Disease Management for Depression in an Ms Clinic
Bibliographic record
Abstract
OBJECTIVE: Evidence-based treatments for depression in multiple sclerosis (MS) are available, but their implementation can be challenging. We explored the feasibility and effectiveness of implementing a disease management program for depression in an MS clinic. METHODS: A non-randomized "before-after" design was used. The University of Calgary MS Clinic performs routine screening for depression using the Center for Epidemiologic Studies Depression Rating Scale (CES-D). During a six month baseline period, the screen results were not systematically acted upon. During a subsequent nine-month study period, a case manager was routinely notified of positive screens. These patients were offered disease management. Major depression was assessed six months later with a blind administration of the Mini Neuropsychiatric Interview (MINI). Quality of life (EQ-5D) and functional status (WHO DAS II) were also measured. RESULTS: Eighty-three patients were enrolled in the study; 54 were in the disease management group and 29 received treatment as usual. There was a lower frequency of major depression in the intervention group six months post-screening. No differences in quality of life or functional status were seen. CONCLUSIONS: Disease management approaches for depression were developed in primary care environments and have been adapted for geriatric and diabetic populations. These strategies may require modification for application in MS clinics. While an intervention for depression was effective in those who received it, its impact on the targeted clinical population was reduced by lower than expected rates of participation and higher than expected rates of treatment at baseline.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".