Occupational performance in mothers of children with cerebral palsy
Bibliographic record
Abstract
Background/Aims Caring for children with cerebral palsy may affect different domains in the caregiver's life. This study aimed to compare the occupational performance of mothers of a child who has cerebral palsy with mothers of a typically developing child. Methods A total of 41 mothers with a child who has cerebral palsy and 45 mothers with a typically developing child were recruited in this cross-sectional study. The age-matched mothers had only one child. The Canadian Occupational Performance Measure was used to collect data on the occupational performance and satisfaction of mothers. Findings There was a statistically significant between-group difference in maternal occupational performance and occupational satisfaction (P<0.05), with mothers of children with cerebral palsy reporting lower scores for both. There were no relationships between demographic variables and the occupational performance and satisfaction of mothers with a child with cerebral palsy (P>0.05). The age of children with cerebral palsy had a direct positive relationship with the mothers' level of occupational satisfaction (P<0.05). Conclusion Mothers who take care of a child with cerebral palsy face significant reductions in occupational performance and satisfaction compared to mothers with a typically developing child, and therefore may need help and education in performing and organising their daily activities and roles.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".