Examining service complexity in children with parents who abuse substances
Bibliographic record
Abstract
Children and youth who have parents who abuse substances are at risk of developing externalizing problems (e.g., rule-breaking, aggressive/antisocial behaviour, underage drinking/drug use) and face a variety of risk factors including family factors (e.g., parenting, level of monitoring, abuse, and neglect), and child-related factors (e.g., mental health, behavioural, substance use problems) that impact levels of family functioning, parenting strengths, school disengagement, externalizing difficulties, and service complexity. Currently, there is lack of information and recognition that children of parents with substance use disorders require mental health services, with limited research regarding the requirements of service intensity and complexity for children’s mental health when focusing on this specific population of children effected by parental substance abuse. To address this gap in literature, data was obtained from 18701 clinically referred children and youth (4 to 18 -years) across the Province of Ontario using the interRAI Child and Youth Mental Health Assessment. Findings revealed that treatment-seeking children of substance abusing parents rated higher on externalizing behaviours, school disengagement, family dysfunction, lack of parenting strengths, and service complexity than children with parents who do not abuse substances. Implications and recommendations for service professionals to support service system integration utilizing an assessment-to-intervention process to support families engaged in mental health and substance use problems are discussed.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".