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Record W7117247569 · doi:10.1002/alz70857_098783

Examining subjective cognitive decline in a Canadian multi‐ethnic cohort of older adults

2025· article· en· W7117247569 on OpenAlexaffabout
Georgia Gopinath, Rachel Yep, Tulip Marawi, Rohina Kumar, Simran Malhotra, Angelina Zhang, Madeline Wood Alexander, Alexander Nyman, Silina Z. Boshmaf, Katie L. Vandeloo, Sandra E. Black, Maged Goubran, Jennifer S Rabin

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSunnybrook HospitalToronto Rehabilitation InstituteUniversity of TorontoOntario Brain InstituteSunnybrook Health Science Centre
Fundersnot available
KeywordsDepression (economics)Cognitive declineEthnic groupAnxietyCohortAssociation (psychology)Cohort studyCognition

Abstract

fetched live from OpenAlex

BACKGROUND: Subjective cognitive decline (SCD) may represent one of the earliest symptoms of Alzheimer's disease. However, SCD remains understudied in diverse ethnoracial groups, particularly among individuals of Asian descent. Leveraging data from a cohort study of Canadian South Asian, Chinese, and White older adults, this study investigated ethnic differences in: (1) SCD burden, (2) the association between self- and study partner-reported SCD, and (3) the demographic and neuropsychiatric factors associated with SCD. METHODS: Participants were South Asian, Chinese, and White adults aged 55-85 enrolled in the observational cohort study, Canadian Multi-Ethnic Research on Aging (CAMERA). Participants were classified as cognitively unimpaired based on a Clinical Dementia Rating global score of 0. SCD was assessed using the self- and study partner-reported Cognitive Functioning Index (CFI). Depression and anxiety symptoms were measured using the Geriatric Depression Scale and Generalized Anxiety Disorder-7 Scale, respectively. Linear regression models were used to examine associations of interest, adjusting for age, sex, years of education, as well as depression and anxiety symptoms. RESULTS: We included 140 participants (mean age=65.8±6.4, 69.3% female) who self-identified as South Asian (n = 38), Chinese (n = 52) or White (n = 50). Self-reported CFI scores were significantly higher in South Asian (β=0.9, p = 0.02) and Chinese participants (β=1.4, p < 0.001) compared to White participants, and did not significantly differ between South Asian and Chinese participants (β=0.5, p = 0.2). Self- and study partner-reported CFI scores were significantly associated across the whole sample (β=0.3, p = 0.01), with no moderation by ethnicity (p>0.05). However, the associations between symptoms of depression and anxiety with self-reported CFI scores were stronger in South Asian and Chinese participants compared to White participants (p < 0.05). The associations between depression and anxiety with CFI did not significantly differ between South Asian and Chinese participants (p>0.05). CONCLUSIONS: In a sample of cognitively unimpaired older adults, self- and study partner-reported SCD were associated, and the strength of the association did not differ across ethnic groups. However, among South Asian and Chinese participants, SCD burden was greater and more strongly associated with depression and anxiety symptoms. These findings underscore the importance of considering ethnoracial differences and neuropsychiatric symptoms when assessing SCD in diverse populations.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.340
Teacher spread0.309 · 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 designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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