Predictors and Correlates of Inattentive/Overactive Behaviors in Internationally Adopted Children
Bibliographic record
Abstract
Children adopted internationally following deprived early care have an elevated risk for difficulties with inattention/overactivity (Kreppner et al., 2001 Kreppner, J. M., O'Connor, T. G., Rutter, M. & the English and Romanian Adoptees Study Team. (2001). Can inattention/overactivity be an institutional deprivation syndrome?, Journal of Abnormal Child Psychology, 29, 513–528.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). The current study sought to identify predictors of inattention/overactivity and child and adoptive family challenges that co-occur with inattention/overactivity difficulties in a sample of internationally adopted children. Forty-eight children (mean age at adoption = 57.98 months, SD = 47.7 months) were examined at 3 yearly assessments, which included semistructured interviews, parent ratings, and neuropsychological assessment with children. Results revealed that older age at adoption, longer time in the adoptive home, and smaller family size were associated with greater parent-rated difficulties with inattention/overactivity. Additionally, greater inattention/overactivity difficulties were associated with poorer expressive language and reading performance, poorer child emotional-behavioral outcomes, and poorer adoptive family functioning. Given the increase in difficulties over time in the adoptive home, longer-term follow-up may be helpful to ensure appropriate intervention. Additionally, interventions may need to be more comprehensive given the connection between inattentive/overactive behaviors and other areas of functioning.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".