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Record W2791381056 · doi:10.1177/2325958218759210

Trajectories of Episodic Disability in People Aging with HIV: A Longitudinal Qualitative Study

2018· article· en· W2791381056 on OpenAlexafffund
Patricia Solomon, Kelly K. O’Brien, Stephanie Nixon, Lori Letts, Larry Baxter, Nicole Gervais

Bibliographic record

VenueJournal of the International Association of Providers of AIDS Care (JIAPAC) · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsUniversity of TorontoMcMaster University
FundersCanadian Institutes of Health ResearchOntario Ministry of Research, Innovation and Science
KeywordsLongitudinal studyGerontologyHuman immunodeficiency virus (HIV)PsychologyQualitative researchDevelopmental psychologyMedicineSociologyFamily medicineSocial science

Abstract

fetched live from OpenAlex

People living with HIV may experience disability which is episodic in nature, characterized by periods of wellness and illness. The purpose of this longitudinal qualitative study was to understand how the episodic nature of HIV and the associated uncertainty shape the disability experience of older adults living with HIV over time. Fourteen men and 10 women who were HIV positive and over 50 years (mean age: 57 years; range: 50-73) participated in 4 interviews over 20 months. Longitudinal analyses of the transcribed interviews identified 4 phenotypes of episodic disability over time: decreasing, increasing, stable, or significant fluctuations. Although all participants experienced uncertainty, acceptance and optimism were hallmarks of those whose phenotypes were stable or improved over time. Understanding a person's episodic trajectory may help to tailor interventions to promote stability, mitigate an upward trajectory of increasing disability, and increase the time between episodes of illness.

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)0.010
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0020.004
Open science0.0010.005
Research integrity0.0010.002
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 head0.018
GPT teacher head0.350
Teacher spread0.331 · 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 designQualitative
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

Citations39
Published2018
Admission routes2
Has abstractyes

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