Parent-youth agreement on self-reported competencies of youth with depressive and suicidal symptoms.
Bibliographic record
Abstract
OBJECTIVE: A multi-informant approach is often used in child psychiatry. The Achenbach System of Empirically Based Assessment uses this approach, gathering parent reports on the Child Behaviour Checklist (CBCL) and youth reports on the Youth Self-Report (YSR), which contain scales assessing both the child's problems and competencies. Agreement between parent and youth perceptions of their competencies on these forms has not been studied to date. METHOD: Our study examined the parent-youth agreement of competencies on the CBCL and YSR from a sample of 258 parent-youth dyads referred to a specialized outpatient clinic for depressive and suicidal disorders. Intraclass correlation coefficients were calculated for all competency scales (activity, social, and academic), with further examinations based on youth's sex, age, and type of problem. RESULTS: Weak-to-moderate parent-youth agreements were reported on the activities and social subscales. For the activities subscale, boys' ratings had a strong correlation with parents' ratings, while it was weak for girls. Also, agreement on activities and social subscales was stronger for dyads with the youth presenting externalizing instead of internalizing problems. CONCLUSION: Agreement on competencies between parents and adolescents varied based on competency and adolescent sex, age, and type of problem.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".