Mapping social determinants of cognitive health in Canada: a scoping review
Bibliographic record
Abstract
INTRODUCTION: We sought to map the literature assessing the associations between the social determinants of health (SDoH) and the cognitive health of adults in Canada. METHODS: We searched the Embase, CENTRAL, Global Health and MEDLINE databases through Ovid, from inception to 20 February 2024, for studies examining associations between SDoH and cognitive health among Canadian adults, irrespective of health or cognitive status. RESULTS: We identified 159 publications covering 93 studies; 27% (n = 25) had nationwide coverage and 48% (n = 45) were from Ontario or Quebec. Of the 410 associations between SDoH and cognition, 20 were from 6 qualitative studies and 390 from 87 quantitative studies. Education was the most frequently evaluated (46%) of the 29 identified SDoH categories, then social support (24%), household/individual income (19%), marital status (17%), occupation (16%), rural or urban area of residence (16%), living arrangement/household composition (12%) and environmental factors (13%). Two-thirds (67%) of the studies examined various cognitive health constructs, while 41% evaluated dementia (all types). Most of the SDoH were from the settings with which individuals directly interact. SDoH related to environmental exposure or pollution, societal norms, beliefs, values and practices were less frequently evaluated. CONCLUSION: This scoping review provides a detailed map of the literature on SDoH and cognitive health in Canada. It highlights the importance of considering a comprehensive range of SDoH and of using diverse data sources and data collection approaches. The results also highlight SDoH that remain largely unexamined and should be prioritized in future research.
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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 | 0.023 | 0.100 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.064 | 0.091 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".