Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term Maintenance
Forming a habit of practicing mindfulness meditation around the same time of day is one strategy that may support long-term maintenance and in turn improve physical and mental health. The purpose of this study was to identify common patterns in the time of day of meditation associated with long-term...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Behavioral Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-328X/15/3/381 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849341755114127360 |
|---|---|
| author | Rylan Fowers Aurel Coza Yunro Chung Hassan Ghasemzadeh Sara Cloonan Jennifer Huberty Vincent Berardi Chad Stecher |
| author_facet | Rylan Fowers Aurel Coza Yunro Chung Hassan Ghasemzadeh Sara Cloonan Jennifer Huberty Vincent Berardi Chad Stecher |
| author_sort | Rylan Fowers |
| collection | DOAJ |
| description | Forming a habit of practicing mindfulness meditation around the same time of day is one strategy that may support long-term maintenance and in turn improve physical and mental health. The purpose of this study was to identify common patterns in the time of day of meditation associated with long-term meditation app use to assess the importance of temporal consistency for maintaining meditation over time. App usage data were collected from a random sample of 15,000 users who had paid for an annual membership to a commercial meditation app in 2017. We constructed three measures of temporal consistency in the time of day of meditation sessions in order to categorize users into one of three behavioral phenotypes: Consistent, Inconsistent, or Indeterminate. Panel data models were used to compare temporal consistency across the three phenotypes. Of the 4205 users (28.0%) in the final analytic sample, 1659 (39.5%) users were Consistent, 2326 (55.3%) were Inconsistent, and 220 users (5.23%) were Indeterminate. Panel models confirmed that temporal consistency had contrasting relationships with meditation maintenance among these three phenotypes (<i>p</i> < 0.01). These findings revealed that temporal consistency was associated with meditation maintenance for less than half of app users, which suggests that other behavioral mechanisms in addition to temporally consistent habits can support meditation app use over time. This has important implications for researchers and policymakers trying to promote the maintenance of meditation and other complex health behaviors, such as increased physical activity and healthier diets. |
| format | Article |
| id | doaj-art-334e29ac7b2a42e39799ad8b71ab591d |
| institution | Kabale University |
| issn | 2076-328X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Behavioral Sciences |
| spelling | doaj-art-334e29ac7b2a42e39799ad8b71ab591d2025-08-20T03:43:34ZengMDPI AGBehavioral Sciences2076-328X2025-03-0115338110.3390/bs15030381Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term MaintenanceRylan Fowers0Aurel Coza1Yunro Chung2Hassan Ghasemzadeh3Sara Cloonan4Jennifer Huberty5Vincent Berardi6Chad Stecher7Select Health, Murray, UT 84123, USACorporate Engagement & Strategic Partnerships, Arizona State University, Tempe, AZ 85281, USACollege of Health Solutions, Arizona State University, Phoenix, AZ 85004, USACollege of Health Solutions, Arizona State University, Phoenix, AZ 85004, USADepartment of Psychology, University of Georgia, Athens, GA 30602, USAFit Minded Inc., Phoenix, AZ 85032, USACrean College of Health and Behavioral Science, Chapman University, Orange, CA 92866, USACollege of Health Solutions, Arizona State University, Phoenix, AZ 85004, USAForming a habit of practicing mindfulness meditation around the same time of day is one strategy that may support long-term maintenance and in turn improve physical and mental health. The purpose of this study was to identify common patterns in the time of day of meditation associated with long-term meditation app use to assess the importance of temporal consistency for maintaining meditation over time. App usage data were collected from a random sample of 15,000 users who had paid for an annual membership to a commercial meditation app in 2017. We constructed three measures of temporal consistency in the time of day of meditation sessions in order to categorize users into one of three behavioral phenotypes: Consistent, Inconsistent, or Indeterminate. Panel data models were used to compare temporal consistency across the three phenotypes. Of the 4205 users (28.0%) in the final analytic sample, 1659 (39.5%) users were Consistent, 2326 (55.3%) were Inconsistent, and 220 users (5.23%) were Indeterminate. Panel models confirmed that temporal consistency had contrasting relationships with meditation maintenance among these three phenotypes (<i>p</i> < 0.01). These findings revealed that temporal consistency was associated with meditation maintenance for less than half of app users, which suggests that other behavioral mechanisms in addition to temporally consistent habits can support meditation app use over time. This has important implications for researchers and policymakers trying to promote the maintenance of meditation and other complex health behaviors, such as increased physical activity and healthier diets.https://www.mdpi.com/2076-328X/15/3/381behavior maintenancemindfulness meditationtemporal consistencyhabit formationapp engagement |
| spellingShingle | Rylan Fowers Aurel Coza Yunro Chung Hassan Ghasemzadeh Sara Cloonan Jennifer Huberty Vincent Berardi Chad Stecher Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term Maintenance Behavioral Sciences behavior maintenance mindfulness meditation temporal consistency habit formation app engagement |
| title | Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term Maintenance |
| title_full | Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term Maintenance |
| title_fullStr | Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term Maintenance |
| title_full_unstemmed | Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term Maintenance |
| title_short | Identifying Common Patterns in the Time of Day of Mindfulness Meditation Associated with Long-Term Maintenance |
| title_sort | identifying common patterns in the time of day of mindfulness meditation associated with long term maintenance |
| topic | behavior maintenance mindfulness meditation temporal consistency habit formation app engagement |
| url | https://www.mdpi.com/2076-328X/15/3/381 |
| work_keys_str_mv | AT rylanfowers identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance AT aurelcoza identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance AT yunrochung identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance AT hassanghasemzadeh identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance AT saracloonan identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance AT jenniferhuberty identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance AT vincentberardi identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance AT chadstecher identifyingcommonpatternsinthetimeofdayofmindfulnessmeditationassociatedwithlongtermmaintenance |