A Longitudinal Study of Siblings of Children with Chronic Disabilities
Bibliographic record
Abstract
OBJECTIVE: To examine the unaffected siblings of 2 different groups with chronic disabilities, pervasive developmental disorder (PDD) and Down syndrome (DS), over 3 years, comparing their adjustment with each other and with the siblings of a nondisabled group. METHOD: This study examines 137 siblings of children with PDD, children with DS, and developmentally normal children (control group) initially and 127 siblings at follow-up 3 years later. Their adjustment is measured by the Survey Diagnostic Instrument (SDI), completed by caregivers and teachers. Predictor variables include sibling self-perception, social support, and relationship with sibling, as indicated by siblings; caregiver psychosocial factors such as parental stress, caregiver depression, and marital relationship; family systems characteristics as viewed by both caregiver and sibling; and difficulty that disabled child causes as perceived by the primary caregiver. RESULTS: Significantly more adjustment problems are found in the siblings of PDD children at both times when compared with siblings of DS and control children. Caregivers of PDD children report the highest levels of distress and depression, and this persists over time. Parent distress was found, at both times, to be related to sibling adjustment problems, regardless of study group. CONCLUSION: These results have implications for preventive intervention for the unaffected siblings of PDD children.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".