# Engagement With Meditation Apps: Cross-Sectional Survey of Use and Associations

## TL;DR

This study explores how much people use meditation apps and finds that most users engage minimally, with factors like education and openness influencing regular use.

## Contribution

The study identifies specific user and app-related factors associated with meditation app engagement using both self-reported and app-verified data.

## Key findings

- Most users of meditation apps engage minimally, with low real-world usage.
- Higher education, openness, and perceived app quality are strongly linked to increased engagement.
- Readiness to change and expectations for sleep and thriving also significantly influence app use.

## 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.