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Record W2507624440 · doi:10.1017/s0144686x16000878

‘I'm happy in my life now, I'm a positive person’: approaches to successful ageing in older adults living with HIV in Ontario, Canada

2016· article· en· W2507624440 on OpenAlexaffabout
Charles A. Emlet, Lesley M. Harris, Charles Furlotte, David J. Brennan, C Pierpaoli

Bibliographic record

VenueAgeing and Society · 2016
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsGerontologyHuman immunodeficiency virus (HIV)PsychologyContext (archaeology)Stigma (botany)Qualitative researchPopulation ageingPopulationAgeingMedicineSociologyPsychiatryEnvironmental healthGeography

Abstract

fetched live from OpenAlex

Abstract Worldwide approximately 3.6 million people aged 50 and older are living and ageing with the human immunodeficiency virus (HIV). Few studies have explored successful ageing from the insider perspective of those living well and ageing with HIV. This study draws upon the lived experience and wisdom of older, HIV-positive adults living in Ontario, Canada in order to understand their views and strategies for successful ageing. This qualitative study involved semi-structured interviews with 30 individuals age 50 years and older who are HIV-positive. Purposive sampling techniques were used to recruit individuals who shared their experiences of successful ageing. Constructivist grounded theory coding techniques were used for analysis. Themes related to successful ageing included resilience strategies and challenges, social support and environmental context. Stigma and struggles to maintain health were identified as impediments to successful ageing. Models of successful ageing must take into account the potential for a subjective appraisal of success in populations suffering from chronic and life-threatening illnesses including HIV. Practitioners can draw upon organically existent strengths in this population in order to provide intervention development for older adults around the world who are struggling to manage their 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 score0.084
Threshold uncertainty score0.420

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 head0.019
GPT teacher head0.227
Teacher spread0.208 · 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

Citations51
Published2016
Admission routes2
Has abstractyes

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