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Record W2296047509 · doi:10.1186/s12889-016-2859-6

Actual sexual risk and perceived risk of HIV acquisition among HIV-negative men who have sex with men in Toronto, Canada

2016· article· en· W2296047509 on OpenAlexafffundabout
Maya Kesler, Rupert Kaul, Juan Liu, Mona Loutfy, Dionne Gesink, Ted Myers, Robert S. Remis

Bibliographic record

VenueBMC Public Health · 2016
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsMaple Leaf Medical ClinicUniversity Health NetworkWomen's College HospitalUniversity of TorontoPublic Health Ontario
FundersCanadian Institutes of Health Research
KeywordsMedicineRisk perceptionDemographyMen who have sex with menBiostatisticsCasualLogistic regressionRisk factorRisk assessmentEpidemiologyOdds ratioGerontologyEnvironmental healthHuman immunodeficiency virus (HIV)Family medicinePsychologySyphilisPerceptionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Theory suggests that perceived human immunodeficiency virus (HIV) risk and actual HIV risk behaviour are cyclical whereby engaging in high risk behaviour can increase perceived risk, which initiates precautionary behaviour that reduces actual risk, and with time reduces perceived risk. While current perceived risk may impact future actual risk, it is less clear how previous actual risk shapes current perceived risk. If individuals do not base their current perceived risk on past behaviour, they lose the protective effect of perceived risk motivating precautionary behaviour. Our goal was to determine the impact of actual risk on perceived risk. METHODS: Sexually active men who have sex with men (MSM) were recruited at the Maple Leaf Medical Clinic in downtown Toronto from September 2010 to June 2012. Participants completed a socio-behavioural questionnaire using an Audio Computer Assisted Self-Interview (ACASI). Actual HIV risk (primary predictor) was constructed by applying principal component analysis (PCA) to eight sexual risk survey questions and comprised three components which reflected sex with casual partners, sex with HIV-positive regular partners and sex with HIV unknown status regular partners. Perceived HIV risk (outcome) was measured by asking participants what the chances were that they would ever get HIV. Multivariable logistic regression was used to measure the association between actual and perceived HIV risk. RESULTS: One hundred and fifty HIV-negative MSM were recruited (median age 44.5 years [IQR 37-50 years]). Twenty percent of MSM perceived their HIV risk to be high. The odds of having a high perceived risk was significantly higher in those with high actual HIV risk indicated by low condom use with an HIV-positive regular partner compared to those with low actual HIV risk indicated by high condom use with an HIV-positive regular partner (Odds Ratio (OR) 18.33, 95% confidence interval (CI) 1.65-203.45). Older age was associated with lower perceived risk but only age 40-49 compared to less than 30 was statistically significant (OR 0.12, 95% CI 0.016-0.86). The odds of having high perceived risk was significantly associated with men who used poppers in the previous 6 months compared to those who did not use poppers (OR 5.64, 95% CI 1.20-26.48). CONCLUSIONS: Perceived HIV risk increased significantly as condom use with an HIV-positive regular partner decreased. However, perceived HIV risk was not associated with condom use with casual partners or HIV unknown status regular partners, even though these behaviours could be considered risky. The relationship between perceived and actual risk in HIV studies is complex and has implications on how health care workers address the issue of risky sexual behaviour and perceived risk.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.310
Teacher spread0.291 · 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

Citations46
Published2016
Admission routes3
Has abstractyes

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