Trend Disparities in Emotional Distress and Suicidality Among Sexual Minority and Heterosexual Minnesota Adolescents From 1998 to 2010
Bibliographic record
Abstract
BACKGROUND: Sexual minority young people have demonstrated higher rates of emotional distress and suicidality in comparison to heterosexual peers. Research to date has not examined trends in these disparities, specifically, whether there have been disparity reductions or increases and how outcomes have differed over time by sex and sexual orientation group. METHODS: Minnesota Student Survey data, collected from 9th and 12th graders in 3 cohorts (1998, 2004, 2010) were used to examine emotional distress and suicidality rates. Logistic regression analyses were completed to examine outcome changes over time within and across sexual orientation/sex groups. RESULTS: With few exceptions, sexual minority youth are at increased risk of endorsing emotional distress and suicidality indicators in each surveyed year between 1998 and 2010. Young people with both-sex partners reported more emotional distress across all health indicators compared to their opposite-sex partnered peers. With a few exceptions, gaps in disparities between heterosexual and sexual minority have not changed from 2004 to 2010. CONCLUSIONS: Disparities in emotional health persist among youth. Research is needed to advance understanding of mental health disparities, with consideration of sexual orientation differences and contextualized to sociocultural status and changes over time. Personalized prevention strategies are needed to promote adolescent mental health.
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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 | 0.000 | 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".