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Record W2908276293 · doi:10.2196/11326

Energy Expenditure and Enjoyment During Active Video Gaming Using an Adapted Wii Fit Balance Board in Adults with Physical Disabilities: Observational Study

2018· article· en· W2908276293 on OpenAlexvenueno aff
Laurie A. Malone, Mohanraj Thirumalai, Sangeetha Padalabalanarayanan, Whitney N. Neal, Sean Bowman, Tapan Mehta

Bibliographic record

VenueJMIR Serious Games · 2018
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersAdministration for Community LivingAustralian GovernmentNational Institute on Disability, Independent Living, and Rehabilitation ResearchU.S. Department of Health and Human Services
KeywordsEnergy expenditureSittingPhysical therapyPsychologyPhysical activityVideo gameObservational studyMetabolic equivalentBalance (ability)Physical medicine and rehabilitationMedicineComputer scienceMultimedia

Abstract

fetched live from OpenAlex

BACKGROUND: Individuals with physical disabilities have fewer opportunities to participate in enjoyable physical activity. One option for increasing physical activity is playing active video games (AVGs); however, many AVGs are inaccessible or offer limited play options. OBJECTIVE: This study aimed to examine energy expenditure and enjoyment in adults with mobility impairment during AVG play using off-the-shelf (OTS) and adapted versions of the Wii Fit balance board (Nintendo). METHODS: During visit 1, participants completed a functional assessment and the familiarization period. During visit 2, metabolic data were collected during a 20-minute baseline and four 10-minute bouts of Wii Fit Plus game play, with two bouts on each of the boards. During the resting period, participants completed the Physical Activity Enjoyment Scale (PACES). Statistical analyses were computed using SPSS software. Data were analyzed separately for individuals who were able to play while standing on both boards (StdStd); those who could not play while standing on the OTS board, but were able to play while standing on the adapted board (aStd); and those who could only play while sitting on the adapted board (aSit). RESULTS: Data were collected for 58 participants (StdStd, n=17; aStd, n=10; aSit, n=31). The sample included 31 men and 27 women with a mean age of 41.21 (SD 12.70) years. Energy expenditure (metabolic equivalent [MET]) during game play was significantly greater than that during rest for all players. Only 17 participants (StdStd group) were able to play using the OTS board. During game play on the adapted board, the average MET values for the two game sets were 2.261 (SD 0.718) kcal/kg/hour and 2.233 (SD 0.751) kcal/kg/hour for the aSit group, 3.151 (SD 1.034) and 2.990 (SD 1.121) for the aStd group, and 2.732 (SD 0.655) and 2.777 (SD 0.803) for the StdStd group. For game play on the adapted board, self-reported ratings of perceived exertion on a 0-10 scale suggested greater exercise intensity levels, with median scores ranging from moderate (3) to very hard (7). The PACES scores indicated that all players enjoyed using the adapted board, with a median score of 4 on a 5-point scale. CONCLUSIONS: The adapted Wii Fit balance board provided an opportunity for individuals with mobility impairments, including wheelchair users, to engage in AVG. All participants were able to utilize the adapted controller and enjoyed the AVG activity. Although the average MET values achieved during AVG represented light-intensity exercise (<3 METs), 16% of sitting participants and 41% of standing participants achieved moderate-intensity exercise (3-6 METs) in at least one of the games. Factors not accounted for, which may have influenced the intensity of exercise, include game selection, limited familiarization period, and discomfort wearing the COSMED portable metabolic system for measurement of oxygen consumption. Accessible AVG controllers offer an innovative approach to overcome various barriers to participation in physical activity. The next steps include assessment of an AVG intervention using an adapted board gaming controller on health and fitness outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT02994199; https://clinicaltrials.gov/ct2/show/NCT02994199 (Archived by Webcite at http://www.webcitation.org/75fc0mN39).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

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

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 head0.029
GPT teacher head0.314
Teacher spread0.285 · 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 teacher head, 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

Citations25
Published2018
Admission routes1
Has abstractyes

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