Evacuation Solutions for Individuals with Functional Limitations in the Indoor Built Environment: A Scoping Review
Bibliographic record
Abstract
The built environment continues to become increasingly accessible to people with disabilities, yet there remains a lack of focus on how these individuals are evacuated in emergencies. The objective of this scoping review was to survey the academic literature to identify solutions for safely evacuating individuals with functional limitations from the indoor built environment (i.e., buildings). Journal articles and conference proceedings published in the year 2002 onwards were included. Two pairs of reviewers independently evaluated 3562 articles from ten databases and identified 99 articles. The results were categorized into six main evacuation solution types: notification, wayfinding, egress, building design, strategy, and training programs. Our findings highlight the importance of tailoring solutions to the needs of individuals with different functional limitations. Future work should focus on expanding the number of solutions available for (1) emergencies beyond fires (e.g., natural disasters); (2) unique building types that may require specialized engineering considerations; and (3) a greater variety of impairments (e.g., seeing, hearing, cognitive). We also emphasize the need for more interdisciplinary work and the importance of including rescuers and rescuees in emergency preparedness discussions. These collaborations will ensure that building designs, organizational procedures, and evacuation aids complement each other to maximize safety. To our knowledge, this is the first scoping review to identify solutions for evacuating individuals with functional limitations from buildings. These findings may help inform future recommendations for new evacuation guidelines around the world.
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 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 | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".