Activity engagement is related to level, but not change in cognitive ability across adulthood.
Bibliographic record
Abstract
It is unclear whether the longitudinal relation between activity participation and cognitive ability is due to preserved differentiation (active individuals have higher initial levels of cognitive ability), or differential preservation (active individuals show less negative change across time). This distinction has never been evaluated after dividing time-varying activity into its two sources of variation: between-person and within-person variability. Further, few studies have investigated how the association between activity participation and cognitive ability may differ from early to older adulthood. Using the PATH Through Life Project, we evaluated whether between- and within-person variation in activity participation was associated with cognitive ability and change within cohorts aged 20-24 years, 40-44 years, and 60-64 years at baseline (n = 7,152) assessed on three occasions over an 8-year interval. Multilevel models indicated that between-person differences in activity significantly predicted baseline cognitive ability for all age cohorts and for each assessed cognitive domain (perceptual speed, short-term memory, working memory, episodic memory, and vocabulary), even after accounting for sex, education, occupational status, and physical and mental health. In each case, greater average participation was associated with higher baseline cognitive ability. However, the size of the relationship involving average activity participation and baseline cognitive ability did not differ across adulthood. Between-person activity and within-person variation in activity level were both not significantly associated with change in cognitive test performance. Results suggest that activity participation is indeed related to cognitive ability across adulthood, but only in relation to the starting value of cognitive ability, and not change over time.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".