Web Site Accessibility Among Doctor of Physical Therapy Programs in the United States
Bibliographic record
Abstract
INTRODUCTION: Given the impetus to improve accessibility for diverse learners seeking physical therapist education, it is critical that all entry points to access information have minimal barriers. This study identified Web site accessibility barriers among Doctor of Physical Therapy (DPT) programs in the United States. REVIEW OF LITERATURE: Web site accessibility has been evaluated among many institutions of higher education, but none focused on DPT education. Individuals with disabilities may be adversely affected by Web site accessibility barriers. SUBJECTS: This cross-sectional study included 262 DPT programs in the United States. Doctor of Physical Therapy program characteristics collected were geographic region, institutional control type (public/private), medical school affiliation, accreditation status, total institutional enrollment, and DPT class size. METHODS: The Web Accessibility Evaluation (WAVE) Tool assessed data related to accessibility barriers among DPT program homepage Uniform Resource Locators. Three primary outcomes from the WAVE Tool included WAVE Total Errors, Error Density, and Total Alerts. RESULTS: Web site homepage accessibility barriers varied among programs for WAVE Total Errors (range 0-150), Error Density (range 0-14.6%), and Total Alerts (range 1-331). Median Total Errors were greater among private (9.0) versus public (5.0) institution Web sites ( P < .001). Median Total Errors were greater among those institutions not affiliated with a medical school (9.0) compared with those that had an affiliated medical school (7.0) ( P = .04). No differences in accessibility barriers were identified according to geographic region or accreditation status ( P > .05). Median Total Errors were significantly different between institutional enrollment quartiles (H[3] = 17.9, P < .001), with no differences noted between DPT class size quartiles for any outcome ( P > .05). Generally, weak-fair inverse correlations were observed between student enrollment for the institution and Web site accessibility barrier outcomes. DISCUSSION AND CONCLUSION: Homepage accessibility barriers varied greatly among DPT programs in the United States. Factors, including being a private institution, no medical school affiliation, and lower institutional enrollment, were related to increased accessibility barriers.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".