The saliency of geographical landmarks for community navigation: A photovoice study with persons living with dementia
Bibliographic record
Abstract
This study uses the photovoice method to explore how persons living with mild-to-moderate dementia perceive neighborhood landmarks and identify characteristics that render these landmarks salient for outdoor navigation. Previous research has highlighted the role of well-designed, stable geographical landmarks in improving the navigability of neighborhoods for persons living with dementia. However, the specific attributes that render landmarks salient have not yet been sufficiently explored, resulting in inadequate evidence-based environmental design guidelines for dementia-friendly communities. To address this gap, a photovoice study was conducted with five community-dwelling persons living with dementia and their care partners, as part of a dementia-friendly neighborhood walking program in the city of Seattle, USA. Photovoice facilitated the exploration of saliency of neighborhood landmarks from an emic perspective by (i) empowering persons living with dementia to identify and take photos of salient landmarks during the group walk and (ii) interpret and reflect on attributes that contributed to saliency using the photos as visual aids in a focus group discussion and survey questionnaire. Participants associated the saliency of landmarks with two groups of attributes: (i) visual distinctiveness, which encompassed physical aspects, such as size, shape, color, texture; and (ii) meaningfulness, which included subjective factors of personal and emotional significance that linked the landmarks to participants' pasts, passions, hobbies, and emotions related to having dementia. Findings suggest that outdoor landmarks should be designed for maximum legibility and noticeability, as well as familiarity, recognizability, and memorability. The evidence from this research also points to the likely positive effect of salient neighborhood landmarks on the community navigation of persons living with dementia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".