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IntroductionSmoking and insufficient physical activity (PA), independently but especially in conjunction, often lead to disease and (premature) death. For this reason, there is need for effective smoking cessation and PA-increasing interventions. Identity-related interventions which aim to influence how people view themselves offer promising prospects, but an overview of the existing evidence is needed first. This is the protocol for a scoping review aiming to aggregate the evidence on identity processes and identity-related interventions in the smoking and physical activity domains.MethodsThe scoping review will be guided by an adaption by Levac et al of the 2005 Arksey and O’Malley methodological framework, the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses: Extension for Scoping Review (PRISMA-ScR) and the 2017 Joanna Briggs Institute guidelines. It will include scientific publications discussing identity (processes) and/or identity-related interventions in the context of smoking (cessation) and/or physical (in)activity, in individuals aged 12 and over. A systematic search will be carried out in multiple databases (eg, PubMed, Web of Science). Records will be independently screened against prepiloted inclusion/exclusion criteria by two reviewers, using the Active Learning for Systematic Reviews machine learning artificial intelligence and Rayyan QCRI, a screening assistant. A prepiloted charting table will be used to extract data from included full-text articles. Findings will be reported according to the PRISMA-ScR guidelines and include study quality assessment.Ethics and disseminationEthical approval is not required for scoping reviews. Findings will aid the development of future identity-related interventions targeting smoking and physical inactivity.

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Background Despite their increasing prevalence and potential, eHealth applications for behavior change suffer from a lack of adherence and from dropout. Advances in virtual coach technology provide new opportunities to improve this. However, these applications still do not always offer what people need. We, therefore, need a better understanding of people’s needs and how to address these, based on both actual experiences of users and their reflections on envisioned scenarios. Methods We conducted a longitudinal study in which 671 smokers interacted with a virtual coach in five sessions. The virtual coach assigned them a new preparatory activity for quitting smoking or increasing physical activity in each session. Participants provided feedback on the activity in the next session. After the five sessions, participants were asked to describe barriers and motivators for doing their activities. In addition, they provided their views on videos of scenarios such as receiving motivational messages. To understand users’ needs, we took a mixed-methods approach. This approach triangulated findings from qualitative data, quantitative data, and the literature. Results We identified 14 main themes that describe people’s views of their current and future behaviors concerning an eHealth application. These themes relate to the behaviors themselves, the users, other parties involved in a behavior, and the environment. The most prevalent theme was the perceived usefulness of behaviors, especially whether they were informative, helpful, motivating, or encouraging. The timing and intensity of behaviors also mattered. With regards to the users, their perceived importance of and motivation to change, autonomy, and personal characteristics were major themes. Another important role was played by other parties that may be involved in a behavior, such as general practitioners or virtual coaches. Here, the themes of companionableness, accountability, and nature of the other party (i.e., human vs AI) were relevant. The last set of main themes was related to the environment in which a behavior is performed. Prevalent themes were the availability of sufficient time, the presence of prompts and triggers, support from one’s social environment, and the diversity of other environmental factors. We provide recommendations for addressing each theme. Conclusions The integrated method of experience-based and envisioning-based needs acquisition with a triangulate analysis provided a comprehensive needs classification (empirically and theoretically grounded). We expect that our themes and recommendations for addressing them will be helpful for designing applications for health behavior change that meet people’s needs. Designers should especially focus on the perceived usefulness of application components. To aid future work, we publish our dataset with user characteristics and 5,074 free-text responses from 671 people.

UNSTRUCTURED Background and objective: Smoking and physical inactivity are two key preventable risk factors of cardiovascular disease. Yet, as with most health behaviors, they are difficult to change. In the interdisciplinary Perfect Fit project, scientists from different fields join forces to develop an evidence-based virtual coach that supports smokers in quitting smoking and increasing their physical activity. Intervention content, design and implementation, and lessons learned are presented to support other research groups working on similar projects. Methods: Six different approaches were used and combined to support the development of the Perfect Fit virtual coach. The approaches used are: (1) literature reviews, (2) empirical studies, (3) collaboration with end-users, (4) content and technical development sprints, (5) interdisciplinary collaboration, and (6) iterative proof-of-concept implementation. Results: The Perfect Fit intervention integrates evidence-based behavior change techniques with new techniques focused on identity change, big data science, sensor technology, and personalized real-time coaching. Intervention content of the virtual coaching matches the individual needs of the end users. Lessons learned include ways to optimally implement and tailor interactions with the virtual coach (e.g., clearly explain why the user is asked for input, tailor the timing and the frequency of the intervention components). Concerning the development process, lessons learned include strategies for effective interdisciplinary collaboration and technical development (e.g., finding a good balance between end-users wishes and legal possibilities). Conclusion: The Perfect Fit development process was interactive, iterative, and challenging at times. Our experiences and lessons learned can inspire and benefit others.