Evidence-Based Research on Barriers and Physical Limitations in Hospital Public Zones Regarding the Universal Design Approach
Bibliographic record
Abstract
The hospital is a public building which has the primary duty to provide services to everyone. So far, it is necessary to take into consideration the principle of Universal Design (UD) in responding to the behavior of users, particularly, persons with disabilities. This research focused on 2 main issues, (1) the physical features of the public areas for measurement and collection regarding to the style, size and location of facilities, and whether they meet the requirement and/or appropriate for people with disabilities, and (2) behavior of users with disabilities in accessing spaces and service facilities in the hospital public zones, focusing on the involvement between activities, behaviors and problems which occur. This research used empirical method to assess and evaluate the physical features by the process of Post Occupancy Evaluation, (POE), using 2 evaluation methods, 1) survey/observation (Cognitive walkthrough) and 2) scenario access audit methods. In detail, the survey/observation focused on the obstacles within a physical environment that affect space and service activities regarding people with different types of disabilities. Identifying the obstructions in public functions and health care facilities was implemented by a group of design specialists. On the other hand, the scenario access audit process was operated by determining the level of accessibility and the real patient flow of patients with disabilities on-sites and spaces in public zones. Therefore, this research speculated on all problems and came up with the design guidelines to improve the physical features of public zones in responding to the usability of the service facilities under the UD approach.
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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 | 0.039 | 0.148 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".