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Record W4323344966 · doi:10.46743/2160-3715/2023.5238

Understanding Lived Experiences of Stigma for People Living with HIV: A Community Based Participatory Research Study

2022· article· en· W4323344966 on OpenAlexaffabout
Brent Oliver, Catherine Pearl, Egbert S. Felix, Deborah Norris, Folasade J. Elizabeth Olaniyan, Kim Samson, Añiela dela Cruz, Gabriel Assselin, Kate Berezowski, Celeste Hayward, Becky Van Tassel Van Tassel, Floyd Visser

Bibliographic record

VenueThe Qualitative Report · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsThe Sharp FoundationUniversity of AlbertaUniversity of CalgaryMount Royal University
Fundersnot available
KeywordsStigma (botany)Participatory action researchQualitative researchCommunity-based participatory researchHuman immunodeficiency virus (HIV)PsychologyCitizen journalismGerontologySociologyMedicinePsychiatryFamily medicinePolitical scienceSocial science

Abstract

fetched live from OpenAlex

The goal of this project was to better understand the experiences and impacts of HIV stigma and discrimination on people living with HIV and to co-create knowledge that has the potential to challenge existing stigma within the healthcare, social services, and public policy sectors in the province of Alberta, Canada. We employed community-based participatory research and a mixed methods design (survey methods and qualitative interviews) to address these questions. An online survey was completed by 148 people living with HIV and semi-structured interviews were conducted with an additional 20 participants. The research findings have been conceptualized within a social ecological model. The four main categories that emerged from the data included personal level factors attributed to HIV stigma, interpersonal factors related to HIV stigma, community factors related to HIV stigma, and HIV stigma in systems and institutions. Within each ecological domain we highlight the strengths and coping strategies people living with HIV identified in the study. Results will be of interest to health researchers and HIV service providers.

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)0.022
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.722
GPT teacher head0.600
Teacher spread0.122 · 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 designQualitative
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

Citations2
Published2022
Admission routes2
Has abstractyes

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