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The Forced Swim Test as a Model of Depressive-like Behavior
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Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
Jingbo Meng1, Syed Ali Hussain1, David C Mohr2
1Department of Communication, Michigan State University, East Lansing, MI, United States.
Journal of Medical Internet Research
|July 20, 2018
Summary
Mobile sensing platforms can improve university mental health services by providing objective data for clinicians and aiding student self-management of depression. However, user preferences for feedback content vary.
Area of Science:
- Digital mental health
- Mobile health interventions
- Clinical psychology
Background:
- University students face high rates of depression.
- Counseling centers are limited by capacity and self-report reliance.
- Mobile behavioral sensing offers a potential solution for enhanced mental health care.
Purpose of the Study:
- Assess the utility of the iSee mobile sensing platform for depression management in university students.
- Explore clinician and student perspectives on ideal behavioral targets and feedback mechanisms.
Main Methods:
- Conducted semistructured interviews with 9 clinicians and 12 students with depression.
- Utilized thematic analysis with an inductive approach for data interpretation.
- Analyzed clinician and student interviews separately to identify divergent and convergent views.
Main Results:
- Clinicians see value in objective data and personalized feedback for students.
- Students desire integrated behavioral targets for self-management and prefer positive feedback.
- Both groups agree on the platform's potential but differ on specific feedback content.
Conclusions:
- Mobile sensing platforms show promise for supporting university counseling services.
- Divergent opinions on feedback content highlight the need for user-centered design.
- Findings inform future research on mobile health interventions for depression.
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