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Record W4390193099 · doi:10.1002/alz.074912

Exploring Culturally‐safe Dementia Care Policy in First Nation Community of the James and Hudson Bay Region in Northern Ontario, Canada

2023· article· en· W4390193099 on OpenAlexaffabout
Hom Lal Shrestha, Lucy Shrestha

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsLaurentian University
Fundersnot available
KeywordsDementiaParticipatory action researchRigourIndigenousFocus groupThematic analysisHealth carePhotovoiceCitizen journalismQualitative researchNursingMedicineGerontologyPsychologySociologyPublic relationsPolitical scienceEconomic growthSocial scienceDisease

Abstract

fetched live from OpenAlex

Abstract Background Culturally‐safe dementia care (CSDC) is new dynamic concept that empowers clinical and traditional health care practitioners to provide culturally respectful care for older adults with dementia. The World Health Organization’s (WHO) recognized diverse Indigenous local community partners, members and leaders as critical community stakeholders for dementia care and prevention worldwide in 2018. However, there is a critical lack of policy framework and evidence‐based research on CSDC globally. As dementia spreads as a global epidemic, the dementia prevalence among First Nations people over the age of 60 is expected to quadruple by 2031, compared to a 2.3‐fold increase among non‐First Nations people in Canada. The Mamow Ahyamowen Partners (2019) study found a higher dementia mortality rate of 7% in the James and Hudson Bay region of Northern Ontario between 1992 and 2014, compared to 23% in Ontario overall. Method A qualitative research design is employed in conjunction with a community‐based participatory rural dementia action research approach to conduct four participatory Focus‐Group Discussions with physicians, nurses, caregivers, and community partners with 24 to 32 participants to explore the knowledge, experience, barriers and challenges to develop knowledge of CSDC policy. Thematic analysis and the Total Quality Framework will be used for quality rigour, and a two‐eyed seeing framework and explanatory dementia models will be applied in the perspectives and worldviews of the physician‐patient‐community to honour cultural care, diet, language, ethical and spiritual pathways. Result This research will lay foundation for policymakers to develop knowledge of CSDC policy, care plan and guidelines. This will guide the development of educational interventions and curricula and community support systems that are aimed at building and sustaining the capacity of healthcare professionals and community partners to begin integrated biomedical and Indigenous traditional dementia care practices. Conclusion This research endeavours to equip physicians, nurses, allied health care workers, community partners (Elders, knowledge‐holders and traditional healers) and the community support systems to initiate CSDC on a global scale to implement the WHO Global Action Plan on the Public Health Response to Dementia (2017‐2025). Inclusion of Indigenous community partners as community stakeholder are underpinning to bridge the dementia equity gap.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.183
Threshold uncertainty score0.948

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0220.004
Scholarly communication0.0040.001
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.131
GPT teacher head0.320
Teacher spread0.190 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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