MétaCan
Menu
Back to cohort
Record W2020726490 · doi:10.1089/jwh.2012.3718

Attitudes and Knowledge Among Obstetrician-Gynecologists Regarding Lesbian Patients and Their Health

2013· article· en· W2020726490 on OpenAlexaffabout
Hasan M. Abdessamad, Mark H. Yudin, Lesley A. Tarasoff, Kimberly D. Radford, Lori E. Ross

Bibliographic record

VenueJournal of Women s Health · 2013
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsCentre for Addiction and Mental HealthSt. Michael's HospitalVitalité Health Network
Fundersnot available
KeywordsLesbianMedicineFamily medicineCurriculumPopulationObstetrics and gynaecologyPsychologyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: The lesbian patient population is underserved. Almost no research has examined the knowledge and attitudes of obstetrician-gynecologists toward lesbian health. Our study sought to address this research gap. METHODS: All 910 obstetrician-gynecologists licensed in Ontario, Canada, were mailed a true-false survey about lesbian health issues, the Homosexuality Attitudes Scale (HAS), and a demographic survey. RESULTS: Of the 910 surveys, 271 were returned. The mean HAS score was 87.6 (standard deviation [SD] 11.5), indicating an overall positive attitude. The mean knowledge score was 76.0% (SD 9.5), indicating that respondents had adequate knowledge about lesbian health; 22% described their lesbian health knowledge-base as unaware. Most respondents reported lack of education on lesbian health in residency (81%) or medical school (78%). The majority reported a desire for formal education pertaining to lesbian health. There was no correlation between HAS and knowledge scores. CONCLUSIONS: Although our results indicate overall adequate knowledge about lesbian health issues, important knowledge gaps were identified. Medical school and residency training curricula should include formal education about lesbian health issues, particularly because most obstetrician-gynecologists report a desire to receive this information.

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 score0.124
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.352
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.

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

Citations53
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Women s HealthSame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207