Adolescents’ psychological health during the economic recession: does public spending buffer health inequalities among young people?
Bibliographic record
Abstract
BACKGROUND: Many OECD countries have replied to economic recessions with an adaption in public spending on social benefits for families and young people in need. So far, no study has examined the impact of public social spending during the recent economic recession on health, and social inequalities in health among young people. This study investigates whether an increase in public spending relates to a lower prevalence in health complaints and buffers health inequalities among adolescents. METHODS: Data were obtained from the 2009/2010 "Health Behaviour in School-aged Children (HBSC)" study comprising 11 - 15-year-old adolescents from 27 European countries (N = 144,754). Socioeconomic position was measured by the Family Affluence Scale (FAS). Logistic multilevel models were conducted for the association between the absolute rate of public spending on family benefits per capita in 2010 and the relative change rate in family benefits (2006-2010) in relation to adolescent psychological health complaints in 2009/2010. RESULTS: The absolute rate of public spending on family benefits in 2010 did not show a significant association with adolescents' psychological health complaints. Relative change rates of public spending on family benefits (2006-2010) were related to better health. Greater socioeconomic inequalities in psychological health complaints were found for countries with higher change rates in public spending on family benefits (2006-2010). CONCLUSIONS: The results partially support our hypothesis and highlight that policy initiatives in terms of an increase in family benefits might partially benefit adolescent health, but tend to widen social inequalities in adolescent health during the recent recession.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".