Behavioral Activation for Comorbid Depression in People With Noncommunicable Disease in India: Protocol for a Randomized Controlled Feasibility Trial
Bibliographic record
Abstract
BACKGROUND: The increasing burden of depression and noncommunicable disease (NCD) is a global challenge, especially in low- and middle-income countries, considering the resource constraints and lack of trained human resources in these settings. Effective treatment of depression in people with NCDs has the potential to enhance both the mental and physical well-being of this population. It will also result in the effective use of the available health care resources. Brief psychological therapies, such as behavioral activation (BA), are effective for the treatment of depression. BA has not been adapted in the community health care services of India, and the feasibility of using BA as an intervention for depression in NCD and its effectiveness in these settings have not been systematically evaluated. OBJECTIVE: Our objective is to adapt BA for the Indian NCD context and test the acceptability, feasibility, and implementation of the adapted BA intervention (BEACON intervention package [BIP]). Additionally, we aim to test the feasibility of a randomized controlled trial evaluation of BIP for the treatment of depression compared with enhanced usual care. METHODS: Following well-established frameworks for intervention adaptation, we first adapted BA (to fit the linguistic, cultural, and resource context) for delivery in India. The intervention was also adapted for potential remote delivery by telephone. In a randomized controlled trial, we will be testing the acceptability, feasibility, and implementation of the adapted BA intervention (BIP). We shall also test if a randomized controlled feasibility trial can be delivered effectively and estimate important parameters (eg, recruitment and retention rates and completeness of follow-up) needed to design a future definitive trial. RESULTS: Following the receipt of approval from all the relevant agencies, the development of the BIP was started on November 28, 2020, and completed on August 18, 2021, and the quantitative data collection was started on August 23, 2021, and completed on December 10, 2021. Process evaluation (qualitative data) collection is ongoing. Both the qualitative and quantitative data analyses are ongoing. CONCLUSIONS: This study may offer insights that could help in closing the gap in the treatment of common mental illness, particularly in nations with limited resources, infrastructure, and systems such as India. To close this gap, BEACON tries to provide BA for depression in NCDs through qualified NCD (BA) counselors integrated within the state-run NCD clinics. The results of this study may aid in understanding whether BA as an intervention is acceptable for the population and how feasible it will be to deliver such interventions for depression in NCD in South Asian countries such as India. The BIP may also be used in the future by Indian community clinics as a brief intervention program. TRIAL REGISTRATION: Clinical Trials Registry of India CTRI/2020/05/025048; https://tinyurl.com/mpt33jv5. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41127.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.035 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.079 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".