Characteristics of Healthy Older Adults that Influence Self-rated Cognitive Function
Bibliographic record
Abstract
OBJECTIVES: We sought to clarify the nature of self-reported cognitive function among healthy older adults by considering the short-term, within-person association (coupling) of subjective cognitive function with objective cognitive performance. We expected this within-person coupling to differ between persons as a function of self-perceived global cognitive decline and depression, anxiety, or neuroticism. METHODS: This was an intensive measurement (short-term longitudinal) study of 29 older adult volunteers between the ages of 65 and 80 years without an existing diagnosis of dementia or mild cognitive impairment. Baseline assessment included neuropsychological testing and self-reported depression, anxiety, and neuroticism, as well as self- and informant-reported cognitive decline (relative to 10 years previously). Intensive within-person measurement occasions included subjective ratings of cognitive function paired with performance on a computerized working memory (n-back) task; each participant attended four or five assessments separated by intervals of at least one day. Statistical analysis was comprised of multilevel linear regression. RESULTS: Comparison of models suggested that both neuroticism and self-rated cognitive decline explained unique variance in the within-person, across-occasion coupling of subjective cognitive function with objective working memory performance. CONCLUSIONS: Self-ratings of cognition may accurately reflect day-to-day variations in objective cognitive performance among older adults, especially for individuals lower in neuroticism and higher in self-reported cognitive decline. Clinicians should consider these individual differences when determining the validity of complaints about perceived cognitive declines in the context of otherwise healthy aging. (JINS, 2018, 24, 57-66).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".