Objective: Issues regarding clinician communication remain an important source of complaints within healthcare. This systematic review aims to determine cancer patients' and their family caregivers' views on which clinicians' communication behaviors can harm (i.e. eliciting negative feelings/consequences for patients/family caregivers). Methods: We searched for all types of peer-reviewed studies that determined adult (≥18 years) cancer patients' and/or family caregivers' perspectives on which clinicians' communication behaviors can harm in several databases (PubMed, Embase, Web of Science, Cochrane Library, Emcare, PsycINFO and Academic Search Premier), supplemented by expert-consultation. Studies were screened using the Artificial intelligence screening tool of ASReview and data was analyzed using Thematic Analysis. To assess the quality of the studies the Qualsyst critical appraisal tool was used. Results: A total of 47 studies were included. Four main themes of harmful communication behaviors were identified: (1) Lack of tailored information provision (e.g. giving too little or too much/specific information) (2) Lack of tailored decision making (ranging from; patient exclusion, to the patients' responsibility, and/or haste) (3) Lack of feeling seen and heard (seen as a disease, not as a human being; not listened to concerns and emotions) (4) Lack of feeling held and remembered (forgotten agreements; lack of care continuity). Conclusions: Our results reveal an overview of patients' and family caregivers' perspectives on which clinicians' communication behaviors can harm. Harm could be prevented when information and decision involvement are tailored and patients' and family caregivers' needs to feel seen, heard, held and remembered are met.

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Tailored motivational messages are helpful to motivate people in eHealth applications for increasing physical activity, but it is not sufficiently clear how such messages can be effectively generated in advance. We, therefore, put forward a theory-driven approach to generating tailored motivational messages for eHealth applications for behavior change, and we examine its feasibility by assessing how motivating the resulting messages are perceived. For this, we designed motivational messages with a specific structure that was based on an adaptation of an existing ontology for tailoring motivational messages in the context of physical activity. To obtain tailored messages, experts in health psychology and coaching successfully wrote messages with this structure for personas in scenarios that differed with regard to the persona’s mood, self-efficacy, and progress. Based on an experiment in which 60 participants each rated the perceived motivational impact of six generic and six tailored messages based on scenarios, we found credible support for our hypothesis that messages tailored to mood, self-efficacy, and progress are perceived as more motivating. A thematic analysis of people’s free-text responses about what they found motivating and demotivating about motivational messages further supports the use of tailored messages, as well as messages that are encouraging and empathetic, give feedback about people’s progress, and mention the benefits of physical activity. To aid future work on motivational messages, we make our motivational messages and corresponding scenarios publicly available.@en

Background: 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 as well as lessons learnt are presented in the hopes of guiding other research groups working on similar projects. Methods: Numerous approaches were used and combined to support the development of the Perfect Fit virtual coach. Approaches include literature reviews, empirical studies, collaboration with end-users, content and technical development sprints, interdisciplinary collaboration and iterative proof-of-concept implementation. Findings: The Perfect Fit intervention integrates evidence-based behavioral change techniques as well as new techniques focused on identity change, big data science, sensor technology and personalized real-time coaching. Intervention content of the virtual coaching matches communication preferences and individual needs of end users. Lessons learnt include ways to optimally implement and tailor interactions from the virtual coach (e.g., ‘explain why user is asked for input’, ‘tailor timing and frequency of intervention components’). With regards to the development process, lessons learnt include strategies for effective interdisciplinary collaboration and technical development (e.g., ‘Find a good balance between wishes of end-users and legal possibilities’). Discussion: The Perfect Fit development process was interactive, iterative and challenging at times. We hope that our experiences and lessons learnt can inspire and benefit others.@en