Literature DB >> 32998937

Digital phenotyping for mental health of college students: a clinical review.

Jennifer Melcher1, Ryan Hays1, John Torous2.   

Abstract

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. © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  adult psychiatry; depression & mood disorders

Mesh:

Year:  2020        PMID: 32998937     DOI: 10.1136/ebmental-2020-300180

Source DB:  PubMed          Journal:  Evid Based Ment Health        ISSN: 1362-0347


  13 in total

1.  Meeting Users Where They Are: User-centered Design of an Automated Text Messaging Tool to Support the Mental Health of Young Adults.

Authors:  Rachel Kornfield; Jonah Meyerhoff; Hannah Studd; Ananya Bhattacharjee; Joseph J Williams; Madhu Reddy; David C Mohr
Journal:  Proc SIGCHI Conf Hum Factor Comput Syst       Date:  2022-04-29

2.  Fairness in Mobile Phone-Based Mental Health Assessment Algorithms: Exploratory Study.

Authors:  Jinkyung Park; Ramanathan Arunachalam; Vincent Silenzio; Vivek K Singh
Journal:  JMIR Form Res       Date:  2022-06-14

Review 3.  Artificial intelligence: A rapid case for advancement in the personalization of Gynaecology/Obstetric and Mental Health care.

Authors:  Gayathri Delanerolle; Xuzhi Yang; Suchith Shetty; Vanessa Raymont; Ashish Shetty; Peter Phiri; Dharani K Hapangama; Nicola Tempest; Kingshuk Majumder; Jian Qing Shi
Journal:  Womens Health (Lond)       Date:  2021 Jan-Dec

4.  Use of Passive Sensing in Psychotherapy Studies in Late Life: A Pilot Example, Opportunities and Challenges.

Authors:  Jihui Lee; Nili Solomonov; Samprit Banerjee; George S Alexopoulos; Jo Anne Sirey
Journal:  Front Psychiatry       Date:  2021-10-28       Impact factor: 4.157

5.  Assessing the Real-time Influence of Racism-Related Stress and Suicidality Among Black Men: Protocol for an Ecological Momentary Assessment Study.

Authors:  Leslie Adams; Godwin Igbinedion; Aubrey DeVinney; Enoch Azasu; Paul Nestadt; Johannes Thrul; Sean Joe
Journal:  JMIR Res Protoc       Date:  2021-10-20

6.  Threats to Global Mental Health From Unregulated Digital Phenotyping and Neuromarketing: Recommendations for COVID-19 Era and Beyond.

Authors:  Hossein Akbarialiabad; Bahar Bastani; Mohammad Hossein Taghrir; Shahram Paydar; Nasrollah Ghahramani; Manasi Kumar
Journal:  Front Psychiatry       Date:  2021-09-14       Impact factor: 4.157

7.  Fluctuations in behavior and affect in college students measured using deep phenotyping.

Authors:  Constanza M Vidal Bustamante; Garth Coombs; Habiballah Rahimi-Eichi; Patrick Mair; Jukka-Pekka Onnela; Justin T Baker; Randy L Buckner
Journal:  Sci Rep       Date:  2022-02-04       Impact factor: 4.996

Review 8.  Opportunities and Challenges for Professionals in Psychiatry and Mental Health Care Using Digital Technologies During the COVID-19 Pandemic: Systematic Review.

Authors:  Hélène Kane; Jade Gourret Baumgart; Wissam El-Hage; Jocelyn Deloyer; Christine Maes; Marie-Clotilde Lebas; Donatella Marazziti; Johannes Thome; Laurence Fond-Harmant; Frédéric Denis
Journal:  JMIR Hum Factors       Date:  2022-02-04

9.  A Machine Learning Approach for Detecting Digital Behavioral Patterns of Depression Using Nonintrusive Smartphone Data (Complementary Path to Patient Health Questionnaire-9 Assessment): Prospective Observational Study.

Authors:  Soumya Choudhary; Nikita Thomas; Janine Ellenberger; Girish Srinivasan; Roy Cohen
Journal:  JMIR Form Res       Date:  2022-05-16

10.  Stress Perceived by University Health Sciences Students, 1 Year after COVID-19 Pandemic.

Authors:  Yolanda Marcén-Román; Angel Gasch-Gallen; Irene Isabel Vela Martín de la Mota; Estela Calatayud; Isabel Gómez-Soria; Beatriz Rodríguez-Roca
Journal:  Int J Environ Res Public Health       Date:  2021-05-14       Impact factor: 3.390

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