Symposia
Disaster Mental Health
Andrew Kirvin-Quamme, B.A.
Woebot Health
Leadville, Colorado
Jennifer Kissinger, B.A.
Woebot Health
Paul Wicks, PhD
Consultant
Wicks Digital Health
Lichfield, England, United Kingdom
Alison Darcy, Ph.D.
Founder & President
Woebot Health
San Francisco, California
Carolyn J. Greene, Ph.D.
University of Arkansas for Medical Sciences
NORTH LITTLE ROCK, Arkansas
Athena Robinson, Ph.D.
Chief Clinical Officer
Woebot Health
San Francisco, California
Who are you? This seemingly mundane question may in fact be one of the most complex and nuanced questions asked in a research study. While the recent proliferation of mobile application (app) mental health intervention research has offered hope for reducing service inaccessibility, standardization of demographic data collection methods and widely disseminated best practices have lagged behind. There is the potential for certain under-served or at-risk groups to benefit from mental health apps, but such benefits will never be realized if the self-identity questions we ask at signup are poorly or insensitively worded or signal that the app is an unsafe space. Moreover, the ability to assess efficacy for underrepresented groups via individual trials as well as meta-analysis will be significantly hindered by lack of uniformity in demographic variables, further limiting accurate, reliable, and generalizable inferences.
Currently, few guidelines exist for the collection of such demographic data and no research has been published that assesses the field’s common practices in this area. Our team is performing a systematic literature review (SLR) intended to formally characterize the state of demographic and self-identity data collection in app-delivered mental health intervention research. The SLR will be completed in August 2022, with results ready for presentation in the proposed ABCT symposium.
The SLR search terms were optimized to capture all currently published clinical trial outcome manuscripts involving app-delivered mental health interventions. Following PRISMA guidelines, two independent coders will assess all retrieved citations against a prespecified set of inclusion and exclusion criteria. Once the final set of included articles is identified, data extraction will be performed by two independent coders. Variables to be extracted were conceptualized with the intent of capturing the breadth of identity categories (e.g., race, ethnicity, gender, age, sexual orientation) that are currently being reported, the frequency each category is reported, common practices for answer choice options, and the degree to which open ended answers are permitted. Once synthesized, the project results will provide a much needed foundation for the future development of demographic data collection standards in app-delivered mental health intervention research.