Videogame and Computer Intervention Effects on Older Adults' Mental Rotation Performance
Bibliographic record
Abstract
Objective: This article examined older adults' performance on two components of a mental rotation task (reaction time and rotation rate) in a home-based intervention study of videogame (Crazy Taxi [CT]) and computerized cognitive training (PositScience InSight). Materials and Methods: Participants were randomized to one of three groups: one group played an off-the-shelf videogame (i.e., CT), the second group engaged in a computerized training program focused on fast perceptual comparisons, visuospatial working memory, rapid scanning of a visual array and pattern recognition, visual discrimination, and selective and divided attention and processing speed (i.e., InSight), and the third (control) group received no training. Training in the two intervention conditions consisted of 60 training sessions of 1 hour each, which were completed in 3 months (5 hours a week). As part of a larger study, participants received mental rotation testing, which was administered immediately before (baseline), after (post-test), and 3 months after (follow-up) training. Results: Although the InSight group showed greater improvements in rotation rate at the immediate post-test, by the 3-month follow-up, the combined treatment groups (CT and InSight) had improved more than controls. Conclusion: The improvements in mental rotation performance found at 3-month follow-up add additional support to previous research, showing visuospatial benefits of both videogame play and cognitive training in older adults. Common elements of both interventions may include expansion of the attentional field of view and faster visual comparison efficiency.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".