Impact of childhood type 1 diabetes on maternal work-family relations
Bibliographic record
Abstract
BACKGROUND: The aim of the study was to evaluate work-family conflict (WFC) and work-family facilitation (WFF) of working mothers of children with type 1 diabetes (T1D) compared with those of working mothers of children under follow-up not requiring treatment and of healthy children, and to explore the impact of organizational resources and the characteristics of the child and his disease on this interface. METHODS: The study included 157 working mothers: 50 mothers of children with T1D, 50 mothers of children on medical follow-up without chronic illness and 57 mothers of healthy children. The participants completed validated questionnaires including the WFC scale, WFF scale, organizational resources support scale, life and work satisfaction questionnaire, a background demographic questionnaire and a child health questionnaire. Mothers of children with T1D also completed a questionnaire relating to diabetes management. RESULTS: Almost half of the mothers of children with T1D found it necessary to reduce their working hours or to change their workplace. This group also reported a significantly higher level of colleague support. There were no significant differences in WFC and WFF between mothers of children with T1D and controls. CONCLUSIONS: This study demonstrates the effect of raising a T1D child on the mother's vocational behavior. Despite the additional burden, work is a source of enrichment for these mothers.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".