A qualitative description of barriers to visual rehabilitation experienced by stroke survivors with visual impairment in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Post-stroke visual impairment (VI) is a common but under-recognized care challenge. Common manifestations of post-stroke VI include: diplopia, homonymous hemianopia, oscillopsia secondary to nystagmus, and visual inattention or neglect. In acute care settings, post-stroke VI recognition and treatment are often sub-optimal as emphasis is placed on survival. Stroke survivors with VI often face inconsistencies when accessing care out of hospital because variable availability and subsidization of visual rehabilitation. We sought to identify gaps in care experienced by stroke survivors with VI from stroke survivors' and care providers' perspectives. METHODS: We conducted a qualitative description study across 12 care sites in Alberta, Canada, using semi-structured interviews. Survivor interviews focused on the health system experience. Provider interviews discussed approaches to care, perceived gaps, and current resources. Interviews were audio-recorded and transcribed. Iterative content analysis was completed using NVivo 12. We promoted rigour through an audit trail, open-ended questions, thick description, and collaborative coding. RESULTS: We completed 50 interviews: 19 survivor interviews and 31 provider interviews. The majority of survivors were male (n = 14) and recruited from community settings (n = 16). Providers varied in profession and location within the care continuum. Two key themes emerged from the provider and survivor interviews pertaining to (a) facets of visual rehabilitation (sub-themes: access, resources, and multidisciplinary professional interaction); and (b) functioning with post-stroke VI (sub-themes: early experiences post-stroke and living with VI in the real world). CONCLUSIONS: The visual rehabilitation model needs to be optimized to ensure transparent inter-disciplinary communication and efficient referral pathways. Future research will focus on evaluating the effectiveness of post-stroke care from multiple perspectives in Alberta.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".