Towards Better Communication Accessibility for People Living with Aphasia: Identifying Barriers and Facilitators in Financial Institutions
Bibliographic record
Abstract
Approximately one-third of stroke survivors live with aphasia, an acquired communication disorder that significantly impacts their ability to understand, speak, read, or write. This condition often leads to social isolation and a reduced quality of life. Financial institutions, as essential community services, present numerous communication barriers for people living with aphasia. This study aims to identify the barriers and facilitators influencing the communicative accessibility of financial institutions for people living with aphasia and to discuss solutions to optimize accessibility. A qualitative descriptive research design was employed, involving semi-structured interviews with people living with aphasia and questionnaires filled by employees from financial institutions. Data were analyzed using thematic analysis to identify key themes related to barriers and facilitators. People living with aphasia identified thirteen types of barriers and forty facilitators, related to physical environmental factors, conversational attitudes and service systems and policies. Financial institution employees highlighted the need for better training and awareness regarding aphasia. The study underscores the significant barriers people living with aphasia face in financial institutions and the potential facilitators that could enhance communicative accessibility. Implementing targeted training programs and standardizing accessibility policies are crucial steps towards improving service access for people living with aphasia.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".