Testing the Goodness-of-Fit of a Multifaceted Preventive Intervention for Children at Risk for Conduct Disorder
Bibliographic record
Abstract
OBJECTIVE: To determine the importance of parents' global adaptive functioning as a predictor of participation rate and subsequent child social competence outcome in 3 program components of an evidence-based, multifaceted, preventive intervention for at-risk children. METHOD: Families of program children (n = 124, mean age 6.6 years at recruitment) were offered 3 program components that continued for 3 years: a 6-week summer program, a biweekly family program that included concurrent parent and child education and skills training groups, and a flexibly tailored home visitation family support program. We used structural equation modelling to test hypotheses about the effects of parental characteristics on program attendance in each of the program components over 3 years, as well as their relation to children's social competence. RESULTS: Predictors of attendance included child IQ, socioeconomic status (SES), and single-parent status for some components but not others, depending on parents' global adaptive functioning. Predictors of child social competence outcome were mediated by attendance in specific program components and were dependent on parent global adaptive functioning. Some components contributed decisively to social competence outcomes, and others did not, despite subjects' participation. CONCLUSIONS: Common family characteristics (that is, child IQ, SES, and single-parent status) predict program attendance differently, depending on parents' global adaptive functioning. Parents' global adaptive functioning determined whether attendance in specific program components mediated children's social competence. In this preventive intervention, as in clinical practice, only knowledge of the goodness-of-fit between participant characteristics and program attributes can ensure optimum benefit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.031 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".