On the Planning and Design of Hospital Circulation Zones
Bibliographic record
Abstract
OBJECTIVE: This present literature review explores current issues and research inconsistencies regarding the design of hospital circulation zones and the associated health-related outcomes. BACKGROUND: Large general hospitals are immense, highly sophisticated institutions. Empirical studies have indicated excessively institutional environments in large medical centers are a cause of negative effects to occupants, including stress, anxiety, wayfinding difficulties and spatial disorientation, lack of cognitional control, and stress associated with inadequate access to nature. The rise of patient-centered and evidence-based movements in healthcare planning and design has resulted in a general rise in the quality of hospital physical environments. However, as a core component of any healthcare delivery system, hospital circulation zones have tended to remain neglected within the comparatively broad palette of research conducted and reported to date. METHOD: A systematic literature review was conducted based upon combinations of key words developed vis-à-vis a literature search in 11 major databases in the realm of the health sciences and the planning and design of built environments for healthcare. RESULTS: Eleven peer-reviewed articles were included in the analysis. Six research themes were identified according to associated health-related outcomes, including wayfinding difficulties and spatial disorientation, communication and socialization patterns, measures and control of excessive noise, patient fall incidents, and occupants' stress and satisfaction levels. CONCLUSIONS: Several knowledge gaps as well as commonalities in the pertinent research literature were identified. Perhaps the overriding finding is that occupants' meaningful exposure to views of nature from within hospital circulation zones can potentially enhance wayfinding and spatial navigation. Future research priories on this subject are discussed.
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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".