An online, updated battery for episodic memory and executive control composites in older adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction Neuropsychological perspectives on aging suggest that episodic memory and executive control are highly vulnerable. Previous studies have used composite indexes representing young and older adults’ relative performance in each of these two domains. However, the episodic memory measures that have made up that composite are often common clinical ones (e.g., Logical Memory from Wechsler Memory Scale) and may therefore be susceptible to practice and/or ceiling effects.Method In the present study, we replaced the previous episodic memory measures with new ones that are novel, reliable, valid, and easy to administer online, and asked how they fit together and with the existing executive control composite. We also examined the relations between the updated composite scores and participant age, sex, and several health characteristics (i.e., depressive and anxiety symptoms, sleep, medications, vascular health, and COVID-19 infection). We administered our updated battery to healthy young (YA; n = 97) and older adults (OA; n = 96) over videoconference.Results Using confirmatory factor analysis with age invariance testing, we successfully replicated the two-factor structure in OAs but not in YAs. YAs had higher episodic memory composite scores than OAs, whereas the inverse was true for executive control. In both age groups, males had higher executive control composite scores than females. Although many of the health-related variables differed between age groups in the expected direction, none were significantly associated with either composite after adjusting for multiple analyses.Conclusions Our findings suggest that this updated battery may be suitable for remote use with healthy older adults and is related to participant sex. Additional studies replicating our factor structures in larger samples will be beneficial.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it