MétaCan
Menu
Back to cohort
Record W2964052380 · doi:10.1002/jia2.25341

A longitudinal study of associations between HIV‐related stigma, recent violence and depression among women living with HIV in a Canadian cohort study

2019· article· en· W2964052380 on OpenAlexafffundabout
Carmen H. Logie, Natania Marcus, Ying Wang, Angela Kaida, Patricia O’Campo, Uzma Ahmed, Nadia O’Brien, Valerie Nicholson, Tracey Conway, Alexandra de Pokomandy, Mylène Fernet, Mona Loutfy

Bibliographic record

VenueJournal of the International AIDS Society · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsMcGill University Health CentreMcGill UniversitySt. Michael's HospitalSimon Fraser UniversityPublic Health OntarioUniversité du Québec à MontréalWomen's College HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchBritish Columbia Centre for Disease ControlUniversity of TorontoDalhousie UniversitySimon Fraser UniversityUniversity of OttawaMcGill UniversityPublic Health Agency of CanadaMcGill University Health CentreKingston UniversityProvidence Health CareOttawa Hospital Research InstituteUniversiteit van AmsterdamStyrelsen för Internationellt UtvecklingssamarbeteMcMaster UniversityPublic Health Agency
KeywordsMedicineHuman immunodeficiency virus (HIV)Stigma (botany)Depression (economics)CohortPsychiatryCohort studyLongitudinal studyGerontologyDemographyFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Women living with HIV (WLHIV) experience stigma and elevated exposure to violence in comparison with HIV-negative women. We examined the mediating role of experiencing recent violence in the relationship between stigma and depression among WLHIV in Canada. METHODS: We conducted a cohort study with WLHIV in three Canadian provinces. Recent violence was assessed through self-reported experiences of control, physical, sexual or verbal abuse in the past three months. At Time 1 (2013-2015) three forms of stigma were assessed (HIV-related, racial, gender) and at Time 2 (2015-2017) only HIV-related stigma was assessed. We conducted structural equation modelling (SEM) using the maximum likelihood estimation method with Time 1 data to identify direct and indirect effects of gender discrimination, racial discrimination and HIV-related stigma on depression via recent violence. We then conducted mixed effects regression and SEM using Time 1 and Time 2 data to examine associations between HIV-related stigma, recent violence and depression. RESULTS: At Time 1 (n = 1296), the direct path from HIV-related stigma (direct effect: β = 0.200, p < 0.001; indirect effect: β = 0.014, p < 0.05) to depression was significant; recent violence accounted for 6.5% of the total effect. Gender discrimination had a significant direct and indirect effect on depression (direct effect: β = 0.167, p < 0.001; indirect effect: β = 0.050, p < 0.001); recent violence explained 23.15% of the total effect. Including Time 1 and Time 2 data (n = 1161), mixed-effects regression results indicate a positive relationship over time between HIV-related stigma and depression (Acoef: 0.04, 95% CI: 0.03, 0.06, p < 0.001), and recent violence and depression (Acoef: 1.95, 95% CI: 0.29, 4.42, p < 0.05), controlling for socio-demographics. There was a significant interaction between HIV-related stigma and recent violence with depression (Acoef: 0.04, 95% CI: 0.01, 0.07, p < 0.05). SEM analyses reveal that HIV-related stigma had a significant direct and indirect effect on depression over time (direct effect: β = 0.178, p < 0.001; indirect effect: β = 0.040, p < 0.001); recent violence experiences accounted for 51% of the total effect. CONCLUSIONS: Our findings suggest that HIV-related stigma is associated with increased experiences of recent violence, and both stigma and violence are associated with increased depression among WLHIV in Canada. There is an urgent need for trauma-informed stigma interventions to address stigma, discrimination and violence.

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 score0.007
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.305
Teacher spread0.290 · 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

Citations55
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueJournal of the International AIDS SocietySame topicHIV/AIDS Research and InterventionsFrench-language works237,207