Assessment tools for measurement of dementia-friendliness of a community: A scoping review
Bibliographic record
Abstract
BACKGROUND: A quantitative assessment of the dementia-friendliness of a community can support planning and evaluation of dementia-friendly community (DFC) initiatives, internal review, and national/international comparisons, encouraging a more systematic and strategic approach to the advancement of DFCs. However, assessment of the dementia-friendliness of a community is not always conducted and continuous improvement and evaluation of the impact of dementia-friendly initiatives are not always undertaken. A dearth of applicable evaluation tools is one reason why there is a lack of quantitative assessments of the dementia-friendliness of communities working on DFC initiatives. PURPOSE: A scoping review was conducted to identify and examine assessment tools that can be used to conduct quantitative assessments of the dementia-friendliness of a community. DESIGN AND METHODS: Peer-reviewed studies related to DFCs were identified through a search of seven electronic databases (MEDLINE, CINAHL, PsycINFO, Embase, EMCare, HealthSTAR, and AgeLine). Grey literature on DFCs was identified through a search of the World Wide Web and personal communication with community leads in Australia, Canada, New Zealand, the United Kingdom, and the United States. Characteristics of identified assessment tools were tabulated, and a narrative summary of findings was developed along with a discussion of strengths and weaknesses of identified tools. RESULTS: Forty tools that assess DFC features (built environment, dementia awareness and attitudes, and community needs) were identified. None of the identified tools were deemed comprehensive enough for the assessment of community needs of people with dementia.
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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".