The Role of Architecture and Design in the Management of Parkinson’s Disease: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is a neurological condition characterized by the development of daily disabling symptoms. Although the architecture and design of a PD patient's environment can hinder or facilitate full participation in daily activities, their putative role in the management of these patients has received little attention to date. OBJECTIVE: We conducted a systematic review to evaluate the evidence of architectural and design features in the management of people with PD. METHODS: An electronic database search of observational and experimental studies was conducted in MEDLINE and Embase from inception to May 2020, with two independent reviewers identifying the studies. Falls, fear of falling, postural instability, gait impairment/disability, and functional mobility were our outcomes of interest. RESULTS: Thirty-six studies were included, among which nineteen were observational and seventeen were experimental studies (overall participants = 2,965). Pavement characteristics, notably unstable surfaces and level differences, were found to be a major cause of falling. Ground-based obstacles and confined/narrowed spaces were found to disturb gait, increase postural instability, and decrease functional mobility. Housing type did not appear to increase risk of falling, nor to significantly explain concerns about falling. CONCLUSION: Findings suggest a need to adjust architectural features of the surrounding space to ensure appropriate care and provide a safe environment to PD patients. More evidence about the impact of such modifications on PD outcomes is needed.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".