Use of the Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood: Revised Edition (DC:0–3R) with Canadian Infants and Young Children Prenatally Exposed to Substances
Bibliographic record
Abstract
Abstract The current study examined the mental health diagnostic profiles of infants and young children prenatally exposed to substances using the Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood, Revised (DC:0–3R) diagnostic system. Participants were 46 biological mother–infant dyads who were engaged in a clinical program for mothers with substance‐use problems and their young children (aged 10–41 months). Diagnostic information was reported for each of the five axes listed in the DC:0–3R diagnostic system based on file reviews. In addition, the children's socioemotional and adaptive behaviors were assessed using the Child Behavior Checklist, Infant–Toddler Social Emotional Assessment, the Social‐Emotional Scale, and the Adaptive Behavior Assessment System (2nd ed.). In this sample of young children with prenatal substance exposure, a broad range of socioemotional symptoms were evident, with almost one third of the children meeting criteria for at least one Axis I mental health diagnosis. In addition, the majority of dyads demonstrated features of a disordered relationship. Children in more problematic relationships demonstrated higher levels of socioemotional and adaptive functioning difficulties and were more likely to have an Axis I diagnosis than were children in adapted relationships. The importance of early intervention efforts aimed at infants with prenatal substance exposure and their biological mothers is highlighted, with a particular focus on enhancing the quality of the mother–child relationship.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".