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Record W6990818986

EFFECTIVENESS OF THE NINTENDO ® WII FIT ™ GAMES ON THE BALANCE OF A COMMUNITY-DWELLING OLDER ADULT IN EASTERN NORTH CAROLINA By

2011· article· en· W6990818986 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsBalance (ability)Test (biology)Balance testPoison controlActivities of daily livingOccupational safety and health
DOInot available

Abstract

fetched live from OpenAlex

The aim of this study was to determine if the Nintendo ® Wii Fit ™ 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 Nintendo ® Wii Fit ™ 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 ™ 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 ™ balance games with walking outside, phase two consisted of the balance and stepping games on the Wii Fit ™ 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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.043
GPT teacher head0.323
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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