Toward a better understanding of barriers to wayfinding technology use for people with disabilities
Bibliographic record
Abstract
Wayfinding is the process of navigating from one's present location to their desired location. While wayfinding technologies are increasingly used by people with disabilities, there is little understanding of the barriers specific to wayfinding technology. The objective of this study was to understand the wayfinding technology barriers experienced by Canadians with disabilities. A total of 213 participants with varying disabilities (i.e. mobility, visual, hearing, memory and learning disabilities) completed a survey of open-ended questions about their personal experiences with different types of technologies. Technologies were categorized into public (i.e. digital and tactile interfaces) and personalized (i.e. mobile/website applications, wearable devices, smart assistive devices), and qualitative content analysis was used. Main themes were identified and either common across both groups (i.e. compatibility, demands on personal resources, information provision, interactability) or specific to one technology type (i.e. stigma, specific to personalized technology). Detailed subthemes provided greater specificity on the types of barriers encountered. For example, infection risk was noted as a barrier to public technology and high costs was a barrier for personalized technology. Results support the inclusion of wayfinding technology within accessibility standards and provide insights to clinicians on how to best support people with disabilities and their use of technology.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".