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±è¿¬Èñ ( Kim Yeon-Hee ) - ¿ï»ê´ëÇб³ »ê¾÷´ëÇпø
¹®¼º¹Ì ( Moon Seong-Mi ) - ¿ï»ê´ëÇб³ °£È£Çаú ±ÇÀΰ¢ ( Kwon In-Gak ) - ¼º±Õ°ü´ëÇб³ ÀÓ»ó°£È£´ëÇпø ±è±¤¼º ( Kim Kwang-Sung ) - û¿î´ëÇб³ º¸°Çº¹Áö°£È£´ëÇÐ Á¤±ÝÈñ ( Jeong Geum-Hee ) - ÇѸ²´ëÇб³ °£È£´ëÇÐ ½ÅÀº¼÷ ( Shin Eun-Suk ) - Àü³²´ëÇб³º´¿ø ¿ÀÇâ¼ø ( Oh Hyang-Soon ) - ¼øõ´ëÇб³ °£È£Çаú ±è¼öÇö ( Kim Soo-Hyun ) - ÀÎÇÏ´ëÇб³ °£È£Çаú
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Abstract
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¸ñÀû: º» ¿¬±¸´Â 2000³âºÎÅÍ 2017³â±îÁö ÀÓ»ó°£È£¿¬±¸¿¡ °ÔÀçµÈ ³í¹®µéÀÇ ÁÖ¿ä¾î¸¦ ÀÌ¿ëÇÑ ÅؽºÆ® ³×Æ®¿öÅ© ºÐ¼®À» ÅëÇØ ¿¬±¸µ¿ÇâÀ» ÆľÇÇϱâ À§ÇÑ °ÍÀÌ´Ù.
¹æ¹ý: 2000³âºÎÅÍ 2017³â±îÁö ÀÓ»ó°£È£¿¬±¸¿¡ °ÔÀçµÈ 600ÆíÀÇ ³í¹®À» ºÐ¼®ÇÏ¿´´Ù. R Åë°èÇÁ·Î±×·¥À» ÀÌ¿ëÇÏ¿© ÅؽºÆ® ¸¶ÀÌ´×À» ½Ç½ÃÇÏ¿´À¸¸ç ¿µ¹® ÁÖ¿ä¾îµéÀÇ ºóµµ, Á߽ɼº, ±×¸®°í ³×Æ®¿öÅ© µµ½ÄÀ» »êÃâÇÏ¿´´Ù.
°á°ú: 2000³âºÎÅÍ 2009³â±îÁö ºó¹øÇÏ°Ô ³ªÅ¸³ ÁÖ¿ä¾î´Â ¡®°£È£»ç(nurse)¡¯, ¡®ÅëÁõ(pain)¡¯, ¡®ºÒ¾È(anxiety)¡¯, ¡®Áö½Ä(knowledge)¡¯, ¡®Åµµ(attitude)¡¯ µîÀ̾ú´Ù. ¡®ÅëÁõ¡¯, ¡®°£È£»ç¡¯, ±×¸®°í ¡®Áö½Ä¡¯Àº ³ôÀº Á߽ɼºÀ» º¸¿´´Ù. ¡®ÇÇ·Î(fatigue)¡¯ÀÇ °æ¿ì Á߽ɼºÀº ³ô¾ÒÀ¸³ª ºóµµ°¡ ³ôÁö´Â ¾Ê¾Ò´Ù. 2010³âºÎÅÍ 2017³âµµ±îÁö ¡®°£È£»ç¡¯, ¡®Áö½Ä¡¯, ±×¸®°í ¡®ÅëÁõ¡¯Àº ³ôÀº ºóµµ¿Í Á߽ɼºÀ» º¸¿´´Ù. ÀÌ ½Ã±â¿¡´Â ¡®Ç÷¾×Åõ¼®(hemodialysis)¡¯°ú ¡®ÁßȯÀÚ½Ç(intensive care unit)¡¯µµ ³ôÀº ºóµµ¿Í Á߽ɼºÀ» º¸¿´´Ù.
°á·Ð: ¡®°£È£»ç¡¯, ¡®ÅëÁõ¡¯, ¡®Áö½Ä¡¯, ¡®Ç÷¾×Åõ¼®¡¯, ±×¸®°í ¡®ÁßȯÀڽǡ¯°ú °°Àº ÁÖ¿ä¾îµéÀº 2000³âµµºÎÅÍ 2017³âµµ±îÁö ÀÓ»ó°£È£¿¬±¸¿¡ °ÔÀçµÈ ¿¬±¸µéÀÇ µ¿ÇâÀ» ¹Ý¿µÇÏ°í ÀÖ´Ù. ÃßÈÄ ºóµµ ¹× Á߽ɼºÀÌ ³ôÀº ÁÖ¿ä¾îµé °£ÀÇ ¿¬°áÀ» ÅëÇØ ³×Æ®¿öÅ©¸¦ ´õ È®Àå½Ãų ¼ö ÀÖ´Â ¿¬±¸µéÀÌ ÇÊ¿äÇÏ´Ù.
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Purpose: The aim of this study was to identify the research trends of articles published in the Journal of Korean Clinical Nursing Research from 2000 to 2017 by a text network analysis using keywords.
Methods: This study analyzed 600 articles. The R program was used for text mining that extracted frequency, centrality rank, and keyword network.
Results: From 2000 to 2009, keywords with high-frequency were ¡®nurse¡¯, ¡®pain¡¯, ¡®anxiety¡¯, ¡®knowledge¡¯, ¡®attitude¡¯, and so on. ¡®Pain¡¯, ¡®nurse¡¯, and ¡®knowledge¡¯ showed a high centrality. ¡®Fatigue¡¯ showed no high frequency but a high centrality. Keywords such as ¡®nurse¡¯, ¡®knowledge¡¯, and ¡®pain¡¯ also showed high frequency and centrality between 2010 and 2017. ¡®Hemodialysis¡¯ and ¡®intensive care unit¡¯ were added to keywords with high frequency and centrality during the period.
Conclusion: The frequency and centrality of keywords such as ¡®nurse¡¯, ¡®pain¡¯, ¡®knowledge¡¯, ¡®hemodialysis¡¯, and ¡®intensive care unit¡¯ reflect the research trends in clinical nursing between 2000 and 2017. Further studies need to expand the keyword networks by connecting the main keywords.
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KeyWords
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°£È£¿¬±¸, ÀÓ»ó°£È£¿¬±¸, ÅؽºÆ® ³×Æ®¿öÅ© ºÐ¼®, ÁÖ¿ä¾î
Nursing Research, Clinical Nursing Research, Text Network Analysis, Keyword
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¿ø¹® ¹× ¸µÅ©¾Æ¿ô Á¤º¸
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µîÀçÀú³Î Á¤º¸
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