Factors influencing discrepancies in self-reported memory and performance on memory recall in the Canadian Community Health Survey—Healthy Aging, 2008–09
Bibliographic record
Abstract
OBJECTIVE: the objectives of this study were: (i) to estimate the rate of discrepancy between participant single-item self-reports of good memory and poor performance on a list-learning task and (ii) to identify the factors including age, gender and health status that influence these discrepant classifications. STUDY DESIGN AND SETTINGS: in total, 14,172 individuals, aged 45-85, were selected from the 2008-09 Canadian Community Health Survey on Healthy Aging. We examined the individual characteristics of participants with and without discrepancies between memory self-reports and performance with a generalised linear model, adjusting for potential covariates. RESULTS: the mean age of respondents was 62.9 years with 56.7% being female, 53.8% having post-secondary graduation and 83% being born in Canada. Higher discrepant classification rates we observed for younger people (6.77 versus 3.65 for lowest and highest group), female (5.90 versus 3.68) and with higher education (6.17 versus 3.52). Discrepant classification rates adjusted with all covariates were higher for those without chronic diseases (5.37 [95% Confidence Interval (CI): 4.16, 6.90] versus 4.05 95% CI: 3.38, 4.86; P = 0.0127), those who did not drink alcohol (5.87 95% CI: 4.69, 7.32 versus 3.70 95% CI: 3.00, 4.55; P < 0.0001), lonely participants (5.45 95% CI: 4.20, 7.04 versus 3.99 95% CI: 3.36, 4.77; P = 0.0081) and bilingual participants (5.67 95% CI: 4.18, 7.64 versus 3.83 95% CI: 3.27, 4.50; P = 0.0102). CONCLUSION: the findings of this study suggest that the self-reported memory and memory performance differ in a substantial proportion of the population. Therefore, relying on a self-reported memory status may not accurately capture those experiencing memory difficulties.
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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 | 0.004 | 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 | 0.001 |
| 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".