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Record W2030735425 · doi:10.1258/ijsa.2008.008390

A survey of Cambodian health-care providers' HIV knowledge, attitudes and intentions to take a sexual history

2009· article· en· W2030735425 on OpenAlexafffund
Gail Webber, Nancy Edwards, Ian D. Graham, Carol Amaratunga, Isabelle Gaboury, Virginia Keane, S. Ros, Ian McDowell

Bibliographic record

VenueInternational Journal of STD & AIDS · 2009
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of CalgaryCanadian Institutes of Health ResearchUniversity of Ottawa
FundersCanadian Health Services Research FoundationCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsMedicinePsychological interventionSexual historyReproductive healthTheory of planned behaviorHuman immunodeficiency virus (HIV)Health careFamily medicineSexually transmitted diseaseCross-sectional studyNursingEnvironmental healthPopulationControl (management)

Abstract

fetched live from OpenAlex

Cambodia has one of the highest prevalence rates of HIV in Asia and is scaling up HIV testing. We conducted a cross-sectional survey with 358 health care providers in Phnom Penh, Cambodia to assess readiness for voluntary testing and counselling for HIV. We measured HIV knowledge and attitudes, and predictors of intentions to take a sexual history using the Theory of Planned Behaviour. Over 90% of health care providers correctly answered knowledge questions about HIV transmission, but their attitudes were often not positive towards people living with HIV. The Theory of Planned Behaviour constructs explained 56% of the variance in intention to take a sexual history: the control providers perceive they have over taking a sexual history was the strongest contributor (51%), while social pressure explained a further 3%. Attitudes about taking a sexual history did not contribute to intention. Interventions with Cambodian health care providers should focus on improving skills in sexual history-taking.

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)0.002
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 score0.208
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.112
GPT teacher head0.455
Teacher spread0.343 · 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

Citations5
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of STD & AIDSSame topicAdolescent Sexual and Reproductive HealthFrench-language works237,207