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Record W7117318732 · doi:10.1002/alz70858_100229

Can Thumbs UP: The Prevention arm of the Canadian Consortium on Neurodegeneration in Aging (CCNA)

2025· article· en· W7117318732 on OpenAlexaffabout
Sylvie Belleville, Nicole Anderson, Paul Brewster, Andrew Lim, Manuel Montero‐Odasso, Haakon B. Nygaard, Howard Feldman, Howard Chertkow, CCNA‐CAN‐THUMBS UP Study Group

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of British ColumbiaSunnybrook HospitalUniversity of VictoriaBaycrest HospitalWestern UniversityInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsDementiaMEDLINENeurodegenerationCommunity-based participatory researchPublic health

Abstract

fetched live from OpenAlex

BACKGROUND: In 2019 Canadian dementia researchers launched the "The Canadian Therapeutic Platform Trial for Multidomain Interventions to Prevent Dementia" (CAN-THUMBS UP; CTU), a national program to advance dementia prevention in Canada and globally. The initiative responded to findings demonstrating that lifestyle interventions could improve cognitive decline and to the Lancet Commission's report that over 40% of dementia cases might be prevented through risk factor mitigation. METHOD: A major focus of CTU was developing and validating the Brain Health PRO Program, a 45-week, bilingual, web-based educational intervention addressing modifiable risk factors. The program consists of 181 ten-minute chapters delivered incrementally on a weekly basis. It was designed to foster engagement and convey the best available evidence for lifestyle changes. A total of 345 participants self-registered, completed initial questionnaires and gained access to the intervention. Dementia literacy, the primary outcome, was measured with the Alzheimer's Disease Knowledge Scale. Secondary outcomes included self-efficacy (General Self-Efficacy Scale), attitude toward dementia, user experience (System Usability Scale and Technology Acceptance Model Questionnaire), lifestyle, standard cognitive testing, smartphone-based cognitive assessment, 24-hour continuous mobility and sleep measures using actigraphy and sleep EEG wearables (Feldman, Belleville et al. 2023). RESULT: The validation study successfully achieved its primary outcome of improving dementia literacy. Positive effects were also observed for secondary outcomes, including self-efficacy and user satisfaction, with preliminary evidence suggesting a reduction in modifiable risk factors. Three additional studies leveraged the CTU infrastructure: SYNERGIC@Home, assessing the feasibility of a home-based intervention to improve gait and cognition; SYNERGIC-2, a randomized controlled trial testing a 12-month home-based personalized multidomain intervention in individuals at risk for dementia, using Brain Health PRO as a control condition; and an implementation sub-study conducted in collaboration with the Federation of Quebec Alzheimer Societies. CONCLUSION: CTU reflects a vibrant, collaborative effort of over 100 investigators, staff, citizen advisors, and partners. Leveraging CCNA's team structure, CTU incorporated contributions in study design, recruitment, technology, program evaluation and participatory research. Larger studies are underway within CCNA to confirm the efficacy of Brain Health PRO in mitigating dementia risk and to examine its implementation in diverse settings.

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)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.029
GPT teacher head0.315
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreProtocol

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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