National level wealth inequality and socioeconomic inequality in adolescent mental wellbeing
Bibliographic record
Abstract
Abstract Background Previous research established a positive association between national income inequality and socioeconomic inequalities in adolescent health, but little is known about the extent to which national level inequalities in accumulated financial resources (i.e. wealth) are associated with these health inequalities. Therefore, we examined the association between national wealth inequality and income inequality and socioeconomic inequalities in adolescent mental wellbeing. Methods Data were from 17 countries participating in three successive waves (2010, 2014 and 2018) of the cross-sectional Health Behaviour in School-aged Children (HBSC) study. We combined individual-level data on adolescents' life satisfaction, psychological and somatic symptoms and socioeconomic status (SES) with country-level data on income and wealth inequality (n = 244771). We performed time-series analysis on a pooled sample of 48 country/year groups. Results Higher levels of national wealth inequality were associated with fewer average psychological and somatic symptoms, while higher levels of national income inequality were associated with more psychological and somatic symptoms. No associations between either national wealth inequality or income inequality and life satisfaction were found. Smaller differences in somatic symptoms between higher and lower SES groups were found in countries with higher levels of national wealth inequality. In contrast, larger differences in psychological symptoms and life satisfaction (but not somatic symptoms) between higher and lower SES groups were found in countries with higher levels of national income inequality. Conclusions Although both national wealth and income inequality are associated with (socioeconomic inequalities in) adolescent mental wellbeing, associations are in opposite directions. Further research is warranted to gain better understanding in the role of national wealth inequality on (socioeconomic inequalities in) adolescent health. Key messages This is one of the first studies to examine if socioeconomic inequalities in adolescent mental wellbeing are associated with national wealth inequality independently from national income inequality. Opposing effects of national wealth inequality and income inequality on socioeconomic inequalities in adolescents’ mental wellbeing warrant further research before policy recommendations can be made.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".