Parental employment quality and the mental health and school performance of children and youth
Bibliographic record
Abstract
BACKGROUND: Lower-quality employment, characterised by excessive or part-time hours, irregular schedules and inadequate earnings, is a key social determinant of health among adults. Research examining parental employment quality in relation to the mental health and school performance of children is lacking. The study objective was to measure the associations between parental employment quality and child mental health symptoms and school performance. METHODS: We conducted a secondary analysis of the cross-sectional 2014 Ontario Child Health Study. Dependent variables were parent-reported child mental health symptoms and school performance. We used latent class analysis (LCA) to characterise employment status, hours, scheduling and earnings of parents. We used linear and multinomial regression to model the associations between parental employment quality, mental health symptoms, and school performance. RESULTS: Our study sample consisted of 9,927 children. The LCA of dual-parent households yielded three classes of parental employment quality, which we labelled 'Dual Parent, High Quality', 'Dual Parent, Primary Earner Model' and 'Dual Parent, Precarious'. The LCA of single-parent households yielded two further classes, which we labelled 'Single Parent, High Quality' and 'Single Parent, Precarious'. Compared with children in the 'Dual Parent, High Quality' group, children in all other groups had higher-level mental health symptoms and lower school performance. Children with 'precarious' parental employment in both groups showed the least favourable outcomes. CONCLUSIONS: Lower-quality parental employment was associated with increased mental health symptoms and poorer school performance among children. A clearer understanding of these relationships and their underlying mechanisms can help inform relevant policies and interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".