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Record W1975804164 · doi:10.1186/1471-2458-13-736

Associations between the legal context of HIV, perceived social capital, and HIV antiretroviral adherence in North America

2013· article· en· W1975804164 on OpenAlexaffabout
J. Craig Phillips, Allison R. Webel, Carol Dawson Rose, Inge B. Corless, Kathleen M. Sullivan, Joachim G. Voss, Dean Wantland, Kathleen M. Nokes, John Brion, Wei‐Ti Chen, Scholastika Iipinge, Lucille Sanzero Eller, Lynda Tyer‐Viola, Marta Rivero‐Méndez, Patrice K. Nicholas, Mallory O. Johnson, Mary Maryland, Jeanne Kemppainen, Carmen J. Portillo, Puangtip Chaiphibalsarisdi, Kenn M. Kirksey, Elizabeth Sefcik, Paula Reid, Yvette P. Cuca, Emily Huang, William L. Holzemer

Bibliographic record

VenueBMC Public Health · 2013
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Ottawa
FundersNational Center for Advancing Translational SciencesNational Institute of Allergy and Infectious DiseasesNational Institute of Nursing ResearchNational Center for Research ResourcesNational Institute of Mental HealthNational Institutes of HealthCenter for AIDS Research, University of WashingtonUniversity of WashingtonCity University of New York
KeywordsCriminalizationMedicineContext (archaeology)Social capitalPublic healthEnvironmental healthGerontologyCriminologyPsychologyPolitical scienceLawGeographyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Human rights approaches to manage HIV and efforts to decriminalize HIV exposure/transmission globally offer hope to persons living with HIV (PLWH). However, among vulnerable populations of PLWH, substantial human rights and structural challenges (disadvantage and injustice that results from everyday practices of a well-intentioned liberal society) must be addressed. These challenges span all ecosocial context levels and in North America (Canada and the United States) can include prosecution for HIV nondisclosure and HIV exposure/transmission. Our aims were to: 1) Determine if there were associations between the social structural factor of criminalization of HIV exposure/transmission, the individual factor of perceived social capital (resources to support one's life chances and overcome life's challenges), and HIV antiretroviral therapy (ART) adherence among PLWH and 2) describe the nature of associations between the social structural factor of criminalization of HIV exposure/transmission, the individual factor of perceived social capital, and HIV ART adherence among PLWH. METHODS: We used ecosocial theory and social epidemiology to guide our study. HIV related criminal law data were obtained from published literature. Perceived social capital and HIV ART adherence data were collected from adult PLWH. Correlation and logistic regression were used to identify and characterize observed associations. RESULTS: Among a sample of adult PLWH (n = 1873), significant positive associations were observed between perceived social capital, HIV disclosure required by law, and self-reported HIV ART adherence. We observed that PLWH who have higher levels of perceived social capital and who live in areas where HIV disclosure is required by law reported better average adherence. In contrast, PLWH who live in areas where HIV transmission/exposure is a crime reported lower 30-day medication adherence. Among our North American participants, being of older age, of White or Hispanic ancestry, and having higher perceived social capital, were significant predictors of better HIV ART adherence. CONCLUSIONS: Treatment approaches offer clear advantages in controlling HIV and reducing HIV transmission at the population level. These advantages, however, will have limited benefit for adherence to treatments without also addressing the social and structural challenges that allow HIV to continue to spread among society's most vulnerable populations.

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)0.002
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 score0.146
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.353
Teacher spread0.291 · 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

Citations36
Published2013
Admission routes2
Has abstractyes

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