La perception maternelle de la qualité de vie d’enfants nés extrêmement prématurés durant la petite enfance : une étude descriptive corrélationnelle
Bibliographic record
Abstract
Introduction: Research on quality of life exclusively in the context of extreme prematurity and preschool is almost non-existent. Objective: The purpose of this descriptive correlational study was to describe the quality of life of children born extremely premature, during infancy, according to maternal perception. The specific objectives were to describe the different dimensions of the quality of life of children born extremely premature and to explore the relationships between certain sociodemographic and clinical variables and quality of life. The study was based on Callista Roy's adaptation model (1976). Method: Forty-two parents of children born extremely premature and aged 2 to 5 years responded to the PedsQL 4.0 during telephone interviews. Results: Overall, the results show that the children have a good quality of life, as perceived by the mothers. Physical functioning was the most optimal dimension of quality of life, while emotional functioning was the least optimal. Furthermore, children from nuclear families have a better global quality of life than children from other family types. Discussion and conclusion: Extreme prematurity requires careful monitoring by nurses to ensure healthy development of toddlers and therefore good quality of life. Future research is needed to further document the quality of life of children born extremely premature at preschool age.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".