Evaluation of satisfaction with geospatial assistive technology (ESGAT): a methodological and usability study
Bibliographic record
Abstract
PURPOSE: Manual wheelchair users are more vulnerable, in situations such as road crossings, hazardous sidewalks or curbs and crossing of buildings and facilities threshold. Geospatial assistive technology (GAT) can help with route planning. However, it is important to ensure the usability of such products, as well as the satisfaction of persons with reduced mobility. The study's aim was (1) to develop and validate a questionnaire on the satisfaction of GAT, in English and French, and to (2) assess satisfaction, efficacy and efficiency of a GAT with manual wheelchair users following a filmed trial in a dense urban area. METHOD: = 8), using Google Maps Pedestrian routeing tool. RESULTS: The Evaluation of satisfaction with geospatial assistive technology (ESGAT) consists in a user profile and their experience with the technology, followed by 12 satisfaction criteria rated from 1-not satisfied to 5-very satisfied. Both questionnaires were rated as feasible and practicable to complete. The usability of Google Maps Pedestrian routeing tool was measured as "moderate" by manual wheelchairs since the total satisfaction score at the ESGAT was 3.9/5 (quite satisfied). The items with the lowest score were navigation assistance, hands-free function and security. The GAT was effective (87.5% have completed their destination) but not efficient (37.5% needed help).IMPLICATIONS FOR REHABILITATIONFor manual wheelchair users paired with geospatial assistive technology:• A 10 minutes questionnaire was developed and validated to assess their satisfaction after testing aid in an urban area.• Satisfaction criteria to address are ease of access (service), learnability, hands-free function, ease of use for planning as well for navigating, transportability/ appearance, content, geographic information, effectiveness, efficiency, navigation assistance and security• A field test is necessary to ensure the effectiveness of the technology in avoiding or announcing potential obstacles such as sidewalk crossing ramp, damaged and congested sidewalk; sidewalk tilt (side slopes); thresholds at destination; verbal indication too soon or too late; incorrect indication; the arrow does not indicate the right direction; readjustment of the route needed; a lack of indication; and human intervention needed.
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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".