High Prevalence of Depression Symptoms Among Bisexual Women: The Association of Sexual Orientation and Gender on Depression Symptoms in a Nationally Representative U.S. Sample
Bibliographic record
Abstract
Bisexual individuals experience higher rates of depression than heterosexual individuals and women experience higher rates of depression than men; however, few studies have quantified the joint effects of sexual orientation and gender. In the 2013–2014 and 2015-2016 National Health and Nutrition Examination Survey, depression symptoms were assessedusing the Patient Health Questionnaire. We used pooled and gender-stratified Poisson regression with robust variances to determine the independent effects of sexual orientation and gender on depression symptoms and calculated relative excess risk due to interaction to examine the joint effects of bisexual orientation and women’s gender on depression symptoms. In adjusted models, depression symptoms were 1.78 times higher in women than in men (99% confidence interval [CI]: 1.776, 1.782), 1.73 times higher in bisexual individuals than in heterosexual individuals (99% CI: 1.726, 1.735), and 3.15 times higher in bisexual women than in heterosexual men (99% CI: 3.145, 3.163). We found evidence for a non-additive model of the excess prevalence of depression symptoms among bisexual women. Gender-specific services addressing the unique mental health needs of bisexual women are needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".