From lists of behaviour change techniques ( BCT s) to structured hierarchies: Comparison of two methods of developing a hierarchy of BCT s

OBJECTIVES: Behaviour change technique (BCT) Taxonomy v1 is a hierarchically grouped, consensus-based taxonomy of 93 BCTs for reporting intervention content. To enhance the use and understanding of BCTs, the aims of the present study were to (1) quantitatively examine the 'bottom-up' hierarchical structure of Taxonomy v1, (2) identify whether BCTs can be reliably mapped to theoretical domains using a 'top-down' theoretically driven approach, and (3) identify any overlap between the 'bottom-up' and 'top-down' groupings. METHODS AND DESIGN: The 'bottom-up' structure was examined for higher-order groupings using a dendrogram derived from hierarchical cluster analysis. For the theory-based 'top-down' structure, 18 experts sorted BCTs into 14 theoretical domains. Discriminant Content Validity was used to identify groupings, and chi-square tests and Pearson's residuals were used to examine the overlap between groupings. RESULTS: Behaviour change techniques relating to 'Reward and Punishment' and 'Cues and Cue Responses' were perceived as markedly different to other BCTs. Fifty-nine of the BCTs were reliably allocated to 12 of the 14 theoretical domains; 47 were significant and 12 were of borderline significance. Thirty-four of 208 'bottom-up' × 'top-down' pairings showed greater overlap than expected by chance. However, only six combinations achieved satisfactory evidence of similarity. CONCLUSIONS: The moderate overlap between the groupings indicates some tendency to implicitly conceptualize BCTs in terms of the same theoretical domains. Understanding the nature of the overlap will aid the conceptualization of BCTs in terms of theory and application. Further research into different methods of developing a hierarchical taxonomic structure of BCTs for international, interdisciplinary work is now required. Statement of contribution What is already known on this subject? Behaviour change interventions are effective in improving health care and health outcomes. The 'active' components of these interventions are behaviour change techniques and over 93 have been identified. Taxonomies of behaviour change techniques require structure to enable potential applications. What does this study add? This study identifies groups of BCTs to aid the recall of BCTs for intervention coding and design. It compares two methods of grouping--'bottom-up' and theory-based 'top-down'--and finds a moderate overlap. Building on identified BCT groups, it examines relationships between theoretical domains and BCTs.