Symposia
Dissemination & Implementation Science
Kendra S. Knudsen, M.A.
Doctoral Student
UCLA
Los Angeles, California
Kendra S. Knudsen, M.A.
Doctoral Student
UCLA
Los Angeles, California
Kimberly D. Becker, Ph.D. (she/her/hers)
Associate Professor
University of South Carolina
Chapin, South Carolina
Karen Guan, PhD
Program Evaluation and Implementation Specialist - New Business
Pacific Clinics
Campbell, California
Resham Gellatly, Ph.D.
Postdoctoral Fellow
University of California, Los Angeles
Los Angeles, California
Vikram Patel, MD
Professor
Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA
Boston, Massachusetts
Kanika Malik, PhD
Assistant Professor
OP Jindal Global University, Sonipat, Haryana, India
Delhi, Haryana, India
Maya Boustani, PhD
Assistant Professor
Department of Psychology, Loma Linda University, Loma Linda, California, USA
Loma Linda, California
Sonal Mathur, PhD
Intervention Director
Sangath
Saket, Delhi, India
Bruce F. Chorpita, Ph.D.
Professor
University of California Los Angeles
Los Angeles, California
Background: The future of global mental health (MH) hinges on designing scalable solutions to advance MH systems. This requires balancing two, often competing treatment needs: to be uncomplicated for mental health workers (MHWs) and to be widely suitable to diverse cases and contexts. To increase accessibility and reduce cost, treatments are commonly simplified by removing or standardizing procedures. Yet, this decreases their utility and applicability across broad contexts. COVID-19 has expanded the service gap (Kazdin, 2019) and has disproportionally impacted low to middle income countries (Rao & Fisher, 2021). Thus, we must urgently build resource-efficient approaches to mobilize MHWs. This study examined the acceptability, feasibility, and potential effectiveness of a low-cost strategy that supports MHWs in India to classify problems and select practices within a flexible, modular MH treatment.
Methods: Local MHWs with varied education (N=18) used a one-page decision-making resource to evaluate fictional, culturally relevant case vignettes before and after a 2h training. MHW-perceived acceptability was assessed with a brief version of the Unified Theory of Acceptance and Use of Technology survey. Feasibility was measured by the integrity of the study protocol and materials. The MHWs’ decisions on problem classification and practice selection were compared with criteria developed among US-trained psychologists (“judges”) with expertise in modular protocols.
Results: Analysis showed an effect of time on MHWs’ accuracy in problem classification, F(1, 17.98) = 51.97, p < .0001, and practice selection, F(1, 18.24) = 19.96, p < .0001. Before training, MHWs classified problems at below-chance levels and selected practices at no-better-than-chance levels. After training, MHWs’ rate of agreement with the judges increased by 46% for problem classification and increased by 25% for practice selection. Agreement on practice selection was mediated by accuracy in problem classification. Results revealed high acceptability and feasibility on all metrics, including significant improvement in MHW confidence after training, F(1,18) = 14.90, p = .001.
Conclusion: These findings have broad implications for mobilizing expanded MHWs during crises, particularly in under-resourced settings. When simplification might compromise scalability, the complexity of flexible, modular interventions is potentially addressable with brief trainings and decision support resources.