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Record W4233321857 · doi:10.32920/ryerson.14646234

A cognitive interference model of sexual functioning for gay men: the relationship between internalized homophobia and erectile function

2021· preprint· en· W4233321857 on OpenAlexafffund
Natalie Stratton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsConcordia UniversityToronto Metropolitan University
FundersCanadian Institutes of Health Research
KeywordsErectile dysfunctionPsychologyAnxietyCognitionClinical psychologyStructural equation modelingDevelopmental psychologyErectile functionPsychiatry

Abstract

fetched live from OpenAlex

Gay men more frequently report erectile difficulties than heterosexual men, possibly due to the additional stress gay men experience as a result of their sexual minority status. Internalized homophobia (IH), defined as the internalization of negative societal attitudes about being gay, is associated with adverse sexual outcomes. However, the mechanisms underlying this relationship remain unclear. According to Barlow’s model of sexual dysfunction, cognitive interference plays a key role in the development and maintenance of erectile dysfunction. The present study examined the cross-sectional and longitudinal relationships between IH, cognitive anxiety symptoms, and erectile function in a sample of 252 HIV-negative gay and bisexual men. Participants completed a battery of self-report questionnaires assessing internalized homophobia, cognitive anxiety symptoms, and erectile functioning at baseline, 3-month, and 6-month follow-ups. Cognitive anxiety symptoms did not mediate the relationship between IH and erectile function at baseline or across 6-months. Limitations and future directions are discussed.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.221
GPT teacher head0.372
Teacher spread0.151 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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