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Record W2579281776 · doi:10.1177/1557988316685492

Depression and Suicidality in Gay Men: Implications for Health Care Providers

2017· article· en· W2579281776 on OpenAlexafffund
Carrie Lee, John L. Oliffe, Mary T. Kelly, Olivier Ferlatte

Bibliographic record

VenueAmerican Journal of Men s Health · 2017
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of British Columbia
FundersMovember Canada
KeywordsMental healthDepression (economics)PsychiatryPsychologyHomosexualityPopulationMinority stressSocioeconomic statusEthnic groupHealth careSexual minoritySexual orientationMedicineClinical psychologySocial psychologyEnvironmental healthSociology

Abstract

fetched live from OpenAlex

Gay men are a subgroup vulnerable to depression and suicidality. The prevalence of depression among gay men is three times higher than the general adult population. Because depression is a known risk factor for suicide, gay men are also at high risk for suicidality. Despite the high prevalence of depression and suicidality, health researchers and health care providers have tended to focus on sexual health issues, most often human immunodeficiency virus in gay men. Related to this, gay men's health has often been defined by sexual practices, and poorly understood are the intersections of gay men's physical and mental health with social determinants of health including ethnicity, locale, education level, and socioeconomic status. In the current article summated is literature addressing risk factors for depression and suicidality among gay men including family acceptance of their sexual identities, social cohesion and belonging, internalized stigma, and victimization. Barriers to gay men's help seeking are also discussed in detailing how health care providers might advance the well-being of this underserved subgroup by effectively addressing depression and suicidality.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.052
GPT teacher head0.482
Teacher spread0.430 · 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 source (direct Gemma or distilled Codex), 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

Citations112
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Men s HealthSame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207