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Completed

NCT Number: NCT05023252

Mobile Self-Tracking of Mental Health

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.

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Key information

Conditions

Schizophrenia Bipolar Disorder Bipolar and Related Disorders Mental Disorders Mood Disorders Post-traumatic Stress Disorder Psychotic Disorders Schizoaffective Disorder Schizophrenia Spectrum and Other Psychotic Disorders Stress Disorders, Post-Traumatic Stress Disorders, Traumatic Trauma and Stressor Related Disorders

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

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

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

About this study

Background: Serious mental illnesses are common, disabling, challenging to treat, and require years of monitoring with adjustments in treatments. Stress or reduced medication adherence can lead to rapid worsening in symptoms and functioning with consequences that include relapse, job loss, homelessness, incarceration, hospitalization and suicide. In usual care, clinician visits are infrequent, with intervals ranging from monthly to yearly. Communication between patients and clinicians between visits is challenging and often nonexistent. Patient illness exacerbations and relapses generally occur with little or no clinician awareness in real time, leaving little opportunity to adjust treatments.

Significance/Impact: For the large population of Veterans with serious mental illness, tools are needed that passively monitor their mental health status, allowing them to self-track their behaviors, quickly detect worsening of mental health, and support prompt assessment and intervention. At least 60% of Veterans with serious mental illness use a smart phone. These generate data that characterize sociability, activity, and sleep. Changes in these behaviors are warning signs of relapse. Passive self-tracking could be used to identify and predict worsening of illness in real time.

Innovation: Passive mobile sensing is a novel approach to illness self-tracking and monitoring. There has been relatively little research on passive self-tracking in serious mental illness, with limited analytics development in this area, and none in VA.

Specific Aims: This project studies passive mobile sensing with Veterans in treatment for serious mental illness. Data are used for self-tracking of behaviors and symptoms. While passive mobile sensing has been feasible, acceptable and safe in patients with serious mental illness, these are studied for the first time in VA. Analytics are developed that use passive data to predict behaviors and symptoms. This project responds to the HSR&D priority areas of Mental Health and Healthcare Informatics. The project has these objectives:

  • Conduct user-centered design of passive mobile self-tracking to support Veterans' management of their mental health.
  • Study the feasibility, acceptability and safety of passive self-tracking of mental health that includes feedback of mental health status to the Veteran.
  • Use mobile sensor and phone utilization data to develop individualized estimates of sociability, activities, and sleep as measured by weekly interviews.
  • Study the predictive value of using data on sociability, activities, and sleep to identify exacerbations of psychiatric symptoms.

Methodology: Activities can be assessed with data on movement, location, and habits. Sociability can be assessed with data on communication and public interactions. Sleep can be assessed using data on light, sound, movement, and phone use. Investigators on this project developed a functional mobile app that monitors and transmits mobile sensor and utilization data. Focus groups and in-lab usability testing inform further app and intervention development. Mixed methods research study deployment in Veterans who passively self-track their behaviors and psychiatric symptoms. If this project meets intended goals, the VA will have a mobile analytics platform that continuously monitors behaviors and symptoms of patients with serious mental illness.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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

Exclusion criteria

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

Treatment and study plan

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.

Other names: VetThrive

Primary outcomes

  1. Feasibility of Passive Self-tracking of Mental Health

    Time frame: 9 months

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

  2. Estimates of Sociability

    Time frame: 9 months

    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.

  3. Identify Exacerbations of Psychiatric Symptoms

    Time frame: 9 months

    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.

  4. Acceptability of Passive Self-tracking of Mental Health

    Time frame: 9 months

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

  5. Safety of Passive Self-tracking of Mental Health

    Time frame: 9 months

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

  6. Estimates of Activities

    Time frame: 9 months

    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.

  7. Estimates of Sleep

    Time frame: 9 months

    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.

Sponsors and collaborators

Lead sponsor

VA Office of Research and Development

Fed

Registry information

Official study title

Passive Mobile Self-Tracking of Mental Health by Veterans With Serious Mental Illness

Important dates

Study start
2021
Primary completion
2024
Study completion
2024
First posted
Aug 26, 2021
Registry last updated
Nov 19, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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