Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial
Abstract Background Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. However, treatment response varies widely across patients, and neither approach is universally effective. Identifying the most effec...
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2025-07-01
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| author | Julia R. Pozuelo Anuja Lahiri Rahul S. P. Singh Arvind Kushwah Mimansa Khanduri Akanksha Shukla Azaz Khan Sruthi G. Varun Shende Yashika Parashar Yashwant K. Mehra Anant Bhan Ronald C. Kessler Daisy R. Singla John A. Naslund Karmel W. Choi Pim Cuijpers Robert DeRubeis Mohammad M. Herzallah Chunling Lu Jordan W. Smoller Tyler J. VanderWeele Abhijit R. Rozatkar Tamonud Modak Michelle Melwyn Joel Debasis Biswas Shubham Atal Umay Kulsum Steven D. Hollon Vikram Patel |
| author_facet | Julia R. Pozuelo Anuja Lahiri Rahul S. P. Singh Arvind Kushwah Mimansa Khanduri Akanksha Shukla Azaz Khan Sruthi G. Varun Shende Yashika Parashar Yashwant K. Mehra Anant Bhan Ronald C. Kessler Daisy R. Singla John A. Naslund Karmel W. Choi Pim Cuijpers Robert DeRubeis Mohammad M. Herzallah Chunling Lu Jordan W. Smoller Tyler J. VanderWeele Abhijit R. Rozatkar Tamonud Modak Michelle Melwyn Joel Debasis Biswas Shubham Atal Umay Kulsum Steven D. Hollon Vikram Patel |
| author_sort | Julia R. Pozuelo |
| collection | DOAJ |
| description | Abstract Background Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. However, treatment response varies widely across patients, and neither approach is universally effective. Identifying the most effective treatment for each patient is critical everywhere, but particularly in low-resource settings where access to mental health care is limited. The Optimizing Depression (OptimizeD) trial aims to explore whether different patients respond differently to behavioral activation therapy versus antidepressant medication and if providing each patient with their optimal treatment improves outcomes in primary care. Methods We plan to randomize 1,500 patients with moderate to severe depression (defined as a Patient Health Questionnaire [PHQ-9] score ≥ 10) from primary healthcare settings in Bhopal, India, with equal allocation either to a culturally adapted behavioral activation therapy delivered by trained counselors (Healthy Activity Program) or to antidepressant medication (fluoxetine). Treatment will last 3 months, with remission (defined as PHQ-9 score < 5) at 3 months as the primary endpoint. Using machine learning, we will attempt to develop a precision treatment rule that leverages baseline clinical, psychological, cognitive, socioeconomic, and biological data to predict which treatment is most likely to achieve remission for each patient. Cost-effectiveness analysis will then assess whether the added costs of optimizing treatment are justified by improvements in remission, recovery, and cost savings at the health system and societal levels. Secondary and exploratory objectives include assessing the effectiveness of optimization in a range of secondary outcomes, evaluating treatment mechanisms, and exploring whether incorporating genetic and biological markers as predictors improves treatment optimization. Discussion The OptimizeD trial will evaluate whether baseline information collected in routine care can inform optimal depression treatment selection and identify predictors of nonresponse to facilitate timely specialist referrals. Findings have the potential to enhance personalized depression care in primary health systems, particularly in low-resource settings, with broader implications for global public health. Trial registration ClinicalTrials.gov (NCT05944926; registered July 2, 2023) and Clinical Trials Registry India (CTRI/2024/01/061932; registered January 29, 2024). |
| format | Article |
| id | doaj-art-d58625c433f84efcb0ec39ddc25f38fe |
| institution | Kabale University |
| issn | 1471-244X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
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| series | BMC Psychiatry |
| spelling | doaj-art-d58625c433f84efcb0ec39ddc25f38fe2025-08-20T04:03:01ZengBMCBMC Psychiatry1471-244X2025-07-0125112010.1186/s12888-025-07030-9Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trialJulia R. Pozuelo0Anuja Lahiri1Rahul S. P. Singh2Arvind Kushwah3Mimansa Khanduri4Akanksha Shukla5Azaz Khan6Sruthi G.7Varun Shende8Yashika Parashar9Yashwant K. Mehra10Anant Bhan11Ronald C. Kessler12Daisy R. Singla13John A. Naslund14Karmel W. Choi15Pim Cuijpers16Robert DeRubeis17Mohammad M. Herzallah18Chunling Lu19Jordan W. Smoller20Tyler J. VanderWeele21Abhijit R. Rozatkar22Tamonud Modak23Michelle Melwyn Joel24Debasis Biswas25Shubham Atal26Umay Kulsum27Steven D. Hollon28Vikram Patel29Department of Global Health and Social Medicine, Harvard Medical SchoolBhopal Hub, SangathBhopal Hub, SangathBhopal Hub, SangathBhopal Hub, SangathBhopal Hub, SangathBhopal Hub, SangathBhopal Hub, SangathBhopal Hub, SangathDepartment of Global Health and Social Medicine, Harvard Medical SchoolBhopal Hub, SangathBhopal Hub, SangathDepartment of Health Care Policy, Harvard Medical SchoolCampbell Family Mental Health Research Institute, Centre for Addiction and Mental HealthDepartment of Global Health and Social Medicine, Harvard Medical SchoolDepartment of Psychiatry, Center for Precision Psychiatry, Massachusetts General HospitalDepartment of Clinical, Neuro and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije UniversiteitDepartment of Psychology, University of PennsylvaniaPalestinian Neuroscience Initiative, Al-Quds UniversityDepartment of Global Health and Social Medicine, Harvard Medical SchoolDepartment of Psychiatry, Center for Precision Psychiatry, Massachusetts General HospitalHarvard T.H. Chan School of Public HealthAll India Institute of Medical Sciences (AIIMS) BhopalAll India Institute of Medical Sciences (AIIMS) BhopalAll India Institute of Medical Sciences (AIIMS) BhopalAll India Institute of Medical Sciences (AIIMS) BhopalAll India Institute of Medical Sciences (AIIMS) BhopalAll India Institute of Medical Sciences (AIIMS) BhopalDepartment of Psychology, Vanderbilt UniversityDepartment of Global Health and Social Medicine, Harvard Medical SchoolAbstract Background Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. However, treatment response varies widely across patients, and neither approach is universally effective. Identifying the most effective treatment for each patient is critical everywhere, but particularly in low-resource settings where access to mental health care is limited. The Optimizing Depression (OptimizeD) trial aims to explore whether different patients respond differently to behavioral activation therapy versus antidepressant medication and if providing each patient with their optimal treatment improves outcomes in primary care. Methods We plan to randomize 1,500 patients with moderate to severe depression (defined as a Patient Health Questionnaire [PHQ-9] score ≥ 10) from primary healthcare settings in Bhopal, India, with equal allocation either to a culturally adapted behavioral activation therapy delivered by trained counselors (Healthy Activity Program) or to antidepressant medication (fluoxetine). Treatment will last 3 months, with remission (defined as PHQ-9 score < 5) at 3 months as the primary endpoint. Using machine learning, we will attempt to develop a precision treatment rule that leverages baseline clinical, psychological, cognitive, socioeconomic, and biological data to predict which treatment is most likely to achieve remission for each patient. Cost-effectiveness analysis will then assess whether the added costs of optimizing treatment are justified by improvements in remission, recovery, and cost savings at the health system and societal levels. Secondary and exploratory objectives include assessing the effectiveness of optimization in a range of secondary outcomes, evaluating treatment mechanisms, and exploring whether incorporating genetic and biological markers as predictors improves treatment optimization. Discussion The OptimizeD trial will evaluate whether baseline information collected in routine care can inform optimal depression treatment selection and identify predictors of nonresponse to facilitate timely specialist referrals. Findings have the potential to enhance personalized depression care in primary health systems, particularly in low-resource settings, with broader implications for global public health. Trial registration ClinicalTrials.gov (NCT05944926; registered July 2, 2023) and Clinical Trials Registry India (CTRI/2024/01/061932; registered January 29, 2024).https://doi.org/10.1186/s12888-025-07030-9DepressionPrimary careBehavioral activationAntidepressantsPrecision mental healthIndia |
| spellingShingle | Julia R. Pozuelo Anuja Lahiri Rahul S. P. Singh Arvind Kushwah Mimansa Khanduri Akanksha Shukla Azaz Khan Sruthi G. Varun Shende Yashika Parashar Yashwant K. Mehra Anant Bhan Ronald C. Kessler Daisy R. Singla John A. Naslund Karmel W. Choi Pim Cuijpers Robert DeRubeis Mohammad M. Herzallah Chunling Lu Jordan W. Smoller Tyler J. VanderWeele Abhijit R. Rozatkar Tamonud Modak Michelle Melwyn Joel Debasis Biswas Shubham Atal Umay Kulsum Steven D. Hollon Vikram Patel Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial BMC Psychiatry Depression Primary care Behavioral activation Antidepressants Precision mental health India |
| title | Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial |
| title_full | Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial |
| title_fullStr | Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial |
| title_full_unstemmed | Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial |
| title_short | Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial |
| title_sort | optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low resource setting protocol for the optimized randomized controlled trial |
| topic | Depression Primary care Behavioral activation Antidepressants Precision mental health India |
| url | https://doi.org/10.1186/s12888-025-07030-9 |
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