Between-Person and Within-Person Associations Among Processing Speed, Attention Switching, and Working Memory in Younger and Older Adults
Bibliographic record
Abstract
UNLABELLED: BACKGROUND/STUDY CONTEXT: Theories of cognitive aging predict associations among processes that transpire within individuals, but are often tested by examining between-person relationships. The authors provide an empirical demonstration of how associations among measures of processing speed, attention switching, and working memory are different when considered between persons versus within persons over time. METHODS: A sample of 108 older adults (M (age) = 80.8, range = 66-95) and 68 younger adults (M (age) = 20.2, range = 18-24) completed measures of processing speed, attention switching, and working memory on six occasions over a 14-day period. Multilevel modeling was used to examine processing speed and attention switching performance as predictors of working memory performance simultaneously across days (within-person) and across individuals (between-person). RESULTS: The findings indicates that simple comparison and response speed predicted working memory better than attention switching between persons, whereas attention switching predicted working memory better than simple comparison and response speed within persons over time. Furthermore, the authors did not observe strong evidence of age differences in these associations either within or between persons. CONCLUSION: The findings of the current study suggest that processing speed is important for understanding between-person and age-related differences in working memory, whereas attention switching is more important for understanding within-person variation in working memory. The authors conclude that theories of cognitive aging should be evaluated by analysis of within-person processes, not exclusively age-related individual differences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".