and implementation. Recent developments have specified intervention content into behaviour change techniques (BCTs) – the ‘active ingredients’, for example goal-setting, self-monitoring of behaviour. BCTs are ‘the smallest components compatible with retaining the postulated active ingredients, i.e. the proposed mechanisms of change. They can be used alone or in combination with other BCTs’ (Michie S, Johnston M. Theories and techniques of behaviour change: developing a cumulative science of behaviour change. Health Psychol Rev 2012;6:1–6). Domain-specific taxonomies of BCTs have been developed, for example healthy eating and physical activity, smoking cessation and alcohol consumption. We need to build on these to develop an internationally shared language for specifying and developing interventions. This technology can be used for synthesising evidence, implementing effective interventions and testing theory. It has enormous potential added value for science and global health.

Objective
(1) To develop a method of specifying content of BCIs in terms of component BCTs; (2) to lay a foundation for a comprehensive methodology applicable to different types of complex interventions; (3) to develop resources to support application of the taxonomy; and (4) to achieve multidisciplinary and international acceptance for future development.

Design and participants
Four hundred participants (systematic reviewers, researchers, practitioners, policy-makers) from 12 countries engaged in investigating, designing and/or delivering BCIs. Development of the taxonomy involved a Delphi procedure, an iterative process of revisions and consultation with 41 international experts; hierarchical structure of the list was developed using inductive ‘bottom-up’ and theory-driven ‘top-down’ open-sort procedures (n = 36); training in use of the taxonomy (1-day workshops and distance group tutorials) (n = 161) was evaluated by changes in intercoder reliability and validity (agreement with expert consensus); evaluating the taxonomy for coding interventions was assessed by reliability (intercoder; test–retest) and validity (n = 40 trained coders); and evaluating the taxonomy for writing descriptions was assessed by reliability (intercoder; test–retest) and by experimentally testing its value (n = 190).

Results
Ninety-three distinct, non-overlapping BCTs with clear labels and definitions formed Behaviour Change Technique Taxonomy version 1 (BCTTv1). BCTs clustered into 16 groupings using a ‘bottom-up’ open-sort procedure; there was overlap between these and groupings produced by a theory-driven, ‘top-down’ procedure. Both training methods improved validity (both p < 0.05), doubled the proportion of coders achieving competence and improved confidence in identifying BCTs in workshops (both p < 0.001) but did not improve intercoder reliability. Good intercoder reliability was observed for 80 of the 93 BCTs. Good within-coder agreement was observed after 1 month (p < 0.001). Validity was good for 14 of 15 BCTs in the descriptions. The usefulness of BCTTv1 to report descriptions of observed interventions had mixed results.

Conclusions
The developed taxonomy (BCTTv1) provides a methodology for identifying content of complex BCIs and a foundation for international cross-disciplinary collaboration for developing more effective interventions to improve health. Further work is needed to examine its usefulness for reporting interventions.

Funding
This project was funded by the Medical Research Council Ref: G0901474/1. Funding also came from the Peninsula Collaboration for Leadership in Applied Health Research and Care.

Publication Type:	Article
Subjects:	R Medicine > RA Public aspects of medicine
Departments:	School of Health & Psychological Sciences
SWORD Depositor:	Symplectic Administrator

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