Walk/Wheelability: An Inclusive Instrument Pair for Participatory Age-Friendly Research and Practice
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Recent critical evaluations of age-friendly efforts have highlighted the need to prioritize the disenfranchised, including people with mobility limitations. This article examines the validity of a 13-item Stakeholders Walkability/Wheelability Audit in Neighborhoods (SWAN13) scale to measure the "walk/wheelability" of street segments from the perspectives of people with mobility limitations. RESEARCH DESIGN AND METHODS: Data were drawn from preliminary studies of the SWANaudit which was conducted in 2 Canadian metropolitan areas. Sixty-one participants who use mobility devices (e.g., walkers, power wheelchairs) and older adults from community organizations audited 195 street segments. We factor analyzed the data from their audits. RESULTS: SWAN13 has a 1-factor structure. 13 items were retained from 85 SWANaudit items. SWAN13 encompassed both physical and social aspects of walk/wheelability. The alpha for the scale was .79. Convergent validity was found with the University of Alabama Life-Space Assessment (ρ = .22, p = .003), especially at the neighborhood level (ρ = .23, p = .002). Significant correlation was also found with subjective assessments of a priori walk/wheelability domains (ρ = .63, p < .001). DISCUSSION AND IMPLICATIONS: Walk/wheelability affects the life space of older adults and people with mobility limitations. It is an important latent variable that should be addressed to promote well-being and social participation. SWAN13 may be used in city-wide surveys to identify neighborhoods that may require age-friendly interventions from mobility perspectives. Detailed audits and interventions may be carried out in tandem using the paired SWANaudit instrument. Walk/wheelability is an inclusive and measurable concept that accounts for the needs of people with various mobility needs.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".