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³×Æ®¿öÅ© ºÐ¼®°ú ÅäÇÈ ¸ðµ¨¸µÀ» È°¿ëÇÑ ±¹³» ÀÓ»ó °£È£»çÀÇ °æÇè°ú °íÃæ ºÐ¼®: ¿Â¶óÀÎ Ä¿¹Â´ÏƼ °Ô½Ã±ÛÀ» Áß½ÉÀ¸·Î

Exploring Nurses¡¯ Experience and Grievance: Network Analysis and Topic Modeling using a Social Networking Service

°£È£ÇàÁ¤ÇÐȸÁö 2021³â 27±Ç 3È£ p.169 ~ 180
KMID : 0614820210270030169
ÁöÇöÁÖ ( Ji Hyun-Ju ) - Yonsei University Graduate School Department of Nursing

ÀӾƸ§ ( Lim A-Rum ) - Yonsei University Graduate School Department of Nursing
À̽ÂÀº ( Lee Seung-Eun ) - Yonsei University College of Nursing

Abstract

¸ñÀû: º» ¿¬±¸´Â °£È£»çµéÀÌ ÀÌ¿ëÇÏ´Â ¿Â¶óÀÎ Ä¿¹Â´ÏƼ °Ô½Ã±ÛÀ» ³×Æ®¿öÅ© ºÐ¼®°ú ÅäÇÈ ¸ðµ¨¸µ ±â¹ýÀ¸·Î ºÐ¼®ÇÏ¿© ±¹³» ÀÓ»ó °£È£»çµéÀÇ °æÇè°ú °íÃæÀ» Ž»öÇÏ°íÀÚ ÁøÇàµÇ¾ú´Ù.

¿¬±¸¹æ¹ý: º» ¿¬±¸ÀÇ ÁøÇàÀýÂ÷´Â ÀÚ·áÀÇ ÃßÃâ, ÅؽºÆ® Á¤Á¦, ½Ã°¢È­ÀÇ 3´Ü°è·Î ÀÌ·ïÁ³´Ù. ¸ÕÀú, À¥ ½ºÅ©·¡ÇÎÀ» ÀÌ¿ëÇÏ¿© ±¹³» ÃÖ´ë ±Ô¸ðÀÇ °£È£»ç ¿Â¶óÀÎ Ä¿¹Â´ÏƼÀÎ ¡¸³Ê½ºÄÉÀÔ¡¹¿¡ 2018³â 6¿ùºÎÅÍ 2019³â 5¿ù±îÁö ÀÛ¼ºµÈ °Ô½Ã±ÛÀ» ÃßÃâÇÏ¿´´Ù. ÅؽºÆ® Á¤Á¦ °úÁ¤¿¡¼­´Â °Ô½Ã±ÛÀ» ¾îÀý ´ÜÀ§·Î ºÐ¸®ÇÏ°í, ºÐ¼®¿¡ È°¿ëÇÒ ¸í»ç¸¸ Á¤¸®ÇÏ¿´´Ù. ½Ã°¢È­ °úÁ¤¿¡¼­´Â µ¿½Ã ÃâÇö ³×Æ®¿öÅ© ºÐ¼®°ú ÅäÇÈ ¸ðµ¨¸µ ±â¹ýÀÌ ÀÌ¿ëµÇ¾ú´Ù.

¿¬±¸°á°ú: ÃÑ 13,200°ÇÀÇ °Ô½Ã±ÛÀÌ ºÐ¼®¿¡ È°¿ëµÇ¾ú´Ù. µ¿½Ã ÃâÇö ³×Å©¿öÅ©ÀÇ Á߽ɿ¡´Â ½Å±Ô°£È£»ç, º´µ¿, °æ·Â, ÀÌÁ÷, °í¹Î µîÀÇ Å°¿öµå°¡ À§Ä¡ÇÏ¿´´Ù. ÅäÇÈ ¸ðµ¨¸µ ºÐ¼® °á°ú¿¡¼­´Â 4°¡Áö ÅäÇÈÀÌ µµÃâµÇ¾ú´Ù. (1) °úµµÇÑ ¾÷¹«·® µî °£È£ ¾÷¹«¿Í °ü·ÃµÈ ¾î·Á¿òÀÌ Æ÷ÇÔµÈ ¡®ÀÓ»ó ¾÷¹«¿Í °ü·ÃµÈ °íÃ桯, (2) »çÁ÷¿¡ ´ëÇÑ Á¶¾ðÀ» ±¸ÇÏ´Â ³»¿ëÀÌ Æ÷ÇÔµÈ ¡®»çÁ÷¿¡ °üÇÑ °í¹Î¡¯, (3) ƯÁ¤ º´¿øÀÇ ±Ù¹« ȯ°æ¿¡ ´ëÇÑ Á¤º¸¸¦ ±¸ÇÏ´Â ¡®Ãë¾÷/ÀçÃë¾÷À» À§ÇÑ Á¤º¸ ¼öÁý¡¯, (4) °£È£»çÀÇ ¾÷¹« ȯ°æ °³¼±À» À§ÇÑ Á¶Á÷ ÇൿÀ» ¿ä±¸ÇÏ´Â ¡®Á¶Á÷Àû Çൿ Ã˱¸¡¯

°á·Ð: ÀÓ»ó °£È£»çµéÀº ¿Â¶óÀÎ Ä¿¹Â´ÏƼ¸¦ ÅëÇØ °æÇèÀ» ³ª´­ »Ó ¾Æ´Ï¶ó Á¶¾ðÀ̳ª Á¤º¸¸¦ ¾ò°íÀÚ ÇÏ°í, Á¶Á÷Àû ÇൿÀ» Ã˱¸Çϱ⵵ ÇÑ´Ù. °£È£»ç ¿Â¶óÀÎ Ä¿¹Â´ÏƼÀÇ °Ô½Ã±ÛÀ» ºÐ¼®ÇÏ´Â °ÍÀº °£È£»çµéÀÇ °æÇè°ú °ü½É»ç¸¦ ÆľÇÇϴµ¥ È¿°úÀûÀÏ ¼ö ÀÖÀ¸¹Ç·Î º´¿øÀ̳ª °£È£Àü¹®´ÜüÀÇ Á¤Ã¥ ¹æÇ⼺À» ¼³Á¤ÇÏ´Â µ¥¿¡ µµ¿òÀÌ µÉ ¼ö ÀÖÀ» °ÍÀÌ´Ù

Purpose: To describe clinical nurses¡¯ experience and grievance in an online community using a co-occurrence networkand topic modeling.

Methods: We analyzed posts from Nurscape, which is the largest online community for nursesin Korea. After extracting posts using web scrapping, text preprocessing was done to detect nouns. In a visualizationphase, co-occurrence network analysis and latent dirichlet allocation-based topic modeling were applied.

Results:A total of 13,200 posts were analyzed. The co-occurrence network¡¯s core keywords were newly graduate nurse,general ward, career, turnover, and grievance. The topic modeling showed four topics: (1) ¡®Clinical practice-relateddifficulties¡¯ described clinical hardships, such as the heavy workload of nurses; (2) ¡®Concerns about resignation¡¯incorporated keywords asking for advice on resignation; (3) ¡®Searching for information on employment/reemployment¡¯focused on the working conditions or working climate of a specific hospital; and (4) ¡®Organizational action call¡¯ capturedthe voices urging organized actions to improve nurses¡¯ work environment.

Conclusion: Clinical nurses shareexperiences through the online community and seek advice or information and urge organizational action. Professional nursing organizations should identify and deal with problems that nurses are currently facing. The resultsof this study can contribute to establishing the policy direction of nursing organizations.
KeyWords
°£È£»ç, ¼Ò¼È ³×Æ®¿öÅ©, µ¥ÀÌÅÍ ¸¶ÀÌ´×, °æÇè, °íÃæ
Nurses, Social networking, Data mining, Experience, Grievance
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ÇмúÁøÈïÀç´Ü(KCI) KoreaMed