Background: Embedding Web-based interventions within physiotherapy has potential, but knowledge on patient adherence to these interventions is limited. Introduction: This study explores which patient-, intervention-, and environment-related factors are determinants of adherence to the online component of e-Exercise, a 12-week blended intervention for patients with hip and/or knee osteoarthritis. Methods: A convergent mixed methods study was performed, embedded within an ongoing trial. Quantitative data of 109 participants that received e-Exercise were used for negative binomial regression analysis. Adherence was defined as the number of online evaluated weeks. Next, semistructured interviews on factors related to adherence to the online component were analyzed. Results: Nineteen participants with missing outcome data because their program was not started were excluded. Of the 90 analyzed participants, 81.1% were evaluated for at least 8 weeks. Adherence was highest for participants with middle education, 1–5-year osteoarthritis duration, and participants who were physiotherapist recruited. The 10 analyzed interviews revealed that sufficient Internet skills, self-discipline, execution of the exercise plan, the intervention's usability, flexibility, persuasive design, added value, and acceptable required time, and research participation were linked to favorable adherence. Discussion: It is unknown if patients who adhered to the online component also adhered to their exercise plans. The relationship between adherence to the online component and clinical outcomes will be addressed in a future study. Conclusions: The majority of the participants adhered to the online component of e-Exercise, illustrating its applicability. The integration within the physiotherapy setting and intervention's persuasive design appear to have an important role in optimizing patient adherence.

Introduction: E-Exercise is an effective 12-week blended intervention consisting of around five face-to-face physiotherapy sessions and a web-based application for patients with hip/knee osteoarthritis. In order to facilitate effective implementation of e-Exercise, this study aims to identify physiotherapists’ experiences and determinants related to the usage of e-Exercise. Methods: An explanatory sequential mixed methods design embedded in a randomized controlled trial comparing e-Exercise with usual physiotherapy in patients with hip/knee osteoarthritis. Usage of e-Exercise was based on recruitment rates of 123 physiotherapists allocated to e-Exercise and objective web-based application usage data. Experiences and determinants related to e-Exercise usage were investigated with a questionnaire and clarified with semi-structured interviews. Results: Of the 123 physiotherapists allocated to e-Exercise, 54 recruited more than one eligible patient, of whom 10 physiotherapists continued using e-Exercise after the study period. Physiotherapists had mixed experiences with e-Exercise. Determinants related to intervention usage were appropriateness, added value, time, workload, professional autonomy, environmental factors, and financial consequences. Physiotherapists recommended to improve the ability to tailor e-Exercise to the individual needs of the patient patients’ individual needs. Discussion: Determinants related to the usage of e-Exercise provided valuable information for the implementation of e-Exercise on broader scale. Most importantly, the flexibility of e-Exercise needs to be improved. Next, there is a need for education on how to integrate an online program within physiotherapy.

The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15–55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days.

Military personnel face significant physical and mental demands, making continuous physiological monitoring essential for understanding health status, managing long-term health risks, and predicting a soldier's readiness to perform in military operations. Recent advancements in wearable technology enable the tracking of biomarkers and psychophysiological indicators, yet current approaches remain fragmented, often focusing on isolated health outcomes rather than comprehensive, actionable insights. This perspective article reviews overarching theoretical health models and examines statistical modeling approaches to better capture the multidimensional nature of health and readiness. Building on these insights, a vision is presented for developing a military health and readiness monitoring system that integrates wearable technology with tailored health indicators and outcomes, aligned with the specific demands of military tasks. The role of advanced tools, such as Large Language Models (LLMs) and Knowledge Graphs in contextualizing health data with operational demands is highlighted, offering a pathway to more accurate and actionable assessments of readiness. This vision outlines key considerations for future development, aiming to empower service members and military leadership with effective tools for health and readiness management.

The emergence of wearable sensors that allow for unobtrusive monitoring of physiological and behavioural patterns introduces new opportunities to study the impact of stress in a real-world context. This study explores to what extent within-subject trends in daily Heart Rate Variability (HRV) and daily HRV fluctuations are associated with longitudinal changes in stress, depression, anxiety, and somatisation. Nine Dutch police officers collected daily nocturnal HRV data using an Oura ring during 15–55 weeks. Participants filled in the Four-Dimensional Symptoms Questionnaire every 5 weeks. A sample of 47 five-week observations was collected and analysed using multiple regression. After controlling for trends in total sleep time, moderate-to-vigorous physical activity and alcohol use, an increasing trend in the seven-day rolling standard deviation of the HRV (HRVsd) was associated with increases in stress and somatisation over 5 weeks. Furthermore, an increasing HRV trend buffered against the association between HRVsd trend and somatisation change, undoing this association when it was combined with increasing HRV. Depression and anxiety could not be related to trends in HRV or HRVsd, which was related to observed floor effects. These results show that monitoring trends in daily HRV via wearables holds promise for automated stress monitoring and providing personalised feedback.