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Record W2901309766 · doi:10.1177/1556264618804740

“Why Don’t You Go Into Suburbs? Why Are You Targeting Us?”: Trust and Mistrust in HIV Vaccine Trials in South Africa

2018· article· en· W2901309766 on OpenAlexafffund
Siyabonga Thabethe, Catherine Slack, Graham Lindegger, Abigail Wilkinson, Douglas Wassenaar, Philippa Kerr, Linda‐Gail Bekker, Kathryn Mngadi, Peter A. Newman

Bibliographic record

VenueJournal of Empirical Research on Human Research Ethics · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Toronto
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health Research
KeywordsHuman immunodeficiency virus (HIV)HIV vaccinePublic relationsPolitical scienceVaccine trialEconomic growthVirologyMedicineEconomics

Abstract

fetched live from OpenAlex

Trust is a key element of high-quality stakeholder relations, which are themselves essential for the success of HIV vaccine trials. Where trust is absent, community stakeholders might not volunteer to become involved in key trial activities, and potential participants might not volunteer for enrollment. We explored site staff and Community Advisory Board (CAB) members' experiences of trust/mistrust among community members and potential participants. We analyzed 10 focus group discussions with site staff and CAB members at two active South African HIV vaccine trial sites. We report on key characteristics perceived to contribute to the trustworthiness of communicators, as well as factors associated with mistrust. Attributes associated with trustworthy communicators included shared racial identity, competence, and independence (not being "captured"). Key foci for mistrust included explanations about site selection, stored samples, vaccination, and Vaccine Induced Sero-Positivity (VISP). Our findings suggest that community members' trust is not necessarily global, in which trials are trusted or not; rather, it appears fairly nuanced and is impacted by various perceived attributes of communicators and the information they provide. We make recommendations for clinical trial site stakeholders invested in building trust and for future research into trust at these sites.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.132
metaresearch head score (Gemma)0.228
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1320.228
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.019
Insufficient payload (model declined to judge)0.0020.000

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 head0.525
GPT teacher head0.590
Teacher spread0.065 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative
DomainMethods
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

Citations40
Published2018
Admission routes2
Has abstractyes

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