Background: The COVID-19 pandemic has been declared an international public health emergency, and it may have long-lasting effects on people’s mental health. There is a need to identify effective health behaviors to mitigate the negative mental health impact of COVID-19. Objective: The objectives of this study were to (1) examine the regional differences in mental health and COVID-19–related worry, attention to news, and stress, in light of the state-level prevalence of COVID-19 cases; (2) estimate the associations between mental health and COVID-19–related worry, attention to news, and stress and health behavior engagement (ie, physical activity, mindfulness meditation); and (3) explore the mediating effect of health behavior engagement on the associations between mental health and COVID-19–related worry, attention to news, and stress. Methods: A cross-sectional survey was distributed to a sample of US adult paying subscribers to the Calm app (data were collected from April 22 to June 3, 2020). The survey assessed COVID-19–related worry, attention to news, and stress; health behavior engagement; and mental health (ie, perceived stress, posttraumatic stress disorder, and anxiety and depression). Statistical analyses were performed using R software. Differences in COVID-19–related worry, attention to news, and stress and mental health by location were assessed using t tests and chi-square tests. Logistic and ordinary least squares models were used to regress mental health and health behavior on COVID-19–related worry, attention to news, and stress; moreover, causal mediation analysis was used to estimate the significance of the mediation effects. Results: The median age of the respondents (N=8392) was 47 years (SD 13.8). Participants in the Mid-Atlantic region (New Jersey, New York, and Pennsylvania) reported higher levels of stress, more severe depression symptoms, greater worry about COVID-19, paying more attention to COVID-19–related news, and more stress related to social distancing recommendations than participants living in other regions. The association between worry about COVID-19 and perceived stress was significantly mediated by changes in physical activity (P<.001), strength of meditation habit (P<.001), and stopping meditation (P=.046). The association between worry about COVID-19 and posttraumatic stress disorder symptoms was significantly mediated by changes in physical activity (P<.001) and strength of meditation habit (P<.001). Conclusions: Our findings describe the mental health impact of COVID-19 and outline how continued participation in health behaviors such as physical activity and mindfulness meditation reduce worsening of mental health due to the COVID-19 pandemic. These data have important implications for public health agencies and health organizations to promote the maintenance of health habits to reduce the residual mental health burden of the COVID-19 pandemic.

Background: Mobile health (mHealth) apps can promote physical activity; however, the pragmatic nature (ie, how well research translates into real-world settings) of these studies is unknown. The impact of study design choices, for example, intervention duration, on intervention effect sizes is also understudied. Objective: This review and meta-analysis aims to describe the pragmatic nature of recent mHealth interventions for promoting physical activity and examine the associations between study effect size and pragmatic study design choices. Methods: The PubMed, Scopus, Web of Science, and PsycINFO databases were searched until April 2020. Studies were eligible if they incorporated apps as the primary intervention, were conducted in health promotion or preventive care settings, included a device-based physical activity outcome, and used randomized study designs. Studies were assessed using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Pragmatic-Explanatory Continuum Indicator Summary-2 (PRECIS-2) frameworks. Study effect sizes were summarized using random effect models, and meta-regression was used to examine treatment effect heterogeneity by study characteristics. Results: Overall, 3555 participants were included across 22 interventions, with sample sizes ranging from 27 to 833 (mean 161.6, SD 193.9, median 93) participants. The study populations’ mean age ranged from 10.6 to 61.5 (mean 39.6, SD 6.5) years, and the proportion of males included across all studies was 42.8% (1521/3555). Additionally, intervention lengths varied from 2 weeks to 6 months (mean 60.9, SD 34.9 days). The primary app- or device-based physical activity outcome differed among interventions: most interventions (17/22, 77%) used activity monitors or fitness trackers, whereas the rest (5/22, 23%) used app-based accelerometry measures. Data reporting across the RE-AIM framework was low (5.64/31, 18%) and varied within specific dimensions (Reach=44%; Effectiveness=52%; Adoption=3%; Implementation=10%; Maintenance=12.4%). PRECIS-2 results indicated that most study designs (14/22, 63%) were equally explanatory and pragmatic, with an overall PRECIS-2 score across all interventions of 2.93/5 (SD 0.54). The most pragmatic dimension was flexibility (adherence), with an average score of 3.73 (SD 0.92), whereas follow-up, organization, and flexibility (delivery) appeared more explanatory with means of 2.18 (SD 0.75), 2.36 (SD 1.07), and 2.41 (SD 0.72), respectively. An overall positive treatment effect was observed (Cohen d=0.29, 95% CI 0.13-0.46). Meta-regression analyses revealed that more pragmatic studies (−0.81, 95% CI −1.36 to −0.25) were associated with smaller increases in physical activity. Treatment effect sizes were homogenous across study duration, participants’ age and gender, and RE-AIM scores. Conclusions: App-based mHealth physical activity studies continue to underreport several key study characteristics and have limited pragmatic use and generalizability. In addition, more pragmatic interventions observe smaller treatment effects, whereas study duration appears to be unrelated to the effect size. Future app-based studies should more comprehensively report real-world applicability, and more pragmatic approaches are needed for maximal population health impacts. Trial Registration: PROSPERO CRD42020169102; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=169102

Background: Mindfulness meditation smartphone apps may improve mental health but lack evidence-based behavioral strategies to encourage their regular use for attaining mental health benefits. In October 2019, the Calm mindfulness meditation app introduced a mood check-in feature, but its effects on participation in meditation have yet to be tested. Objective: The objective of this study was to investigate how a mood check-in feature impacts meditation behavior in Calm app subscribers. Methods: This was a retrospective longitudinal analysis of mobile app usage data from a random sample of first-time subscribers to the Calm app (n=2600) who joined in summer 2018 or summer 2019. The mood check-in feature allows users to rate their mood using an emoji after completing a meditation session and displays a monthly calendar of their past mood check-ins. Regression analyses were used to compare the rate of change in meditation behavior before and after the introduction of mood check-ins and to estimate how usage of mood check-ins was associated with individuals’ future meditation behavior (ie, intent-to-treat effects). Additional regression models examined the heterogenous effect of mood check-ins between subscribers who were active or inactive users prior to the introduction to mood check-ins (ie, above or below the median number of weeks with any meditation within their cohort). In order to confirm the specific associations between mood check-ins and meditation engagement, we modeled the direct relationship between the use of mood check-ins in previous weeks and subsequent meditation behavior (ie, treatment on the treated effects). Results: During the first 9 months of their subscription, the 2019 cohort completed an average of 0.482 more sessions per week (95% CI 0.309 to 0.655) than the 2018 cohort; however, across both cohorts, average weekly meditation declined (–0.033 sessions per week, 95% CI –0.035 to –0.031). Controlled for trends in meditation before mood check-ins and aggregate differences between the 2018 and 2019 samples, the time trend in the number of weekly meditation sessions increased by 0.045 sessions among the 2019 cohort after the introduction of mood check-ins (95% CI 0.039 to 0.052). This increase in meditation was most pronounced among the inactive subscribers (0.063 sessions, 95% CI 0.052 to 0.074). When controlled for past-week meditation, use of mood check-ins during the previous week was positively associated with the likelihood of meditating the following week (odds ratio 1.132, 95% CI 1.059 to 1.211); however, these associations were not sustained beyond 1 week. Conclusions: Using mood check-ins increases meditation participation in Calm app subscribers and may be especially beneficial for inactive subscribers. Mobile apps should consider incorporating mood check-ins to help better engage a wider range of users in app-based meditation, but more research is warranted.

Potent lifestyle interventions to increase moderate-to-vigorous physical activity (MVPA) are urgently needed for population-level chronic disease prevention. This trial tested the independent and joint effects of a mobile health system automating adaptive goal setting and immediate financial reinforcement for increasing daily walking among insufficiently active adults. Participants were randomized into a 2 (adaptive versus static goal setting) × 2 (immediate versus delayed financial incentive timing) condition factorial trial to increase walking. Principles of reinforcement and behavioral economics directed intervention design. Participants wore accelerometers daily that remotely measured MVPA bout-minutes of ≥3 minutes/day for 1 year. Primary outcomes were between-condition differences in: (1) engaging ≥1 bout of MVPA on each day and (2) on days with ≥1 bout, daily total MVPA minutes. Participants (N=512 adults, 133,876 day-level observations) were recruited between 2016 and 2018 and were 64.5% female, aged 18–60 years, 18.8% Hispanic, 6.1% African American, and 83% White. Mixed effects hurdle models tested treatment group × phase (time) interactions using an intent-to-treat approach in 2021. Engaging in any ambulatory MVPA was greater for Adaptive versus Static Goal groups (OR=2.34, 95% CI=2.10, 2.60 vs OR=1.66, 95% CI=1.50, 1.84; p<0.001) and for Immediate versus Static Reinforcement groups (OR=2.16 95% CI=1.94, 2.40 vs OR=1.77, 95% CI=1.59, 1.97; p<0.01). The Immediate Reinforcement group increased by 16.54 MVPA minutes/day whereas the Delayed Reinforcement group increased by 9.91 minutes/day (p<0.001). The combined Adaptive Goals + Immediate Reinforcement group increased by 16.52 MVPA minutes/day, significantly more than either Delayed Reinforcement group. This study offers automated and scalable behavior change strategies for increasing walking among adults most at risk for chronic diseases attributed to sedentary lifestyles. This study is registered at www.clinicaltrials.gov NCT02717663.

Background: Physical and mental health benefits can be attained from persistent, long-term performance of mindfulness meditation with a mobile meditation app, but in general, few mobile health app users persistently engage at a level necessary to attain the corresponding health benefits. Anchoring or pairing meditation with a mobile app to an existing daily routine can establish an unconsciously initiated meditation routine that may improve meditation persistence. Objective: The purpose of this study was to test the use of either personalized anchors or fixed anchors for establishing a persistent meditation app routine with the mobile app, Calm. Methods: We conducted a randomized controlled trial and randomly assigned participants to one of 3 study groups: (1) a personalized anchor (PA) group, (2) fixed anchor (FA) group, or (3) control group that did not use the anchoring strategy. All participants received app-delivered reminder messages to meditate for at least 10 minutes a day using the Calm app for an 8-week intervention period, and app usage data continued to be collected for an additional 8-week follow-up period to measure meditation persistence. Baseline, week 8, and week 16 surveys were administered to assess demographics, socioeconomic status, and changes in self-reported habit strength. Results: A total of 101 participants across the 3 study groups were included in the final analysis: (1) PA (n=56), (2) FA (n=49), and (3) control group (n=62). Participants were predominantly White (83/101, 82.2%), female (77/101, 76.2%), and college educated (ie, bachelor’s or graduate degree; 82/101, 81.2%). The FA group had a significantly higher average odds of daily meditation during the intervention (1.14 odds ratio [OR]; 95% CI 1.02-1.33; P=.04), and all participants experienced a linear decline in their odds of daily meditation during the 8-week intervention (0.96 OR; 95% CI 0.95-0.96; P<.001). Importantly, the FA group showed a significantly smaller decline in the linear trend of their odds of daily meditation during the 8-week follow-up (their daily trend increased by 1.04 OR from their trend during the intervention; 95% CI 1.01-1.06; P=.03). Additionally, those who more frequently adhered to their anchoring strategy during the intervention typically used anchors that occurred in the morning and showed a significantly smaller decline in their odds of daily meditation during the 8-week follow-up period (1.13 OR; 95% CI 1.02-1.35; P=.007). Conclusions: The FA group had more persistent meditation with the app, but participants in the FA or PA groups who more frequently adhered to their anchoring strategy during the intervention had the most persistent meditation routines, and almost all of these high anchorers used morning anchors. These findings suggest that the anchoring strategy can create persistent meditation routines with a mobile app. However, future studies should combine anchoring with additional intervention tools (eg, incentives) to help more participants successfully establish an anchored meditation routine. Trial Registration: ClinicalTrials.gov NCT04378530; https://clinicaltrials.gov/ct2/show/NCT04378530