Brief Online Help-seeking Barrier Reduction Intervention
| Status: | Completed |
|---|---|
| Conditions: | Psychiatric |
| Therapuetic Areas: | Psychiatry / Psychology |
| Healthy: | No |
| Age Range: | Any |
| Updated: | 8/19/2018 |
| Start Date: | August 10, 2017 |
| End Date: | September 20, 2017 |
Randomized Controlled Trial of an Online Machine Learning-Driven Risk Assessment and Intervention Platform for Increasing the Use of Crisis Services
Objective: Mental illness is a leading cause of disease burden; however, many barriers
prevent people from seeking mental health services. Technological innovations may improve the
ability to reach under-served populations by overcoming many existing barriers. The
investigators evaluated a brief, automated risk assessment and intervention platform designed
to increase the use of crisis resources provided to individuals who were online and in
crisis. Hypothesis: The investigators hypothesized that individuals assigned to the
intervention condition would report using crisis resources at higher rates than individuals
in the control condition. Method: Participants, users of the digital mental health app Koko,
were randomly assigned to treatment or control conditions upon accessing the app and were
included in the study after their posts were identified by machine learning classifiers as
signaling a current mental health crisis. Participants in the treatment condition received a
brief Barrier Reduction Intervention (BRI) designed to increase the use of crisis service
referrals provided on the app. Participants were followed-up several hours later to assess
the use of crisis services.
prevent people from seeking mental health services. Technological innovations may improve the
ability to reach under-served populations by overcoming many existing barriers. The
investigators evaluated a brief, automated risk assessment and intervention platform designed
to increase the use of crisis resources provided to individuals who were online and in
crisis. Hypothesis: The investigators hypothesized that individuals assigned to the
intervention condition would report using crisis resources at higher rates than individuals
in the control condition. Method: Participants, users of the digital mental health app Koko,
were randomly assigned to treatment or control conditions upon accessing the app and were
included in the study after their posts were identified by machine learning classifiers as
signaling a current mental health crisis. Participants in the treatment condition received a
brief Barrier Reduction Intervention (BRI) designed to increase the use of crisis service
referrals provided on the app. Participants were followed-up several hours later to assess
the use of crisis services.
Inclusion Criteria:
- Participants identified as experiencing a mental health crisis by a hybrid
human-machine computation system evaluating semantic content of posts made on digital
platforms.
Exclusion Criteria:
- Participants who were not identified as experiencing a mental health crisis.
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