Journal of Research in Rehabilitation Sciences

Can Functional Movement Screen Test Predict Nonstructural Scoliosis in University Girl Students?

Document Type : Original Articles

Authors

1 PhD Student, Department of Sport Medicine and Health, School of Physical Education and Sport Sciences, University of Tehran, Tehran, Iran

2 Professor, Department of Sport Medicine and Health, School of Physical Education and Sport Sciences, University of Tehran, Tehran, Iran

3 Assistant Professor, Department of Sport Medicine and Health, School of Physical Education and Sport Sciences, University of Tehran AND Department of Sport Sciences, School of Humanities, Tarbiat Modares University, Tehran AND Department of Sport Rehabilitation, School of Sport Science, Bu Ali Sina University, Hamadan, Iran

4 Associate Professor, Department of Sport Medicine and Health, School of Physical Education and Sport Sciences, University of Tehran, Tehran, Iran

10.22122/jrrs.v14i1.3113

Abstract

Introduction: Scoliosis is a complex deformity of the spine. The possibility of surgery decrease by early diagnosis. The aim of this study was to investigate the efficiency of the functional movement screen test to predict scoliosis.Materials and Methods: Of 1672 university girl students, 98 were selected and divided into two group of scoliosis (43 cases with left thoracic curvature) and health (55 cases). The degree of curvature and functional movements were assessed by photography and functional movement screen test, respectively. Logistic regression analysis was used to evaluate the effect of predictor variables (functional movement screen test) on the criterion variable (scoliosis and health).Results: There was significant inverse correlation between scoliosis with deep squat (P < 0.001), hurdle step (P < 0.001), in-line lunge (P = 0.006), active straight-leg raise (P < 0.001), trunk stability push-up (P < 0.001), and rotary stability (P < 0.001). The logistic regression analysis revealed that low scores in hurdle step (P = 0.006) and active straight leg raising (P=0.02) could predict probability of scoliosis.Conclusion: Movement assessment seems to be an effective way to predict the probability of nonstructural scoliosis.

Keywords

  1. Romano M, Minozzi S, Zaina F, Saltikov JB, Chockalingam N, Kotwicki T, et al. Exercises for adolescent idiopathic scoliosis: A Cochrane systematic review. Spine (Phila Pa 1976) 2013; 38(14): E883-E893.
  2. Bettany-Saltikov J, Parent E, Romano M, Villagrasa M, Negrini S. Physiotherapeutic scoliosis-specific exercises for adolescents with idiopathic scoliosis. Eur J Phys Rehabil Med 2014; 50(1): 111-21.
  3. Rosenberg JJ. Scoliosis. Pediatr Rev 2011; 32(9): 397-8.
  4. Pin LH, Mo LY, Lin L, Hua LK, Hui HP, Hui DS, et al. Early diagnosis of scoliosis based on school-screening. J Bone Joint Surg Am 1985; 67(8): 1202-5.
  5. Fong DYT. Should screening for scoliosis be conducted? ArgoSpine News and Journal 2012; 24(1-2): 46-9.
  6. Alves de Araujo ME, Bezerra da SE, Bragade MD, Cader SA, Shiguemi Inoue SA, Dantas EH. The effectiveness of the Pilates method: Reducing the degree of non-structural scoliosis, and improving flexibility and pain in female college students. J Bodyw Mov Ther 2012; 16(2): 191-8.
  7. Hawes MC, O'brien JP. The transformation of spinal curvature into spinal deformity: pathological processes and implications for treatment. Scoliosis 2006; 1(1): 3.
  8. Han J, Xu Q, Yang Y, Yao Z, Zhang C. Evaluation of quality of life and risk factors affecting quality of life in adolescent idiopathic scoliosis. Intractable Rare Dis Res 2015; 4(1): 12-6.
  9. Filipovic V, Viskic-stalec N. The mobility capabilities of persons with adolescent idiopathic scoliosis. Spine (Phila Pa 1976) 2006; 31(19): 2237-42.
  10. Daryabor A, Arazpour M, Sharifi G, Bani MA, Aboutorabi A, Golchin N. Gait and energy consumption in adolescent idiopathic scoliosis: A literature review. Ann Phys Rehabil Med 2017; 60(2): 107-16.
  11. Cook G. Movement: Functional movement systems: Screening, assessment, corrective strategies. 1st ed. Portland, OR: Lotus Publishing; 2011. p. 79, 90-106.
  12. Mitchell UH, Johnson AW, Adamson B. Relationship between functional movement screen scores, core strength, posture, and body mass index in school children in Moldova. J Strength Cond Res 2015; 29(5): 1172-9.
  13. Plichta SB, Kelvin EA. Munro's Statistical Methods for Health Care Research. Philadelphia, PA: Wolters Kluwer Health/Lippincott Williams and Wilkins; 2012. p. 309.
  14. Anderson BE, Neumann ML, Huxel Bliven KC. Functional movement screen differences between male and female secondary school athletes. J Strength Cond Res 2015; 29(4): 1098-106.
  15. Butler RJ, Plisky PJ, Southers C, Scoma C, Kiesel KB. Biomechanical analysis of the different classifications of the Functional Movement Screen deep squat test. Sports Biomech 2010; 9(4): 270-9.
  16. Leal JS, Aroeira RMC, Gressler V, Greco M, Pertence AEM, Lamounier JA. Accuracy of photogrammetry for detecting adolescent idiopathic scoliosis progression. Spine J 2018. [In Press].
  17. Ernst MJ, Rast FM, Bauer CM, Marcar VL, Kool J. Determination of thoracic and lumbar spinal processes by their percentage position between C7 and the PSIS level. BMC Res Notes 2013; 6: 58.
  18. Linek P, Saulicz E, Kuszewski M, Wolny T. Ultrasound assessment of the abdominal muscles at rest and during the aslr test among adolescents with scoliosis. Clin Spine Surg 2017; 30(4): 181-6.
  19. Lederman E. Neuromuscular rehabilitation in manual and physical therapies: principles to practice. London, UK: Churchill Livingstone/Elsevier; 2010.
  20. Mohler ML. The ability of the FMS to predict knee injury in female collegiate athletes [MSc Thesis]. Greensboro, NC: The University of North Carolina; 2014.
Journal of Research in Rehabilitation Sciences
Volume 14, Issue 1 - Serial Number 1
March 2018
Pages 9-14