Associations between parental attitudes towards mental illness and self-reported mental health among young people: Evidence from the Health Survey for England
Bibliographic record
Abstract
ABSTRACT Background The prevalence of mental health problems among young adults has rapidly increased over the past decade. The argument that reductions in stigma lead to less under-reporting over time is often presented as a potential explanation. As a first step towards understanding how stigma influence self-reporting in this age group, we examine the extent to which parents’ attitudes are related to young people’s self-reported mental health. Methods We leveraged the household design of the 2014 Health Survey for England to test whether mothers’ (complete-case n = 630) and fathers’ ( n = 428) prejudice and tolerance towards people with mental illness is associated with the self-reporting of any specific mental disorder and non-specific psychological distress (GHQ-12) in participants aged 13-24. Associations were tested in random-intercept Poisson models (nesting participants in households) adjusting for parents’ sociodemographics and mental health, and participants’ own sociodemographics. Results Mothers were on average less prejudiced (81.2 versus 74.1 out of 100) but as tolerant (72.0 versus 70.0 out of 100) as fathers. In fully-adjusted models: 1) those with a less prejudiced (PR for a one-unit increase = 1.036, 95%CI 1.007-1.066) and more tolerant (PR = 1.038, 95%CI 1.011-1.066) mother had a higher probability of reporting a mental disorder; 2) those with a less prejudiced (PR = 1.034, 95%CI 1.006-1.062) father had a higher probability of reporting a mental disorder; 3) those with a more tolerant father also had a higher probability of reporting a high level of psychological distress (PR = 1.024, 95%CI 1.008-1.041). Conclusion Parents’ attitudes were associated with their children’s mental health, more so with specific mental disorders compared with non-specific psychological distress. New data collection efforts are needed to understand changes in parental attitudes over time and its relationship with self-reporting among young people.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".