BACKGROUND: Physical activity engagement following a cancer diagnosis is positively associated with survival, reduced risk of disease recurrence, and reduced cancer-specific and all-cause mortality. However, rates of physical activity engagement are low among individuals diagnosed with and being treated for breast cancer or prostate cancer.
OBJECTIVE: The purpose of this study was to describe the systematic process of developing an e-cycling intervention aimed at increasing physical activity among individuals living with prostate cancer or breast cancer and outline the key components to be implemented.
METHODS: The Medical Research Council guidance for developing complex interventions and the Behaviour Change Wheel were used to guide intervention development. Information was gathered from the literature and through discussions with end users to understand factors influencing e-cycling. These factors were mapped onto the Theoretical Domains Framework to identify potential mechanisms of action. Behavior change techniques were selected from theory and evidence to develop intervention content. Interested parties, including cycling instructors, end users, and behavior change experts, reviewed and refined the intervention.
RESULTS: Anticipated barriers and facilitators to e-cycling engagement were mapped onto 11 of the 14 domains of the Theoretical Domains Framework. A total of 23 behavior change techniques were selected to target these domains over 4 one-to-one e-cycling sessions delivered by trained cycling instructors in the community. Cycling instructors were provided a 3-hour classroom training session on delivering the intervention and a 3-hour practical session with feedback. The outcome of this work is a theory and evidence-informed intervention aimed at promoting e-cycling behavior among individuals being treated for breast cancer or prostate cancer, which is currently being implemented and evaluated.
CONCLUSIONS: Transparent intervention development and reporting of content is important for comprehensively examining intervention implementation. The implementation of this intervention package is currently being evaluated in a pilot randomized controlled trial. If the intervention is found to be effective and the content and delivery are acceptable, this intervention will form a basis for the development of e-cycling interventions in other survivors of cancer.
BACKGROUND: ISRCTN Registry ISRCTN39112034 https://www.isrctn.com/ISRCTN39112034; and IRSCTN Registry ISRCTN42852156; https://www.isrctn.com/ISRCTN42852156.

Despite the health benefits of physical activity, many older adults living in long-term care facilities lead sedentary lifestyles and do not meet minimum physical activity recommendations. Determining the behavior change techniques (BCTs) used in physical activity interventions can help us understand the underlying mechanisms by which behavioral change is achieved. The purpose of this systematic review was to identify and evaluate BCTs in physical activity interventions for the elderly residents. Six electronic databases were searched and 15 eligible studies were retained. Nine promising BCTs associated with physical activity promotion among elderly residents were identified: credible source, social support (unspecified), goal setting (outcome), goal setting (behavior), demonstration of the behavior, instruction on how to perform a behavior, self-monitoring of behavior, self-monitoring of outcome(s) of behavior, and adding objects to the environment. Future research is encouraged to select and tailor these BCTs to the specific needs and preferences of the target population.

Social recovery capital (SRC) is the combination of social resources that can be used to initiate and sustain addiction recovery through friends, family, and peers. Broadly, understanding one\'s SRC allows us to get a sense of where one has social support for recovery and where there may be social barriers to their recovery process. SRC is often a vital component of many people\'s recovery journey, yet our understanding of how best to use this concept in research and practice remains underdeveloped. To improve understanding of the role of social recovery capital and strategies to measure and increase it, we present a roadmap involving a five-pronged research agenda to: (1) Refine the measurement of social recovery capital; (2) Model the complexity of social recovery capital empirically; (3) Integrate personality science with social recovery capital research; (4) Optimize evidence-based behavior change techniques of social recovery capital; and (5) Incorporate an intersectional framework when examining or applying social recovery capital. Overall, this five-pronged research agenda seeks to enhance the clinical utility of SRC research to maximize the impact of SRC on one\'s recovery.

BACKGROUND: Worldwide, physical inactivity (PIA) and sedentary behavior (SB) are recognized as significant challenges hindering the achievement of the United Nations (UN) sustainable development goals (SDGs). PIA and SB are responsible for 1.6 million deaths attributed to non-communicable diseases (NCDs). The World Health Organization (WHO) has urged governments to implement interventions informed by behavioral theories aimed at reducing PIA and SB. However, limited attention has been given to the range of theories, techniques, and contextual conditions underlying the design of behavioral theories. To this end, we set out to map these interventions, their levels of action, their mode of delivery, and how extensively they apply behavioral theories, constructs, and techniques.
METHODS: Following the scoping review methodology of Arksey and O\'Malley (2005), we included peer-reviewed articles on behavioral theories interventions centered on PIA and SB, published between 2010 and 2023 in Arabic, French, and English in four databases (Scopus, Web of Science [WoS], PubMed, and Google Scholar). We adopted a framework thematic analysis based on the upper-level ontology of behavior theories interventions, Behavioral theories taxonomies, and the first version (V1) taxonomy of behavior change techniques(BCTs).
RESULTS: We included 29 studies out of 1,173 that were initially screened/searched. The majority of interventions were individually focused (n = 15). Few studies have addressed interpersonal levels (n = 6) or organizational levels (n = 6). Only two interventions can be described as systemic (i.e., addressing the individual, interpersonal, organizational, and institutional factors)(n = 2). Most behavior change interventions use four theories: The Social cognitive theory (SCT), the socioecological model (SEM), SDT, and the transtheoretical model (TTM). Most behavior change interventions (BCIS) involve goal setting, social support, and action planning with various degrees of theoretical use (intensive [n = 15], moderate [n = 11], or low [n = 3]).
CONCLUSIONS: Our review suggests the need to develop systemic and complementary interventions that entail the micro-, meso- and macro-level barriers to behavioral changes. Theory informed BCI need to integrate synergistic BCTs into models that use micro-, meso- and macro-level theories to determine behavioral change. Future interventions need to appropriately use a mix of behavioral theories and BCTs to address the systemic nature of behavioral change as well as the heterogeneity of contexts and targeted populations.

Planning-based interventions are often used to help individuals form habits. Existing literature suggests a one-size-fits all approach to habit formation, but planning interventions may be optimized if tailored to individual differences and/or behavioral complexity. We test the hypothesis that planning to do a relatively complex behaviour (exercise) at a time that matches an individuals\' diurnal preference will facilitate behavioral engagement; whereas for a simpler behaviour (calcium supplementation), the optimal time-of-day for a new behavior will occur in the morning. Young, women volunteers (N = 317) were randomly assigned to take calcium supplements or to exercise for 4 weeks and to control (no planning) or to one of three planning interventions (morning plan; evening plan; unassigned-time plan). Participants reported diurnal preference at baseline and habit strength and behavioral frequency weekly. Fitbit Zips and Medication Event Monitoring System Caps (MEMS) were used to objectively assess behavioral engagement. Multilevel modelling found that calcium-supplementation was greatest for morning-types in the morning-cue condition, whereas exercise was greatest for morning-types with morning cues and evening-types with evening cues. Habit-formation strategies may depend on diurnal preference and behavioral complexity. Future research can evaluate the role of other individual differences.

The optimal treatment and organization of care for people with obesity is one of the greatest challenges facing today\'s health services. While surgery and pharmacotherapy offer effective treatment options for some people with obesity, behavioral interventions are important to support long-term behavioral change. However, little is known about the most effective components of behavioral interventions, and this is especially the case for people with complex or severe obesity (i.e. body mass index [BMI] > 35 kg/m2). Accordingly, the current rapid review aimed to identify which behavior change techniques (BCTs) are effective for weight loss in adults with (severe) obesity. A secondary aim was to review the effects of BCTs on dietary behaviors and physical activity, and psychological outcomes, recognizing that behavioral interventions commonly target these. A search of Scopus, Ovid Medline, and Web of Science resulted in 1227 results, with 22 reviews eligible for inclusion. The most commonly reported BCTs were self-monitoring and goal setting, but these had variable effects on weight in adults with obesity. Combining these BCTs with other self-regulatory techniques led to increased weight loss. Further, for adults with severe obesity, so-called \'nudge\' techniques and self-regulatory techniques were associated with greater weight loss. Three reviews also found that while self-monitoring increased physical activity, behavioral commitments increased changes to dietary behaviors. BCTs were not associated with psychological well-being. The review confirms that behavioral interventions have an impact in weight management, including for individuals with more complex or severe obesity, but highlights the need for further investigation of their use within clinical settings.

UNASSIGNED: Overweight and obesity are among the most prevalent health problems worldwide leading to various diseases and having a significant impact on the healthcare system. In Germany, the prevalence of obesity among adults is 19%. Mobile health applications offer a new approach to treatment and prevention and have been proven effective in previous studies. However, it is essential to investigate the availability and quality of these digital applications. The aim of this systematic assessment is to evaluate the accessibility and quality of digital health applications in German language designed to treat obesity.
UNASSIGNED: In January 2024, a systematic search for mobile health applications was conducted on both the Google Play Store and Apple App Store. Just those apps available in German for both iOS and Android were considered acceptable. The German Mobile Application Rating Scale (MARS-G) was used to assess the quality of the apps. The content of mobile health applications was evaluated using the guideline from the German Obesity Society for the treatment of obesity. The characteristics of the apps were summarized and presented, and the results were analyzed using descriptive statistics and presented in tables.
UNASSIGNED: After screening, ten apps were included in the review. The apps varied in terms of calorie tracking, individual workout plans, educational aspects, nutritional plans, and exercises for behavioral change. On average, 6.4 out of 12 items of the German Obesity guideline recommendations were fulfilled. The MARS score (possible range from 1-5) reached a mean of 3.39 (SD = 0.39). The section \"Engagement\" had the lowest quality score with a mean of 3.14 (SD = 0.57), while the section \"Aesthetics\" achieved the highest mean of 3.57 (SD = 0.52).
UNASSIGNED: Most German mobile health applications for managing obesity meet some guideline recommendations. They demonstrate adequate to good quality according to the MARS score. Assessing the quality of mobile health applications can be challenging for patients, despite being easily accessible and low-threshold. However, such digital health applications, reimbursed by the German SHI, offer evidence-based information, even if access can be associated with higher hurdles.

BACKGROUND: Behavior change techniques (BCTs) are considered as active components of implementation strategies, influencing determinants and, ultimately, implementation performance. In our previous Delphi study, experts formulated \'implementation hypotheses\', detailing how specific combinations of BCTs and strategies (referred to as BCT-strategy combinations) might influence determinants and guideline implementation within youth care. For example, educational meetings providing instructions on guideline use were hypothesized to enhance practitioners\' knowledge and, consequently, guideline implementation. However, these hypotheses have not been verified in practice yet.
METHODS: We conducted a cross-sectional study involving practitioners and management professionals from youth (health)care organizations. Using questionnaires, we obtained data on the presence of BCT-strategy combinations and their perceived influence on determinants and implementation performance. Chi-squared tests and regression analyses were employed to determine the influence of specific BCT-strategy combinations on determinants and implementation performance.
RESULTS: Our analyses included data from 104 practitioners and 34 management professionals. Most of the management professionals indicated that the BCT-strategy combinations positively influenced or had the potential to influence their implementation performance. At the practitioner level, half of the combinations were perceived to have a positive influence on determinants and implementation performance. Furthermore, practitioners who reported the absence of BCT-strategy combinations were more skeptical about their potential influence on determinants and implementation performance.
CONCLUSIONS: Several BCT-strategy combinations were perceived to improve or potentially improve implementation performance of both practitioners and management professionals. In the development and evaluation of implementation efforts, we advocate for clearly describing the implementation effort\'s objective and using frameworks that detail the BCTs inducing behavior change, the strategy employed, and the processes driving the observed changes. Understanding these interconnected processes is important in designing targeted, evidence-based behavior change interventions. This understanding optimizes resource allocation and contributes to the overall success of implementation efforts in youth care.

The development of neuroscientific techniques enabling the recording of brain and peripheral nervous system activity has fueled research in cognitive science. Recent technological advancements offer new possibilities for inducing behavioral change, particularly through cost-effective Internet-based interventions. However, limitations in laboratory equipment volume have hindered the generalization of results to real-life contexts. The advent of Internet of Things (IoT) devices, such as wearables, equipped with sensors and microchips, has ushered in a new era in behavior change techniques. Wearables, including smartwatches, electronic tattoos, and more, are poised for massive adoption, with an expected annual growth rate of 55% over the next five years. These devices enable personalized instructions, leading to increased productivity and efficiency, particularly in industrial production. Additionally, the healthcare sector has seen a significant demand for wearables, with over 80% of global consumers willing to use them for health monitoring. This research explores the primary biometric applications of wearables and their impact on users\' well-being, focusing on the integration of behavior change techniques facilitated by IoT devices. Wearables have revolutionized health monitoring by providing real-time feedback, personalized interventions, and gamification. They encourage positive behavior changes by delivering immediate feedback, tailored recommendations, and gamified experiences, leading to sustained improvements in health. Furthermore, wearables seamlessly integrate with digital platforms, enhancing their impact through social support and connectivity. However, privacy and data security concerns must be addressed to maintain users\' trust. As technology continues to advance, the refinement of IoT devices\' design and functionality is crucial for promoting behavior change and improving health outcomes. This study aims to investigate the effects of behavior change techniques facilitated by wearables on individuals\' health outcomes and the role of wearables in promoting a healthier lifestyle.

BACKGROUND: With the development of emerging technologies, digital behavior change interventions (DBCIs) help to maintain regular physical activity in daily life.
OBJECTIVE: To comprehensively understand the design implementations of habit formation techniques in current DBCIs, a systematic review was conducted to investigate the implementations of behavior change techniques, types of habit formation techniques, and design strategies in current DBCIs.
METHODS: The process of this review followed the PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. A total of 4 databases were systematically searched from 2012 to 2022, which included Web of Science, Scopus, ACM Digital Library, and PubMed. The inclusion criteria encompassed studies that used digital tools for physical activity, examined behavior change intervention techniques, and were written in English.
RESULTS: A total of 41 identified research articles were included in this review. The results show that the most applied behavior change techniques were the self-monitoring of behavior, goal setting, and prompts and cues. Moreover, habit formation techniques were identified and developed based on intentions, cues, and positive reinforcement. Commonly used methods included automatic monitoring, descriptive feedback, general guidelines, self-set goals, time-based cues, and virtual rewards.
CONCLUSIONS: A total of 32 commonly design strategies of habit formation techniques were summarized and mapped to the proposed conceptual framework, which was categorized into target-mediated (generalization and personalization) and technology-mediated interactions (explicitness and implicitness). Most of the existing studies use the explicit interaction, aligning with the personalized habit formation techniques in the design strategies of DBCIs. However, implicit interaction design strategies are lacking in the reviewed studies. The proposed conceptual framework and potential solutions can serve as guidelines for designing strategies aimed at habit formation within DBCIs.