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Record W7116917142 · doi:10.1002/alz70860_106762

Sustaining Community Support for Families Affected by Dementia: The Memory Café Initiative in Rural British Columbia

2025· article· en· W7116917142 on OpenAlexaffabout
Donna Benson, Barb Stewart, Eric Ping Hung Li

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsPenticton Regional HospitalUniversity of British Columbia, Okanagan CampusNew Brunswick Health Research Foundation
Fundersnot available
KeywordsCommunity engagementDementiaCommunity developmentCommunity participationSustainabilitySustainable communityTraining (meteorology)

Abstract

fetched live from OpenAlex

BACKGROUND: Community organizations play a crucial role in dementia-focused programs, yet funding uncertainty remains a challenge. This study examines the Memory Café, a community-led initiative in rural British Columbia that fosters social engagement, education, and support for individuals with dementia and their caregivers. Over two years, Medical Arts Research and DB Foundation for Health Research, in partnership with a local university, hosted 10 Memory Café events in rural communities, including Cawston, Keremeos, and Princeton. These events, supported by local government funding, engaged diverse partners-Indigenous leaders, musicians, artists, businesses, and healthcare professionals. Activities included musical performances, calligraphy workshops, Tai Chi, and interactive "memory box" sessions. Keynote speakers, including caregivers with lived experience, provided education and social support. The initiative catalyzed long-term community projects, including: Forget-Me-Not Café (Penticton): Inspired a weekly dementia-friendly café. Stretching Group (Keremeos): Led by a retired therapist, promoting movement for cognitive health. Community Benches (Cawston): Installed by a local carpenter to create dementia-friendly spaces. METHOD: The research team employed a community-based participatory action research (CBPAR) approach, collaborating with local stakeholders to design and implement the Memory Café events. They conducted survey with key community partners, volunteers, and participants to assess the program's impact. as well as to evaluate their experiences and gather feedback for improving future initiatives. Observational data were also collected during the events to document engagement levels and interactions among participants. RESULTS: Four key sustainability factors were identified: · Engaging Community Stakeholders: Collaborative meetings fostered shared ownership, identifying volunteers and funding sources. · Leveraging Local Resources: Partnerships with businesses and organizations provided funding, venues, and services. · Incorporating Community Feedback: Surveys informed program improvements, increasing engagement. · Removing Barriers to Participation: Transportation support, free events, and sensory-friendly spaces enhanced accessibility. CONCLUSION: The Memory Café model demonstrates a scalable, community-driven approach to dementia-friendly initiatives. By fostering partnerships, leveraging resources, and engaging stakeholders, community organizations can build sustainable support systems for individuals with dementia and their caregivers. Future efforts will explore digital engagement and volunteer training to expand impact.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.002
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.021
GPT teacher head0.310
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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