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Record W2902842438 · doi:10.1371/journal.pone.0208410

Establishing trust in HIV/HCV research among people who inject drugs (PWID): Insights from empirical research

2018· article· en· W2902842438 on OpenAlexaff
Roberto Abadie, Shira M. Goldenberg, Melissa Welch-Lazoritz, Celia B. Fisher

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsSimon Fraser University
FundersNational Institute on Drug AbuseHIV and Drug Abuse Prevention Research Ethics Training Institute, Fordham UniversityNational Institutes of HealthFordham University
KeywordsQualitative researchBiobankContext (archaeology)Empirical researchMedicinePsychologySocial psychologyEnvironmental healthSociologyGeography

Abstract

fetched live from OpenAlex

BACKGROUND: The establishment of trust between researchers and participants is critical to advance HIV and HCV prevention particularly among people who inject drugs (PWID) and other marginalized populations, yet empirical research on how to establish and maintain trust in the course of community health research is lacking. This paper documents ideas about trust between research participants and researchers amongst a sub-sample of PWID who were enrolled in a large, multi-year community health study of social networks and HIV/HCV risk that was recently conducted in rural Puerto Rico. METHODS: Qualitative research was nested within a multi-year Social Network and HIV/HCV Risk study involving N = 360 PWID > 18 years of age living in four small, rural Puerto Rican communities. Semi-structured interviews were conducted between March 2017 and April 2017 with a subset of 40 active PWID who had been enrolled in the parent study. Interview questions invited participants to draw upon their recent experience as research participants to better understand how PWID perceive and understand participant-researcher trust within the context of HIV/HCV-related epidemiological research. RESULTS: Fear of police, stigma and concerns regarding confidentiality and anonymity were identified as structural factors that could compromise participation in HIV/HCV-related research for PWID. While monetary compensation was an important motivation, participants also valued the opportunity to learn about their HIV/HCV status. During their participation in the study, gaining knowledge of safe injection practices was perceived as a valuable benefit. Participant narratives suggested that PWID may adopt an incremental and ongoing approach in their assessment of the trustworthiness of researchers, continuously assessing the extent to which they trust the research staff throughout the course of the research. Trust was initially generated through peer Respondent Driven Sampling recruitment. Research staff who maintained a presence in the community for the entire duration of the prospective study reinforced trust between participants and the research team. CONCLUSION: Although PWID face numerous structural barriers to research-related trust in HIV/HCV research, we found that using a peer-based recruitment method like RDS, and employing a research staff who are knowledgeable about the targeted population, culturally sensitive to their needs, and who maintain a long-term presence in the community may help mitigate many of these barriers. The reputation of the research is built incrementally as participants join the study. This contributes to a "street reputation" that grows as current or former participants vouch for the study. Establishing trust was identified as only the first step towards building a collaborative relationship with participants, and our findings suggest that steps to address criminalization and stigmatization also are necessary to support research trust.

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)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.002

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 head0.245
GPT teacher head0.434
Teacher spread0.189 · 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

Citations52
Published2018
Admission routes1
Has abstractyes

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