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Record W2097703436 · doi:10.1177/1049732311431944

Perceptions of Sexual Risk Compensation Following Posttrial HIV Vaccine Uptake Among Young South Africans

2012· article· en· W2097703436 on OpenAlexaff
Catherine MacPhail, Jennifer N. Sayles, William E. Cunningham, Peter A. Newman

Bibliographic record

VenueQualitative Health Research · 2012
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of Toronto
FundersCenter for HIV Identification, Prevention, and Treatment Services, University of California, Los AngelesNational Institute on Minority Health and Health DisparitiesNational Center on Minority Health and Health DisparitiesNational Institute of Mental HealthNational Institute on AgingNational Institutes of Health
KeywordsFocus groupHIV vaccineFeelingQualitative researchCondomRisk compensationHuman immunodeficiency virus (HIV)Compensation (psychology)MoralityMedicinePsychologySocial psychologyFamily medicineSociologyPolitical scienceVaccine trial

Abstract

fetched live from OpenAlex

Concerns about the impact of risk compensation on advances in biomedical human immunodeficiency virus (HIV) prevention technologies have been documented. We conducted an exploratory qualitative study using focus group discussions with young South African men and women (aged 18 to 24 years) to explore perceptions of risk compensation with regard to a hypothetical posttrial HIV vaccine. During the discussions, participants expressed their disquiet about the potential for risk compensation and the manner in which this might manifest among young people. Discussions specifically focused on reductions in condom use, an increase in multiple partners, and increased frequency of sex. The discussions also revealed contradictory feelings about HIV vaccines: appreciation for their development tempered by concerns about loss of control and undermining morality. Women were particularly concerned with the possibility of increased partner concurrency and infidelity. We suggest that concerns in HIV vaccine target populations about the impact of possible risk compensation be incorporated into strategies for vaccine introduction once vaccines move from the hypothetical to reality.

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)0.046
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0460.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.489
GPT teacher head0.607
Teacher spread0.118 · 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.

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

Citations21
Published2012
Admission routes1
Has abstractyes

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