An exploration of the knowledge structure in studies on old people physical activities in Journal of Exercise Rehabilitation : by semantic network analysis

Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old peo-ple. This research was intended to analyze 51 research papers pub-lished in the Journal of Exercise Rehabilitation (JER) through semantic network analysis. The...

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Published inJournal of exercise rehabilitation Vol. 16; no. 1; pp. 69 - 77
Main Authors Jeon, Sang-Wan, Kim, Ji-Youn
Format Journal Article
LanguageEnglish
Published Korea (South) Korean Society of Exercise Rehabilitation 01.02.2020
한국운동재활학회
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ISSN2288-176X
2288-1778
DOI10.12965/jer.2040010.005

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Abstract Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old peo-ple. This research was intended to analyze 51 research papers pub-lished in the Journal of Exercise Rehabilitation (JER) through semantic network analysis. The subjects of the study were the keywords that the authors of each paper used in journal search sites from 2013 to 2019. The present researcher analyzed the frequency, density, and centrality of the keywords of the indicators through semantic network analysis and then visualized them on the basis of findings using UCINET6 and the NetDraw program. Also, the researcher classified the hidden clus-ters by CONCOR (Convergence of iterated Correlations) analysis, which is a kind of cluster analysis. As a result, it was found that the keyword with the highest frequency was “exercise,” followed by “cognition, “physical-activity,” “old-women,” “Korean,” “fall,” and “training.” It was also found that most of the high-frequency keywords, such as “ex-ercise,” “cognition,” “old-women,” “program” and “depression” had high centrality. These keywords were classified into four clusters: (a) mental health research, (b) physical health research, (c) social behavior research, and (d) leisure efficacy research. This suggests that the old people-related research papers published in the JER have derived ef-fective methods of maintaining physical and mental health using scien-tific exercise programs, and especially address the effects of exercise intervention for old women.
AbstractList Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old people. This research was intended to analyze 51 research papers published in the (JER) through semantic network analysis. The subjects of the study were the keywords that the authors of each paper used in journal search sites from 2013 to 2019. The present researcher analyzed the frequency, density, and centrality of the keywords of the indicators through semantic network analysis and then visualized them on the basis of findings using UCINET6 and the NetDraw program. Also, the researcher classified the hidden clusters by CONCOR (Convergence of iterated Correlations) analysis, which is a kind of cluster analysis. As a result, it was found that the keyword with the highest frequency was "exercise," followed by "cognition, "physicalactivity," "old-women," "Korean," "fall," and "training." It was also found that most of the high-frequency keywords, such as "exercise," "cognition," "old-women," "program" and "depression" had high centrality. These keywords were classified into four clusters: (a) mental health research, (b) physical health research, (c) social behavior research, and (d) leisure efficacy research. This suggests that the old people-related research papers published in the JER have derived effective methods of maintaining physical and mental health using scientific exercise programs, and especially address the effects of exercise intervention for old women.
Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old people. This research was intended to analyze 51 research papers published in the Journal of Exercise Rehabilitation (JER) through semantic network analysis. The subjects of the study were the keywords that the authors of each paper used in journal search sites from 2013 to 2019. The present researcher analyzed the frequency, density, and centrality of the keywords of the indicators through semantic network analysis and then visualized them on the basis of findings using UCINET6 and the NetDraw program. Also, the researcher classified the hidden clusters by CONCOR (Convergence of iterated Correlations) analysis, which is a kind of cluster analysis. As a result, it was found that the keyword with the highest frequency was “exercise,” followed by “cognition, “physicalactivity,” “old-women,” “Korean,” “fall,” and “training.” It was also found that most of the high-frequency keywords, such as “exercise,” “cognition,” “old-women,” “program” and “depression” had high centrality. These keywords were classified into four clusters: (a) mental health research, (b) physical health research, (c) social behavior research, and (d) leisure efficacy research. This suggests that the old people-related research papers published in the JER have derived effective methods of maintaining physical and mental health using scientific exercise programs, and especially address the effects of exercise intervention for old women.
Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old peo-ple. This research was intended to analyze 51 research papers pub-lished in the Journal of Exercise Rehabilitation (JER) through semantic network analysis. The subjects of the study were the keywords that the authors of each paper used in journal search sites from 2013 to 2019. The present researcher analyzed the frequency, density, and centrality of the keywords of the indicators through semantic network analysis and then visualized them on the basis of findings using UCINET6 and the NetDraw program. Also, the researcher classified the hidden clus-ters by CONCOR (Convergence of iterated Correlations) analysis, which is a kind of cluster analysis. As a result, it was found that the keyword with the highest frequency was “exercise,” followed by “cognition, “physical-activity,” “old-women,” “Korean,” “fall,” and “training.” It was also found that most of the high-frequency keywords, such as “ex-ercise,” “cognition,” “old-women,” “program” and “depression” had high centrality. These keywords were classified into four clusters: (a) mental health research, (b) physical health research, (c) social behavior research, and (d) leisure efficacy research. This suggests that the old people-related research papers published in the JER have derived ef-fective methods of maintaining physical and mental health using scien-tific exercise programs, and especially address the effects of exercise intervention for old women.
Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old people. This research was intended to analyze 51 research papers published in the Journal of Exercise Rehabilitation (JER) through semantic network analysis. The subjects of the study were the keywords that the authors of each paper used in journal search sites from 2013 to 2019. The present researcher analyzed the frequency, density, and centrality of the keywords of the indicators through semantic network analysis and then visualized them on the basis of findings using UCINET6 and the NetDraw program. Also, the researcher classified the hidden clusters by CONCOR (Convergence of iterated Correlations) analysis, which is a kind of cluster analysis. As a result, it was found that the keyword with the highest frequency was "exercise," followed by "cognition, "physicalactivity," "old-women," "Korean," "fall," and "training." It was also found that most of the high-frequency keywords, such as "exercise," "cognition," "old-women," "program" and "depression" had high centrality. These keywords were classified into four clusters: (a) mental health research, (b) physical health research, (c) social behavior research, and (d) leisure efficacy research. This suggests that the old people-related research papers published in the JER have derived effective methods of maintaining physical and mental health using scientific exercise programs, and especially address the effects of exercise intervention for old women.Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old people. This research was intended to analyze 51 research papers published in the Journal of Exercise Rehabilitation (JER) through semantic network analysis. The subjects of the study were the keywords that the authors of each paper used in journal search sites from 2013 to 2019. The present researcher analyzed the frequency, density, and centrality of the keywords of the indicators through semantic network analysis and then visualized them on the basis of findings using UCINET6 and the NetDraw program. Also, the researcher classified the hidden clusters by CONCOR (Convergence of iterated Correlations) analysis, which is a kind of cluster analysis. As a result, it was found that the keyword with the highest frequency was "exercise," followed by "cognition, "physicalactivity," "old-women," "Korean," "fall," and "training." It was also found that most of the high-frequency keywords, such as "exercise," "cognition," "old-women," "program" and "depression" had high centrality. These keywords were classified into four clusters: (a) mental health research, (b) physical health research, (c) social behavior research, and (d) leisure efficacy research. This suggests that the old people-related research papers published in the JER have derived effective methods of maintaining physical and mental health using scientific exercise programs, and especially address the effects of exercise intervention for old women.
Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old people. This research was intended to analyze 51 research papers published in the Journal of Exercise Rehabilitation (JER) through semantic network analysis. The subjects of the study were the keywords that the authors of each paper used in journal search sites from 2013 to 2019. The present researcher analyzed the frequency, density, and centrality of the keywords of the indicators through semantic network analysis and then visualized them on the basis of findings using UCINET6 and the NetDraw program. Also, the researcher classified the hidden clusters by CONCOR (Convergence of iterated Correlations) analysis, which is a kind of cluster analysis. As a result, it was found that the keyword with the highest frequency was “exercise,” followed by “cognition, “physical-activity,” “old-women,” “Korean,” “fall,” and “training.” It was also found that most of the high-frequency keywords, such as “exercise,” “cognition,” “old-women,” “program” and “depression” had high centrality. These keywords were classified into four clusters: (a) mental health research, (b) physical health research, (c) social behavior research, and (d) leisure efficacy research. This suggests that the old people-related research papers published in the JER have derived effective methods of maintaining physical and mental health using scientific exercise programs, and especially address the effects of exercise intervention for old women. KCI Citation Count: 1
Author Jeon, Sang-Wan
Kim, Ji-Youn
AuthorAffiliation 1 Exercise Rehabilitation Convergence Institute, Gachon University, Incheon, Korea
2 Department of Exercise Rehabilitation & Welfare, College of Health Science, Gachon University, Incheon, Korea
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Keywords Journal of Exercise Rehabilitation
Semantic network analysis
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Knowledge structure
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Snippet Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old peo-ple. This research...
Physical activity, a key component of maintaining health, is becoming an essential alternative in reducing medical expenses for the old people. This research...
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심리과학
TableOfContents Abstract INTRODUCTION MATERIALS AND METHODS Subjects for analysis and data collection Analytical method Data integrity RESULTS Extraction of keywords Sematic network between keywords DISCUSSION CONFLICT OF INTEREST ACKNOWLEDGMENTS REFERENCES
Title An exploration of the knowledge structure in studies on old people physical activities in Journal of Exercise Rehabilitation : by semantic network analysis
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