Self-Reported Health and Patterns of Romantic Love in Adolescents from Eight European Countries and Regions
Bibliographic record
Abstract
Purpose: Sexual minority youth (SMY) are at increased risk of poor health, but it remains unclear whether this phenomenon is universal. In this study, nationally representative samples of 15-year olds from eight European countries and regions were investigated to test if adolescents who have been in love with same- or both-gender partners report poorer health than those exclusively in love with opposite-gender partners or who have never been in love. Methods: A subsample of 13,674 adolescents participating in the 2014 Health Behaviour in School-aged Children (HBSC) study was used. We conducted binary logistic regression, adjusted for gender, region, and relative family affluence, to analyze associations between self-reported romantic love, multiple psychosomatic symptoms, and poor self-rated health. Results: Adolescents reporting same-gender love (adjusted odds ratio [aOR] = 1.50, 95% confidence interval [CI]: 1.11–2.02) and both-gender love (aOR = 3.57, 95% CI: 2.65–4.83) had significantly higher odds for multiple psychosomatic symptoms than those who reported opposite-gender love. Similarly, both SMY groups had higher odds of poor self-rated health (aOR = 2.95, 95% CI: 1.64–5.31 and aOR = 3.08, 95% CI: 1.79–5.31, respectively). Those who reported that they have never been in love had significantly lower odds for multiple symptoms. Adjustment for sociodemographic variables and stratifying by gender did not substantially change the odds ratios. Conclusion: Adolescents in love with same- and both-gender partners reported poorer subjective health outcomes than those in love with opposite-gender partners or who reported never being in love, suggesting that SMY health inequalities are found across various European countries and regions.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".