Applying the BCT taxonomy to code sedentary behaviour reduction interventions: challenges and reflections

Abstract

Background: Several recent reviews have sought to describe interventions and potentially explain effectiveness by specifying component behaviour change techniques (BCTs) using recently established BCT taxonomies. We applied this method to deconstruct the content of interventions to reduce adult sedentary behaviour (low energy-expending waking behaviour while seated). Methods: Interventions were identified through systematic database searches, were and the presence or absence of discrete techniques within these specified using BCT Taxonomy v1. Interventions were categorised as ‘very promising’, ‘quite promising’, or ‘non-promising’ according to observed outcomes. BCTs were compared across promising/non-promising interventions. Results: Of thirty-eight interventions, fifteen (39%) were very promising, eight quite promising (21%), and fifteen non-promising (39%). Most promising interventions included the BCTs ‘self-monitoring,’ ‘problem solving,’ and ‘restructuring the social or physical environment’. Links between effectiveness and intervention components were qualified by poorly reported intervention descriptions, unclear differentiation between intervention and control groups, low-quality evaluation methods, and our coding of whether, rather than how, BCTs were used. Discussion: Applying the BCT taxonomy enables systematic identification of intervention components that may inform future intervention design. Yet, the utility and robustness of such findings is dependent on methodological and reporting quality. Additionally, coding for the mere presence or absence of BCTs may overlook variation attributable to dosage, and interactions between components. While intervention reports should more clearly specify content, reviewers may also benefit from adopting more granular approaches to identifying content, including optimal dose and combination of intervention components that are likely to be effective.