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Record W2958610901 · doi:10.1186/s12954-019-0309-3

Hiring, training, and supporting Peer Research Associates: Operationalizing community-based research principles within epidemiological studies by, with, and for women living with HIV

2019· article· en· W2958610901 on OpenAlexafffundabout
Angela Kaida, Allison Carter, Valerie Nicholson, Jo Lemay, Nadia O’Brien, Saara Greene, Wangari Tharao, Karène Proulx‐Boucher, Rebecca Gormley, Anita C. Benoit, Mélina Bernier, Jamie Thomas‐Pavanel, Johanna Lewis, Alexandra de Pokomandy, Mona Loutfy

Bibliographic record

VenueHarm Reduction Journal · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsYork UniversityUniversité de MontréalPublic Health OntarioUniversity of TorontoSimon Fraser UniversityMcGill UniversityMcGill University Health CentreWomen's College HospitalMcMaster UniversityHIV Legal NetworkAIDS VancouverWomen's Health In Women's HandsPositive Living Society of British ColumbiaCAAN Communities, Alliances & Network
FundersFonds de Recherche du Québec - SantéCanadian HIV Trials Network, Canadian Institutes of Health ResearchCanadian Institutes of Health ResearchOntario HIV Treatment Network
KeywordsOperationalizationHealth psychologyHuman immunodeficiency virus (HIV)Quality of Life ResearchPsychologyPeer reviewEpidemiologyGerontologyPublic healthApplied psychologyMedical educationMedicineNursingPolitical scienceFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: A community-based research (CBR) approach is critical to redressing the exclusion of women-particularly, traditionally marginalized women including those who use substances-from HIV research participation and benefit. However, few studies have articulated their process of involving and engaging peers, particularly within large-scale cohort studies of women living with HIV where gender, cultural and linguistic diversity, HIV stigma, substance use experience, and power inequities must be navigated. METHODS: Through our work on the Canadian HIV Women's Sexual and Reproductive Health Cohort Study (CHIWOS), Canada's largest community-collaborative longitudinal cohort of women living with HIV (n = 1422), we developed a comprehensive, regionally tailored approach for hiring, training, and supporting women living with HIV as Peer Research Associates (PRAs). To reflect the diversity of women with HIV in Canada, we initially hired 37 PRAs from British Columbia, Ontario, and Quebec, prioritizing women historically under-represented in research, including women who use or have used illicit drugs, and women living with HIV of other social identities including Indigenous, racialized, LGBTQ2S, and sex work communities, noting important points of intersection between these groups. RESULTS: Building on PRAs' lived experience, research capacity was supported through a comprehensive, multi-phase, and evidence-based experiential training curriculum, with mentorship and support opportunities provided at various stages of the study. Challenges included the following: being responsive to PRAs' diversity; ensuring PRAs' health, well-being, safety, and confidentiality; supporting PRAs to navigate shifting roles in their community; and ensuring sufficient time and resources for the translation of materials between English and French. Opportunities included the following: mutual capacity building of PRAs and researchers; community-informed approaches to study the processes and challenges; enhanced recruitment of harder-to-reach populations; and stronger community partnerships facilitating advocacy and action on findings. CONCLUSIONS: Community-collaborative studies are key to increasing the relevance and impact potential of research. For women living with HIV to participate in and benefit from HIV research, studies must foster inclusive, flexible, safe, and reciprocal approaches to PRA engagement, employment, and training tailored to regional contexts and women's lives. Recommendations for best practice are offered.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.131
metaresearch head score (Gemma)0.137
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1310.137
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0160.016
Scholarly communication0.0100.008
Open science0.0100.027
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0050.002

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 head0.903
GPT teacher head0.717
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
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

Citations79
Published2019
Admission routes3
Has abstractyes

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