App-based meditation habits maintain reductions in depression symptoms among autistic adults.

LAY ABSTRACT: Existing research has identified an increased risk of depression among autistic adults, which can negatively impact their adaptive functioning abilities and socioeconomic outcomes. Mobile app-based meditation is a feasible, accessible, and effective self-care solution for depression among neurotypical adults, but there is limited evidence for the long-term benefits of app-based meditation among autistic adults. Habits are a key behavioral strategy for maintaining behavior change, and anchoring is one effective habit formation intervention that has yet to be tested among autistic adults. This study demonstrates that it is both feasible and effective to integrate the anchoring habit formation strategy into an app-based meditation intervention for establishing meditation habits among autistic adults. In addition, the study shows that app-based meditation habits were successful at maintaining reductions in depressive symptoms over 6 months. These results demonstrate the power of anchoring-based habit formation interventions for establishing healthy habits among autistic adults, which offers a promising behavioral intervention technique for establishing other healthy habits among autistic adults. The study also shows that app-based meditation habits are an effective long-term self-care solution for managing depressive symptoms among autistic adults that should be used by mental health providers and policymakers. Future research should test this combined anchoring and app-based meditation intervention technique among larger samples of autistic adults and over longer durations to better understand the mechanisms underlying the success of this intervention.

Mindfulness Meditation App Abandonment During the COVID-19 Pandemic: An Observational Study.

Objectives: Mindfulness meditation apps are used by millions of adults in the USA to improve mental health. However, many new app subscribers quickly abandon their use. The purpose of this study was to determine the behavioral, demographic, and socioeconomic factors associated with the abandonment of meditation apps during the COVID-19 pandemic. Method: A survey was distributed to subscribers of a popular meditation app, Calm, at the start of the COVID-19 pandemic in March 2020 that assessed meditation app behavior and meditation habit strength, as well as demographic and socioeconomic information. App usage data were also collected from the start of each participant's subscription until May 2021. A total of 3275 respondents were included in the analyses. Participants were divided into three cohorts according to their subscription start date: (1) long-term subscribers (> 1 year before pandemic start), (2) pre-pandemic subscribers (< 4 months before pandemic start), and (3) pandemic subscribers (joined during the pandemic). Results: Meditating after an existing routine was associated with a lower risk of app abandonment for pre-pandemic subscribers (hazard ratio = 0.607, 95% CI: 0.422, 0.874; p = 0.007) and for pandemic subscribers (hazard ratio = 0.434, 95% CI: 0.285, 0.66; p < 0.001). Additionally, meditating "whenever I can" was associated with lower risk of abandonment among pandemic subscribers (hazard ratio = 0.437, 95% CI: 0.271, 0.706; p < 0.001), and no behavioral factors were significant predictors of app abandonment among the long-term subscribers. Conclusions: These results show that combining meditation with an existing daily routine was a commonly utilized strategy for promoting persistent meditation app use during the COVID-19 pandemic for many subscribers. This finding supports existing evidence that pairing new behaviors with an existing routine is an effective method for establishing new health habits. Preregistration: This study is not pre-registered.

Time of Day Preferences and Daily Temporal Consistency for Predicting the Sustained Use of a Commercial Meditation App: Longitudinal Observational Study.

BACKGROUND: The intensive data typically collected by mobile health (mHealth) apps allows factors associated with persistent use to be investigated, which is an important objective given users' well-known struggles with sustaining healthy behavior. OBJECTIVE: Data from a commercial meditation app (n=14,879; 899,071 total app uses) were analyzed to assess the validity of commonly given habit formation advice to meditate at the same time every day, preferably in the morning. METHODS: First, the change in probability of meditating in 4 nonoverlapping time windows (morning, midday, evening, and late night) on a given day over the first 180 days after creating a meditation app account was calculated via generalized additive mixed models. Second, users' time of day preferences were calculated as the percentage of all meditation sessions that occurred within each of the 4 time windows. Additionally, the temporal consistency of daily meditation behavior was calculated as the entropy of the timing of app usage sessions. Linear regression was used to examine the effect of time of day preference and temporal consistency on two outcomes: (1) short-term engagement, defined as the number of meditation sessions completed within the sixth and seventh month of a user's account, and (2) long-term use, defined as the days until a user's last observed meditation session. RESULTS: Large reductions in the probability of meditation at any time of day were seen over the first 180 days after creating an account, but this effect was smallest for morning meditation sessions (63.4% reduction vs reductions ranging from 67.8% to 74.5% for other times). A greater proportion of meditation in the morning was also significantly associated with better short-term engagement (regression coefficient B=2.76, P<.001) and long-term use (B=50.6, P<.001). The opposite was true for late-night meditation sessions (short-term: B=-2.06, P<.001; long-term: B=-51.7, P=.001). Significant relationships were not found for midday sessions (any outcome) or for evening sessions when examining long-term use. Additionally, temporal consistency in the performance of morning meditation sessions was associated with better short-term engagement (B=-1.64, P<.001) but worse long-term use (B=55.8, P<.001). Similar-sized temporal consistency effects were found for all other time windows. CONCLUSIONS: Meditating in the morning was associated with higher rates of maintaining a meditation practice with the app. This is consistent with findings from other studies that have hypothesized that the strength of existing morning routines and circadian rhythms may make the morning an ideal time to build new habits. In the long term, less temporal consistency in meditation sessions was associated with more persistent app use, suggesting there are benefits from maintaining flexibility in behavior performance. These findings improve our understanding of how to promote enduring healthy lifestyles and can inform the design of mHealth strategies for maintaining behavior changes.

Using mobile meditation app data to predict future app engagement: an observational study.

OBJECTIVE: Meditation with mobile apps has been shown to improve mental and physical health. However, regular, long-term meditation app use is needed to maintain these health benefits, and many people have a difficult time maintaining engagement with meditation apps over time. Our goal was to determine the length of the timeframe over which usage data must be collected before future app abandonment can be predicted accurately in order to better target additional behavioral support to those who are most likely to stop using the app. METHODS: Data were collected from a randomly drawn sample of 2600 new subscribers to a 1-year membership of the mobile app Calm, who started using the app between July and November of 2018. App usage data contained the duration and start time of all meditation sessions with the app over 365 days. We used these data to construct the following predictive model features: total daily sessions, total daily duration, and a measure of temporal similarity between consecutive days based on the dynamic time warping (DTW) distance measure. We then fit random forest models using increasingly longer periods of data after users subscribed to Calm to predict whether they performed any meditation sessions over 2-week intervals in the future. Model fit was assessed using the area under the receiver operator characteristic curve (AUC), and an exponential growth model was used to determine the minimal amount of data needed to reach an accurate prediction (95% of max AUC) of future engagement. RESULTS: After first subscribing to Calm, 83.1% of the sample used the Calm app on at least 1 more day. However, by day 350 after subscribing, 58.0% of users abandoned their use of the app. For the persistent users, the average number of daily sessions was 0.33 (SD = 0.02), the average daily duration of meditating was 3.93 minutes (SD = 0.25), and the average DTW distance to the previous day was 1.50 (SD = 0.17). The exponential growth models revealed that an average of 64 days of observations after subscribing to Calm are needed to reach an accurate prediction of future app engagement. DISCUSSION: Our results are consistent with existing estimates of the time required to develop a new habit. Additionally, this research demonstrates how to use app usage data to quickly and accurately predict the likelihood of users' future app abandonment. This research allows future researchers to better target just-in-time interventions towards users at risk of abandonment.

Using Personalized Anchors to Establish Routine Meditation Practice With a Mobile App: Randomized Controlled Trial.

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.

Identifying App-Based Meditation Habits and the Associated Mental Health Benefits: Longitudinal Observational Study.

BACKGROUND: Behavioral habits are often initiated by contextual cues that occur at approximately the same time each day; so, it may be possible to identify a reflexive habit based on the temporal similarity of repeated daily behavior. Mobile health tools provide the detailed, longitudinal data necessary for constructing such an indicator of reflexive habits, which can improve our understanding of habit formation and help design more effective mobile health interventions for promoting healthier habits. OBJECTIVE: This study aims to use behavioral data from a commercial mindfulness meditation mobile phone app to construct an indicator of reflexive meditation habits based on temporal similarity and estimate the association between temporal similarity and meditation app users' perceived health benefits. METHODS: App-use data from June 2019 to June 2020 were analyzed for 2771 paying subscribers of a meditation mobile phone app, of whom 86.06% (2359/2771) were female, 72.61% (2012/2771) were college educated, 86.29% (2391/2771) were White, and 60.71% (1664/2771) were employed full-time. Participants volunteered to complete a survey assessing their perceived changes in physical and mental health from using the app. Receiver operating characteristic curve analysis was used to evaluate the ability of the temporal similarity measure to predict future behavior, and variable importance statistics from random forest models were used to corroborate these findings. Logistic regression was used to estimate the association between temporal similarity and self-reported physical and mental health benefits. RESULTS: The temporal similarity of users' daily app use before completing the survey, as measured by the dynamic time warping (DTW) distance between app use on consecutive days, significantly predicted app use at 28 days and at 6 months after the survey, even after controlling for users' demographic and socioeconomic characteristics, total app sessions, duration of app use, and number of days with any app use. In addition, the temporal similarity measure significantly increased in the area under the receiver operating characteristic curve (AUC) for models predicting any future app use in 28 days (AUC=0.868 with DTW and 0.850 without DTW; P<.001) and for models predicting any app use in 6 months (AUC=0.821 with DTW and 0.802 without DTW; P<.001). Finally, a 1% increase in the temporal similarity of users' daily meditation practice with the app over 6 weeks before the survey was associated with increased odds of reporting mental health improvements, with an odds ratio of 2.94 (95% CI 1.832-6.369). CONCLUSIONS: The temporal similarity of the meditation app use was a significant predictor of future behavior, which suggests that this measure can identify reflexive meditation habits. In addition, temporal similarity was associated with greater perceived mental health benefits, which demonstrates that additional mental health benefits may be derived from forming reflexive meditation habits.

Associations Between Rural or Urban Status, Health Outcomes and Behaviors, and COVID-19 Perceptions Among Meditation App Users: Longitudinal Survey Study.

BACKGROUND: Rural and urban differences in health outcomes and behaviors have been well-documented, with significant rural health disparities frequently highlighted. Mobile health (mHealth) apps, such as meditation apps, are a novel method for improving health and behaviors. These apps may be a critical health promotion strategy during the COVID-19 pandemic and could potentially be used to address rural health disparities. However, limited research has assessed whether meditation app health outcomes are associated with rural and urban residence, and it is unclear whether disparities in health and behaviors between rural and urban populations would persist among meditation app users. OBJECTIVE: We aimed to explore associations between rural or urban status, psychological outcomes, and physical activity among users of a mobile meditation app. We further aimed to explore associations between rural or urban status and perceived effects of COVID-19 on stress, mental health, and physical activity, and to explore changes in these outcomes in rural versus urban app users over time. METHODS: This study was a secondary analysis of a national survey conducted among subscribers to the meditation app Calm. Eligible participants completed online baseline surveys from April to June 2020, and follow-up surveys from June to September 2020, assessing demographics, psychological outcomes, physical activity, and perceived effects of COVID-19 on stress, mental health, and physical activity. RESULTS: Participants (N=8392) were mostly female (7041/8392, 83.9%), non-Hispanic (7855/8392, 93.6%), and White (7704/8392, 91.8%); had high socioeconomic status (income ≥US $100,000: 4389/8392, 52.3%; bachelor's degree or higher: 7251/8392, 86.4%); and resided in a metropolitan area core (rural-urban commuting area code 1: 7192/8392, 85.7%). Rural or urban status was not associated with baseline stress, depression, anxiety, pre-COVID-19 and current physical activity, or perceived effects of COVID-19 on stress, mental health, and physical activity. Repeated-measures models showed overall decreases in depression, anxiety, and perceived effects of COVID-19 on physical activity from baseline to follow-up, and no significant changes in stress or perceived effects of COVID-19 on stress and mental health over time. Models also showed no significant main effects of rural or urban status, COVID-19 statewide prevalence at baseline, or change in COVID-19 statewide prevalence. CONCLUSIONS: We did not find associations between rural or urban status and psychological outcomes (ie, stress, depression, and anxiety), physical activity, or perceived effects of COVID-19 on stress, mental health, and physical activity. Rural or urban status does not appear to drive differences in outcomes among meditation app users, and the use of mHealth apps should continue to be explored as a health promotion strategy in both rural and urban populations. Furthermore, our results did not show negative cumulative effects of COVID-19 on psychological outcomes and physical activity among app users in our sample, the majority of whom were urban, White, female, and of high socioeconomic status. Further research is needed to investigate meditation app use as a health promotion strategy in rural and urban populations.

Evaluation of Mood Check-in Feature for Participation in Meditation Mobile App Users: Retrospective Longitudinal Analysis.

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.

The Effect of Meditation and Physical Activity on the Mental Health Impact of COVID-19-Related Stress and Attention to News Among Mobile App Users in the United States: Cross-sectional Survey.

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.