Association Between the Parenting Competence and Quality of Life of Family Caregivers of Children Aged 0-3 Years: Cross-Sectional Study
Bibliographic record
Abstract
Background: The quality of life (QoL) for family caregivers significantly influences not only their own well-being but also the well-being of children aged 0-3 years. Competence stands out as a crucial subjective factor that impacts this QoL. Objective: This study aimed to examine the factors affecting the QoL of caregivers of children aged 0-3 years and its correlation with parenting competency. Methods: Caregivers of children aged 0-3 years from the child health department of a tertiary hospital in Changsha, Hunan Province, were chosen as the study sample through convenience sampling. The study investigated the relationship between parenting competency and the caregivers' QoL, utilizing general information, the parenting competency scale, and the family caregiver quality of life scale. Results: In this study, 291 family caregivers, including 13 fathers and 278 mothers of children aged 0-3 years, were evaluated. The mean (SD) parenting competence score was 68.70 (9.816) and the mean (SD) QoL score was 56.81 (8.922). It was found that higher caregiver QoL scores were significantly associated with greater parenting competence (R=0.665, P<.001). Furthermore, each dimension of parenting competence demonstrated a significant positive correlation with each dimension of the QoL (P<.001). Conclusions: The data suggest a notable association between parenting competence and QoL among family caregivers of children aged 0-3 years. This association has implications for improving fertility rates, as enhancing parenting competence may reduce childcare-related stress and thereby enhance the overall QoL.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".