Experiences of Older Adults with Mild Cognitive Impairment from Cognitive Self-Training Using Touchscreen Tablets
Bibliographic record
Abstract
Background:“Tablet Enhancement of Cognition and Health” (TECH) is a cognitive intervention that includes two components: 5 weeks of daily self-training using puzzle-game apps on a touch screen tablet and weekly group sessions. This study aimed to (i) explore experiences of older adults with mild cognitive impairment (MCI) following their participation in TECH, (ii) identify hindering and enabling factors to self-training, and (iii) describe participants' perceived and objective cognitive changes and examine factors associated with their satisfaction from TECH. Materials and Methods:We used quantitative and qualitative measures; a phenomenological qualitative design using focus groups and interviews of 14 older adults with MCI and a focus group of the TECH facilitators. Satisfaction with TECH, self-training time, and perceived and objective cognitive changes (using the Montreal Cognitive Assessment) were evaluated. Results:Qualitative data were classified into three categories: Memory problems, Hindering and enabling factors to self-training, and Meaningful group sessions. The TECH facilitators reported positive changes, less cognitive complaints, and commitment and satisfaction of the participants. Participants reported overall satisfaction from TECH and performed a median interquartile range of 22.6 (19.9–42.8) self-training hours. Higher satisfaction was correlated with a higher objective cognitive change (r = 0.95, P < 0.01) and less training time (r = −0.91, P < 0.01). Discussion and Conclusions:Participants in the current study actively engaged in daily self-training using touch screen-tablet-puzzle-game and functional apps, driven by both internal and external motivators. Despite the lack of cognitive improvement, they expressed satisfaction with their participation in TECH. Therefore, encouraging older adults to engage in meaningful cognitive stimulating activities is recommended.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".