Sexual identity visibility, mental health, and body dissatisfaction in bisexual cisgender men: associations with straight and gay community bi-negativity
Bibliographic record
Abstract
Bisexual cisgender men experience stigma from both straight and LGBTQ+ communities, yet the sources and pathways of harm are rarely disaggregated. We examined how bi-negativity from straight and gay communities relates to sexual identity visibility (outness), mental health and well-being, and body dissatisfaction. In a pre-registered study of UK-based bisexual cisgender men (N = 200; 80.5% White), participants completed measures of bi-negativity, sexual identity visibility, mental health and well-being, body dissatisfaction, and perceived gay community stress. Straight community bi-negativity was associated with poorer mental health and well-being, which in turn was associated with greater body dissatisfaction; no serial mediation pathway via sexual identity visibility emerged. Gay community bi-negativity showed no direct relationship to body dissatisfaction or mental health and well-being, but was positively associated with sexual identity visibility and indirectly linked to better mental health via increased visibility, contrary to our predictions. Perceived gay community stress did not moderate pathways from gay community bi-negativity. Findings show distinct routes by which dual-source bi-negativity influences bisexual men’s mental health and well-being and body image, underscoring the urgency of reducing straight community prejudice and supporting bisexual visibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".