NEIGHBORHOOD LIFE FOR PERSONS WITH DEMENTIA: A SYSTEMATIC REVIEW AND META-SYNTHESIS OF WALKING INTERVIEWS
Bibliographic record
Abstract
Abstract The number of persons with dementia (PwDs) is rising significantly, with most still residing in the community and spending much time within their neighborhoods. This study aims to provide a critical and comprehensive review of existing qualitative studies documenting the impact of neighborhood environments on PwDs’ attitudes and perceptions toward their neighborhood life. A systematic search of Web of Science, Pubmed, CINAHL Ultimate, APA PsycInfo, Academic Search Ultimate, and EMBASE was conducted. Empirical studies on community-dwelling PwDs that use walking interviews in the neighborhoods were included in the review/synthesis. Meta-synthesis guided data collection, quality assessment, and analysis. The search resulted in 17317 articles of which 17 met the eligibility criteria. They had a combined sample of 186 people with memory problems, mild cognitive impairment, or dementia. Preliminary results suggest three themes— (1) Physical environment: Land use, urban design, transportation, wayfinding and legibility, and outdoor interaction and comfort are integral for PwDs connecting with the neighborhood; (2) Social Environment: Care, support, and connections foster PwDs‘social health, while neighborhood engagement and belonging enhance their identity and quality of life; (3) Technological Environment: Access to and use of technology can bridge gaps in PwDs’ everyday communication and activity, facilitating their presence and engagement. This is the first effort to synthesize qualitative evidence obtained directly from community-dwelling PwDs who face additional challenges in maintaining a positive neighborhood life. The significant roles of the many environmental elements/features across the physical, social, and technology domains can guide future research and practice toward creating dementia-friendly communities.
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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 | 0.027 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".