“My body’s a 50 year‐old but my brain is definitely an 85 year‐old”: exploring the experiences of men ageing with HIV‐associated neurocognitive challenges
Bibliographic record
Abstract
INTRODUCTION: Research investigating HIV, neurocognition and ageing is well developed using neuropsychometric or other quantitative approaches; however, little is known about individuals' subjective experiences. The purpose of this article is to explore the experiences of men aged 50 and older who self-identify as having HIV-associated neurocognitive challenges. In particular, this study uses the Episodic Disability Framework (EDF) to explore participants' perceptions regarding: 1) symptoms/impairments, difficulties with day-to-day activities, challenges with social inclusion and uncertainty; 2) ageing as related to their HIV-associated neurocognitive challenges, and 3) the episodic nature of their HIV-associated neurocognitive challenges. METHODS: This qualitative, interpretive study involved in-depth, semi-structured interviews with 12 men aged 50 years and older who self-identified as having HIV-associated neurocognitive challenges. Participants were recruited from a neurobehavioural research unit (NBRU) at a large hospital in Toronto, Canada. Data were analyzed thematically and with reference to the EDF. RESULTS: Participants' experiences reflected all concepts within the EDF to some extent. Difficulties with daily activities were diverse but were addressed using similar living strategies. Participants described challenges with work and social relationships resulting from neurocognitive challenges. Participants downplayed the significance of uncertainty in their lives, which they attributed to effective living strategies. Most men reported confusion regarding the link between their neurocognitive challenges and ageing. Others discussed ageing as an asset that helped with coping. CONCLUSIONS: This is the first study to use a disability framework to examine the subjective experiences of men ageing with HIV-associated neurocognitive challenges. Findings reframe the episodic disability experienced by these individuals as being predictably linked to certain triggers. As such, support for managing neurocognitive challenges could focus on triggers that exacerbate the condition in addition to the impairments themselves. The study also describes ageing as not only a source of problems but also as an asset among men growing older with HIV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".