Gender differences in mental health following the transition into parenthood: Longitudinal evidence from the UK
Bibliographic record
Abstract
Previous studies have largely omitted a dynamic analysis of how the transition into parenthood shapes gender differences in mental health trajectories. This study adopts a life course approach to examine how transitioning into parenthood affects men's and women's mental health across multiple domains over time, using large-scale panel data from the 'UK Household Longitudinal Study' (2009-2020). Results from fixed effects models with discrete-time trends show that: (1) women's mental health is more largely affected by parenthood than men's; (2) women's overall mental health shows stable improvements following childbirth, while men's shows mostly insignificant changes; (3) role and social functioning are largely improved among women following childbirth, but only marginally among men; (4) emotional functioning and vitality demonstrate the counteracting effects of parenthood for both genders, with increases in feeling happy but a deterioration in feeling calm and having energy, particularly during care-intensive years; (5) women show larger variations by socioeconomic characteristics than men, with women from higher socioeconomic backgrounds and working full-time experiencing smaller mental health benefits from parenthood compared to less privileged women or having lower paid work constraints. Overall, transitioning to parenthood leads to distinct changes in mental health domains with heterogeneous effects across genders and socioeconomic groups.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".