Treatment for substance use disorder in mothers of young children: A systematic review of maternal substance use and child mental health outcomes
Bibliographic record
Abstract
Substance use disorders (SUD) in mothers of young children can negatively impact the family unit and promote the intergenerational cycle of mental health disorders. This systematic review aims to: 1) provide an overview of substance use treatments for mothers of young children (from birth to 5 years old); 2) synthesize findings on maternal substance use and child/maternal mental health outcomes; and 3) identify key treatment components. Database searches in Medline, PsycINFO, PubMED, and PsycARTICLES were conducted on May 7th, 2024. A total of 14, 916 articles were identified following duplicate removal. Articles were screened following PRISMA guidelines. Eight articles (n = 900) met inclusion criteria. Outcomes of interest included maternal substance use, child/maternal mental health, and treatment components. All studies indicated maternal substance use treatments were at least as, or more, effective in improving maternal substance use and child/maternal mental health outcomes compared to controls. Treatment components included: mother/family mental health, basic needs, parenting skills, occupation/education, operant conditioning, crisis management, and medical education. Operant conditioning was the only treatment component which appeared to positively impact maternal substance use outcomes; no other treatment components were associated with outcomes of interest. This review provides preliminary evidence highlighting the benefits of substance use treatments for mothers of young children on substance use and mental health outcomes. Future randomized controlled trials with harmonized outcome measures and qualitative data that identifies treatment needs of mothers with lived experience are crucial to evaluate maternal substance use treatments and improve treatment development.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".