Mobile Self-Tracking of Mental Health

NCT05023252 | Completed Results

• 1 other identifier: IIR 19-392
• Study Type: interventional
• Target: 87
• Locations: 1 country
• Sites: 1

Brief Summary

Serious mental illnesses require years of monitoring and adjustments in treatment. Stress, substance abuse or reduced medication adherence cause rapid worsening of symptoms, with consequences that include job loss, homelessness, suicide, incarceration, and hospitalization. Treatment visits can be infrequent. Illness exacerbations usually occur with no clinician awareness, leaving little opportunity to make treatment adjustments. Tools are needed that quickly detect illness worsening. At least two thirds of Veterans with serious mental illness use a smartphone. These phones generate data that characterize sociability, activity and sleep. Changes in these are warning signs for relapse. Members of this project developed an app that monitors and transmits these mobile data. This project studies passive mobile sensing that allows Veterans to self-track their activities, sociability and sleep; and studies whether this can be used to track symptoms. The project intends to produce a mobile platform that monitors the clinical status of patients, identifies risk for relapse, and allows early intervention.

Conditions

Schizophrenia; Bipolar Disorder; Schizoaffective Disorder; Post-traumatic Stress Disorder

Keywords

Mental health care; Informatics; Predictive Modeling; Bipolar disorder; Psychotic Disorders; Machine learning

Outcome Measures

Primary Outcomes (7)

• Feasibility of Passive Self-tracking of Mental Health

  Feasibility of passive self-tracking of mental health. The number of participants who completed the study.

  9 months

• Estimates of Sociability

  Use mobile sensor and phone utilization data to develop individualized estimates of sociability. There was an effort to calculate an estimate of sociability for each participant. Some participants had insufficient data collected to calculate an estimate. The intent is to determine the number of participants for whom this outcome can be estimated. The investigators report here on the number of participants for whom an estimate of sociability could be successfully calculated.

  9 months

• Identify Exacerbations of Psychiatric Symptoms

  Study the predictive value of using data on sociability, activities, and sleep to identify exacerbations of psychiatric symptoms. There was an effort to calculate identify exacerbations of psychiatric symptoms for each participant. Some participants had insufficient data collected to identify exacerbations. The intent is to determine the number of participants for whom this outcome can be estimated. The investigators report here on the number of participants for whom exacerbations of psychiatric symptoms could be successfully calculated.

  9 months

• Acceptability of Passive Self-tracking of Mental Health

  Acceptability of passive self-tracking of mental health. The number of participants who completed the study.

  9 months

• Safety of Passive Self-tracking of Mental Health

  Safety of passive self-tracking of mental health. The number of participants with a serious adverse event.

  9 months

• Estimates of Activities

  Use mobile sensor and phone utilization data to develop individualized estimates of activities. There was an effort to calculate an estimate of activity for each participant. Some participants had insufficient data collected to calculate an estimate. The intent is to determine the number of participants for whom this outcome can be estimated. The investigators report on the number of participants for whom an estimate of activity could be successfully calculated.

  9 months

• Estimates of Sleep

  Use mobile sensor and phone utilization data to develop individualized estimates of sleep. There was an effort to calculate an estimate of sleep for each participant. Some participants had insufficient data collected to calculate an estimate. The intent is to determine the number of participants for whom this outcome can be estimated. The investigators report here on the number of participants for whom an estimate of sleep could be successfully calculated.

  9 months

Study Arms (1)

mobile application

EXPERIMENTAL

Participants use a mobile application on their smartphone

Other: mobile application

Interventions

mobile application OTHER

VetThrive is a mobile smartphone application that monitors and transmits mobile sensor and utilization data. This app is deployed in Veteran patients who passively self-track their behaviors and psychiatric symptoms.

Also known as: VetThrive

mobile application

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Veteran patient at the Greater Los Angeles Veterans Healthcare Center with a chart diagnosis of serious mental illness, defined as a diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder
• Risk for symptoms based on having had, during the past year, psychiatric hospitalization, psychiatric emergency care, lived at a crisis program, or more than 6 outpatient visits; and,
• Ownership of a smartphone with a data plan

You may not qualify if:

• Under age 18
• Has a conservator/legally authorized representative

Sponsors & Collaborators

• VA Office of Research and Development: lead

Study Sites (1)

VA Greater Los Angeles Healthcare System, West Los Angeles, CA

West Los Angeles, California, 90073-1003, United States

Location

Related Publications (4)

• Young AS, Choi A, Cannedy S, Hoffmann L, Levine L, Liang LJ, Medich M, Oberman R, Olmos-Ochoa TT. Passive Mobile Self-tracking of Mental Health by Veterans With Serious Mental Illness: Protocol for a User-Centered Design and Prospective Cohort Study. JMIR Res Protoc. 2022 Aug 5;11(8):e39010. doi: 10.2196/39010.

  PMID: 35930336 RESULT

• Medich M, Cannedy SL, Hoffmann LC, Chinchilla MY, Pila JM, Chassman SA, Calderon RA, Young AS. Clinician and Patient Perspectives on the Use of Passive Mobile Monitoring and Self-Tracking for Patients With Serious Mental Illness: User-Centered Approach. JMIR Hum Factors. 2023 Oct 24;10:e46909. doi: 10.2196/46909.

  PMID: 37874639 RESULT

• Lin Z, Weinberger E, Nori-Sarma A, Chinchilla M, Wellenius GA, Jay J. Daily heat and mortality among people experiencing homelessness in 2 urban US counties, 2015-2022. Am J Epidemiol. 2024 Nov 4;193(11):1576-1582. doi: 10.1093/aje/kwae084.

  PMID: 38844692 RESULT

• Chinchilla M, Lulla A, Agans D, Chassman S, Gabrielian SE, Young AS. Pathways to social integration among homeless-experienced adults with serious mental illness: a qualitative perspective. BMC Health Serv Res. 2024 Oct 4;24(1):1180. doi: 10.1186/s12913-024-11678-6.

  PMID: 39367388 RESULT

MeSH Terms

Conditions

Schizophrenia; Bipolar Disorder; Psychotic Disorders; Stress Disorders, Post-Traumatic

Condition Hierarchy (Ancestors)

Schizophrenia Spectrum and Other Psychotic Disorders; Mental Disorders; Bipolar and Related Disorders; Mood Disorders; Stress Disorders, Traumatic; Trauma and Stressor Related Disorders

Results Point of Contact

• Title: Alexander Young MD
• Organization: Veterans Health Administration, Greater Los Angeles Veterans Healthcare Center

alexander.young@va.gov

310-478-3711

Study Officials

• Alexander Stehle Young, MD MSHS

  VA Greater Los Angeles Healthcare System, West Los Angeles, CA

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: Yes

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: SINGLE GROUP
• Sponsor Type: FED
• Responsible Party: SPONSOR

Model Details: Participants in the trial are enrolled in an intervention group for 9 months

Study Record Dates

• First Submitted: August 16, 2021
• First Posted: August 26, 2021
• Study Start: October 18, 2021
• Primary Completion: July 22, 2024
• Study Completion: July 22, 2024
• Last Updated: November 19, 2025
• Results First Posted: October 15, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)