Engagement With Meditation Apps: Cross-Sectional Survey of Use and Associations.
Julia Adams, Jonathan N. Davies, Prai Wattanatakulchat, Julieta Galante, Felicity Miller, Simon D'Alfonso, Nicholas T. van Dam
Journal of Medical Internet Research February 2, 2026 DOI: 10.2196/71960 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Cross-sectional survey Longitudinal Peer reviewed |
|---|---|
| Sample size | 536 |
| Population | Recent meditation app users across 5 English-speaking countries |
| Topics | Meditation |
| Keywords | Behavior change Engagement Meditation apps |
| Key findings | Users who are more educated, open to new experiences, and have stronger expectations that meditation apps will help them are more likely to engage regularly with the apps. |
Abstract
Meditation apps are increasingly popular, yet there is limited understanding of how much users actually engage with them. While meditation apps show promise for supporting mental health, engagement in real-world settings appears to be notably low. The patterns of app use and the factors that influence usage remain relatively unclear. This study aims to examine the extent of meditation app use and the factors associated with user engagement. We conducted a cross-sectional survey of 536 recent meditation app users across 5 English-speaking countries. Engagement data were collected via self-report and app-verified screenshots. Assessed factors included user characteristics (age, education, income, sex, country, personality, self-efficacy, readiness and expectations for change, self-compassion, and quality of life), mental health (distress, well-being, life satisfaction, anxiety, depression, support, and stress), and app-related elements (therapeutic alliance, appeal, functionality, aesthetics, information, quality, and perceived impact). The 4 outcome variables representing engagement were app-verified minutes, self-reported minutes, app-verified minutes per year (adjusted for app download date), and self-reported minutes per year (adjusted for app download date). Associations between app use and variables of interest were examined using correlations. Factors with significant associations were then included in multivariable regression models to identify those most strongly associated with engagement. Age (ρ=0.13-0.15, PPFDR, where FDR is false discovery rate), expectations for sleep (ρ=0.12-0.33, PFDR<.05), and expectations for thriving (ρ=0.12-0.18, PFDR<.05) were associated with all outcome measures except adjusted objective minutes. Readiness to change was associated with all outcome measures (ρ=0.24-0.33, PFDR<.05). Among app factors, appeal (ρ=0.18-0.23, PFDR<.05) and perceived impact (ρ=0.23-0.32, PFDR<.05) were associated with all outcome measures except adjusted self-report minutes, while perceived quality (r=0.28-0.51, PFDR<.05) was associated with all outcome measures. Robust linear regressions showed that greater readiness to change (β=0.005-0.026, P=.006-.02), higher education level (β=0.029-0.540, P<.001), and higher openness (β=0.004-0.010, P=.008-.03) were associated with increased engagement. Additionally, greater expectations for sleep (β=0.004-0.009, P=.02-.04), greater expectation match (β=0.023, P=.03), and higher perceived app quality (β=0.008-0.042, P=.001-.01) were uniquely associated with increased engagement. Most individuals who download meditation apps engage minimally. Our findings suggest that users who are more educated, open to new experiences, and hold strong beliefs in the effectiveness of meditation apps are more likely to use them regularly. Longitudinal studies are needed to examine patterns of use and strengthen causal inferences.
Comparable studies
Other cross-sectional and survey studies on meditation, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Construct Validity of the Five Facet Mindfulness Questionnaire in Meditating and Nonmeditating Samples Experienced meditators and nonmeditating comparison groups | 2008 | Cross-sectional study | |
| Neural Correlates of Dispositional Mindfulness During Affect Labeling Adult participants | 2007 | Observational cross-sectional | n = 27 |
| Assessing mindfulness in children and adolescents: Development and validation of the Child and Adolescent Mindfulness Measure (CAMM). School-aged children and adolescents | 2011 | Cross-sectional validation study | n = 1,413 |
| Mindfulness and self-compassion as predictors of psychological wellbeing in long-term meditators and matched nonmeditators Experienced meditators and demographically matched nonmeditators | 2012 | Cross-sectional study | n = 152 |
| Mechanisms of Action in the Inverse Relationship Between Mindfulness and Psychological Distress Undergraduates | 2008 | Cross-sectional, correlational |
Citations in the library
Cited by 2
Cites 22
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- Dose-response Relationship of Reported Lifetime Meditation Practice with Mental Health and Wellbeing: a Cross-sectional Study. Mindfulness 2022
- Prevalence and 20-year trends in meditation, yoga, guided imagery and progressive relaxation use among US adults from 2002 to 2022 Scientific Reports July 1, 2024
and 17 more in the library