Telehealth/m-Health
Simay I. Ipek, B.A.
Clinical Research Coordinator
Massachusetts General Hospital
Boston, Massachusetts
Adam Jaroszewski, Ph.D.
Post-Doctoral Fellow
Massachusetts General Hospital
Boston, Massachusetts
Natasha H. Bailen, Ph.D.
Psychologist
Massachusetts General Hospital
Boston, Massachusetts
Jennifer L. Greenberg, Psy.D.
Assistant Professor
Massachusetts General Hospital/Harvard Medical School
Boston, Massachusetts
Sabine Wilhelm, Ph.D.
Professor, Director of CORD and CDMH
Harvard Medical School
Boston, Massachusetts
Background: Previous research has shown that although substance use disorder (SUD) prevalence rates are similar across race and ethnicity, racial and ethnic minorities are at increased risk for disorder persistence due to delays in access and poor quality of care. Further, co-occurrence of SUD with anxiety and mood disorders, which is common in the general population, is even more likely to occur in minority populations. A review investigating minority inclusion in DMHI studies showed that many studies do not include or have low rates of Latinx/Hispanic participants and have extremely low rates of African American recruitment. Evidence suggests that racial and ethnic minorities are already underrepresented in DMHI studies, and due to higher chronicity of SUD within minorities, studies might disproportionately exclude these subgroups by having exclusion criteria for disordered substance and alcohol use.
Method: A systematic search was conducted of articles published between 2000 and 2022. Electronic databases (e.g., Google Scholar, PsycINFO) were used to identify clinical trials testing the efficacy of digital interventions for anxiety and/or mood disorders. Example search terms included: depress*, anxiety, digital intervention, digital mental health. Reference lists from the identified manuscripts were also searched for additional relevant studies.
Results: Among the 113 studies included, a logistic regression revealed that the odds of a participant being excluded from a mood disorder DMHI study based on a SUD exclusion criterion was approximately 60% lower than from an anxiety disorder DMHI study (35% vs 57%, OR = 0.402, 95 CI% [-1.71, -.137], p = .0229). Among 55 studies with SUD exclusion, 27% did not mention the measure used for detecting SUDs and 25% used criteria that were not based on a standardized measure such as AUDIT or SCID-I.
Conclusion: Digital mental health interventions promise to expand care by overcoming barriers such as cost, access, and stigma. However, many DMHI studies exclude those with a SUD. Given the high co-occurrence of SUDs with mood and anxiety disorders, extant results may be limited in their generalizability. Moreover, among DMHI studies, racial and ethnic minorities might be more likely to be inadvertently excluded from anxiety disorder studies than mood disorder studies because these subgroups are more likely to have co-occurring SUDs. In addition, nearly 52% of DMHI studies either do not report or report unstandardized measures for their SUD exclusion which may contribute to invalid exclusionary practices. Researchers planning DMHIs should consider modifying their in/exclusion criteria to develop and test more inclusive, generalizable, and accessible treatments.