Biopsychosocial Correlates of Subjective Cognitive Decline and Related Worry in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
INTRODUCTION: Subjective cognitive decline (SCD), a self-reported decline in cognition in otherwise cognitively healthy people, has been acknowledged as a risk factor for Alzheimer's disease. Using data from the Canadian Longitudinal Study on Aging (CLSA), a large national study with participants' ages of 45-85 years at baseline, we sought to identify correlates of SCD and SCD-related worry. METHODS: In our primary analysis using a Poisson regression model, associations between biopsychosocial variables and SCD were identified (analytic sample: n = 21,920). In a second analysis using an ordinal regression model, associations between biopsychosocial variables and SCD-related worry were identified (analytic sample: n = 12,694). RESULTS: Multiple risk and protective factors of cognitive decline were not associated with SCD within our sample (i.e., physical activity, hypertension, vision problems), as well as minority stress variables such as sexual orientation and race. Rather, psychosocial variables (i.e., depression, perceived social status, and personality traits) showed a more consistent association with SCD within the sample. Greater SCD-related worry, which is believed to increase the risk of future dementia, was associated with specific personality traits, depression, age, gender, and sexuality. CONCLUSION: The results from this study confirm the association between multiple health variables and SCD but also emphasize the importance of considering psychological and social factors when conceptualizing SCD and its risk factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".