1
|
Benjet C, Zainal NH, Albor Y, Alvis-Barranco L, Carrasco-Tapias N, Contreras-Ibáñez CC, Cudris-Torres L, de la Peña FR, González N, Guerrero-López JB, Gutierrez-Garcia RA, Jiménez-Peréz AL, Medina-Mora ME, Patiño P, Cuijpers P, Gildea SM, Kazdin AE, Kennedy CJ, Luedtke A, Sampson NA, Petukhova MV, Kessler RC. A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students: A Secondary Analysis of a Randomized Clinical Trial. JAMA Psychiatry 2023; 80:768-777. [PMID: 37285133 PMCID: PMC10248814 DOI: 10.1001/jamapsychiatry.2023.1675] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 04/10/2023] [Indexed: 06/08/2023]
Abstract
Importance Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT. Objective To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors. Design, Setting, and Participants This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022. Interventions Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435). Main Outcomes and Measures Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline. Results The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P = .003) or treatment as usual (40.0% [2.7%]; P = .001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P = .007; self-guided i-CBT: 25.4% [8.8%]; P = .004; treatment as usual: 31.0% [9.4%]; P = .001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P = .14; treatment as usual: 53.0% [6.0%]; P = .25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P = .001; treatment as usual: 41.8% [3.2%]; P < .001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P = .07). Conclusions and Relevance Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings. Trial Registration ClinicalTrials.gov Identifier: NCT04780542.
Collapse
Affiliation(s)
- Corina Benjet
- Center for Global Mental Health, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Nur Hani Zainal
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Yesica Albor
- Center for Global Mental Health, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City, Mexico
| | | | | | | | - Lorena Cudris-Torres
- Programa de Psicología, Fundación Universitaria del Area Andina, Valledupar, Colombia
| | - Francisco R. de la Peña
- Unidad de Fomento a la Investigacion, Direccion de Servicios Clínicos, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Noé González
- Center for Global Mental Health, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City, Mexico
| | | | | | - Ana Lucía Jiménez-Peréz
- Facultad de Ciencias Administrativas y Sociales, Universidad Autónoma de Baja California, Ensenada, Mexico
| | - Maria Elena Medina-Mora
- Center for Global Mental Health, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Pamela Patiño
- Center for Global Mental Health, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Pim Cuijpers
- Department of Clinical, Neuro-, and Developmental Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Sarah M. Gildea
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Alan E. Kazdin
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Chris J. Kennedy
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Alex Luedtke
- Department of Statistics, University of Washington, Seattle
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Nancy A. Sampson
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Maria V. Petukhova
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Ronald C. Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| |
Collapse
|