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Äڷγª19 Ãʱâ À¯Çà ½Ã±â¿¡¼­ ´ëÇлýÀÇ °¨¿°¿¹¹æÇàÀ§ ¼öÇ൵¿¡ ¹ÌÄ¡´Â ¿µÇâ ¿äÀÎ

Factors Influencing University Students¡¯ Infection Prevention Behaviors Compliance in the Early Stage of COVID-19

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KMID : 0608420210340030190
ÀÌÇöÁÖ ( Lee Hyun-Ju ) - Woosuk University College of Nursing

¹ÚÁøÈñ ( Park Jin-Hee ) - Woosuk University College of Nursing
±èÁöÇý ( Kim Ji-Hye ) - Woosuk University College of Nursing
°­Çª¸§ ( Kang Pu-Rum ) - Woosuk University College of Nursing

Abstract

¸ñÀû: º» ¿¬±¸ÀÇ ¸ñÀûÀº Äڷγª19 Ãʱâ À¯Çà ½Ã±â¿¡¼­ ´ëÇлýÀÇ °¨¿°¿¹¹æÇàÀ§ ¼öÇ൵¿¡ ¿µÇâÀ» ¹ÌÄ¡´Â ¿äÀÎÀ» ÆľÇÇϱâ À§ÇÔÀÌ´Ù.
¹æ¹ý: º» ¿¬±¸´Â ÀÏ°³ Á¾ÇÕ´ëÇп¡ ÀçÇÐ ÁßÀÎ ´ëÇлý 261¸íÀ» ´ë»óÀ¸·Î 2020³â 7¿ù 29ÀϺÎÅÍ 8¿ù 2ÀϱîÁö ¿Â¶óÀÎÀ» ÅëÇØ ¼³¹®Á¶»ç¸¦ ½Ç½ÃÇÏ¿´´Ù. ¼öÁýµÈ ÀÚ·á´Â SPSS 24.0À» ÀÌ¿ëÇÏ¿© ºóµµºÐ¼®, ±â¼úÅë°è, t-test, ANOVA, »ó°ü°ü°è, ´ÙÁßȸ±ÍºÐ¼®À» ½ÃÇàÇÏ¿´´Ù.

°á°ú: ´ëÇлýÀÇ Äڷγª19¿¡ °ü·Ã À§ÇèÀνÄÀÇ Æò±Õ Á¡¼ö´Â 3.80Á¡, °Ç°­À§±â¼ÒÅë Æò±Õ Á¡¼ö´Â 3.92Á¡, °¨¿°¿¹¹æÇàÀ§ È¿´É°¨ Æò±Õ Á¡¼ö´Â 4.42Á¡, °¨¿°¿¹¹æÇàÀ§ ¼öÇ൵ Æò±Õ Á¡¼ö´Â 4.54Á¡À̾ú´Ù. °¨¿°¿¹¹æÇàÀ§ ¼öÇ൵¿¡ ¿µÇâÀ» ¹ÌÄ¡´Â ¿äÀÎÀº °¨¿°¿¹¹æÇàÀ§ È¿´É°¨(¥â=.48 p<.001), °Ç°­À§±â¼ÒÅë(¥â=.16, p=.003), ÁÖ°üÀû °Ç°­»óÅÂ(¥â=.12, p=.015), ´Ü°ú´ëÇÐ À¯Çü(¥â=.11, p=.041) À̾ú´Ù.

°á·Ð: ´ëÇлýÀÇ Äڷγª19 °ü·Ã °¨¿°¿¹¹æÇàÀ§ ¼öÇ൵ Çâ»óÀ» À§ÇÏ¿© ½ÅÁ¾ °¨¿°º´°ú °¨¿°¿¹¹æÇàÀ§ÀÇ È¿°ú¿¡ ´ëÇÑ Á¤È®ÇÑ Áö½Ä°ú Á¤º¸ Àü´Þ¿¡ ÃÊÁ¡À» µÐ ÁßÀç Á¦°øÀÌ °í·ÁµÇ¾î¾ß ÇÒ °ÍÀÌ´Ù.

Purpose: The study aims to identify factors that influence university students¡¯ compliance with infection prevention behaviors in the early stage of COVID-19.

Methods: A survey was conducted online from July 29 to August 2, 2020, involving 261 students enrolled in general universities. Frequency analysis, descriptive statistics, t-test, ANOVA, correlation, and multiple regression analysis were carried out on the collected data using SPSS 24.0.

Results: The average score of university students¡¯ risk perception of COVID-19 was 3.80, while the average score of health risk communication was 3.92. The average score of efficacy beliefs was 4.42 and the average score of practicing infection prevention behaviors was 4.54. Factors influencing the level of infection prevention behaviors were efficacy of preventive behaviors (¥â=.48 p<.001), health risk communication (¥â=.16, p=.003), subjective health status (¥â=.12, p=.015), and the type of college (¥â=.11, p=.041).

Conclusion: In order to improve college students' infection prevention behaviors related to COVID-19, consideration should be given to providing interventions that focus on accurate knowledge and dissemination of accurate information about new infectious diseases and effectiveness of infection preventive behaviors.
KeyWords
Äڷγª19, À§ÇèÀνÄ, °Ç°­À§±â¼ÒÅë, °¨¿°¿¹¹æÇàÀ§ È¿´É°¨, °¨¿°¿¹¹æÇà À§ ¼öÇ൵
COVID-19, Risk perception, Health risk communication, Efficacy belief, Preventive behaviors
¿ø¹® ¹× ¸µÅ©¾Æ¿ô Á¤º¸
µîÀçÀú³Î Á¤º¸
ÇмúÁøÈïÀç´Ü(KCI)