The effect of work-family conflicts on withdrawal behaviours in the healthcare sector
Bibliographic record
Abstract
Building on two competing theoretical frameworks (the Stress Management Model and the Domain-Specific Predictor-to-Outcomes Model) we developed a model to test the incidence of six forms of work-family interferences (time-, strain- and behavioral-based family interferences with work – FIW – and work interferences with family – WIF) on four withdrawal behaviours (absenteeism, late arrival, early departure, and work interruptions) using cross-sectional data from a sample of nurses working for a regional hospital in Canada.Data was collected through a paper-and-pen questionnaire and 402 complete questionnaires were analyzed using multivariate regression. Results suggest that the domain-specific predictor-to-outcomes model produces a better explanation of the dependent variables, as the strain-based FIW explain respondents’ absenteism and work interruptions. We didn’t find support for the other hypotheses deduced from this model (influence of time- and behavior-based FIW on withdrawal behaviors) as well as those steming from the stress management model (time-, strain- and behavior-based WIF influence on withdrawal behaviors).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".