A comparative effectiveness study of the breaking the cycle and Maxxine Wright intervention programs for substance-involved mothers and their children: study protocol
Bibliographic record
Abstract
Abstract Background Children of substance-involved mothers are at especially high risk for exposure to adverse childhood experiences (ACEs) and poor mental health and development. Early interventions that support mothers, children, and the mother-child relationship have the greatest potential to reduce exposure to early adversity and the mental health problems associated with these exposures. Currently, there is a lack of evidence from the real-world setting demonstrating effectiveness and return on investment for intervention programs that focus on the mother-child relationship in children of substance-involved mothers. Methods One hundred substance-involved pregnant and/or parenting women with children between the ages of 0–6 years old will be recruited through the Breaking the Cycle and Maxxine Wright intervention programs, in Toronto, Ontario, Canada and Surrey, British Columbia, Canada, respectively. Children’s socioemotional development and exposure to risk and protective factors, mothers’ mental health and history of ACEs, and mother-child relationship quality will be assessed in both intervention programs. Assessments will occur at three time points: pre-intervention, 12-, and 24-months after engagement in the intervention program. Discussion There is a pressing need to identify interventions that promote the mental health of infants and young children exposed to early adversity. Bringing together an inter-disciplinary research team and community partners, this study aligns with national strategies to establish strong evidence for infant mental health interventions that reduce child exposure to ACEs and support the mother-child relationship. This study was registered with clinicaltrials.gov (NCT05768815) on March 14, 2023.
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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 | 0.034 | 0.032 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".