Measurement-based care vs. standard care for major depressive disorder in Pakistan: protocol for a randomized control trial
Bibliographic record
Abstract
Introduction Low and middle-income countries (LMICs) hold the majority of disease burden attributed to major depressive disorder (MDD). Despite this, there remains a substantial gap for access to evidence-based treatments for MDD in LMICs like Pakistan. Measurement-based care (MBC) incorporates systematic administration of validated outcome measures to guide treatment decision making and is considered a low-cost approach to optimise better clinical outcomes for individuals with MDD but there is a paucity of evidence on the efficacy of MBC in LMICs. Objectives This protocol highlights a randomized trial which will include Pakistani outpatients with moderate to severe major depression. Methods Participants will be randomised to either MBC (guided by schedule), or standard treatment (guided by clinicians’ judgement), and will be prescribed with paroxetine (10–60mg/day) or mirtazapine (7.5–45mg/day) for 24 weeks. Outcomes will be evaluated by raters blind to study protocol and treatment. Results National Bioethics Committee (NBC) of Pakistan has given full ethics approval. The trial is being conducted and reported as per recommendation of the CONSORT statement for RCTs. Conclusions With increasing evidence from high-income settings supporting the effectiveness of MBC for MDD, it is now necessary to explore its feasibility, utility. and efficacy in low-resource settings. The results of the proposed trial could inform the development of a low-cost and scalable approach to efficiently optimise outcomes for individuals with MDD in Pakistan. Disclosure of Interest None Declared
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".