Challenges Related to the Implementation of Measurement-Based Care for the Treatment of Major Depressive Disorder: A Feasibility Study
Bibliographic record
Abstract
Measurement-based care (MBC) involves systematically assessing patients' symptoms and adverse events using standardized scales to guide treatment. While MBC has been shown to enhance the quality of care and outcomes in the pharmacotherapy of major depressive disorder (MDD), it is still rarely used in clinical practice. In this study, the feasibility of implementing MBC was assessed for patients with MDD seen in a large outpatient psychiatry clinic.Adults diagnosed with MDD were assessed at baseline and during a 12-week follow-up by phone or via emailed links with: the 9-item Patient Health Questionnaire (PHQ-9), an adverse effect rating scale, and a published suicide risk management protocol (SRMP). Antidepressants were recommended based on preferences expressed by the participant and treating psychiatrist; dosages were adjusted by the treating psychiatrist based on symptomatic improvement and adverse events.Over 2 years, 52 (21.2%) of 246 patients referred to the study were enrolled, 28 (53.8%) completed all assessments at all follow-up visits, 45 (87.0%) participants were prescribed one of the recommended antidepressants, and 22 (42.3%) remitted. Of the 27 participants presenting with suicidal ideation, 18 (66.6%) experienced a full resolution of these ideations.These findings highlight the challenges in implementing MBC for the pharmacotherapy of MDD and confirm some barriers to its broad adoption in clinical practice. The study also highlights its benefits in the selected group of patients who engage in MBC. Future studies need to continue to explore innovative ways to facilitate its broader implementation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".