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Record W4389134477 · doi:10.1080/00918369.2023.2287034

Access to Healthcare and Unmet Needs in the Canadian Lesbian-Gay-Bisexual Population

2023· article· en· W4389134477 on OpenAlexaffabout
Patrick M. Hickey, Lisa A. Best, David Speed

Bibliographic record

VenueJournal of Homosexuality · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsLesbianHealth careSexual minorityHomosexualityHealth equityPopulationPsychologySexual orientationMedicineFamily medicineNursingPublic healthSocial psychologyPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

Individuals who identify as a sexual minority, including those who are lesbian, gay, or bisexual (LGB), face barriers to healthcare as well as increased discrimination, stigmatization, and negative experiences during healthcare use. Further, few healthcare providers have education and training focused on the specific healthcare needs of individuals who are part of a sexual minority group. Given the limited research on Canadian healthcare access for sexual minorities, our purpose was to use data (n > 2,800) from the 2015–16 Canadian Community Health Survey (CCHS) to investigate the perceptions of healthcare access for LGB and non-LGB Canadians. Although non-LGB and LGB participants reported comparable access to a regular care provider and were equally likely to have consulted with a general practitioner in the past 12 months, LGB respondents were more likely to have seen a specialist and reported more unmet health needs. Although we expected the linear effects of both race and sex to vary by LGB status, this effect only occurred in one model. Current results have implications for addressing health inequalities for sexual minorities, including poorer health outcomes and greater discrimination.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.256
GPT teacher head0.515
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of HomosexualitySame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207