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 in | Journal of exercise rehabilitation Vol. 16; no. 1; pp. 69 - 77 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Korea (South)
Korean Society of Exercise Rehabilitation
01.02.2020
한국운동재활학회 |
Subjects | |
Online Access | Get full text |
ISSN | 2288-176X 2288-1778 |
DOI | 10.12965/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. |
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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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Cites_doi | 10.1186/s13098-015-0106-4 10.1016/j.sbspro.2013.05.053 10.3390/ijerph16244972 10.1007/s11192-005-0257-4 10.12965/jer.150223 10.12965/jer.1836632.316 10.3389/fpsyg.2019.02145 10.1038/sj.sc.3101389 10.1007/s00223-019-00623-z 10.1016/j.eiar.2014.09.012 10.1016/j.vaccine.2017.05.052 10.1016/S0140-6736(15)60461-5 10.12965/jer.130081 10.1123/jpah.2017-0502 10.1038/s41598-018-23932-z 10.1137/16M1066142 10.1080/02701367.2000.10608893 10.1093/gerona/glr010 10.1016/j.dhjo.2017.03.006 10.1186/s13643-017-0597-1 10.12965/jer.1632590.295 10.12965/jer.1734922.461 10.2466/06.13.PMS.114.2.693-697 10.12965/jer.1836418.209 10.1123/jpah.2019-0350 10.1016/j.compbiomed.2019.103332 10.1093/gerona/gln001 10.12965/jer.1836228.114 10.1371/journal.pone.0077455 10.1007/s11914-015-0274-z 10.12965/jer.1836176.088 10.1016/j.jesf.2019.08.003 |
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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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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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