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Record W2773862085 · doi:10.1089/g4h.2017.0065

Effects of Kinect Adventures Games Versus Conventional Physical Therapy on Postural Control in Elderly People: A Randomized Controlled Trial

2017· article· en· W2773862085 on OpenAlexaboutno aff
Jéssica Maria Ribeiro Bacha, Gisele Cristine Vieira Gomes, Tatiana Beline de Freitas, Larissa Alamino Pereira de Viveiro, Keyte Guedes da Silva, Gessika Costa Bueno, Eliana Maria Varise, Camila Torriani‐Pasin, Angélica Castilho Alonso, Natália Mariana Silva Luna, Júlia María D’Andréa Greve, José Eduardo Pompeu

Bibliographic record

VenueGames for Health Journal · 2017
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
FundersUniversidade de São Paulo
KeywordsCardiorespiratory fitnessPhysical therapyRandomized controlled trialGaitMedicinePhysical medicine and rehabilitationPsychological interventionAnalysis of varianceCognitionPost-hoc analysisTest (biology)RehabilitationPsychologySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the effectiveness of Kinect Adventures games versus conventional physiotherapy to improve postural control (PC), gait, cardiorespiratory fitness, and cognition of the elderly. In addition, we evaluated the safety, acceptability, and adherence to the interventions. MATERIALS AND METHODS: The study was a randomized clinical trial in which 46 elderly individuals were selected, mean age 69.3 (5.34) years. Participants were allocated to the Kinect Adventures Training Group (KATG) or the Conventional Physical Therapy Group (CPTG), 23 individuals in each group. Participants of both groups participated in 14 training sessions lasting 1 hour each, twice a week. The KATG practiced four Kinect Adventures games. The CPTG participated in conventional physiotherapy. The primary outcome was PC: Mini-Balance Evaluation Systems Test (Mini-BESTest), and secondary outcomes were gait: Functional Gait Assessment (FGA), cardiorespiratory fitness: Six-minute step test (6MST), and cognition: Montreal Cognitive Assessment (MoCA). Acceptability was assessed through a questionnaire created by the researchers themselves. Adherence was assessed by the "frequency of the number of elderly individuals who completed the interventions and safety through the presence of adverse effects." Participants were assessed immediately pre- and posttreatment and fourth week after the end of the treatment. Statistical analysis was done through repeated-measures analysis of variance and Tukey post hoc test. RESULTS: Both groups presented a significant improvement in the PC (Mini-BEST), gait (FGA), and cognition (MoCA) posttreatment that was maintained at fourth week after treatment (post hoc Tukey test; P < 0.05). Regarding cardiorespiratory fitness (6MST), the KATG presented improvement posttreatment and maintenance of the results in the fourth week after treatment. CPTG showed improvement only in fourth week after treatment (post hoc Tukey tests; P < 0.05). Regarding the acceptability, the questionnaire showed that both groups were satisfied with regard to the proposed interventions. There was 91% adherence in both training sessions. Regarding the safety, 34% and 26% of the individuals of the KATG and CPTG, respectively, presented adverse effects of delayed muscle pain in the lower limbs after the first session only. CONCLUSION: There were no significant differences between the KATG and CPTG; both interventions provided positive effects on PC, gait, cardiorespiratory fitness, and cognition of the elderly.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.021
GPT teacher head0.398
Teacher spread0.377 · 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 designRandomized trial
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

Citations112
Published2017
Admission routes1
Has abstractyes

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