Background Many global health challenges may be targeted by changing people’s behaviour. Behaviours including cigarette smoking, physical inactivity and alcohol misuse, as well as certain dietary behaviours, contribute to deaths and disability by increasing the risk of cancers, cardiovascular diseases and diabetes. Interventions have been designed to change these health behaviours with a view to reducing these health risks. However, the effectiveness of these interventions has been quite variable and further information is needed to enhance their success. More information is needed about the specific processes that underlie the effectiveness of intervention strategies. Aim Researchers have developed a taxonomy of 93 behaviour change techniques (i.e. the active components of an intervention that bring about behavioural change), but little is known regarding their potential mechanisms of action (i.e. the processes through which a behaviour change technique affects behaviour). We therefore aimed to examine links between behaviour change techniques and mechanisms of action. Method First, we conducted a literature synthesis study of 277 behaviour change intervention studies, from which we extracted information on links, described by authors, between behaviour change techniques and mechanisms of action, and identified an average of 10 links per intervention report. Second, behaviour change experts (n = 105) were engaged in a three-round consensus study in which they discussed and rated their confidence in the presence/absence of ‘links’ and ‘non-links’ between commonly used behaviour change techniques (n = 61) and a set of mechanisms of action (n = 26). Ninety links and 460 ‘non-links’ reached the pre-set threshold of 80% agreement. To enhance the validity of these results, a third study was conducted that triangulated the findings of the first two studies. Discrepancies and uncertainties between the studies were included in a reconciliation consensus study with a new group of experts (n = 25). The final results identified 92 definite behaviour change technique–mechanism of action links and 465 definite non-links. In a fourth study, we examined whether or not groups of behaviour change techniques used together frequently across interventions revealed shared theoretical underpinnings. We found that experts agreed on the underlying theory for three groups of behaviour change techniques. Results Our results are potentially useful to policy-makers and practitioners in selecting behaviour change techniques to include in behaviour change interventions. However, our data do not demonstrate that the behaviour change techniques are effective in targeting the mechanism of action; rather, the links identified may be the ‘best bets’ for interventions that are effective in changing mechanisms of action, and the non-links are unlikely to be effective. Researchers examining effectiveness of interventions in either primary studies or evidence syntheses may consider these links for further investigation. Conclusion To make our results usable by researchers, practitioners and policy-makers, they are available in an online interactive tool, which enables discussion and collaboration (https://theoryandtechniquetool.humanbehaviourchange.org/); accessed 1 March 2020. This work, building on previous work to develop the behaviour change technique taxonomy, is part of an ongoing programme of work: the Human Behaviour Change Project (www.humanbehaviourchange.org/; accessed 1 March 2020). Funding This project was funded by the Medical Research Council via its Methodology Panel: ‘Developing methodology for designing and evaluating theory-based complex interventions: an ontology for linking behaviour change techniques to theory’ (reference MR/L011115/1).

Background: To efficiently search, compare, test and integrate behaviour change theories, they need to be specified in a way that is clear, consistent and computable. An ontology-based modelling system (OBMS) has previously been shown to be able to represent five commonly used theories in this way. We aimed to assess whether the OBMS could be applied more widely and to create a database of behaviour change theories, their constructs and propositions. Methods: We labelled the constructs within 71 theories and used the OBMS to represent the relationships between the constructs. Diagrams of each theory were sent to authors or experts for feedback and amendment. The 71 finalised diagrams plus the five previously generated diagrams were used to create a searchable database of 76 theories in the form of construct-relationship-construct triples. We conducted a set of illustrative analyses to characterise theories in the database. Results: All 71 theories could be satisfactorily represented using this system. In total, 35 (49%) were finalised with no or very minor amendment. The remaining 36 (51%) were finalised after changes to the constructs (seven theories), relationships between constructs (15 theories) or both (14 theories) following author/expert feedback. The mean number of constructs per theory was 20 (min. = 6, max. = 72), with the mean number of triples per theory 31 (min. = 7, max. = 89). Fourteen distinct relationship types were used, of which the most commonly used was ‘influences’, followed by ‘part of’. Conclusions: The OBMS can represent a wide array of behavioural theories in a precise, computable format. This system should provide a basis for better integration and synthesis of theories than has hitherto been possible.

Background: Overuse of antibiotics has contributed to antimicrobial resistance; a growing public health threat. In long-term care facilities, levels of inappropriate prescribing are as high as 75%. Numerous interventions targeting long-term care facilities' antimicrobial stewardship have been reported with varying, and largely unexplained, effects. Therefore, this review aimed to apply behavioural science frameworks to specify the component behaviour change techniques of stewardship interventions in long-term care facilities and identify those components associated with improved outcomes. Method: A systematic review (CRD42018103803) was conducted through electronic database searches. Two behavioural science frameworks, the Behaviour Change Wheel and Behaviour Change Technique Taxonomy were used to classify intervention descriptions into intervention types and component behaviour change techniques used. Study design and outcome heterogeneity prevented meta-analysis and meta-regression. Interventions were categorised as 'very promising' (all outcomes statistically significant), 'quite promising' (some outcomes statistically significant), or 'not promising' (no outcomes statistically significant). 'Promise ratios' (PR) were calculated for identified intervention types and behaviour change techniques by dividing the number of (very or quite) promising interventions featuring the intervention type or behaviour change technique by the number of interventions featuring the intervention type or behaviour change technique that were not promising. Promising intervention types and behaviour change techniques were defined as those with a PR ≥ 2. Results: Twenty studies (of19 interventions) were included. Seven interventions (37%) were 'very promising', eight 'quite promising' (42%) and four 'not promising' (21%). Most promising intervention types were 'persuasion' (n = 12; promise ratio (PR) = 5.0), 'enablement' (n = 16; PR = 4.33) and 'education' (n = 19; PR = 3.75). Most promising behaviour change techniques were 'feedback on behaviour' (n = 9; PR = 8.0) and 'restructuring the social environment' (e.g. staff role changes; n = 8; PR = 7.0).