Effects of improvement on selective attention: Developing appropriate somatosensory video game interventions for institutional-dwelling elderly with disabilities
Bibliographic record
Abstract
The purpose of this study was to develop appropriate somatosensory video game interventions on enhancing selective attention of institutional-dwelling elderly with disabilities. Fifty-eight participants aged 65~92 were recruited and divided into four groups, 4-week and 8-week experimental and two control groups, for evaluating the one-month carry-forward effects by Vienna Test System. Fourteen participants in experimental groups voluntarily completed 30-minute Xbox games 3 times per week for a total of 4 and 8 weeks. The results showed that: (1) except sum of incorrect reaction, a majority of participants whose selective attentions had significant improvements in immediate effect, carry-forward effects and overall effect in 8-week group (p <.05); (2) 5 out of 8 items in selective attention tests had significant immediate and carry-forward effects and one overall effect in 4-week intervention (p <.05) and (3) The results conclude that using somatosensory video games is a viable approach to promote selective attention of institutional-dwelling elderly with disabilities. The present study also found that this approach could motivate elderly to participate with a variety of sound, music and sensory stimulations and is a viable and valuable direction to promote quality of life in long-term care system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".