Association between the frequency of daily intellectual activities and cognitive domains: A cross‐sectional study in older adults with complaints of forgetfulness
Bibliographic record
Abstract
OBJECTIVES: Frequent engagement in intellectual activities has been shown to reduce the risk of developing dementia. The present study sought to examine the association between the frequency of daily intellectual activities and cognitive domains in older adults with complaints of forgetfulness. METHODS: A cross-sectional study was conducted as a part of regional health examination in Tokyo from 2014 to 2016. A total of 436 participants were asked the frequency of intellectual activities in four categories: 1) reading, 2) writing, 3) using technology, and 4) watching TV and listening to the radio. The Japanese version of the Montreal Cognitive Assessment (MoCA-J) scale was used for the cognitive assessments. The relationships between MoCA-J scores and each intellectual activity were explored. RESULTS: Binominal logistic regression analysis revealed that the frequencies of reading, writing, and using technology were significantly related to the language and attention, language, and memory domains, respectively, even after adjusting for demographic characteristics. CONCLUSIONS: The results suggested that the frequency of daily intellectual activities differed depending on the activity type, and each activity was related to a specific cognitive domain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".