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Record W1980120781 · doi:10.1080/09540121.2012.748866

Social–structural factors associated with supportive service use among a cohort of HIV-positive individuals on antiretroviral therapy

2013· article· en· W1980120781 on OpenAlexafffundabout
Nadia O’Brien, Alexis Palmer, Wendy Zhang, Warren Michelow, Anya Shen, Eric Abella Roth, Chelsey L. Rhodes, Kate Salters, Julio Montaner, Robert S. Hogg

Bibliographic record

VenueAIDS Care · 2013
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of British ColumbiaUniversity of WaterlooSimon Fraser UniversityUniversity of VictoriaSt. Paul's Hospital
FundersCanadian Institutes of Health ResearchInternational AIDS SocietyPublic Health Agency
KeywordsSupportive housingMedicineSocial supportCohortSocioeconomic statusOdds ratioGerontologyCohort studyConfidence intervalDemographyFamily medicineEnvironmental healthPsychologyInternal medicinePopulation

Abstract

fetched live from OpenAlex

As mortality rates decrease in British Columbia, Canada, supportive services (e.g. housing, food, counseling, addiction treatment) are increasingly conceptualized as critical components of care for people living with HIV/AIDS. Our study investigates social and clinical correlates of supportive service use across differing levels of engagement. Among 915 participants from the Longitudinal Investigations into Supportive and Ancillary health services (LISA) cohort, 742 (81%) reported using supportive services. Participants were nearly twice as likely to engage daily in supportive services if they self-identified as straight (95% confidence interval [CI], adjusted odds ratio [AOR]: 1.69), had not completed high school (95% CI, AOR: 1.97), had an annual income of < $15,000 (95% CI, AOR: 1.81), were unstably housed (95% CI, AOR: 1.89), were currently using illicit drugs (95% CI, AOR: 1.60), or reported poor social capital in terms of perceived neighborhood problems (95% CI, AOR: 1.15) or standard of living (95% CI, AOR: 1.70). Of interest, after adjusting for sociodemographic and socioeconomic variables, no clinical markers remained an independent predictor of use of supportive services. High service use by those demonstrating social and clinical vulnerabilities reaffirms the need for continued expansion of supportive services to facilitate a more equitable distribution of health among persons living with HIV.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.011
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.311
Teacher spread0.284 · 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

Citations3
Published2013
Admission routes3
Has abstractyes

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