Validation of a measure of maternal perception of the child’s health status
Bibliographic record
Abstract
BACKGROUND: The main objective of this population-based and cross-sectional study was to determine the validity of maternal perception as an indicator of the 17-month-old child's health status. METHODS: Data from this study came from the Quebec Longitudinal Study of Child Development (QLSCD, Round 1999) which was based on a representative sample of babies born in Québec in 1997 and 1998. The analyses were based on the 2045 children aged 17 months who participated in the survey in 1999. Maternal perception of the child's health status was examined as a function of a series of children's health indicators, namely the presence of acute health problems (last 3 months), asthma attacks since birth, presence of chronic problem and hospitalizations during the previous 12 months. Confounding influences of both maternal and child-related characteristics were controlled in the analyses. RESULTS: Sequential logistic regressions indicated that maternal perception was strongly associated with the different health indicators even after controlling for confounding variables. However, a significant interaction between the child's gender and the presence of chronic health problems was observed. The association between maternal perception of the child's health and the presence of chronic health problems was stronger for boys than for girls. CONCLUSIONS: The analyses confirm that the mother's perception of the health status of her 17-month-old child corresponds with the actual health status of the child as reflected by the presence or absence of selected health problems.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".