Child self-report and parent ratings of health-related quality of life in school-aged children born preterm
Bibliographic record
Abstract
Recent progress in science and medicine is that regions such as the United States, Canada, Australia, and Western Europe have witnessed dramatic declines in infant morbidity and mortality. The most significant of these declines has occurred among infants born prematurely and low birth weight (LBW)--the cohort that represents the highest proportion of illness and death among infants Despite these medical advances, recent longitudinal studies have provided clear evidence of physical health problems; cognitive and neuropsychological dysfunction; and other social, emotional, and behavioral problems among children born prematurely. A number of studies have indicated that premature and LBW infants are still at risk for psychosocial, physical, and mental problems despite the immediate contributions of post-natal interventions to their increased chance for survival The extant research has demonstrated that children born prematurely and LBW are at risk for problems in health, neuropsychological functioning, learning, academic achievement, behavior, and psychosocial adjustment. Research has further demonstrated that a variety of physical and psychological conditions are associated with poorer QOL among children. However, few studies have examined pediatric QOL among preterm school-aged children. Moreover, existing studies have not explored the relationship between cognitive, academic, and social/emotional functioning and QOL. The current study compared child and parent ratings of health-related quality of life among school-aged children born preterm (n = 26) and full-term (n = 28). Given the increased rates of physical, psychological, and cognitive problems among the preterm population, it was hypothesized that children born prematurely would have significantly poorer proxy-reported and self-reported QOL than children born preterm.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".