Remembering the Past and Foreseeing the Future while Dealing with the Present: A Comparison of Young Adult and Elderly Cohorts on a Multitask Simulation of Occupational Activities
Bibliographic record
Abstract
Thirty-five young adult and 38 elderly cybernauts, matched for education, sex, alcohol consumption, and time/day of computer use were compared on a computerized simulation of professional activities of daily living (ADLs). The program quantified performance in terms of speed and accuracy on four major constructs: (1) planning (a 30-item office party script); (2) prospective memory (injections, sleep, phone); (3) working memory (PASAT, D2, and CES analogs); and (4) retrospective memory. Participants had to organize an office party, self inject insulin and go to bed at requisite times of day, do "office work" at unpredictable times of day, and answer the phone that blinked but did not ring (near threshold stimulus). The elderly were markedly and equally impaired on all four constructs (F = 24.3, p < .000). The elderly were also equally and markedly impaired on slave and central executive systems (c.f. Baddeley's model) and on event-based and time-based prospective memory (c.f. McDaniel's model)-findings arguing against a "frontal" model of cognitive decline. This supports Salthouse's concept of a "general factors" decline in normal aging due to diffuse deterioration of the brain. On the other hand, as expected from previous findings, the balance of omissiveness/commissiveness was significantly increased in the elderly sample's error profile. Furthermore, the balance of speed and accuracy was significantly increased in the elderly. This defines limits of the "general factors" model. The elderly also markedly underused a clock icon which had to be clicked on to get the virtual time of day necessary for integrating all the required actions. Prospective memory explained 11% of the aging variance despite partialing out of the three other constructs, making it appear as a golden standard of sensititivity to normal aging-though perhaps provided it be implemented in a distracting, multitask, strategically demanding context.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".