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Record W7117761900 · doi:10.1136/bmjopen-2025-108960

Evaluating the impact of a national brain health education course for older adults with intellectual and developmental disabilities and caregivers: Brain Health-IDD Program protocol

2025· article· en· W7117761900 on OpenAlexafffundabout
Yona Lunsky, Nicole Bobbette, Mary Chiu, Anupam Thakur, Tiziana Volpe, Robert Balogh, Amy Baskin, Marie-Joëlle Beaudoin, Matthew J Dever, Anna Durbin, Adeen Fogle, Colleen Kelly, Johanna Lake, Gill Lefkowitz, Heidi Mallett, Janet McCabe, Judy Noonan, Avra Selick, Shahin Shooshtari, Sanjeev Sockalingam, Laura St. John, Lee Steel, Alicia Thatcher, Mary McCarron

Bibliographic record

VenueBMJ Open · 2025
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsUniversity of SaskatchewanUniversity of ManitobaManitoba HealthUniversity of CalgaryOntario Tech UniversityOntario Shores Centre for Mental Health SciencesQueen's UniversityUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchAzrieli Foundation
KeywordsMental healthLife course approachProtocol (science)AddictionResearch ethicsIntellectual disabilityPublic healthEthical issuesInternational Classification of Functioning, Disability and Health

Abstract

fetched live from OpenAlex

INTRODUCTION: Adults with intellectual and/or developmental disabilities (IDD) experience higher rates of age-related health concerns, including dementia, than adults without disabilities. Despite this, current efforts to support brain health in ageing have often excluded this population. To address this gap, we will codesign, codeliver and evaluate a national virtual brain health education programme, Brain Health-IDD, for ageing individuals with IDD, family caregivers and health and social care providers. METHODS AND ANALYSIS: This study will evaluate the Brain Health-IDD Program, an interactive virtual psychoeducation course codesigned and coled by an interdisciplinary team of clinicians and people with lived experience. Three participant groups will be recruited from across Canada: adults with IDD, aged 40 years and older; family caregivers who have a family member with IDD aged 40 years and older or who are themselves aged 60 years and older; and health or social service providers who support adults with IDD aged 40 years and older. Outcomes will be measured at baseline, postcourse and 3-month follow-up. Data will be collected through structured surveys, including both closed and open-ended questions, and focus group interviews.Primary outcomes are participation, satisfaction and changes in knowledge and self-efficacy related to brain health among the three participant groups. Secondary outcomes for both adults with IDD and family caregivers include changes in health-related behaviours (social connections, sleep hygiene and physical activity), physical health, mental wellbeing, resilience and whether cognitive screening is initiated for adults with IDD and for caregivers. For health and social service providers, secondary outcomes include changes in brain health promotion practices and whether cognitive screening for older adults with IDD is initiated.Analysis of open-text survey responses and qualitative data from focus group interviews will explore the experiences of participants with the Brain Health-IDD Program. ETHICS AND DISSEMINATION: Institutional ethics approval was obtained from the Centre for Addiction and Mental Health Research Ethics Board. Programme findings and resources will be shared with advocacy groups, disability agencies, family caregiver organisations, clinicians and policymakers in the fields of disability, health and ageing at the provincial, national and international levels.

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)0.022
metaresearch head score (Gemma)0.015
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: Protocol
Teacher disagreement score0.040
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.015
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0040.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0400.007

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 head0.167
GPT teacher head0.586
Teacher spread0.419 · 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".

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Citations0
Published2025
Admission routes3
Has abstractyes

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