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Record W3013856022 · doi:10.2196/16000

Development and Preliminary Usability Evaluation of a Somatosensory Square Dance System for Older Chinese Persons: Mixed Methods Study

2020· article· en· W3013856022 on OpenAlexvenueno aff
Chin-Wen Yu, Pei‐Luen Patrick Rau, Xueqian Liu

Bibliographic record

VenueJMIR Serious Games · 2020
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsPreprintUsabilityDanceSquare (algebra)Computer scienceHuman–computer interactionWorld Wide WebVisual artsArtMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: Chinese square dancing, known as guangchang wu in Chinese, is a well-known public fitness activity that provides an entertaining way for older Chinese women to improve their flexibility, lower extremity strength, overall coordination, and balance. However, injuries, noise conflicts, and lack of space are challenging aspects of this activity. Somatosensory games (SG) are an increasingly popular physical fitness approach to enhance the selective attention of older persons with indoor engagement and exercises. OBJECTIVE: The objectives of this study were to develop a newly designed somatosensory square dance system for older Chinese people and to evaluate its usability. METHODS: This is a mixed methods study. The newly designed somatosensory square dance system is a somatic training tool that provides adequate Chinese square dance fitness training based on Laban Movement Analysis (LMA) and design guidelines established in a previous stage. The usability evaluation involved a questionnaire and interviews. Twelve participants were interviewed before and after experiencing the 15-minute dancing and learning process within the program. In addition, participants scored their experience satisfaction in psychological, physiological, and relaxation sections on a scale of 1 to 5 using a questionnaire. Qualitative content analysis and quantitative analysis of the satisfaction scores supported understanding of usability problems. RESULTS: Based on the interview results, 6/12 (50%) of the participants thought the system could help them correct their dancing movements indoors without being affected by poor outdoor weather. Among the participants, 3/12 (25%) indicated that this indoor system could enable them to enjoy fitness activities in a private space. Moreover, 3/12 participants (25%) stated that this system could promote family relationships by providing easy dancing movements. All participants were highly satisfied with the relaxation aspect of the system (4.45/5). The participants were all psychologically satisfied and interested in the novel features of the system, with an average score of 4.16/5. Physiologically, participants affirmed that the system could help them maintain good health (4.91/5). CONCLUSIONS: The results of this study suggest that the somatosensory square dance system can be used as an indoor fitness tool to improve older Chinese square dancers' health conditions with reasonable dance training. Noise and space conflicts can be addressed. The Laban Elated Square Dance system, which was modified by therapists based on LMA and square dance design guidelines, was highly approved by dancers because it decreased the possibility of injuries, falls, and joint damage by considering the physical and psychological difficulties of older persons. Different features will be considered in the next stage, such as greater selection of exercises and difficulty level settings. Users' social needs will also be explored in subsequent stages.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.060
GPT teacher head0.401
Teacher spread0.340 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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