Experiences accessing healthcare among 2SLGBTQIA+ people in Canada and the United States
Bibliographic record
Abstract
Members of 2SLGBTQIA+ communities experience pervasive barriers to accessing healthcare services, including discrimination, care providers lacking knowledge or training, and limited specialized care compared to the general population (Comeau et al., 2023;Tami et al., 2022).An online questionnaire was administered to 534 participants across Canada and the United States to assess experiences of healthcare access between 2SLGBTQIA+ and non-2SLGBTQIA+ respondents.The final sample was composed of 296 2SLGBTQIA+ participants and 238 non-2SLGBTQIA+ respondents.A series of Chi-square tests and t-tests were used to identify differences across the two groups.2SLGBTQIA+ participants reported worse overall access to health services, difficulties affording, and were more likely to have unmet health needs compared to non-2SLGBTQIA+ respondents.Further, 2SLGBTQIA+ individuals were significantly more likely to experience a delay in receiving care and a negative impact on access due to the distance to healthcare.Interestingly, 2SLGBTQIA+ individuals were more like to report having a mental healthcare provider, while also reporting significantly greater difficulty affording such care compared to non-2SLGBTQIA+.Importantly, no significant differences were found between the two groups on access to a primary healthcare provider and wait-times for health services.Results demonstrate the disparities in access to healthcare experienced by 2SLGBTQIA+ individuals and identified key barriers including distance and affordability.The results of this study highlight the unique health service needs of 2SLGBTQIA+ individuals and can be used to address key barriers to accessing care for marginalized communities.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".