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Record W4388973413 · doi:10.1177/17455057231205677

Access to and quality of care for sexual and gender minority women living with HIV in Metro Vancouver, Canada: Results from a longitudinal cohort study

2023· article· en· W4388973413 on OpenAlexafffundabout
Hannah T. Perrin, Kate Shannon, A.J. Lowik, Ashleigh J. Rich, Stefan Baral, Melissa Braschel, Kathleen Deering

Bibliographic record

VenueWomen s Health · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersNational Institute of Mental HealthCanadian Institutes of Health ResearchNational Institutes of HealthCanadian HIV Trials Network, Canadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsSexual minorityDemographyMedicineCohortLongitudinal studyReproductive healthHealth equityLogistic regressionGerontologySexual identityHealth careIntersectionalityGeneralized estimating equationCohort studySexual orientationPsychologyPublic healthHuman sexualitySocial psychologyPopulationGender studiesSociologyNursingPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: While scarce, literature suggests that women at the intersection of HIV status and gender and/or sexual minority identities experience heightened social and health disparities within health care systems. OBJECTIVES: This study examines the association between sexual and/or gender minority identities and: (1) experiences of poor treatment by health professionals and (2) being unable to access health services among a cohort of women living with HIV in Metro Vancouver, Canada. DESIGN: Data were drawn from a longitudinal community-based cohort of women living with HIV (Sexual Health and HIV/AIDS Women's Longitudinal Needs Assessment). METHODS: We examined associations between sexual and/or gender minority identities and the two outcomes. We drew on explanatory variables to measure sexual minority and gender minority identities independently and a combined variable measuring sexual and/or gender minority identities. The associations between each of these three variables and each outcome were analysed using bivariate and multivariable logistic regression models with generalized estimating equations for repeated measures over time. Adjusted odds ratios and 95% confidence intervals are reported. RESULTS: The study sample included 1460 observations on 315 participants over 4.5 years (September 2014 to February 2019). Overall, 125 (39.7%) reported poor treatment by health professionals and 102 (32.4%) reported being unable to access health care services when needed at least once over the study period. A total of 110 (34.9%) of participants reported sexual and/or gender minority identities, 106 (33.7%) reporting sexual minority identities, with 29 (9.2%) reporting gender minority identities. In multivariable analysis, adjusting for confounders, sexual minority identities, and combined sexual and/or gender minority identities were significantly associated with increased odds of experiencing poor treatment by health professionals (sexual minority adjusted odds ratio = 1.39 (0.94-2.05); sexual and/or gender minority adjusted odds ratio = 1.48 (1.00-2.18)) and being unable to access health services (sexual minority adjusted odds ratio = 1.89 (1.20-2.97); sexual and/or gender minority adjusted odds ratio = 1.91 (1.23-2.98)). In multivariable analysis, gender minority identities were not significantly associated with increased odds of experiencing poor treatment by health professionals (gender minority adjusted odds ratio = 1.38; 95% CI = 0.76-2.52) and being unable to access health services (gender minority adjusted odds ratio = 1.72; 95% CI = 0.89-3.31) possibly due to low sample size among women with gender minority identities. CONCLUSION: Our findings suggest the need for access to inclusive, affirming, trauma-informed health care services tailored specifically for and by women living with HIV with sexual and/or gender minority identities.

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)0.002
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 score0.047
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.100
GPT teacher head0.419
Teacher spread0.319 · 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

Citations3
Published2023
Admission routes3
Has abstractyes

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