Parenthood and psychological distress among English Millennials during the second wave of the COVID-19 pandemic: evidence from the Next Steps cohort study
Bibliographic record
Abstract
PURPOSE: The COVID-19 pandemic led to disproportionate mental health responses in younger adults and parents. The aim of the study was to investigate how Millennial parents' experiences were associated with psychological distress over the first year of the pandemic. METHODS: We examined data in September 2020 (n men = 994; n women = 1824) and February 2021 (n men = 1054; n women = 1845) from the Next Steps cohort study (started ages 13-14 in 2003-04). In each wave, we examined differences in GHQ-12 scores between parent groups defined by the age and number of children, adjusting for background characteristics at ages 13-14, psychological distress at ages 25-26, and other circumstances during the pandemic. We also examined if differences varied by work status, financial situation before the outbreak and relationship status. RESULTS: Whereas mothers with one or two children and children aged 0-2 reported less distress than non-mothers in September 2020, there were no such differences in February 2021. Fathers with three or more children reported more distress in February 2021. Compared with non-fathers who worked, fathers were also disproportionally distressed if they were working with one child or with children aged 2 or less in September 2020. CONCLUSION: The distribution of psychological distress among Millennial parents and non-parents has varied by age, sex, parenting stage, work status and the timing of the pandemic. Generous family policies are needed, with special attention dedicated to parents combining work and family responsibilities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".