The Potential for Digital Phenotyping in Understanding Mindfulness App Engagement Patterns: A Pilot Study

被引:1
|
作者
Gray, Lucy [1 ]
Marcynikola, Natalia [1 ]
Barnett, Ian [2 ]
Torous, John [1 ,3 ]
机构
[1] Harvard Med Sch, Beth Israel Deaconess Med Ctr, Div Digital Psychiat, Boston, MA USA
[2] Univ Penn, Perelman Sch Med, Dept Biostat Epidemiol & Informat, Div Biostat, Philadelphia, PA USA
[3] Beth Israel Deaconess Med Ctr, Div Digital Psychiat, 330 Brookline Ave, Boston, MA 02215 USA
来源
关键词
digital phenotyping; engagement; mindfulness; mobile health (mHealth);
D O I
10.1089/jicm.2023.0698
中图分类号
R [医药、卫生];
学科分类号
10 ;
摘要
Background: Low app engagement is a central barrier to digital mental health efficacy. With mindfulness-based mental health apps growing in popularity, there is a need for new understanding of factors influencing engagement. This study utilized digital phenotyping to understand real-time patterns of engagement around app-based mindfulness. Different engagement metrics are presented that measure both the total number of app-based activities participants completed each week, as well as the proportion of days that participants engaged with the app each week.Method: Data were derived from two iterations of a four-week study exploring app engagement in college students (n = 169). This secondary analysis investigated the relationships between general and mindfulness-based app engagement with passive data metrics (sleep duration, home time, and screen duration) at a weekly level, as well as the relationship between demographics and engagement. Additional clinically focused analysis was performed on three case studies of participants with high mindfulness activity completion.Results: Demographic variables such as gender, race/ethnicity, and age lacked a significant association with mindfulness app-based engagement. Passive data variables such as sleep and screen duration were significant predictors for different metrics of general and mindfulness-based app engagement at a weekly level. There was a significant interaction effect for screen duration between the number of mindfulness activities completed and whether or not the participant received a mindfulness notification. K-means clusters analyses using passive data features to predict mindfulness activity completion had low performance.Conclusions: While there are no simple solutions to predicting engagement with mindfulness apps, utilizing digital phenotyping approaches at a population and personal level offers new potential. The signal from digital phenotyping warrants more investigation; even small increases in engagement with mindfulness apps may have a tremendous impact given their already high prevalence of engagement, availability, and potential to engage patients across demographics.
引用
收藏
页码:1108 / 1115
页数:8
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