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Record W4285035741 · doi:10.1002/jia2.25913

Does resource insecurity drive HIV‐related stigma? Associations between food and housing insecurity with HIV‐related stigma in cohort of women living with HIV in Canada

2022· article· en· W4285035741 on OpenAlexaffabout
Carmen H. Logie, Nina Sokolovic, Mina Kazemi, Shaz Islam, Peggy Frank, Rebecca Gormley, Angela Kaida, Alexandra de Pokomandy, Mona Loutfy

Bibliographic record

VenueJournal of the International AIDS Society · 2022
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsMcGill UniversityMcGill University Health CentreSimon Fraser UniversityAIDS VancouverBlack Coalition for AIDS PreventionWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsStigma (botany)MedicineFood insecurityHuman immunodeficiency virus (HIV)CohortEnvironmental healthPsychiatryGerontologyFood securityVirology

Abstract

fetched live from OpenAlex

INTRODUCTION: Women living with HIV across global contexts are disproportionately impacted by food insecurity and housing insecurity. Food and housing insecurity are resource insecurities associated with poorer health outcomes among people living with HIV. Poverty, a deeply stigmatized phenomenon, is a contributing factor towards food and housing insecurity. HIV-related stigma-the devaluation, mistreatment and constrained access to power and opportunities experienced by people living with HIV-intersects with structural inequities. Few studies, however, have examined food and housing insecurity as drivers of HIV-related stigma. This study aimed to estimate the associations between food and housing insecurity with HIV-related stigma among women living with HIV in Canada. METHODS: This prospective cohort study of women living with HIV (≥16 years old) in three provinces in Canada involved three waves of surveys collected at 18-month intervals between 2013 and 2018. To understand associations between food and housing security and HIV-related stigma, we conducted linear mixed effects regression models. We adjusted for socio-demographic characteristics associated with HIV-related stigma. RESULTS AND DISCUSSION: Among participants (n = 1422), more than one-third (n = 509; 36%) reported baseline food insecurity and approximately one-tenth (n = 152, 11%) housing insecurity. Mean HIV-related stigma scores were consistent across waves 1 (mean [M] = 57.2, standard deviation [SD] = 20.0, N = 1401) and 2 (M = 57.4, SD = 19.0, N = 1227) but lower at wave 3 (M = 52.8, SD = 18.7, N = 918). On average, across time, food insecure participants reported HIV-related stigma scores that were 8.6 points higher (95% confidence interval [CI]: 6.4, 10.8) compared with food secure individuals. Similarly, participants reporting insecure housing at wave 1 tended to experience greater HIV-related stigma (6.2 points, 95% CI: 2.7, 9.6) over time compared to stably housed participants. There was an interaction between time and housing insecurity, whereby baseline housing insecurity was no longer associated with higher HIV-related stigma at the third wave. CONCLUSIONS: Among women living with HIV in Canada, experiencing food and housing insecurity was associated with consistently higher levels of HIV-related stigma. In addition to the urgent need to tackle food and housing insecurity among people living with HIV to optimize wellbeing, getting to the heart of HIV-related stigma requires identifying and dismantling resource insecurity-related stigma drivers.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.303
Teacher spread0.276 · 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.

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

Citations35
Published2022
Admission routes2
Has abstractyes

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