Aims
This study aimed to evaluate the effect of remote monitoring using the Cardiovascular Risk Management (CVRM)-Box on blood pressure control, weight management, medication prescriptions, and consultation frequency in primary care patients at high risk of cardiovascular disease (CVD).

Methods and results
In this matched cohort study, patients with a > 5% 10-year CVD mortality risk in primary care (2020–2024) were compared to propensity score-matched controls over 12 months. The CVRM-Box included smartphone-connected devices (blood pressure monitor, weighing scale, activity tracker) linked to general practitioner electronic health records.

Compared to controls, the intervention group showed modest reductions in office-measured systolic {−1.1 mmHg [95% confidence interval (CI), −3.7 to −1.5]; P = 0.39} and diastolic blood pressure [−0.04 mmHg (95% CI, −1.6 to 1.5); P = 0.96]. Sensitivity analyses yielded similar results. However, CVRM-Box assessments showed reductions in systolic [−5.5 mmHg (95% CI, −7.6 to −3.3); P < 0.001] and diastolic blood pressure [−3.8 mmHg (95% CI, −5.1 to −2.4); P < 0.001]. The intervention group also experienced greater reductions in weight [−0.9 kg (95% CI, −1.6 to −0.2); P = 0.01] and body mass index [−0.3 kg/m² (95% CI, −0.5 to −0.01); P = 0.007]. Additionally, antihypertensive medication use increased [0.12 (95% CI, 0.06 to 0.23); P = 0.04], while consultation frequency decreased (rate ratio 0.82; P = 0.002).

Conclusion
While office measurements showed no additional blood pressure reduction, CVRM-Box measurements demonstrated significant decreases. The intervention also improved target blood pressure achievement, promoted weight reduction, increased antihypertensive use, and reduced consultation frequency.

Objective
Adopting healthy behavior is vital for preventing chronic diseases. Mobile health (mHealth) interventions utilizing virtual coaches (i.e., artificial intelligence conversational agents) can offer scalable and cost-effective solutions. Additionally, targeting multiple unhealthy behaviors, like low physical activity and smoking, simultaneously seems beneficial. We developed Perfect Fit, an mHealth intervention with a virtual coach providing personalized feedback to simultaneously promote smoking cessation and physical activity. Through innovative methods (e.g., sensor technology) and iterative development involving end-users, we strive to overcome challenges encountered by mHealth interventions, such as shortage of evidence-based interventions and insufficient personalization. This paper outlines the content of Perfect Fit and the protocol for evaluating its feasibility, acceptability, and preliminary effectiveness, the role of participant characteristics, and the study's feasibility.
Methods
A single-arm, mixed-method, real-world evaluation study will be conducted in the Netherlands. We aim to recruit 100 adult daily smokers intending to quit within 6 weeks. The personalized intervention will last approximately 16 weeks. Primary outcomes include Perfect Fit's feasibility and acceptability. Secondary outcomes are preliminary effectiveness and study feasibility, and we will measure participant characteristics. Quantitative data will be collected through questionnaires administered at baseline, post-intervention and 2, 6, and 12 months post-intervention. Qualitative data will be gathered via semi-structured interviews post-intervention. Data analysis will involve descriptive analyses, generalized linear mixed models (quantitative) and the Framework Approach (qualitative), integrating quantitative and qualitative data during interpretation.
Conclusions
This study will provide novel insight into the potential of interventions like Perfect Fit, as a multiple health behavior change strategy. Findings will inform further intervention development and help identify methods to foster feasibility and acceptability. Successful mHealth interventions with virtual coaches will prevent chronic diseases and promote public health.

Background: Medical procedures can cause considerable stress and anxiety among children. Current interventions mainly diminish stress and anxiety during procedures, while stress and anxiety often build up at home. Moreover, interventions often focus on either distraction or preparation. eHealth can combine multiple strategies and provide a low-cost solution that can be used outside the hospital. Objective: To develop an eHealth solution to diminish preprocedural stress and anxiety, and to evaluate the app on use, usability and user experience in practice. We also aimed to gain in-depth insights in children's and caregivers' opinions and experiences to inform future improvements. Methods: This is a multi-study report on the development (Study 1) and evaluation (Study 2) of a first version of the developed app. In study 1 we adopted a participatory design approach in which children's experiences were central to the design process. We performed an experience journey session with stakeholders (n = 13) to map the child's outpatient journey, identify pains and gains, and formulate the desired experience journey. Iterative development and testing with children (n = 8) and caregivers (n = 6) resulted in a working prototype. The prototype was tested with children, resulting in a first version of the Hospital Hero app. The app was evaluated on use, user-experience and usability during an eight-week pilot study in practice (Study 2). We triangulated data from online interviews with children and caregivers (n = 21) and online questionnaires (n = 46). Results: Multiple stress and anxiety experience touchpoints were identified. The Hospital Hero app supports children in their hospital journey by facilitating preparation at home and providing distraction at the hospital. The pilot study showed that the app was evaluated positively on usability and user-experience and is considered feasible. Qualitative data showed five themes: (1) user-friendliness, (2) coherence and power of storytelling, (3) motivation and reward, (4) fit with real hospital journey, (5) procedural comfort. Discussion: Using participatory design, we developed a child-centered solution that supports children in the entire hospital journey and may diminish preprocedural stress and anxiety. Future efforts should create a more tailored journey, define an optimal engagement window and formulate implementation strategies.