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• W4210305655 abstract "<sec> <title>BACKGROUND</title> During the COVID-19 pandemic, people had to adapt their daily life routines to the currently implemented public health measures, which is likely to have resulted in a lack of in-person social interactions, physical activity, or sleep. Such changes can have a significant impact on mental health. Mobile sensing apps can passively record the daily life routines of people, thus making them aware of maladaptive behavioral adjustments to the pandemic. </sec> <sec> <title>OBJECTIVE</title> This study aimed to explore the views of people on mobile sensing apps that passively record behaviors and their potential to increase awareness and helpfulness for self-managing mental health during the pandemic. </sec> <sec> <title>METHODS</title> We conducted an anonymous web-based survey including people with and those without mental disorders, asking them to rate the helpfulness of mobile sensing apps for the self-management of mental health during the COVID-19 pandemic. The survey was conducted in May 2020. </sec> <sec> <title>RESULTS</title> The majority of participants, particularly those with a mental disorder (n=106/148, 72%), perceived mobile sensing apps as very or extremely helpful for managing their mental health by becoming aware of maladaptive behaviors. The perceived helpfulness of mobile sensing apps was also higher among people who experienced a stronger health impact of the COVID-19 pandemic (<i>β</i>=.24; 95% CI 0.16-0.33; <i>P</i>&lt;.001), had a better understanding of technology (<i>β</i>=.17; 95% CI 0.08-0.25; <i>P</i>&lt;.001), and had a higher education (<i>β</i>=.1; 95% CI 0.02-0.19; <i>P</i>=.02). </sec> <sec> <title>CONCLUSIONS</title> Our findings highlight the potential of mobile sensing apps to assist in mental health care during the pandemic. </sec>" @default.
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• W4210305655 date "2020-09-08" @default.
• W4210305655 modified "2023-09-27" @default.
• W4210305655 title "Mobile Sensing Apps and Self-management of Mental Health During the COVID-19 Pandemic: Web-Based Survey (Preprint)" @default.
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• W4210305655 doi "https://doi.org/10.2196/preprints.24180" @default.
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