Bisexuality, poverty and mental health: A mixed methods analysis
Bibliographic record
Abstract
Bisexuality is consistently associated with poor mental health outcomes. In population-based data, this is partially explained by income differences between bisexual people and lesbian, gay, and/or heterosexual individuals. However, the interrelationships between bisexuality, poverty, and mental health are poorly understood. In this paper, we examine the relationships between these variables using a mixed methods study of 302 adult bisexuals from Ontario, Canada. Participants were recruited using respondent-driven sampling to complete an internet-based survey including measures of psychological distress and minority stress. A subset of participants completed a semi-structured qualitative interview to contextualize their mental health experiences. Using information regarding household income, number of individuals supported by the income and geographic location, participants were categorized as living below or above the Canadian Low Income Cut Off (LICO). Accounting for the networked nature of the sample, participants living below the LICO had significantly higher mean scores for depression and posttraumatic stress disorder symptoms and reported significantly more perceived discrimination compared to individuals living above the LICO. Grounded theory analysis of the qualitative interviews suggested four pathways through which bisexuality and poverty may intersect to impact mental health: through early life experiences linked to bisexuality or poverty that impacted future financial stability; through effects of bisexual identity on employment and earning potential; through the impact of class and sexual orientation discrimination on access to communities of support; and through lack of access to mental health services that could provide culturally competent care. These mixed methods data help us understand the income disparities associated with bisexual identity in population-based data, and suggest points of intervention to address their impact on bisexual mental health.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".