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Record W2116485848 · doi:10.1080/13548506.2011.608803

Cognitive factors and willingness to participate in an HIV vaccine trial among HIV-positive injection drug users

2012· article· en· W2116485848 on OpenAlexafffund
Shayesta Dhalla, Gary Poole, Joel Singer, David M. Patrick, Thomas Kerr

Bibliographic record

VenuePsychology Health & Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsBC Centre for Disease ControlAIDS VancouverSt. Paul's HospitalHIV Legal NetworkUniversity of British Columbia
FundersNational Institute on Drug AbuseCanadian Institutes of Health Research
KeywordsOptimismHIV vaccineHuman immunodeficiency virus (HIV)Psychological interventionSelf-efficacyMedicineVaccine trialCognitionDrugClinical psychologyInternal medicinePsychologyDemographyImmunologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

There are gaps in our knowledge of the role cognitive factors play in determining people's willingness to participate (WTP) in therapeutic HIV vaccine trials. Using a cross-sectional study of HIV-positive injection drug users (IDU), we determined the role of three cognitive factors: HIV treatment optimism, self-efficacy beliefs, and knowledge of vaccine trial concepts in relation to WTP in a hypothetical phase 3 therapeutic HIV vaccine trial. WTP was 54%. Participants tended to be low in HIV treatment optimism (mean = 3.9/10), high in self-efficacy (mean = 79.8/100), and low in knowledge (mean = 4.1/10). Items pertaining to HIV treatment optimism and knowledge of HIV vaccine trial concepts were generally unrelated to WTP. An increase in self-efficacy had a statistically significant positive association with WTP (OR = 1.61, 95% CI = 1.04-2.46, p < 0.05). Furthermore, most of these HIV-positive participants had high levels of self-efficacy, so we are most confident about this relationship at such levels. These findings indicate that interventions focused on increasing self-efficacy could enhance WTP among HIV-positive IDU.

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 score0.024
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.085
GPT teacher head0.481
Teacher spread0.396 · 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

Citations8
Published2012
Admission routes2
Has abstractyes

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