Effectiveness of the Nintendo(RTM) Wii Fit (TM) games on the balance of a community-dwelling older adult in eastern North Carolina
Bibliographic record
Abstract
The aim of this study was to determine if the Nintendoâ„—E¼ Wii Fit TM was an effective and motivating modality for fall prevention with an older adult who has MG and lives in Eastern North Carolina. With the increasing number of older adults it is imperative for occupational therapists to address balance and fall-prevention. The Nintendoâ„—E¼ Wii Fit TM is currently being implemented in occupational and physical therapy; however there is limited research. There is limited research on this topic as this is an innovative approach to balance rehabilitation. The current study aimed to provide additional evidence regarding the use of the Wii Fit TM to improve balance. The single-subject study selected an active community-dwelling older adult with Myasthenia Gravis for participation. The study consisted of three phases: phase one combined the Wii Fit TM balance games with walking outside phase two consisted of the balance and stepping games on the Wii Fit TM only and phase three consisted of walking only. Motivation was measured with a Likert-scale and self-perception of occupational performance was measured through the Canadian Occupational Performance Measure (COPM). The Four Square Step Test (FSST) and Timed Get Up and Go Test (TGUG) were used to assess the participant's balance and risk for falling; the Survey of Activities and Fear of Falling in the Elderly (SAFE) determined the participant's fear of falling and activity restriction. After the course of the study the participant's balance scores as measured by the FSST and TGUG were analyzed to determine any change. There was a significant negative correlation between the participant's FSST score and each phase (p=0.048; r=-0.712); however there was not a significant negative correlation between the participant's score on the TGUG and each phase (p=0.107; r=-0.488). These test scores indicate an improvement in dynamic balance and functional mobility. The participant reported the highest COPM and motivation scores for phase 3 walking outside only indicating that he was not as motivated to complete the activities on the Wii Fit TM . There was also a decrease in the participant's fear of falling score on the SAFE. The current study provides supporting evidence on the effectiveness of the Wii Fit TM for improving balance and reducing a risk for falling; however the study exemplifies the need for additional research.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".