Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Mobile health applications (apps) provide an opportunity for easy, just-in-time, access to health promotion and self-management support. The number and breadth of health-related apps in the marketplace has provided a programmatic resource with immense potential for public health. However, poor user engagement with these apps remains a significant unresolved challenge. Objectives: Given the information on when a user might benefit from which type of support, the primary aim of this quality improvement study was to assess the effect of offering this support via a push notification containing a tailored health message versus not sending a push notification on proximal engagement with the app. Secondary aims examined whether this effect varies by number of weeks in the program, day of the week, and time of day. Methods: The quality improvement study analyzes the causal effects of push notifications on proximal engagement in 1,255 users of a commercial workplace wellbeing intervention product over 89 days. The test application employs a micro-randomized trial (MRT) design to send push notifications. At one of six available times per day (8:30AM, 12:30PM, 5:30PM, 6:30PM, 7:30PM or 8:30PM; selected randomly), available users were randomized with equal probability to be sent or not sent a push notification containing a tailored health message. Availability rules were pre-specified and depended on time since the previous sent push notification, time since previous user engagement with the app, and day of the week. Push notifications contained health messages tailored to the user as well as to the user’s current context. The primary outcome was whether the user engaged with the app over the next 24 hours. A generalization of log-linear regression analysis, adapted for use with data arising from a MRT, was used to examine the effect of sending a push vs not sending a push on the probability of engagement over the next 24 hours. Results: Users were 3.9% more likely to engage with the app in the next 24 hours when a tailored health message was sent vs when it was not sent (95%CI, 1.01 to 1.08; p<0.05). The effect of sending the message attenuated over the course of the study, but not significantly (p=0.84). When sent a tailored health message on weekends, users were 8.7% more likely to engage with the app (95% CI, 1.01 to 1.17; p<0.05); whereas on weekdays users were 2.5% more likely to engage with the app (95% CI, 0.98 to 1.07; p=0.27). The effect of sending a tailored health message was greatest at 12:30PM on weekends: 11.8% more likely to engage (90% CI, 1.02 to 1.13; p<0.10). Conclusion: Sending a push notification containing a tailored health message was associated with greater engagement in a mobile health app. Results suggested that users are more likely to engage with the app within 24 hours when push notifications are sent at mid-day on weekends. This has potential implications for other mobile health apps that rely on user-engagement and self-monitoring.

The utility of heart rate variability (HRV) for characterizing psychological stress is primarily impacted by methodological considerations such as study populations, experienced versus induced stress, and method of stress assessment. Here, we review studies on the associations between HRV and psychological stress, examining the nature of stress, ways stress was assessed, and HRV metrics used. The review was performed according to the PRISMA guidelines on select databases. Studies that examined the HRV-stress relationship via repeated measurements and validated psychometric instruments were included (n = 15). Participant numbers and ages ranged between 10 and 403 subjects and 18 and 60 years, respectively. Both experimental (n = 9) and real-life stress (n = 6) have been explored. While RMSSD was the most reported HRV metric (n = 10) significantly associated with stress, other metrics, including LF/HF (n = 7) and HF power (n = 6) were also reported. Various linear and nonlinear HRV metrics have been utilized, with nonlinear metrics used less often. The most frequently used psychometric instrument was the State-Trait Anxiety Inventory (n = 10), though various other instruments have been reported. In conclusion, HRV is a valid measure of the psychological stress response. Standard stress induction and assessment protocols combined with validated HRV measures in different domains will improve the validity of findings.

JMIR Human Factors - a leading peer-reviewed ehealth journal

Mobile health (m-Health) resources are emerging as a significant tool to overcome mental health support access barriers due to their ability to rapidly reach and provide support to individuals in need of mental health support. m-Health provides an approach to adapt and initiate mental health support at precise moments, when they are most likely to be effective for the individual. However, poor adoption of mental health apps in the real world suggests that new approaches to optimising the quality of m-Health interventions are critically needed in order to realise the potential translational benefits for mental health support. The micro-randomised trial is an experimental approach for optimising and adapting m-Health resources. This trial design provides data to construct and optimise m-Health interventions. The data can be used to inform when and what type of m-Health interventions should be initiated, and thus serve to integrate interventions into daily routines with precision. Here, we illustrate this approach in a case study, review implementation issues that need to be considered while conducting an MRT, and provide a checklist for mental health m-Health intervention developers.

Despite the unprecedented access to self-monitoring health apps, lack of optimal user engagement remains a significant challenge. Push notification prompts with contextually tailored messages offers a promising strategy to improve engagement. To increase the efficacy of push-notifications on engaging individuals with health apps, greater attention to the modifiable components of push notifications that influence responsiveness is needed. This study examines the effect of message content and frequency of push notifications, along with past app usage on responding to notifications within 24 h, and engaging with self-monitoring in JOOL Health smartphone app. Mixed models were applied on a de-identified data set of 18,000 contextually tailored push notifications sent by JOOL Health App to 1414 participants. The content in sent messages on behavioural topics were mapped into either tailored suggestions or tailored insights. Our findings suggest that push notifications with tailored suggestions were more effective overall in encouraging self-monitoring, but amongst frequent app users, push-notifications containing insights was associated with greater self-monitoring. People who were not using the app as frequently were less likely to respond to a prompt. This study suggests that push-notification content does have an impact on subsequent use of key app features, and app developers should consider what content is likely to work best for who, and under what circumstances. Secondary data-analysis of commercial apps presents a unique opportunity to elucidate and optimize health behaviors.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet