Population-Based Service Planning for Implementation of MBCT: Linking Epidemiologic Data to Practice
Bibliographic record
Abstract
The study explored population-based service planning for mindfulness-based cognitive therapy (MBCT). Evidence suggests the usefulness of MBCT in relapse prevention for individuals reporting three or more major depressive episodes.Depression data were from the Canadian Community Health Survey. A simulation model estimated recurrence rates and population sizes to sustain MBCT therapists (each conducting two ten-person groups per year).Approximately 4.2% of the population are candidates for MBCT, and about 13 candidates would arise annually per 10,000 population. If MBCT was acceptable to 20%, for example, a population of 200,000 could support two therapists.A large proportion of the population is eligible for MBCT introduction; however, after introduction, the rate of emergence of candidates would yield a smaller patient pool, which may limit implementation in small population centers. Treatment acceptability is a key variable. These analyses highlight the potential value of epidemiologic data and simulation modeling in planning.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".