Factors That Affect the Quality of Life of Mothers Caring for Children With Medical Needs at Home: Cross-Sectional Questionnaire Study
Bibliographic record
Abstract
Background The number of children requiring daily medical care is on the rise, with many being cared for at home. This situation places a significant burden on mothers, who often serve as the primary caregivers. Objective This study aimed to clarify the factors that affect the quality of life of mothers with children who require home health care. Methods A questionnaire study was conducted among mothers of children needing medical care at home, with 46 participants responding. The questionnaire included items regarding the child’s condition, the mother’s situation, and the World Health Organization Quality of Life-26scale. Results Factors influencing the quality of life of mothers included whether the child attended daycare or school (β=.274; P=.04), the duration of home care (β=.305; P=.02), and the presence or absence of position changes (β=–.410; P=.003). The presence or absence of position changes had the most significant impact (adjusted R2=.327). Conclusions The most significant factor affecting the quality of life of mothers of children requiring home medical care is the presence or absence of positional changes.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".