Kinect Project: People with dementia or mild cognitive impairment learning to play group motion‐based games
Bibliographic record
Abstract
INTRODUCTION: Motion-based technologies (MBTs) could provide nonpharmacologic interventions for people with cognitive impairment (PCI; e.g., dementia or mild cognitive impairment). This study examined the use of errorless learning techniques to empower PCI to use MBT. METHODS: Thirty-eight PCI were recruited to a 10-week (20 × 1-hour sessions) Xbox Kinect bowling group. Video recorded data from first, middle, and final sessions were coded to track (1) number of prompts per turn, (2) independent turn completion, and (3) duration of turns. These values were compared using repeated measures analysis of variance. RESULTS: Learning and improvement over time was demonstrated in 23 participants who were available for final analysis by significant decreases in number of prompts per turn and turn duration and significant increases in turns completed independently. DISCUSSION: Errorless learning supported PCI to learn MBT and improve over time as evidenced by their need for fewer prompts, shorter turns, and more turns completed independently, confirming the potential of MBT to provide leisure activities for PCI.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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; both teacher heads agree on what is shown here.
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".