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Researchers, practitioners, and policymakers develop interventions to change behavior based on their understanding of how behavior change techniques (BCTs) impact the determinants of behavior. A transparent, systematic, and accessible method of linking BCTs with the processes through which they change behavior (i.e., their mechanisms of action [MoAs]) would advance the understanding of intervention effects and improve theory and intervention development. The purpose of this study is to triangulate evidence for hypothesized BCT-MoA links obtained in two previous studies and present the results in an interactive, online tool. Two previous studies generated evidence on links between 56 BCTs and 26 MoAs based on their frequency in literature synthesis and on expert consensus. Concordance between the findings of the two studies was examined using multilevel modeling. Uncertainties and differences between the two studies were reconciled by 16 behavior change experts using consensus development methods. The resulting evidence was used to generate an online tool. The two studies showed concordance for 25 of the 26 MoAs and agreement for 37 links and for 460 "nonlinks." A further 55 links were resolved by consensus (total of 92 [37 + 55] hypothesized BCT-MoA links). Full data on 1,456 possible links was incorporated into the online interactive Theory and Technique Tool (https://theoryandtechniquetool.humanbehaviourchange.org/). This triangulation of two distinct sources of evidence provides guidance on how BCTs may affect the mechanisms that change behavior and is available as a resource for behavior change intervention designers, researchers and theorists, supporting intervention design, research synthesis, and collaborative research., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Purpose: Behaviour change techniques are fundamental to the development of any behaviour change intervention, but surprisingly little is known about their properties. Key questions include when, why, how, in which contexts, for which behaviours, in what combinations, compared with what, and for whom behaviour change techniques are typically effective. The aims of the present paper are to: (1) articulate the scope of the challenge in understanding the properties of behaviour change techniques, (2) propose means by which to tackle this problem, and (3) call scientists to action., Methods: Iterative consensus (O'Connor et al., 2020, Br. J. Psychol., e12468) was used to elicit and distil the judgements of experts on how best to tackle the problem of understanding the nature and operation of behaviour change techniques., Results: We propose a worldwide network of 'Centres for Understanding Behaviour Change' (CUBiC) simultaneously undertaking research to establish what are the single and combined properties of behaviour change techniques across multiple behaviours and populations. We additionally provide a first attempt to systematize an approach that CUBiC could use to understand behaviour change techniques and to begin to harness the efforts of researchers worldwide., Conclusion: Better understanding of behaviour change techniques is vital for improving behaviour change interventions to tackle global problems such as obesity and recovery from COVID-19. The CUBiC proposal is just one of many possible solutions to the problems that the world faces and is a call to action for scientists to work collaboratively to gain deeper understanding of the underpinnings of behaviour change interventions., (© 2020 The Authors. British Journal of Health Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Aims: To estimate the strengths of associations between use of behaviour change techniques (BCTs) and clusters of BCTs in behavioural smoking cessation interventions and comparators with smoking cessation rates., Method: Systematic review and meta-regression of biochemically verified smoking cessation rates on BCTs in interventions and comparators in randomized controlled trials, adjusting for a priori-defined potential confounding variables, together with moderation analyses. Studies were drawn from the Cochrane Tobacco Addiction Group Specialised Register. Data were extracted from published and unpublished (i.e. obtained from study authors) study materials by two independent coders. Adequately described intervention (k = 143) and comparator (k = 92) groups were included in the analyses (n = 43 992 participants). Using bivariate mixed-effects meta-regressions, while controlling for key a priori confounders, we regressed smoking cessation on (a) three BCT groupings consistent with dual-process theory (i.e. associative, reflective motivational and self-regulatory), (b) 17 expert-derived BCT groupings (i.e. BCT taxonomy version 1 clusters) and (c) individual BCTs from the BCT taxonomy version 1., Results: Among person-delivered interventions, higher smoking cessation rates were predicted by BCTs targeting associative and self-regulatory processes (B = 0.034, 0.041, P < 0.05), and by three individual BCTs (prompting commitment, social reward, identity associated with changed behaviour). Among written interventions, BCTs targeting taxonomy cluster 10a (rewards) predicted higher smoking cessation (B = 0.394, P < 0.05). Moderation effects were observed for nicotine dependence, mental health status and mode of delivery., Conclusions: Among person-delivered behavioural smoking cessation interventions, specific behaviour change techniques and clusters of techniques are associated with higher success rates., (© 2020 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Background: Behavioral interventions typically include multiple behavior change techniques (BCTs). The theory informing the selection of BCTs for an intervention may be stated explicitly or remain unreported, thus impeding the identification of links between theory and behavior change outcomes., Purpose: This study aimed to identify groups of BCTs commonly occurring together in behavior change interventions and examine whether behavior change theories underlying these groups could be identified., Methods: The study involved three phases: (a) a factor analysis to identify groups of co-occurring BCTs from 277 behavior change intervention reports; (b) examining expert consensus (n = 25) about links between BCT groups and behavioral theories; (c) a comparison of the expert-linked theories with theories explicitly mentioned by authors of the 277 intervention reports., Results: Five groups of co-occurring BCTs (range: 3-13 BCTs per group) were identified through factor analysis. Experts agreed on five links (≥80% of experts), comprising three BCT groups and five behavior change theories. Four of the five BCT group-theory links agreed by experts were also stated by study authors in intervention reports using similar groups of BCTs., Conclusions: It is possible to identify groups of BCTs frequently used together in interventions. Experts made shared inferences about behavior change theory underlying these BCT groups, suggesting that it may be possible to propose a theoretical basis for interventions where authors do not explicitly put forward a theory. These results advance our understanding of theory use in multicomponent interventions and build the evidence base for further understanding theory-based intervention development and evaluation., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Objective: Over 90 behaviour change techniques (BCTs) have been specified but there is limited guidance to assist non-specialist practitioners in the choice of which BCTs to select for use with clients. This paper describes the development of MAP, a theory-based mnemonic designed to aid practitioners in their use of BCTs. Each BCT is MAPed to one or more of three recognized routes to behaviour change, namely Motivation development, Action control, and Prompted or cued route., Design: A cross-sectional online discriminant content validity (DCV) questionnaire., Methods: Fourteen judges participated, decided whether each BCT affects behaviour via each of the three routes, and provided a confidence rating for each judgement. Wilcoxon one-sample tests classified each BCT to a route or combination of routes. Intraclass correlation coefficients (ICC) assessed agreement between judges., Results: Fifty-eight BCTs were judged to affect behaviour via a single route; 28, 21, and nine BCTs were judged to act via the Motivation, Action, or Prompted routes, respectively. Judges did not agree on a route for 35 BCTs. Overall ICC (0.89) value was high and did not differ between routes., Conclusions: There was good agreement on candidate BCTs for interventions designed to operate through Motivation, Action, or Prompted/Cued psychological processes. MAP is a mnemonic that can be used by non-specialist practitioners who implement behaviour change with their clients. MAP is not a replacement for sophisticated theory-based organization of BCTs required for theory testing. While providing practical guidance, further work is necessary to establish effectiveness of BCTs tailored to each route., (© 2020 The British Psychological Society.)

Objectives: The aim of this study was to identify which behaviour change techniques (BCTs) were present in intervention and control groups of randomised controlled trials (RCTs) included in a Cochrane systematic review., Setting: The RCTs included were conducted in community, primary and/or ambulatory-care settings., Participants: The data set was derived from 86 RCTs from an interim update of the Cochrane review of the effectiveness of pharmacist services on non-hospitalised patient outcomes., Primary and Secondary Outcome Measures: The primary outcome was the identification of BCTs scheduled for delivery in intervention and control groups of the RCTs. The secondary outcome measure was to identify which BCTs are not being utilised in intervention and control groups of the RCTs., Results: The intervention and control groups included 31 and 12 BCTs, respectively. The number of identifiable BCTs/study ranged from 0 to 12 in the intervention groups (mean 3.01 (SD 2.4)) and 0 to 6 in the control groups (mean 0.38 (SD 0.84)). The most commonly identified BCTs in the intervention groups were: instruction on how to perform the behaviour (55%, n=47) (also the most common BCT in control groups); problem solving (29%, n=25); information about health consequences (24%, n=21); social support (practical) (24%, n=21); and social support (unspecified) (23%, n=20) (the second most common BCT in control groups). Thirteen trials had no identifiable BCTs in either group., Conclusion: The pharmacist interventions presented in this study did not use the full range of available BCTs. Furthermore, the reporting of BCTs was incomplete for both intervention and control groups, thereby limiting the utility and reproducibility of the interventions. Future interventions should be designed and reported using relevant taxonomies and checklists for example, BCT taxonomy and TIDieR (the template for intervention description and replication)., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Despite advances in behavioral science, there is no widely shared understanding of the "mechanisms of action" (MoAs) through which individual behavior change techniques (BCTs) have their effects. Cumulative progress in the development, evaluation, and synthesis of behavioral interventions could be improved by identifying the MoAs through which BCTs are believed to bring about change., Purpose: This study aimed to identify the links between BCTs and MoAs described by authors of a corpus of published literature., Methods: Hypothesized links between BCTs and MoAs were extracted by two coders from 277 behavior change intervention articles. Binomial tests were conducted to provide an indication of the relative frequency of each link., Results: Of 77 BCTs coded, 70 were linked to at least one MoA. Of 26 MoAs, all but one were linked to at least one BCT. We identified 2,636 BCT-MoA links in total (mean number of links per article = 9.56, SD = 13.80). The most frequently linked MoAs were "Beliefs about Capabilities" and "Intention." Binomial test results identified up to five MoAs linked to each of the BCTs (M = 1.71, range: 1-5) and up to eight BCTs for each of the MoAs (M = 3.63, range: 1-8)., Conclusions: The BCT-MoA links described by intervention authors and identified in this extensive review present intervention developers and reviewers with a first level of systematically collated evidence. These findings provide a resource for the development of theory-based interventions, and for theoretical understanding of intervention evaluations. The extent to which these links are empirically supported requires systematic investigation., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Background: Understanding the mechanisms through which behavior change techniques (BCTs) can modify behavior is important for the development and evaluation of effective behavioral interventions. To advance the field, we require a shared knowledge of the mechanisms of action (MoAs) through which BCTs may operate when influencing behavior., Purpose: To elicit expert consensus on links between BCTs and MoAs., Methods: In a modified Nominal Group Technique study, 105 international behavior change experts rated, discussed, and rerated links between 61 frequently used BCTs and 26 MoAs. The criterion for consensus was that at least 80 per cent of experts reached agreement about a link. Heat maps were used to present the data relating to all possible links., Results: Of 1,586 possible links (61 BCTs × 26 MoAs), 51 of 61 (83.6 per cent) BCTs had a definite link to one or more MoAs (mean [SD] = 1.44 [0.96], range = 1-4), and 20 of 26 (76.9 per cent) MoAs had a definite link to one or more BCTs (mean [SD] = 3.27 [2.91], range = 9). Ninety (5.7 per cent) were identified as "definite" links, 464 (29.2 per cent) as "definitely not" links, and 1,032 (65.1 per cent) as "possible" or "unsure" links. No "definite" links were identified for 10 BCTs (e.g., "Action Planning" and "Behavioural Substitution") and for six MoAs (e.g., "Needs" and "Optimism")., Conclusions: The matrix of links between BCTs and MoAs provides a basis for those developing and synthesizing behavioral interventions. These links also provide a framework for specifying empirical tests in future studies., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Background: The behavior change technique (BCT) taxonomy v1 is often used in systematic reviews for identifying active components of interventions. Its utility could be enhanced by linking BCTs to specific target behaviors and qualifying BCT delivery style., Purpose: To determine whether behavioral targets and delivery styles of BCTs can be coded reliably and to determine the utility of coding these characteristics., Methods: As part of a large systematic review of 142 smoking cessation trials, two researchers independently coded publicly and privately held intervention and comparator group materials, specifying the behavioral target (quitting, abstinence, medication adherence, or treatment engagement) and delivery style (tailored vs. not tailored; active participation vs. passive receipt) of each BCT., Results: Researchers coded 3,843 BCTs, which were reliably attributed to behavioral targets (AC1 = 0.92, PABAK = 0.91). Tailoring (AC1 = 0.80, PABAK = 0.74) and participation (AC1 = 0.71, PABAK = 0.64) were also coded reliably. There was considerable variability between groups in quitting and abstinence BCTs (ranges: 0-41; 0-18) and in tailoring and participation (ranges: 0-20; 0-32), but less variability for medication adherence and treatment engagement (ranges: 0-6; 0-7)., Conclusions: Behavioral targets and delivery styles of BCTs can be reliably identified and occur with sufficient frequency in smoking cessation trials for inclusion in quantitative syntheses (e.g., meta-regression analyses). Systematic reviewers could consider adopting these methods to evaluate the impact of intervention components targeting different behaviors, as well as the benefits of different BCT delivery styles., (© Society of Behavioral Medicine 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: Healthy eating, physical activity and smoking interventions for low-income groups may have small, positive effects. Identifying effective intervention components could guide intervention development. This study investigated which content and delivery components of interventions were associated with increased healthy behavior in randomised controlled trials (RCTs) for low-income adults., Method: Data from a review showing intervention effects in 35 RCTs containing 45 interventions with 17,000 participants were analysed to assess associations with behavior change techniques (BCTs) and delivery/context components from the template for intervention description and replication (TIDieR) checklist. The associations of 46 BCTs and 14 delivery/context components with behavior change (measures of healthy eating, physical activity and smoking cessation) were examined using random effects subgroup meta-analyses. Synergistic effects of components were examined using classification and regression trees (meta-CART) analyses based on both fixed and random effects assumptions., Results: For healthy eating, self-monitoring, delivery through personal contact, and targeting multiple behaviors were associated with increased effectiveness. Providing feedback, information about emotional consequences, or using prompts and cues were associated with reduced effectiveness. In synergistic analyses, interventions were most effective without feedback, or with self-monitoring excluding feedback. More effective physical activity interventions included behavioral practice/rehearsal or instruction, focussed solely on physical activity or took place in home/community settings. Information about antecedents was associated with reduced effectiveness. In synergistic analyses, interventions were most effective in home/community settings with instruction. No associations were identified for smoking., Conclusion: This study identified BCTs and delivery/context components, individually and synergistically, linked to increased and reduced effectiveness of healthy eating and physical activity interventions. The identified components should be subject to further experimental study to help inform the development effective behavior change interventions for low-income groups to reduce health inequalities.

Competing Interests: Competing Interests Susan Michie (Principal Investigator), Marie Johnston (Co-Investigator), and Rachel N. Carey are members of the Human Behaviour-Change Project. Karina W. Davidson (Co-Principal Investigator), Donald Edmondson (Co-Principal Investigator), and Jennifer A. Sumner (Co-Investigator) are members of the Resource and Coordinating Center for the Science of Behavior Change Research Network.

Objective: Communication of the content of a behaviour change intervention (BCI) involves clear description followed by appropriate recognition and interpretation. We investigated accuracy of recognition of BCI descriptions and the effects of training in the behaviour change taxonomy BCTTv1., Methods: Materials were 166 written descriptions of two BCIs previously written by 166 separate writers after viewing a video of the BCI. Each of the current participants (12 naïve and 12 trained in BCTTv1) was presented with a random sample of the written descriptions and asked to form groups of descriptions they judged to be describing the same intervention. For each participant, we assessed the number of groupings of BCI descriptions, their purity (containing only one BCI) and their differentiation (having a dominant BCI)., Results: All except one participant classified the descriptions into more than two groupings. Naïve participants created significantly more groupings, fewer 'pure' groupings and less differentiated groupings (all Mann-Whitney p < .05)., Conclusions: Written communications of BCI contents may not be recognised and interpreted adequately to support implementation. BCT taxonomy training may lead to some progress in interpreting the active content of interventions but, based on this limited study, further progress is needed if BCIs for accurate implementation.

Background: Behaviour change interventions are likely to be reproducible only if reported clearly. We assessed whether the behaviour change technique taxonomy version 1 (BCTTv1), with and without training in identifying BCTs, improves the clarity and replicability of written reports of observed behaviour change interventions., Methods: Three studies assessed effects of using and training in the use of BCTTv1 on the clarity and replicability of intervention descriptions written after observing videos of smoking cessation interventions. Study 1 examined the effects of using and not using BCTTv1. Study 2 examined the effects of using BCTTv1 and training in use of BCTTv1 compared no use and no training. Study 3 employed a within-group design to assess change in descriptions written before and after training. One-hundred and 66 'writers' watched videos of behaviour change interventions and wrote descriptions of the active components delivered. In all studies, the participants' written descriptions were evaluated by (i) 12 'raters' (untrained in BCTTv1) for clarity and replicability and (ii) 12 'coders' (trained in BCTTv1) for reliability of BCT coding. Writers rated the usability and accessibility of using BCTTv1 to write descriptions., Results: Ratings of clarity and replicability did not differ between groups in study 1 (all ps > 0.05), were poorer for trained users in study 2 (all ps < 0.01) and improved following training in study 3 (all ps < 0.05). BCT identification was more reliable from descriptions written by trained BCTTv1 users (p < 0.05; study 2) but not simple use of BCTTv1 (p = 0.93; study 1) or by writers who had written a description without BCTTv1, before training (p = 0.50; study 3). Writers reported that using BCTTv1 was difficult but 'useful', 'good' and 'desirable' and that their descriptions would be clear and replicable (all means above mid-point of the scale)., Conclusions: Effects of training to use BCTTv1 on the quality of written reports of observed interventions were mixed, with some suggestion of improved clarity and replicability of reporting in the within- (study 3) but not the between-group studies (studies 1 and 2). Potential benefits of using BCTTv1 may have been limited by the artificial nature and time constraints of the task.

Background: Systematic reviews of behaviour change interventions for smoking cessation vary in scope, quality, and applicability. The current review aims to generate more accurate and useful findings by (1) a detailed analysis of intervention elements that change behaviour (i.e. behaviour change techniques (BCTs)) and potential moderators of behaviour change (i.e. other intervention and sample characteristics) and (2) assessing and controlling for variability in support provided to comparison groups in smoking cessation trials., Methods: A systematic review will be conducted of randomized controlled trials of behaviour change interventions for smoking cessation in adults (with or without pharmacological support), with a minimum follow-up of 6 months, published after 1995. Eligible articles will be identified through the Cochrane Tobacco Addiction Group Specialized Register. Study authors will be asked for detailed descriptions of smoking cessation support provided to intervention and comparison groups. All data will be independently coded by two researchers. The BCT taxonomy v1 (tailored to smoking cessation interventions) and template for intervention description and replication criteria will be used to code intervention characteristics. Data collection will further include sample and trial characteristics and outcome data (smoking cessation rates). Multilevel mixed-effects meta-regression models will be used to examine which BCTs and/or BCT clusters delivered to intervention and comparison groups explain smoking cessation rates in treatment arms (and effect sizes) and what key moderators of behaviour change are. Predicted effect sizes of each intervention will be computed assuming all interventions are compared against comparison groups receiving the same levels of behavioural support (i.e. low, medium, and high levels). Multi-disciplinary advisory board members (policymakers, health care providers, and (ex-)smokers) will provide strategic input throughout the project to ensure the review's applicability to policy and practice., Discussion: By capturing BCTs in intervention and comparison groups, this systematic review will provide more accurate estimates of the effectiveness of smoking cessation interventions, the most promising BCTs and/or BCT clusters associated with smoking cessation rates in intervention and comparison arms, and important moderators of behaviour change. The results could set new standards for conducting meta-analyses of behaviour change interventions and improve research, service delivery, and training in the area of smoking cessation., Systematic Review Registration: PROSPERO CRD42015025251.

Purpose: The aim of this paper is to assess the frequency of identification as well as the inter-coder and test-retest reliability of identification of behavior change techniques (BCTs) in written intervention descriptions., Methods: Forty trained coders applied the "Behavior Change Technique Taxonomy version 1" (BCTTv1) to 40 intervention descriptions published in protocols and repeated this 1 month later., Results: Eighty of 93 defined BCTs were identified by at least one trained coder, and 22 BCTs were identified in 16 (40 %) or more of 40 descriptions. Good inter-coder reliability was observed across 80 BCTs identified in the protocols: 66 (80 %) achieved mean prevalence and bias-adjusted kappa (PABAK) scores of 0.70 or greater, and 59 (74 %) achieved mean scores of 0.80 or greater. There was good within-coder agreement between baseline and 1 month, demonstrating good test-retest reliability., Conclusions: BCTTv1 can be used by trained coders to identify BCTs in intervention descriptions reliably. However, some frequently occurring BCT definitions require further clarification.

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.

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., (© 2014 The British Psychological Society.)

Background: CONSORT guidelines call for precise reporting of behavior change interventions: we need rigorous methods of characterizing active content of interventions with precision and specificity., Objectives: The objective of this study is to develop an extensive, consensually agreed hierarchically structured taxonomy of techniques [behavior change techniques (BCTs)] used in behavior change interventions., Methods: In a Delphi-type exercise, 14 experts rated labels and definitions of 124 BCTs from six published classification systems. Another 18 experts grouped BCTs according to similarity of active ingredients in an open-sort task. Inter-rater agreement amongst six researchers coding 85 intervention descriptions by BCTs was assessed., Results: This resulted in 93 BCTs clustered into 16 groups. Of the 26 BCTs occurring at least five times, 23 had adjusted kappas of 0.60 or above., Conclusions: "BCT taxonomy v1," an extensive taxonomy of 93 consensually agreed, distinct BCTs, offers a step change as a method for specifying interventions, but we anticipate further development and evaluation based on international, interdisciplinary consensus.

Objective: To test and optimize the feasibility and acceptability of a physical activity (PA) and healthy eating behavior change intervention for obese adults with obesity-related co-morbidities or additional risk factors for co-morbidities., Methods: Open-pilot intervention study using an uncontrolled pre and post design with ongoing measures on intervention acceptability and feasibility. Participants received 5 weekly nurse-led one-hour long group sessions. Acceptability and feasibility were assessed throughout. PA, dietary behavior and weight were measured before and after the intervention., Results: Of 74 consenting participants, 61 (82%) received and 47 (64%) completed the intervention. Average ratings of intervention materials and components by participants ranged between 4.1 and 4.9 out of 5. Average facilitator satisfaction rating was 90% (range 75-100%). The intervention delivery was feasible as indicated by ratings and comments from participants and the facilitator. Participants lost -0.86 kg of weight t(45)=3.84, p=0.0001, and increased PA by an additional 1.6 (SD=2.7) sessions/week, t(31)=-3.3, p=0.002. No significant dietary differences emerged., Conclusion: The intervention was acceptable to the facilitator and participants and feasible for delivery. Several intervention aspects were further optimized., Practice Implications: The current study outlines a PA and dietary behavior change pilot intervention coupled with a systematic and transparent process of intervention optimization., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

Background: Many theories of behaviour are potentially relevant to predictive and intervention studies but most studies investigate a narrow range of theories. Michie et al. (2005) agreed 12 'theoretical domains' from 33 theories that explain behaviour change. They developed a 'Theoretical Domains Interview' (TDI) for identifying relevant domains for specific clinical behaviours, but the framework has not been used for selecting theories for predictive studies. It was used here to investigate clinicians' transfusion behaviour in intensive care units (ICU). Evidence suggests that red blood cells transfusion could be reduced for some patients without reducing quality of care., Objectives: (1) To identify the domains relevant to transfusion practice in ICUs and neonatal intensive care units (NICUs), using the TDI. (2) To use the identified domains to select appropriate theories for a study predicting transfusion behaviour., Methods: An adapted TDI about managing a patient with borderline haemoglobin by watching and waiting instead of transfusing red blood cells was used to conduct semi-structured, one-to-one interviews with 18 intensive care consultants and neonatologists across the UK., Results: Relevant theoretical domains were: knowledge, beliefs about capabilities, beliefs about consequences, social influences, behavioural regulation. Further analysis at the construct level resulted in selection of seven theoretical approaches relevant to this context: Knowledge-Attitude-Behaviour Model, Theory of Planned Behaviour, Social Cognitive Theory, Operant Learning Theory, Control Theory, Normative Model of Work Team Effectiveness and Action Planning Approaches., Conclusions: This study illustrated, the use of the TDI to identify relevant domains in a complex area of inpatient care. This approach is potentially valuable for selecting theories relevant to predictive studies and resulted in greater breadth of potential explanations than would be achieved if a single theoretical model had been adopted.

Background: The development and description of interventions to change professional practice are often limited by the lack of an explicit theoretical and empirical basis. We set out to develop an intervention to promote appropriate disclosure of a diagnosis of dementia based on theoretical and empirical work., Methods: We identified three key disclosure behaviours: finding out what the patient already knows or suspects about their diagnosis; using the actual words 'dementia' or 'Alzheimer's disease' when talking to the patient; and exploring what the diagnosis means to the patient. We conducted a questionnaire survey of older peoples' mental health teams (MHTs) based upon theoretical constructs from the Theory of Planned Behaviour (TPB) and Social Cognitive Theory (SCT) and used the findings to identify factors that predicted mental health professionals' intentions to perform each behaviour. We selected behaviour change techniques likely to alter these factors., Results: The change techniques selected were: persuasive communication to target subjective norm; behavioural modelling and graded tasks to target self-efficacy; persuasive communication to target attitude towards the use of explicit terminology when talking to the patient; and behavioural modelling by MHTs to target perceived behavioural control for finding out what the patient already knows or suspects and exploring what the diagnosis means to the patient. We operationalised these behaviour change techniques using an interactive 'pen and paper' intervention designed to increase intentions to perform the three target behaviours., Conclusion: It is feasible to develop an intervention to change professional behaviour based upon theoretical models, empirical data and evidence based behaviour change techniques. The next step is to evaluate the effect of such an intervention on behavioural intention. We argue that this approach to development and reporting of interventions will contribute to the science of implementation by providing replicable interventions that illuminate the principles and processes underlying change.

Background and aims: Behavioural smoking cessation trials have used comparators that vary considerably between trials. Although some previous meta‐analyses made attempts to account for variability in comparators, these relied on subsets of trials and incomplete data on comparators. This study aimed to estimate the relative effectiveness of (individual) smoking cessation interventions while accounting for variability in comparators using comprehensive data on experimental and comparator interventions. Methods: A systematic review and meta‐regression was conducted including 172 randomised controlled trials with at least 6 months follow‐up and biochemically verified smoking cessation. Authors were contacted to obtain unpublished information. This information was coded in terms of active content and attributes of the study population and methods. Meta‐regression was used to create a model predicting smoking cessation outcomes. This model was used to re‐estimate intervention effects, as if all interventions have been evaluated against the same comparators. Outcome measures included log odds of smoking cessation for the meta‐regression models and smoking cessation differences and ratios to compare relative effectiveness. Results: The meta‐regression model predicted smoking cessation rates well (pseudo R2 = 0.44). Standardising the comparator had substantial impact on conclusions regarding the (relative) effectiveness of trials and types of intervention. Compared with a 'no support comparator', self‐help was 1.33 times (95% CI = 1.16–1.49), brief physician advice 1.61 times (95% CI = 1.31–1.90), nurse individual counselling 1.76 times (95% CI = 1.62–1.90), psychologist individual counselling 2.04 times (95% CI = 1.95–2.15) and group psychologist interventions 2.06 times (95% CI = 1.92–2.20) more effective. Notably, more elaborate experimental interventions (e.g. psychologist counselling) were typically compared with more elaborate comparators, masking their effectiveness. Conclusions: Comparator variability and underreporting of comparators obscures the interpretation, comparison and generalisability of behavioural smoking cessation trials. Comparator variability should, therefore, be taken into account when interpreting and synthesising evidence from trials. Otherwise, policymakers, practitioners and researchers may draw incorrect conclusions about the (cost) effectiveness of smoking cessation interventions and their constituent components. [ABSTRACT FROM AUTHOR]

Background: To investigate the effect of in-person delivered behavioural interventions in people with multimorbidity and which behaviour change techniques (BCTs), targeting lifestyle behaviours, are associated with better outcomes. Methods: Systematic review of randomised controlled trials. We searched MEDLINE, EMBASE, CENTRAL, and CINAHL and screened reference list of reviews including people with multimorbidity, registries, and citation tracking of included studies. Meta-analyses using random-effects model to assess the effect of behavioural interventions and meta-regression analyses and effectiveness ratios to investigate the impact of mediators on effect estimates. Cochrane 'Risk of Bias Tool' 2.0 and the GRADE assessment to evaluate the overall quality of evidence. Results: Fourteen studies involving 1,378 people. Behavioural interventions had little to no effect on physical activity (standardised mean difference 0.38, 95% CI −0.12–0.87) and the effect on weight loss was uncertain (BMI mean difference −0.17, 95% CI −1.1–0.83) at the end-treatment follow-up. Small improvements were seen in health-related quality of life (SMD 0.29, 95% CI 0.17–0.42) and physical function (SMD 0.42, 95% CI 0.12–0.73), and moderate improvements were seen for depression symptoms (SMD −0.70, 95% CI −0.97–0.42). Studies using the BCTs 'action planning' and 'social support (practical)' reported greater physical activity and weight loss. Conclusions: Behavioural interventions targeting lifestyle behaviours may improve health-related quality of life and physical function, and reduce depression, whereas little to no effect was achieved on physical activity and weight loss in people with multimorbidity. However, the evidence for physical activity and weight loss were of low quality and the end-treatment benefits diminished over time. [ABSTRACT FROM AUTHOR]

Despite its importance, underreporting of the active content of experimental and comparator interventions in published literature has not been previously examined for behavioural trials. We assessed completeness and variability in reporting in 142 randomised controlled trials of behavioural interventions for smoking cessation published between 1/1996 and 11/2015. Two coders reliably identified the potential active components of experimental and comparator interventions (activities targeting behaviours key to smoking cessation and qualifying as behaviour change techniques, BCTs) in published, and in unpublished materials obtained from study authors directly. Unpublished materials were obtained for 129/204 (63%) experimental and 93/142 (65%) comparator groups. For those, only 35% (1200/3403) of experimental and 26% (491/1891) of comparator BCTs could be identified in published materials. Reporting quality (#published BCTs/#total BCTs) varied considerably between trials and between groups within trials. Experimental (vs. comparator) interventions were better reported (B(SE) = 0.34 (0.11), p <.001). Unpublished materials were more often obtained for recent studies (B(SE) = 0.093 (0.03), p =.003) published in behavioural (vs. medical) journals (B(SE) = 1.03 (0.41), p =.012). This high variability in underreporting of active content compromises reader's ability to interpret the effects of individual trials, compare and explain intervention effects in evidence syntheses, and estimate the additional benefit of an experimental intervention in other settings. [ABSTRACT FROM AUTHOR]

Reducing obesity is an important preventive strategy for people who are at increased risk of major disabling or life-threatening conditions. Behavioural treatments for obesity are complex and involve several components aiming to facilitate behaviour change. Systematic reviews need to assess the components that moderate intervention effects. Electronic databases and journals were searched for randomised controlled trials of behavioural interventions targeting dietary and/or physical activity change for obese adults (mean BMI≥30, mean age≥40 years) with risk factors and follow-up data≥12 weeks. A reliable taxonomy of theory-congruent behaviour change techniques (BCTs; Abraham & Michie, 2008) was used to identify programme components. Meta-regression suggested that increasing numbers of identified BCTs are not necessarily associated with better outcomes. The BCTs provision of instructions (β =− 2.69, p=0.02), self-monitoring (β = − 3.37, p<0.001), relapse prevention (β = − 2.63, p=0.02) and prompting practice (β = − 3.63, p<0.001) could be linked to more successful interventions. Studies including more BCTs aimed at dietary change that are congruent with Control Theory were associated with greater weight loss (β = − 1.13, p=0.04). Post-hoc ratings of intervention components in published trials can lead to the identification of components and theories for behaviour change practice and research. [ABSTRACT FROM PUBLISHER]

Testing mechanisms of action (MoAs) hypothesized to underlie behavior change can enhance intervention effectiveness. Rigorous measurement of putative mechanisms is critical to this effort, but measures are rarely validated with respect to target MoAs. This study aimed to elucidate challenges of linking measures to putative MoAs and to identify priorities for future research. This study was a systematic exploration of written comments by experts in behavioral intervention research and theories of behavior change (N = 20) capturing their opinions about a task querying whether self-report measures from the Science Of Behavior Change (SOBC) Measures Repository were related to a set of MoAs identified by the Human Behaviour Change Project (HBCP). Six themes were identified: 1) Study Value, 2) Measure Properties, 3) Mechanism Properties, 4) Miscellaneous Measure Concerns, 5) Conceptual Challenges, and 6) Approaches to Developing Measure-Mechanism Links. Experts noted challenges such as lack of measure validation, poor measure properties (e.g., double-barreled items), overly broad MoA definitions that limited their utility, lack of clarity around the term "related," and more. Nonetheless, experts expressed the importance of the exercise. Suggestions included developing and refining measures that are validate for assessing MoAs, clarifying and elaborating MoA definitions, and conducting further, more granular research. This systematic examination of expert comments highlights issues that need further investigation to advance behavioral science, specifically pertaining to identifying valid measures of MoAs in behavioral and process research. This study highlights the challenges and opportunities for future research on linking measures and MoA in behavioral science and subsequently enhancing the efficacy of behavioral interventions. • Comments on an effort to link measures to MoAs of behavior change were examined. • Behavior-change experts found these efforts essential for scientific progress. • Measure and MoA concerns (e.g., quality, definitions) impaired link creation. • Varied interpretations of the term "related" places caveats on measure-MoA links. • Clarity, specificity, and standardized criteria are needed in future studies. [ABSTRACT FROM AUTHOR]