Computer and Videogame Interventions for Older Adults' Cognitive and Everyday Functioning
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: This study compared older adults' gains in cognitive and everyday functioning after a 60-session home-based videogame intervention with gains seen under formal cognitive training and usual care/no intervention. MATERIALS AND METHODS: Participants were randomized to one of three groups: one group played an off-the-shelf videogame (i.e., Crazy Taxi), the second group engaged in a computerized training program focused on visual attention and processing speed (i.e., PositScience InSight), and the third 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). Participants received a broad battery of cognitive and everyday functioning assessments immediately before (pretest), after (post-test), and 3 months after (follow-up) training. RESULTS: Both training conditions improved on direct assessments of trained outcomes. In the InSight-trained group, we found transfer to untrained measures of visual attention and processing speed that were similar to the trained tasks, and these gains endured for up to 3 months. Participants in the videogame condition showed small additional benefits, not emerging until 3 months after intervention completion, on a measure of both attention and mood. No trained groups showed gain on visuospatial skills or memory. CONCLUSION: Training effects were highly specific to the target of training. Training effects to visual attention and processing speed were, as expected, larger for InSight-trained participants but were also seen for videogame participants. Given that past research has shown that videogame training leads to greater engagement than cognitive training, videogame interventions may represent a choice for more modest gains in a more engaging context.
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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 | 0.001 | 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 | 0.002 | 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