Journal of International Academy of Physical Therapy Research (국제물리치료학회지)

International Academy of Physical Therapy Research (국제물리치료연구학회)
권호 표지
DOI QR코드

DOI QR Code

Semantic Network Analysis of Physiotherapy Research: Based on Studies Published in the Journal of IAPTR

  • Go, Junhyeok (Department of Health Science, Kyungbok University) ;
  • Yeum, Dongmoon (Department of Social Welfare, Changshin University) ;
  • Kim, Nyeonjun (Department of Physical Therapy, Pohang University) ;
  • Choi, Myungil (Department of Advertising & Public Relations, Namseoul University)
  • Received : 2019.10.01
  • Accepted : 2019.11.11
  • Published : 2019.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Background: Physical therapy has been widely studied in various fields, however, the academic trends and characteristics has not been systematically analyzed. Semantic network analysis is used as an approach for this study. Objective: To explore academic trends and knowledge system in the physiotherapy research in the Journal of International Academy Physical Therapy (J of IAPTR) Study design : Literature review Method: Semantic network analysis was conducted using the titles of 272 articles published in the Journal of IAPTR from 2010 to 2019. Results: Frequency analysis revealed following most frequently used key words; Stroke (27 times), Balance (21 times), Elder (13 times), Forward head posture (FHP, 11 times), Muscle activity (9 times). The relationship between the presented keywords is divided into six subgroups (FHP and pain, walk and quality, elder and balance, stroke and apoptosis, muscle strength and function) according to their correlation and frequency to be used together. Conclusion: The study is considered to be of help to researchers who want to identify research trends in physiotherapy.

Keywords

References

  1. https://www.wcpt.org/what-is-physical-therapy. About WCPT what is physical therapy. World Confederation for Physical Therapy. 2016.
  2. Ju JY, Kim HS. The Effect of Home Visiting Physical Therapy Based on Wellness on ADL, Depressive Disorder, Quality of Life in Chronic Stroke Patients. J Korea Entertain Ind Assoc. 2015;9(4):423-30. https://doi.org/10.21184/jkeia.2015.12.9.4.423
  3. Koh MS, Jeon, HS, Hwang SJ. Effects of Group Task-Oriented Circuit Training on Motor Function, ADLs and Quality of Life in Individuals with Chronic Stroke : A Case Study. J Korea Acad Indus Coop Soc. 2015;16(3):1894-903. https://doi.org/10.5762/KAIS.2015.16.3.1894
  4. Park SJ, Song KS, Lee HJ, et al. Development and Usability Evaluation of a Functional Game Based on Inertial Sensor for Knee Rehabilitation in Total Knee Arthroplasty Patient. J Rehabil Welf Eng & Assist Technol. 2019;13(2):127-33.
  5. Lee SS. A Content Analysis of Journal Articles Using the Language Network Analysis Methods. J Korean Soci for Infor Manage. 2014;31(4):49-68. https://doi.org/10.3743/KOSIM.2014.31.4.049
  6. Kim HJ. A Study on Analysis of the Research Trend and the Knowledge Structure of Music Education by Analyzing Keyword Network. Res in Music Pedag. 2018;19(1):1-30.
  7. Zhao PS, Lee JH, Lee MH. Characterizing the Structure of China's Passenger Railway Network Based on the Social Network Analysis(SNA) Approaches : Focused on the 2008, 2013, and 2018 Railway Service Data, Respectively. J Korea Conten Assoc. 2019;10:685-97.
  8. Noh JA. Analysis of Research Trends related to Young Children with Developmental Delays through Keyword Network Analysis. J Spec Child Educ. 2019;21(1):246-69.
  9. Park HW, L Leydesdorff. Understanding the KrKwic: A computer program for the analysis of Korean text. J Korean Data Anal Soc. 2004;6(5):1377-88.
  10. Lee SJ, JH Choi, HW Kim. Semantic network analysis on the MIS research keywords: APJIS and MIS Quarterly 2005-2009. Asia Pac J Inf Syst. 2010;20(4):25-51. https://doi.org/10.1111/j.1365-2575.2008.00324.x
  11. Borgatti SP, Everett MG, Freeman LC. Ucinet for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies; 2002.
  12. Freeman LC. Graphic techniques for exploring social network data. Carrington PJ, Scott J, Wasserman S, eds. Cambridge: Cambridge University Press; 2005:248-69.
  13. Kamada T, Kawai S. An algorithm for drawing general undirected graphs. Inf Process Lett. 1988;31(1):7-15. https://doi.org/10.1016/0020-0190(89)90102-6
  14. Newman ME. Fast algorithm for detecting community structure in networks. Phys Rev E Stat Nonlin Soft Matter Phys. 2004;69(6):1-5.
  15. Im JH, Lee KS, Kim KY, et al. Follow-up study on mortality in Korean stroke patients. J Korean Med Assoc. 2011;54(11):1199-208. https://doi.org/10.5124/jkma.2011.54.11.1199
  16. Dworzynski K, Ritchie G, Playford ED. Stroke rehabilitation: long-term rehabilitation after stroke. Clin Med (Lond). 2015;15(5):461-4. https://doi.org/10.7861/clinmedicine.15-5-461
  17. Eitivipart AC, Viriyarojanakul S, Redhead L. Musculoskeletal disorder and pain associated with smartphone use: A systematic review of biomechanical evidence. Hong Kong Physiother J. 2018;38(2):77-90 https://doi.org/10.1142/S1013702518300010
  18. Hamilton MT, Healy GN, Dunstan DW, et al. Too little exercise and too much sitting: inactivity physiology and the need for new recommendations on sedentary behavior. Curr cardiovasc Risk Rep. 2008;2(4);292-8. https://doi.org/10.1007/s12170-008-0054-8
  19. Nejati P, Lotfian S, Moezy A, et al. The study of correlation between forward head posture and neck pain in Iranian office workers. Int J Occup Med Environ Health. 2015;28(2):295-303.
  20. Mahmoud NF, Hassan KA, Abdelmajeed SF, et al. The Relationship Between Forward Head Posture and Neck Pain: a Systematic Review and Meta-Analysis. Curr Rev Musculoskelet Med. 2019.