Examining the impact of a change in maternity leave policy in Canada on maternal mental health care visits to the physician
Bibliographic record
Abstract
PURPOSE: Maternity leave is a critical employee benefit that allows mothers to recover from the stress of pregnancy and childbirth and bond with their new baby. We aimed to examine the association between the extension of a maternity leave policy and maternal use of mental health services and prescription drugs in a universal public healthcare system. METHODS: This study uses administrative medical records from 18,000 randomly selected women who gave birth three months before and after an extension of the maternity leave policy. More specifically, mothers who gave birth after January 1st 2001, were entitled to 50 weeks of paid maternity leave, while mothers who gave birth before that date were entitled to only 26 weeks of paid maternity leave. Medical records were analyzed over a seven-year period (i.e., from October 1998 to March 2006). We examined the number and costs of mothers' medical visits for mental health care in the five years following delivery, as well as maternal use of prescribed medication for mental health problems. RESULTS: We found that mothers with extended maternity leave had - 0.12 (95%CI=-0.21; -0.02) fewer medical visits than mothers without a more generous maternity leave and that the cost of mental health services was Can$5 less expensive per women. These differences were found specifically during the extended maternity leave period. CONCLUSIONS: The extra time away from work may help mothers to balance new family dynamics which may result in less demand on the healthcare system.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".