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Record W4281610621 · doi:10.1521/aeap.2022.34.3.226

People Living With HIV in St. Petersburg, Russia: Gender and Exposure Group Differences in HIV Care Engagement, Psychosocial Health, Substance Use, and Transmission Risk Behavior

2022· article· en· W4281610621 on OpenAlexaboutno aff
Yuri A. Amirkhanian, Jeffrey A. Kelly, Wayne DiFranceisco, Sergey Tarima, Timothy L. McAuliffe, А. В. Кузнецова

Bibliographic record

VenueAIDS Education and Prevention · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsSerostatusPsychosocialMedicineQuarter (Canadian coin)Mental healthSocial supportDepression (economics)PsychiatryGerontologyTransmission (telecommunications)Men who have sex with menSubstance abuseHuman immunodeficiency virus (HIV)Clinical psychologyViral loadFamily medicinePsychology

Abstract

fetched live from OpenAlex

This study examined psychosocial and health needs of persons living with HIV (PLWH) in Russia. The study combined baseline datasets from two social network samples of PLWH in St. Petersburg (N = 872). Samples were recruited between 2014 and 2018 by enrolling a PLWH seed who was either out-of-care or treatment nonadherent as well as network members surrounding each seed, assessing each participant's HIV care, transmission risk, substance use, and mental health characteristics. Almost one-quarter of participants said they were never offered antiretroviral therapy (ART), and—among those offered ART—one-quarter refused or discontinued therapy and 45% were <95% ART-adherent. Almost half of participants had detectable viral load, and many reported continued condomless intercourse with potentially nonconcordant serostatus partners or needle sharing. Over 46% of participants had elevated scores on measures of depression, hopelessness, state anxiety, or poor social support. Study findings illustrate unmet needs of PLWH in Russia.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.034
GPT teacher head0.333
Teacher spread0.299 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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