Exploring the experience of cognitive changes among community-dwelling stroke survivors: a qualitative study
Bibliographic record
Abstract
PURPOSE: Cognitive deficits are common among stroke survivors and impact their functional independence. Despite the prevalence of cognitive deficits after stroke, cognitive function is largely overlooked in post-stroke care. The aim of this qualitative study was to explore the experiences of individuals living with post-stroke cognitive changes to understand the impact of these changes on their daily lives. MATERIALS AND METHODS: Semi-structured interviews were conducted with a purposeful sample of thirteen community-dwelling adults 50 years and older with chronic stroke who self-identified cognitive changes post-stroke. Interviews were transcribed and an inductive thematic analysis was completed. RESULTS: Four key themes were identified: 1) inability to maintain everyday activities; 2) experiencing emotional responses to living with post-stroke cognitive changes; 3) a shrinking social world and; 4) seeking care for cognitive health post-stroke. CONCLUSIONS: Post-stroke cognitive changes were described by participants as a driving force behind negative shifts in their daily lives, emotional health, and social connections after stroke. Despite seeking care for their post-stroke cognitive changes, many participants were unable to find support in mainstream healthcare. There is a demonstrated need to further elucidate the gaps in care for post-stroke cognitive deficits and implement community interventions targeting cognitive health post-stroke.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".