Characterizing Emotional State Transitions During Prolonged Use of a Mindfulness and Meditation App: Observational Study

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

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.

Sustaining the Quality of Life for University Employees with Obesity Using Mindfulness Activities and Work Engagement: A Quasi-Experimental Design

Using an e-calendar, a web-based intervention program, informal mindfulness activities, and work engagement, this study evaluated the sustainability of the quality of life for staff with obesity at a Malaysian public university. The participants were identified through the human resources department of the university. The inclusion criteria required an age of 20–59 years and BMI ≥ 25. The exclusion criteria were pregnancy, the use of weight loss pills or supplements that can influence weight, chronic illness, and the use of medication that requires physician monitoring. Thirty-one university staff were assessed for quality of life using a within-subject repeated-measures design. The participants were asked to use the study website for 10 to 15 min/day for 36 weeks. Data was captured by a pretest, posttest, and two follow-up surveys. The results showed an increase in the posttest mean scores for all domains representing the quality of life. As expected, three domains increased at follow-up 1 and were maintained at follow-up 2. This suggests that informal mindfulness practices and work engagement using an e-calendar are practical means to increase and sustain the quality of life of employees. In conclusion, the quality of life among university staff with obesity can be improved using informal mindfulness activities and work engagement, and an e-calendar is another alternative method of practicing mindfulness at home and at the workplace. The implications of this study are also discussed.