Parental employment quality during childhood and mental health in adolescence: a 10-year longitudinal study
Bibliographic record
Abstract
Socioeconomic conditions play an important role in shaping the mental health outcomes of children and youth. Socioeconomic disadvantage in early life is often a product of precarious parental employment. Although more and more parents are participating in the workforce, a growing share of working parents rely on jobs that are insecure, unstable, and low paying. Against the backdrop of these trends, we examined the relationship between parental employment quality during childhood and mental health in adolescence among dual-parent families in Canada. Data were drawn from the National Longitudinal Survey of Children and Youth (n = 3955). We used latent class analysis to construct longitudinal and multidimensional profiles of maternal and paternal employment quality across early (ages 4-5), middle (ages 8-9), and late (ages 12-13) childhood. We then quantified associations between childhood profiles of parental employment quality and emotional and behavioural difficulties in adolescence (ages 14-15). Latent class analysis identified three types of household employment arrangements: 'High Quality', 'Primary Earner', and 'Precarious'. After adjusting for baseline child, parent, and household characteristics, parental employment quality during childhood was a significant predictor of emotional (but not behavioural) difficulties. Relative to their counterparts in the 'High Quality' group, adolescents exposed to 'Primary Earner' and 'Precarious' parental employment were nearly twice as likely to report serious emotional difficulties. We conclude that low-quality (e.g., precarious) parental employment contributes to the mental health challenges that young people face, reinforcing the importance of stable and rewarding jobs for fostering the emotional well-being of children and youth.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".