Integrated treatment programs for pregnant and parenting people support longer retention compared to standard treatment programs: A population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Integrated treatment programs for pregnant and parenting people seek to provide wrap-around services and supports to overcome the barriers and constraints associated with the gendered contexts of substance use and help-seeking. We investigated retention in outpatient treatment among pregnant people and mothers, comparing integrated treatment programs with standard treatment programs in Ontario, Canada. METHODS: We conducted a population-based retrospective cohort study of females (n = 4440) admitted to 11 integrated treatment programs (cases) and 10 standard treatment programs (controls) between 2008 and 2015. Data sources included linked administrative health data merged with primary data on program characteristics. Exposure was program type and outcomes included days in treatment and number of visits. Multi-level negative binomial regression estimated the effects of program type on retention measures, controlling for individual- and program-level covariates. RESULTS: Relative to standard treatment, integrated treatment programs offered more services in-house or through partnerships, with specific advantages around the availability of prenatal or primary care and child-minding. Controlling for individual- and program-level covariates, individuals in integrated treatment programs spent more days in treatment (adjusted incidence rate ratio [aIRR] = 5.41, 95 % CI 4.10-7.13) and had more visits (aIRR = 5.18, 95 % CI 4.305-6.23) than did controls in standard treatment programs. CONCLUSIONS: This study contributes to a growing body of evidence on the implementation and effectiveness of wrap-around comprehensive service models, or integrated treatment programs, designed for pregnant and parenting people who use substances. Integrated treatment models constitute a promising approach to supporting families affected by substance use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".