한국전문물리치료학회지 (Physical Therapy Korea)

  • 제27권2호
  • /
  • Pages.140-148
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  • 2020
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  • 1225-8962(pISSN)
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  • 2287-982X(eISSN)
한국전문물리치료학회 (Korean Research Society of Physical Therapy)
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Prediction Model for the Risk of Scapular Winging in Young Women Based on the Decision Tree

  • Gwak, Gyeong-tae (Kinetic Ergocise Based on Movement Analysis Laboratory) ;
  • Ahn, Sun-hee (Kinetic Ergocise Based on Movement Analysis Laboratory) ;
  • Kim, Jun-hee (Kinetic Ergocise Based on Movement Analysis Laboratory) ;
  • Weon, Young-soo (Kinetic Ergocise Based on Movement Analysis Laboratory) ;
  • Kwon, Oh-yun (Kinetic Ergocise Based on Movement Analysis Laboratory)
  • 투고 : 2020.01.16
  • 심사 : 2020.03.04
  • 발행 : 2020.05.20
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초록

Background: Scapular winging (SW) could be caused by tightness or weakness of the periscapular muscles. Although data mining techniques are useful in classifying or predicting risk of musculoskeletal disorder, predictive models for risk of musculoskeletal disorder using the results of clinical test or quantitative data are scarce. Objects: This study aimed to (1) investigate the difference between young women with and without SW, (2) establish a predictive model for presence of SW, and (3) determine the cutoff value of each variable for predicting the risk of SW using the decision tree method. Methods: Fifty young female subjects participated in this study. To classify the presence of SW as the outcome variable, scapular protractor strength, elbow flexor strength, shoulder internal rotation, and whether the scapula is in the dominant or nondominant side were determined. Results: The classification tree selected scapular protractor strength, shoulder internal rotation range of motion, and whether the scapula is in the dominant or nondominant side as predictor variables. The classification tree model correctly classified 78.79% (p = 0.02) of the training data set. The accuracy obtained by the classification tree on the test data set was 82.35% (p = 0.04). Conclusion: The classification tree showed acceptable accuracy (82.35%) and high specificity (95.65%) but low sensitivity (54.55%). Based on the predictive model in this study, we suggested that 20% of body weight in scapular protractor strength is a meaningful cutoff value for presence of SW.

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참고문헌

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피인용 문헌

  1. Decision Tree Algorithm-Based Model and Computer Simulation for Evaluating the Effectiveness of Physical Education in Universities vol.2020, 2020, https://doi.org/10.1155/2020/8868793