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Record W4387001593 · doi:10.37989/gumussagbil.1320977

Health Professionals’ Attitudes Towards Lesbian and Gay Individuals, and Levels of Homophobia and Empathy: A Case of Turkey

2023· article· en· W4387001593 on OpenAlexaboutno aff
Merve Aydın, Ceyda Uzun Şahin

Bibliographic record

VenueGümüşhane Üniversitesi Sağlık Bilimleri Dergisi · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLesbianEmpathyPsychologySnowball samplingHealth carePopulationHealth professionalsScale (ratio)MedicineSocial psychologyCartographyEnvironmental health

Abstract

fetched live from OpenAlex

This study aimed to determine the attitudes, homophobia, and empathy levels of healthcare professionals toward Lesbian and Gay individuals. This descriptive and cross-sectional study’s population consisted of healthcare workers working in hospitals in Turkey between April 2022 and August 2022. Using snowball method, 678 healthcare professionals who consented to participate in the study were recruited for the study. The data were collected using a questionnaire developed by the researchers, the Attitudes Toward Lesbians and Gays Scale (ATLGS), the Hudson and Ricketts Homophobia Scale (HRHS), and the Toronto Empathy Scale (TES).79.4% of the participants reported that caring for Lesbian and Gay (LG) individuals is no different from caring for heterosexual individuals. Low homophobia levels, work experience, and the existence of gay friends were identified as factors significantly influencing healthcare professionals’ positive attitudes toward LG. Healthcare professionals have partially positive attitudes about LG individuals and partially homophobic attitudes, and their empathetic abilities influence their attitudes toward them.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.071
GPT teacher head0.394
Teacher spread0.324 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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