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Record W2971771125 · doi:10.1136/bmjopen-2019-031262

Living strategies for disability in men ageing with HIV in Ontario, Canada: a longitudinal qualitative study

2019· article· en· W2971771125 on OpenAlexafffundabout
Patricia Solomon, Kelly K. O’Brien, Rebecca McGuff, Michelle Sankey

Bibliographic record

VenueBMJ Open · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsUniversity of TorontoMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMedicineFeelingGerontologyQualitative researchActivities of daily livingLongitudinal studyIndependent livingHuman immunodeficiency virus (HIV)PsychiatryFamily medicinePsychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: To examine the living strategies used by older men living with HIV to deal with the episodic nature of disability and associated uncertainty, over time. DESIGN: Qualitative longitudinal study in which men living with HIV were interviewed on four occasions over 20 months. SETTING: Men were recruited from HIV community organisations in Canada. PARTICIPANTS: 14 men with a median age of 57.5 years and median time since diagnosis of 21.5 years. RESULTS: Five themes depict the living strategies used to deal with the episodic nature of disability and uncertainty over time. Actively engaging in problem-solving by prioritising and modifying activities and avoiding stress, advocating for support, being positive and future oriented, engaging in healthy pursuits and providing social support to others helped men to mitigate their disability. By following participants over time, we were able to gather insights into triggers of episodes of disability, and perceptions of the success of implementing their living strategies and avoiding uncertainty. CONCLUSIONS: Participants used living strategies to deal with uncertainty and mitigate episodes of disability over time. This study supports the importance of programmes that promote self-management for older men living with HIV through helping them identify triggers of disability, set realistic goals and problem-solve. These may help build self-efficacy, increase sense of control, and decrease feelings of uncertainty and episodes of disability.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.077
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.004
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.099
GPT teacher head0.440
Teacher spread0.341 · 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

Citations4
Published2019
Admission routes3
Has abstractyes

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