The Effect of Virtual Intelligence Games Applied to Older Adults on Cognitive Skills
Bibliographic record
Abstract
Objective : This study aimed to evaluate cognitive status, quality of life, and mood in older adults through intelligence games loaded onto smartphones. Methods : In this study, 60 older adults aged 65 and over, who voluntarily participated and visited the outpatient clinic of the Department of Physical Therapy and Rehabilitation at Kırıkkale University Faculty of Medicine, were evaluated. The sociodemographic information of the older adults such as age, height, weight, etc., was recorded. The cognitive statuses were assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), the quality of life was evaluated using the Nottingham Health Profile, and the depression statuses were assessed with the Geriatric Depression Scale (GDS). Those older adults meeting the inclusion criteria, with a MMSE score below 24, were included in the study, totaling 50 participants. Subsequently, the individuals were randomly divided into 2 groups: training and control, with each group consisting of 25 older adults. The training group was requested to play intelligence games developed by researchers and installed on their smartphones at least once a day for 8 weeks. Both the training and control groups were assessed using a questionnaire created before and after the training period. Results : According to the statistical analysis conducted, a significant difference was found between the training and control groups in the MMSE, MoCA, and GDS scores after the training. There was a significant difference found in the total score of sleep, emotional state, and overall quality of life ( P < .05), while no significant differences were detected among the other parameters ( P > .05). Conclusion : In conclusion, it was determined that technological advancements and the intelligence games loaded onto their smartphones, which they can access anytime and anywhere, improved the cognitive status of older adults in areas such as memory, attention, calculation, and shape matching and, it was observed that these activities enhanced their mood, sleep, and overall quality of life.
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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 | 0.001 | 0.003 |
| 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".