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Record W4398236686 · doi:10.14283/jpad.2024.98

Validation of a Community-Based Approach Toward Personalized Dementia Risk Reduction: The Kimel Family Centre for Brain Health and Wellness

2024· article· en· W4398236686 on OpenAlexafffundabout
Nicole D. Anderson, Donald J. D’Amico, Sara Rotenberg, Donna Rose Addis, Jenna B. Gillen, Dan H. Moore, Joyla A. Furlano, Brian Tan, M. M. Binns, Matthew Santarossa, Howard Chertkow

Bibliographic record

VenueThe Journal of Prevention of Alzheimer s Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsBaycrest Hospital
FundersCanadian Institutes of Health ResearchAlzheimer SocietyConsortium canadien en neurodégénérescence associée au vieillissement
KeywordsDementiaReduction (mathematics)GerontologyPsychologyMedicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND/OBJECTIVES: The Kimel Family Centre for Brain Health and Wellness is a research-driven community centre testing the efficacy of personalized dementia risk reduction programming on dementia risk and cognition. The objective of this protocol is to validate this approach by following people for two years. DESIGN/SETTING: Participants will receive a comprehensive dementia risk assessment, including nonmodifiable and modifiable risk factors, from which they will receive a Personalized Dementia Risk Report and Program Strategy, indicating their health conditions increasing and their risk level in five modifiable risk domains: physical activity, brain-healthy eating, cognitive engagement, social connections, and mental wellbeing. Equipped with this information, participants will enroll in programs within the Centre to address their risk factors. Changes to their dementia risk, cognition, and Personalized Program Strategy will be communicated through re-assessments of risk factors every six months (risk and cognition) and every year (comprehensive assessment). PARTICIPANTS: Participants (n = 450) will be 50 years of age or older, without a diagnosis of dementia, and sufficiently fluent in English to complete the assessments and understand program instructors. One goal is that our participant sample will include people of low income (with fundraising providing free community centre membership), and from various ethno-racial backgrounds. INTERVENTION: Participants will select programs to meet their Personalized Program Strategy. For physical activity, they will gradually work toward the Canadian Society for Exercise Physiology guidelines. For brain-healthy eating, they will learn about the Brain Health Food Guide and food label reading, and then take additional programs. For cognitive engagement and mental wellbeing, they will take at least one hour of relevant programming per week. Social connections will be reinforced throughout all programs. All participants will also have access to the Canadian Consortium on Neurodegeneration's CAN-THUMBS Up online, educational program on modifiable dementia risk factors, called Brain Health PRO. MEASUREMENTS: The comprehensive assessment includes numerous dementia risk factors, but the primary measures are risk in the five domains, health conditions proximal to those five risk domains, and cognition, and how these are affected by adherence and quality of goal-directed future simulation. We hypothesize a reduced risk in the five domains within six months, improvements in health biomarkers within a year, and maintenance of cognition within two years, with these benefits accruing with greater adherence, but only up to a point, at which benefits will plateau, and greater benefits among participants whose goal-directed simulations are more vivid, personally-relevant, achievable, and positive. CONCLUSIONS: This innovative approach overcomes a number of limitations present in prior multidomain dementia prevention trials. Adapting a preference clinical trial that is embedded in a community centre, where participants have autonomy to choose programs to address their modifiable dementia risk factors, has real-world applicability in the global effort to reduce dementia risk.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.365
Teacher spread0.299 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations5
Published2024
Admission routes3
Has abstractyes

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