Glass-Box Testing the Centre for Addiction and Mental Health Integrated Care Pathway for Major Depressive and Alcohol Use Disorders: Is It More Than a Sum of Its Components?
Bibliographic record
Abstract
ABSTRACT Objectives: Integrated care pathways (ICP) have been successfully developed in multiple areas of medicine with evidence supporting their superior effectiveness when compared to treatment as usual (TAU). There are lack of data indicating that specifically integration of services plays a crucial role in ICP effectiveness rather than simple combination of effective treatment techniques for concurrent major depressive and alcohol use disorders. Methods: A clinical chart review was completed to compare patients receiving ICP to those receiving TAU analyzed by univariate and multivariate regression models to see if allocation to ICP would be a significant determinant of reduction in drinking. Results: Of the 237 patients included into the analyses, 133 patients received ICP treatment and 104 received TAU. Patients were similar in their demographics, but there were differences in several baseline characteristics, 2 of which were significantly associated with reduction of drinking as the primary outcome—baseline alcohol consumption measured as standard drinks per week [SD/w; β = −0.24, 95% confidence interval (CI) −0.38 to −0.10, P < 0.001] and cannabis use (β = −17.58, 95% CI −30.89 to −4.28, P < 0.01). Receiving ICP treatment versus TAU was associated with significantly higher reduction in drinking (β = 40.23, 95% CI 30.39 to 52.26, P < 0.001). Almost all treatment parameters were associated with reduction in drinking in univariate analyses and after adjusting for baseline SD/w and cannabis use. In multivariate models only treatment model (β = 27.23, 95% CI 12.47 to 41.99, P < 0.001), baseline SD/w and cannabis use contributed significantly; the assignment to integrated treatment group explained 72% of the variability. Conclusions: ICP treatment model is associated with superior treatment outcomes in comparison to TAU. Integration of treatment techniques seems to be more important that the techniques themselves or their intensity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".