ArticleJournal of medical Internet research2018
Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study.
Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 21 citations in OpenAlex.
- The user experience of ambulatory assessment and mood monitoring in depression: a systematic review & meta-synthesis.NPJ digital medicine · 2025Article
- Beyond Detection: Towards Actionable Sensing Research in Clinical Mental Healthcare.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2024Article
- The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental Health.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2023Article
- Risk factors and digital interventions for anxiety disorders in college students: Stakeholder perspectives.World journal of clinical cases · 2023Review
- Using Health Forum Data to Assess User Needs for mHealth App Development: A Feasibility Study on Alzheimer's Disease.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Developing a Mobile App for Young Adults with Nonsuicidal Self-Injury: A Prototype Feedback Study.International journal of environmental research and public health · 2022Article
- Online mental health interventions designed for students in higher education: A user-centered perspective.Internet interventions · 2021Review
- Understanding Mental Health App Use Among Community College Students: Web-Based Survey Study.Journal of medical Internet research · 2021Article
- Patient and physician perspectives of a smartphone application for depression: a qualitative study.BMC psychiatry · 2021Article
- Understanding Participant Needs for Engagement and Attitudes towards Passive Sensing in Remote Digital Health Studies.International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare · 2020Article
- "Energy is a Finite Resource": Designing Technology to Support Individuals across Fluctuating Symptoms of Depression.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2020Article
- Provider Perspectives on Integrating Sensor-Captured Patient-Generated Data in Mental Health Care.Proceedings of the ACM on human-computer interaction · 2019Article
- Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations.JMIR mHealth and uHealth · 2019Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundToday, college students are dealing with depression at some of the highest rates in decades. As the primary mental health service provider, university counseling centers are limited in their capacity and efficiency to provide mental health care due to time constraints and reliance on students' self-reports. A mobile behavioral-sensing platform may serve as a solution to enhance the efficiency and accessibility of university counseling services.
objectiveThe main objectives of this study are to (1) understand the usefulness of a mobile sensing platform (ie, iSee) in improving counseling services and assisting students' self-management of their depression conditions, and (2) explore what types of behavioral targets (ie, meaningful information extracted from raw sensor data) and feedback to deliver from both clinician and students' perspectives.
methodsWe conducted semistructured interviews with 9 clinicians and 12 students with depression recruited from a counseling center at a large Midwestern university. The interviews were 40-50 minutes long and were audio recorded and transcribed. The interview data were analyzed using thematic analysis with an inductive approach. Clinician and student interviews were analyzed separately for comparison. The process of extracting themes involved iterative coding, memo writing, theme revisits, and refinement.
resultsFrom the clinician perspective, the mobile sensing platform helps to improve counseling service by providing objective evidence for clinicians and filling gaps in clinician-patient communication. Clinicians suggested providing students with their sensed behavioral targets organized around personalized goals. Clinicians also recommended delivering therapeutic feedback to students based on their sensed behavioral targets, including positive reinforcement, reflection reminders, and challenging negative thoughts. From the student perspective, the mobile sensing platform helps to ease continued self-tracking practices. Students expressed their need for integrated behavioral targets to understand correlations between behaviors and depression. They also pointed out that they would prefer to avoid seeing negative feedback.
conclusionsAlthough clinician and student participants shared views on the advantages of iSee in supporting university counseling, they had divergent opinions on the types of behavioral targets and feedback to be provided via iSee. This exploratory work gained initial insights into the design of a mobile sensing platform for depression management and informed a more conclusive research project for the future.
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