Full metadata
Title
Using Individual Characteristics and Habit Measures to Predict Meditation App Use Behavior
Description
Meditation app usage is associated with decreases in stress, anxiety, and depression symptoms. Many meditation app subscribers, however, quickly abandon or reduce their app usage. This dissertation presents three manuscripts which 1) determined the behavioral, demographic, and socioeconomic factors associated with the abandonment of a meditation app, Calm, during the COVID-19 pandemic, 2) determined which participant characteristics predicted meditation app usage in the first eight weeks after subscribing, and 3) determined if changes in stress, anxiety, and depressive symptoms from baseline to Week 8 predicted meditation app usage from Weeks 8-16. In Manuscript 1, a survey was distributed to Calm subscribers in March 2020 that assessed meditation app behavior and meditation habit strength, and demographic information. Cox proportional hazards regression models were estimated to assess time to app abandonment. In Manuscript 2, new Calm subscribers completed a baseline survey on participants’ demographic and baseline mental health information and app usage data were collected over 8 weeks. In Manuscript 3, new Calm subscribers completed a baseline and Week 8 survey on demographic and mental health information. App usage data were collected over 16 weeks. Regression models were used to assess app usage for Manuscripts 2 and 3. Findings from Manuscript 1 suggest meditating after an existing routine decreased risk of app abandonment for pre-pandemic subscribers and for pandemic subscribers. Additionally, meditating “whenever I can” decreased risk of abandonment among pandemic subscribers. No behavioral factors were significant predictors of app abandonment among the long-term subscribers. Findings from Manuscript 2 suggest men had more days of meditation than women. Mental health diagnosis increased average daily meditation minutes. Intrinsic motivation for meditation increased the likelihood of completing any meditation session, more days with meditation sessions, and more average daily meditation minutes. Findings from Manuscript 3 suggest improvements in stress increased average daily meditation minutes. Improvements in depressive symptoms decreased daily meditation minutes. Evidence from this three-manuscript dissertation suggests meditation cue, time of day, motivation, symptom changes, and demographic and socioeconomic variables may be used to predict meditation app usage.
Date Created
2022
Contributors
- Sullivan, Mariah (Author)
- Stecher, Chad (Thesis advisor)
- Huberty, Jennifer (Committee member)
- Buman, Matthew (Committee member)
- Larkey, Linda (Committee member)
- Chung, Yunro (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
119 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.171757
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: Ph.D., Arizona State University, 2022
Field of study: Exercise and Nutritional Sciences
System Created
- 2022-12-20 06:19:18
System Modified
- 2022-12-20 06:19:18
- 1 year 10 months ago
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