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Record W2588052450 · doi:10.1521/aeap.2017.29.1.62

“HIV Is Not Going to Kill Me, Old Age Is!”: The Intersection of Aging and HIV for Older HIV-Infected Adults in Rural Communities

2017· article· en· W2588052450 on OpenAlex
Katherine Quinn, Chris Sanders, Andrew E. Petroll

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIDS Education and Prevention · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsLakehead University
FundersNational Institute of Mental HealthNational Institute on Aging
KeywordsMedicineGerontologyHuman immunodeficiency virus (HIV)Qualitative researchPsychological interventionRural areaThematic analysisPopulationEnvironmental healthFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

Older adults with HIV/AIDS living in rural areas face unique challenges to accessing HIV care and medications, and suffer greater mortality than non-rural HIV-infected individuals. This qualitative study examined the intersection of aging and HIV to identify factors that affect overall health, engagement in care, and medication adherence among this understudied population. Qualitative interviews were conducted by phone with 29 HIV-positive adults over the age of 50 living in U.S. rural counties and analyzed using thematic content analysis. Individuals reported complex medical needs in addition to their HIV and noted difficulty discerning whether symptoms were associated with HIV or aging. Although reported medication adherence rates were high, participants also cited several barriers to maintaining adherence. Given the increase in rural individuals living with HIV, interventions are needed to address the complex intersection of aging and HIV, especially for those in rural environments.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.282

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)0.0000.000

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 head0.368
Teacher spread0.342 · 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