Digital phenotyping for mental health of college students: a clinical review
Open accessAbstract
Experiencing continued growth in demand for mental health services among students, colleges are seeking digital solutions to increase access to care as classes shift to remote virtual learning during the COVID-19 pandemic. Using smartphones to capture real-time symptoms and behaviours related to mental illnesses, digital phenotyping offers a practical tool to help colleges remotely monitor and assess mental health and provide more customised and responsive care. This narrative review of 25 digital phenotyping studies with college students explored how this method has been deployed, studied and has impacted mental health outcomes. We found the average duration of studies to be 42 days and the average enrolled to be 81 participants. The most common sensor-based streams collected included location, accelerometer and social information and these were used to inform behaviours such as sleep, exercise and social interactions. 52% of the studies included also collected smartphone survey in some form and these were used to assess mood, anxiety and stress among many other outcomes. The collective focus on data that construct features related to sleep, activity and social interactions indicate that this field is already appropriately attentive to the primary drivers of mental health problems among college students. While the heterogeneity of the methods of these studies presents no reliable target for mobile devices to offer automated help—the feasibility across studies suggests the potential to use these data today towards personalising care. As more unified digital phenotyping research evolves and scales to larger sample sizes, student mental health centres may consider integrating these data into their clinical practice for college students.
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User research indicated that students do not like to be monitored and consider passive sensing tracking (eg, collection of location and acceleration data) as too invasive.
“However, this was chosen because user research indicated that students do not like to be monitored and consider passive sensing tracking (eg, collection of location and acceleration data) as too invasive. This is in line with studies examining the acceptability of sensing technology among university students [110,111].”
From Optimization of a Transdiagnostic Mobile Emotion Regulation Intervention for University Students: Protocol for a Microrandomized Trial (2023) · cites this paper as [110]
The Passive data section reports privacy concerns about sharing social data, and the Discussion reports high unacceptability of keystroke data among college students. But the review does not say students generally dislike being monitored or consider location and accelerometer sensing too invasive; its Discussion instead describes digital phenotyping for college mental health as feasible and acceptable. (LLM, conf=0.85)
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“This is in line with studies examining the acceptability of sensing technology among university students [110,111].”
Result
- Authors
- Melcher, J., Hays, R., & Torous, J.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Torous, John
- ORCID
- Torous, John
- Venue
- Evidence Based Mental Health
- Publisher
- BMJ
- Published
- 2020-09-30
- Volume
- 23
- Issue
- 4
- Pages
- 161-166
- ISSN
- 1362-0347 (ISSN-L)
- 1468-960X
- PMC
- PMC10231503
- OpenAlex
- W3091396385
- Cited by
- 121
- References
- 34
- Citations by year
- 2026: 12 · 2025: 21 · 2024: 23 · 2023: 23 · 2022: 27 · 2021: 15
- FWCI
- 2.55
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Evidence-Based Mental Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Keywords
- digital phenotyping, college student mental health, smartphone sensors, sleep, physical activity, social interaction, mood, anxiety, stress, COVID-19 remote learning, individualized care, student mental health services
- MeSH terms
- Smartphone, Biological Variation, Population, Betacoronavirus, COVID-19, SARS-CoV-2, Adult, Mental Disorders, Female, Humans, Male, Mental Health, Mental Health Services, Pneumonia, Viral, Surveys and Questionnaires, Students, Telemedicine, Coronavirus Infections, Young Adult, Pandemics
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