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Record W2098204073 · doi:10.1080/09540121.2013.774317

Protective and risk factors associated with stigma in a population of older adults living with HIV in Ontario, Canada

2013· article· en· W2098204073 on OpenAlexaffabout
Charles A. Emlet, David J. Brennan, Sarah Brennenstuhl, Sergio Rueda, Trevor Hart, Sean B. Rourke

Bibliographic record

VenueAIDS Care · 2013
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsSt. Michael's HospitalUniversity of TorontoToronto Metropolitan UniversityOntario HIV Treatment NetworkInstitute for Work & HealthPublic Health Ontario
Fundersnot available
KeywordsStigma (botany)Human immunodeficiency virus (HIV)Clinical psychologyCohortCoping (psychology)PsychologyPopulationMedicineSocial supportCross-sectional studyGerontologyPsychiatryDemographyEnvironmental healthImmunologySocial psychology

Abstract

fetched live from OpenAlex

Although the deleterious effects of HIV stigma are well documented, less is known about how various types of stigma impact older adults living with HIV disease and what factors exacerbate or lessen the effects of HIV stigma. Using cross-sectional data from the OHTN cohort study (OCS), we undertook multiple linear regression to determine the predictors of overall HIV stigma, and enacted, anticipated, and internalized stigma subscales in a sample of OCS participants age 50 and over (n = 378). Being female, heterosexual, engaging in maladaptive coping, and having poor self-rated health were associated with greater overall stigma while being older, having greater mastery, increased emotional-informational social support, and a longer time since HIV diagnosis were associated with lower levels of stigma. The final model accounted for 31% of the variance in overall stigma. Differences in these findings by subscale and implications for practice 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)0.000
metaresearch head score (Gemma)0.002
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 score0.018
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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

Citations86
Published2013
Admission routes2
Has abstractyes

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