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Behavior change interventions can unintendedly widen existing socio-economic health inequalities. Understanding why interventions are (in)effective among people with lower socio-economic position (SEP) is essential. Therefore, this scoping review aims to describe what is reported about the behavior change techniques (BCTs) applied within interventions and their effectiveness in encouraging physical activity and healthy eating, and reducing smoking and alcohol consumption according to SEP. A systematic search was conducted in 12 electronic databases, and 151 studies meeting the eligibility criteria were included and coded for health behavioral outcomes, SEP-operationalization, BCTs (type and number) and effectiveness. Findings suggest that approaches for measuring, defining and substantiating lower SEP vary. Current studies of behavior change interventions for people of different SEP do not systematically identify BCTs, making systematic evaluation of BCT effectiveness impossible. The effectiveness of interventions is mainly evaluated by overall intervention outcomes and SEP-moderation effects are mostly not assessed. Using different SEP-operationalizations and not specifying BCTs hampers systematic evidence accumulation regarding effective (combinations of) BCTs for the low SEP population. To learn which BCTs effectively improve health behaviors among people with lower SEP, future intervention developers should justify how SEP is operationalized and must systematically describe and examine BCTs.

This intervention development study aimed to work with a wide range of stakeholders across the UK to integrate existing global evidence on the effectiveness and implementation of breastfeeding support for mothers with/without long‐term conditions and co‐develop a complex intervention optimised for delivery in healthcare settings. The intervention development process was informed by four systematic reviews, conducted alongside an embedded programme of co‐production work between 2020 and 2025, involving: two stakeholder working groups (SWG) and two parent panels (PP) that met at regular intervals during the study; six focus group discussions (FGD) to ensure engagement with parents from socially disadvantaged groups; and 10 co‐production workshops (Co‐PW) involving parents, third sector organisations, healthcare practitioners, managers, commissioners, policymakers, and academics. Systematic reviews synthesised data from 116 randomised controlled trials and 16 process evaluations of breastfeeding support interventions for healthy mothers; and 22 trials and 24 studies on views/experiences of breastfeeding support in mothers with long‐term conditions. The co‐production work involved 23 stakeholders and 16 parents in SWG and PP meetings, 15 parents in FGD, and 128 stakeholders in Co‐PW. The resulting Action for Breastfeeding (A4B) Programme comprised four core components (antenatal, postnatal, follow‐up, and signposting) with associated implementation strategies, mechanisms of action, and outcomes for evaluation. Materials and guidance to support adoption and delivery were co‐designed. The A4B Programme provides an evidence‐based and co‐produced intervention to deliver organised support for breastfeeding mothers in healthcare settings, with proposed adaptations for mothers with long‐term conditions. Some uncertainties remain and these will be investigated in our future work. Summary There is strong evidence that breastfeeding support works, yet many women still stop early due to lack of adequate support, indicating that improvements amply demonstrated in research are not effectively translating into real‐world outcomes. This intervention development study combined the use of high‐quality evidence on both effectiveness and implementation, alongside an extensive programme of stakeholder engagement work, to improve potential for context‐adapted real‐world adoption. To promote sustainable and inclusive scale‐up, the Action for Breastfeeding Programme is optimised for delivery in healthcare settings and includes adaptations for women with long‐term conditions, ensuring that tailored support can be delivered for all women.

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.

Background. There is limited knowledge of the key determinants of antimicrobial prescribing behavior (APB) in hospitals. An understanding of these determinants is required for the successful design, adoption, and implementation of quality improvement interventions in antimicrobial stewardship programs. Methods. Qualitative semistructured interviews were conducted with doctors (n = 10), pharmacists (n = 10), and nurses and midwives (n = 19) in 4 hospitals in London. Interviews were conducted until thematic saturation was reached. Thematic analysis was applied to the data to identify the key determinants of antimicrobial prescribing behaviors. Results. The APB of healthcare professionals is governed by a set of cultural rules. Antimicrobial prescribing is performed in an environment where the behavior of clinical leaders or seniors influences practice of junior doctors. Senior doctors consider themselves exempt from following policy and practice within a culture of perceived autonomous decision making that relies more on personal knowledge and experience than formal policy. Prescribers identify with the clinical groups in which they work and adjust their APB according to the prevailing practice within these groups. A culture of \"noninterference' in the antimicrobial prescribing practice of peers prevents intervention into prescribing of colleagues. These sets of cultural rules demonstrate the existence of a \"prescribing etiquette,\" which dominates the APB of healthcare professionals. Prescribing etiquette creates an environment in which professional hierarchy and clinical groups act as key determinants of APB. Conclusions. To influence the antimicrobial prescribing of individual healthcare professionals, interventions need to address prescribing etiquette and use clinical leadership within existing clinical groups to influence practice.

The effectiveness of digital health interventions is commonly assumed to be related to the level of user engagement with the digital health intervention, including measures of both digital health intervention use and users' subjective experience. However, little is known about the relationships between the measures of digital health intervention engagement and physical activity or sedentary behavior. This study aims to describe the direction and strength of the association between engagement with digital health interventions and physical activity or sedentary behavior in adults and explore whether the direction of association of digital health intervention engagement with physical activity or sedentary behavior varies with the type of engagement with the digital health intervention (ie, subjective experience, activities completed, time, and logins). Four databases were searched from inception to December 2019. Grey literature and reference lists of key systematic reviews and journals were also searched. Studies were eligible for inclusion if they examined a quantitative association between a measure of engagement with a digital health intervention targeting physical activity and a measure of physical activity or sedentary behavior in adults (aged ≥18 years). Studies that purposely sampled or recruited individuals on the basis of pre-existing health-related conditions were excluded. In addition, studies were excluded if the individual engaging with the digital health intervention was not the target of the physical activity intervention, the study had a non-digital health intervention component, or the digital health interventions targeted multiple health behaviors. A random effects meta-analysis and direction of association vote counting (for studies not included in meta-analysis) were used to address objective 1. Objective 2 used vote counting on the direction of the association. Overall, 10,653 unique citations were identified and 375 full texts were reviewed. Of these, 19 studies (26 associations) were included in the review, with no studies reporting a measure of sedentary behavior. A meta-analysis of 11 studies indicated a small statistically significant positive association between digital health engagement (based on all usage measures) and physical activity (0.08, 95% CI 0.01-0.14, SD 0.11). Heterogeneity was high, with 77% of the variation in the point estimates explained by the between-study heterogeneity. Vote counting indicated that the relationship between physical activity and digital health intervention engagement was consistently positive for three measures: subjective experience measures (2 of 3 associations), activities completed (5 of 8 associations), and logins (6 of 10 associations). However, the direction of associations between physical activity and time-based measures of usage (time spent using the intervention) were mixed (2 of 5 associations supported the hypothesis, 2 were inconclusive, and 1 rejected the hypothesis). The findings indicate a weak but consistent positive association between engagement with a physical activity digital health intervention and physical activity outcomes. No studies have targeted sedentary behavior outcomes. The findings were consistent across most constructs of engagement; however, the associations were weak.

Background Behavior change is essential for promoting health and preventing illness; yet, motivating individuals to adopt and maintain healthy behaviors remains a significant challenge. Multiple models have been developed in Psychology and Behavioral Sciences to understand and encourage behavior change, including the Capability, Opportunity, Motivation, Behavior model (COM-B model), the Health Belief Model, the Behavior Change Wheel, the Theoretical Domains Framework (TDF), nudge theory, and Behavior Change Techniques (BCTs). Among these, the Fogg Behavior Model (FBM), developed by Dr. BJ Fogg, offers a specific and valuable framework for facilitating behavior change. This scoping review aims to analyze studies that apply the FBM in health, particularly its impact on changing health-related behaviors. By synthesizing the evidence, this review provides valuable insights into the use and impact of the FBM in promoting behavior change in health, with implications for future research and practice. Objective To investigate the application of the FBM within the health domain, focusing on its role in behavior change interventions. Methods A comprehensive search of multiple databases, including MEDLINE/PubMed, Cochrane Library, Epistemonikos, and PsycINFO, was conducted to identify studies applying the FBM in health-related interventions. The search strategy incorporated terms related to the FBM, health behavior change, and relevant health outcomes, with no restrictions on publication date. Unpublished and grey literature was also searched. Eligibility criteria included studies that applied the FBM in health interventions and reported outcomes. The review followed PRISMA-ScR and SAGER guidelines to ensure comprehensive reporting and consideration of sex and gender variables. Data were synthesized using a narrative approach, summarizing findings descriptively and thematically. Results Six studies met the inclusion criteria, covering sexual and reproductive health, vaccination, chronic disease management, general wellness, and healthcare adherence. The FBM was applied through motivation (anticipation, sensation, belonging), ability enhancement (reducing effort, increasing accessibility, integrating behaviors into routines), and prompts (reminders, calls to action, environmental cues). Effectiveness varied across studies. Gestational weight management reduced gestational diabetes (10.34% vs. 34.48%, p = 0.028), hypertension (3.45% vs. 27.59%, p = 0.030), and cesarean rates (41.38% vs. 72.41%, p = 0.017). HPV vaccination interventions increased intent to vaccinate (63.3–96.7%, p < 0.001), with 30% receiving the first dose within three months. Diabetes self-management improved dietary adherence (p = 0.04), physical activity (p = 0.005), and glucose monitoring (p = 0.02). Parental nutrition interventions increased knowledge (d = 1.07), beliefs (d = 0.61), and behavior change (d = 0.59). A vaginal birth intervention raised intention by 29% (p < 0.05). Conclusions Our scoping review highlights the FBM as an effective framework for promoting health behavior change across various domains. By systematically applying motivation, ability, and prompts, FBM-based interventions demonstrated positive outcomes. However, limitations such as the lack of long-term follow-ups and sex- and gender-disaggregated data indicate areas for future research. Expanding its application to diverse populations, integrating digital health technologies, and addressing structural and cultural barriers will enhance its impact. Strengthening methodological rigor and comparative analyses with other behavior change models will further refine its effectiveness for broader public health applications. Despite its potential, the FBM remains underutilized in public health research. Trial registration Open Science Framework osf.io/jpwxg.

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using “ontologies.” In information science, an ontology is a systematic method for articulating a “controlled vocabulary” of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine’s Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science.

The theory of planned behavior is a social cognition theory that has been widely applied to identify the psychological determinants of intentions and behavior in health contexts. Our 2015 meta-analysis of theory applications in chronic illness contributed to a burgeoning evidence base comprising syntheses supporting theory predictions in health behavior. In this review, we identify limitations of prior meta-analyses of theory applications in health behavior and highlight salient evidence gaps, summarize how recent meta-analyses of the theory have addressed some of the limitations, outline outstanding research questions, and suggest future research syntheses, including those currently in progress, to resolve them. We point to recent and ongoing meta-analyses addressing theory hypotheses and assumptions not tested in previous syntheses, such as perceived behavioral control moderating effects and indirect effects of environmental (e.g., sociostructural variables) and intrapersonal (e.g., personality traits) determinants on health behavior mediated by theory constructs. We also highlight meta-analyses examining behavioral effects of constructs representing extended processes (e.g., habit, implicit cognition) in the context of the theory. Further, we summarize recent meta-analyses addressing directional and causal inferences in theory effects, including meta-analyses of longitudinal studies and experimental and intervention research. We also highlight attempts to test the mechanisms of action of interventions based on the theory including the change meta-analysis method and mediation analyses. We conclude by summarizing the advances that recent meta-analyses of the theory have made to the evidence base of health behavior determinants and interventions and highlighting suggestions for meta-analyses that will further progress the evidence base.

Since its earliest days, the field of behavioral medicine has leveraged technology to increase the reach and effectiveness of its interventions. Here, we highlight key areas of opportunity and recommend next steps to further advance intervention development, evaluation, and commercialization with a focus on three technologies: mobile applications (apps), social media, and wearable devices. Ultimately, we argue that future of digital health behavioral science research lies in finding ways to advance more robust academic-industry partnerships. These include academics consciously working towards preparing and training the work force of the twenty first century for digital health, actively working towards advancing methods that can balance the needs for efficiency in industry with the desire for rigor and reproducibility in academia, and the need to advance common practices and procedures that support more ethical practices for promoting healthy behavior.

Purpose: Theory-based interventions aimed at promoting health behavior change in cancer survivors seem to be effective but remain scarce. More information on intervention features is also needed. This review aimed to synthesize the evidence from randomized controlled trials evaluating the efficacy of theory-based interventions (and its features) on physical activity (PA) and/or diet behaviors in cancer survivors. Methods: A systematic search in three databases (PubMed, PsycInfo, and Web of Science) identified studies that (i) targeted adult cancer survivors and (ii) included theory-based randomized controlled trials designed to influence PA, diet, or weight management. A qualitative synthesis of interventions' effectiveness, extensiveness of theory use, and applied intervention techniques was conducted. Results: Twenty-six studies were included. Socio-Cognitive Theory was the most used theory, showing promising results in PA-only trials and mixed findings in multiple-behavior interventions. Mixed findings were observed for interventions based on the Theory of Planned Behavior and Transtheoretical Model. Limited findings were found in diet-only interventions. A large variability in the extensiveness of theory use, and in intervention techniques was found. Further research is required to understand how and why these interventions offer promise for improving behavior. Conclusions: Theory-based interventions seem to improve PA and diet behaviors in cancer survivors. Further studies, including thorough intervention descriptions, are needed to confirm these findings and identify the optimal features and content of lifestyle theory-based interventions for cancer survivors. Implications for cancer survivors: This systematic review can contribute to the development of more effective interventions to promote long-term adherence to healthy lifestyle behaviors.