A Questionnaire Survey on the Difficulties Faced by Supervisors during Clinical Training: An Objective Analysis Using Text Mining

[Purpose] To objectively examine the guidance-related difficulties faced by clinical training supervisors (supervisors). [Participants and Methods] We conducted a questionnaire survey, asking physical therapists of 42 facilities to voluntarily respond. [Results] The most frequent difficulty faced by...

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Published in:Rigaku ryoho kagaku 2019, Vol.34(2), pp.205-209
Main Authors: NINOMIYA, Shogo, YOSHIMURA, Osamu, KUSUMOTO, Masazumi, YOSHIDA, Yuichi, TASAKI, Shuichiro
Format: Article
Language:Japanese
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clinical training supervisors
physical therapy education
Supervisors
text mining
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container_issue 2
container_start_page 205
container_title Rigaku ryoho kagaku
container_volume 34
creator NINOMIYA, Shogo
YOSHIMURA, Osamu
KUSUMOTO, Masazumi
YOSHIDA, Yuichi
TASAKI, Shuichiro
description [Purpose] To objectively examine the guidance-related difficulties faced by clinical training supervisors (supervisors). [Participants and Methods] We conducted a questionnaire survey, asking physical therapists of 42 facilities to voluntarily respond. [Results] The most frequent difficulty faced by the respondents was , followed by and , in this order. In text mining-based analysis of their free descriptions, the most frequent word was “students”, followed by “guidance”, “reports”, “understanding”, and “training”, in this order. The results also revealed a strong correlation with frequent words that were characteristic and related to reporting guidance. Furthermore, geometric figures outlining the relationships among words were created. [Conclusion] It may be necessary to clarify the difficulties faced by supervisors, in order to improve the quality of physical therapy education.
doi_str_mv 10.1589/rika.34.205
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subjects clinical training supervisors
physical therapy education
Supervisors
text mining
title A Questionnaire Survey on the Difficulties Faced by Supervisors during Clinical Training: An Objective Analysis Using Text Mining
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