Creating dementia-friendly communities: Challenging stigma and building understanding through public education
Bibliographic record
Abstract
Stigma is a well-documented barrier to community and social engagement for people living with dementia. Awareness raising and public education have been identified as essential for developing communities that are supportive of people living with dementia and enable their social inclusion. A public dementia education program, co-designed and delivered by people living with dementia and targeted to people working in public-facing service roles, was developed to increase awareness of dementia and challenge stigma. This quality improvement study evaluates this dementia-friendly community education program in terms of participants’ reactions to the program, knowledge acquisition, change in behavior, and impacts associated with the program. A survey methodology was used to assess immediate reactions to the workshop (N = 110), and at a three-month follow-up to assess longer-term impacts of the program (N = 36). The workshop was well received with >88% of respondents being satisfied with the topics covered, delivery format, and program materials; >65% of respondents reported being more knowledgeable in all workshop topic areas as a result of the program. At follow-up, >80% of respondents reported that they implemented dementia-friendly actions as outlined in the workshop but were able do so more frequently for individual-level actions, rather than organizational-level actions. Respondents valued hearing the experiences of a person with lived experience. The study findings highlight the value of practical education targeted to public service sector personnel and codesigned and delivered by people living with dementia as a strategy for fostering change towards more dementia-friendly communities. Targeting leadership and management may affect greater change at organizational levels.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| 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".