The Canadian Multi‐Ethnic Research on Aging (CAMERA) Study: Objectives and Design
Bibliographic record
Abstract
Abstract Background Despite being among the fastest‐growing ethnoracial groups in Canada and the United States, individuals of Asian descent are significantly underrepresented in research on Alzheimer’s disease and related dementias (ADRD). Limited evidence suggests a lower incidence of dementia among Asian Americans compared to their White counterparts; however, there is variability in risk factors among Asian American subgroups. Understanding this heterogeneity is crucial for tailoring dementia prevention and intervention strategies in Asian populations. To address this gap, we launched the CAnadian Multi‐Ethnic Research on Aging (CAMERA) study in Toronto, Canada. Method CAMERA is a 5‐year longitudinal observational study based at Sunnybrook Health Sciences Centre in Toronto, Canada. CAMERA aims to enroll 300 cognitively unimpaired adults aged 55‐85 who self‐identify as South Asian, Chinese, or non‐Hispanic White (n = 100/group). Participants are recruited from the greater Toronto area using culturally appropriate, community‐based participatory approaches. We formed a community advisory board (CAB) comprising community members who share the same identity, language, culture, and values as CAMERA participants. The CAB actively engages in the research process, participant recruitment, research questions, and knowledge translation. In terms of the study protocol, at baseline (Year 1), Year 3, and Year 5, participants complete clinical, cognitive, brain MRI, blood (for genetic and biomarker analysis), and language‐ and culturally neutral eye‐tracking assessments. Every year, participants complete a series of questionnaires via REDCap covering demographic, community, cultural and social, mental and physical health, and sex‐specific health factors. Result As of April 2024, we have enrolled 131 participants. Of those, 92 participants completed baseline Year 1 testing. Of the 92 participants, 31 (33.7%) self‐identified as South Asian, 36 (39.1%) as Chinese, and 25 (27.2%) as non‐Hispanic White. Participants have a mean age of 68.1 years (SD = 6.2), and are mostly female (62 (67.4%)). Conclusion To our knowledge, this will be the first longitudinal cohort study that brings together sensitive brain imaging tools, novel blood‐based markers, and comprehensive cognitive data to investigate ADRD risk in understudied Asian subgroups. This research will yield currently unavailable data to inform the development of precision strategies to prevent and delay ADRD in Asian and other populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".