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Record W4403379430 · doi:10.3390/ijerph21101352

Analyzing Social Support from Facebook on Viral Suppression among Young Black Men Who Have Sex with Men Living with HIV: A Pilot Study

2024· article· en· W4403379430 on OpenAlexfundno aff
Eleanor E. Friedman, Natascha Del Vecchio, Joseph A. Mason, Samantha A. Devlin, Jessica P. Ridgway, John A. Schneider

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2024
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute of Mental HealthSchool of Medicine, New York UniversityDirectorate for Biological SciencesYork University
KeywordsMen who have sex with menHuman immunodeficiency virus (HIV)Social supportPsychologyGerontologyDemographyMedicineSocial psychologyVirologySociology

Abstract

fetched live from OpenAlex

Social support has been associated with viral suppression among persons living with HIV (PWH). We examined cross-sectional data from young Black men who have sex with men to see if sociodemographic factors, medical history, and egocentric Facebook social support measures are related to viral suppression. Differences between participants were examined using Chi-square, Fisher’s exact, or Wilcoxon Rank Sum Tests, with significance set at p = 0.10. Degree centrality (p = 0.074) and Eigenvector centrality (p = 0.087) were significant, indicating that PWH with unsuppressed viral loads had more social connections. These results contrast prior studies in the literature. Further research on online social support for PWH is needed.

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)0.004
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.052
GPT teacher head0.389
Teacher spread0.338 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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