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Record W2135305114 · doi:10.1177/1049732309348362

Accounts of HIV Seroconversion Among Substance-Using Gay and Bisexual Men

2009· article· en· W2135305114 on OpenAlexafffund
Jeffrey P. Aguinaldo, Ted Myers, Karen Ryder, Dennis J. Haubrich, Liviana Calzavara

Bibliographic record

VenueQualitative Health Research · 2009
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of TorontoToronto Metropolitan UniversityWilfrid Laurier University
FundersCanadian Institutes of Health Research
KeywordsSeroconversionPsychologySubstance useMen who have sex with menHuman immunodeficiency virus (HIV)HomosexualityClinical psychologySocial psychologyMedicineFamily medicine

Abstract

fetched live from OpenAlex

Statistical associations between substance use and seroconversion among gay and bisexual men abound. However, these associations often ignore men's own interpretations of their seroconversion. Using in-depth interviews with gay and bisexual men who reported using drugs or alcohol at the time of their seroconversion, we identify how these men explain the events that led to HIV transmission. Whereas a small minority of respondents reported substance use to explain their seroconversion, the majority reported three competing explanations. These participants claimed that they lacked sufficient knowledge about the behavioral risks that led to their seroconversion; that their decision to engage in unsafe sex was because of negative personal affect; and that they "trusted the wrong person." We link these findings to prevention and suggest that gay and bisexual men who use substances for recreational purposes will benefit from prevention efforts designed to address issues of gay and bisexual men rather than substance-using men.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.442
GPT teacher head0.609
Teacher spread0.167 · 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 designQualitative
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

Citations9
Published2009
Admission routes2
Has abstractyes

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