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  • 标题:Analysis of Cyberincivility in Posts by Health Professions Students: Descriptive Twitter Data Mining Study
  • 本地全文:下载
  • 作者:De Gagne, Jennie C ; Cho, Eunji ; Yamane, Sandra S
  • 期刊名称:JMIR Medical Education
  • 电子版ISSN:2369-3762
  • 出版年度:2021
  • 卷号:7
  • 期号:2
  • 页码:e28805
  • DOI:10.2196/28805
  • 语种:English
  • 出版社:JMIR Publications Inc., Toronto, Canada
  • 摘要:BackgroundHealth professions students use social media to communicate with other students and health professionals, discuss career plans or coursework, and share the results of research projects or new information. These platforms allow students to share thoughts and perceptions that are not disclosed in formal education settings. Twitter provides an excellent window through which health professions educators can observe students’ sociocultural and learning needs. However, despite its merits, cyberincivility on Twitter among health professions students has been reported. Cyber means using electronic technologies, and incivility is a general term for bad manners. As such, cyberincivility refers to any act of disrespectful, insensitive, or disruptive behavior in an electronic environment. ObjectiveThis study aims to describe the characteristics and instances of cyberincivility posted on Twitter by self-identified health professions students. A further objective of the study is to analyze the prevalence of tweets perceived as inappropriate or potentially objectionable while describing patterns and differences in the instances of cyberincivility posted by those users. MethodsWe used a cross-sectional descriptive Twitter data mining method to collect quantitative and qualitative data from August 2019 to February 2020. The sample was taken from users who self-identified as health professions students (eg, medicine, nursing, dental, pharmacy, physician assistant, and physical therapy) in their user description. Data management and analysis were performed with a combination of SAS 9.4 for descriptive and inferential statistics, including logistic regression, and NVivo 12 for descriptive patterns of textual data. ResultsWe analyzed 20 of the most recent tweets for each account (N=12,820). A total of 639 user accounts were analyzed for quantitative analysis, including 280 (43.8%) medicine students and 329 (51.5%) nursing students in 22 countries: the United States (287/639, 44.9%), the United Kingdom (197/639, 30.8%), unknown countries (104/639, 16.3%), and 19 other countries (51/639, 8.0%). Of the 639 accounts, 193 (30.2%) were coded as having instances of cyberincivility. Of these, 61.7% (119/193), 32.6% (63/193), and 5.7% (11/193) belonged to students in nursing, medicine, and other disciplines, respectively. Among 502 instances of cyberincivility identified from 641 qualitative analysis samples, the largest categories were profanity and product promotion. Several aggressive or biased comments toward other users, politicians, or certain groups of people were also found. ConclusionsCyberincivility is a multifaceted phenomenon that must be considered in its complexity if health professions students are to embrace a culture of mutual respect and collaboration. Students’ perceptions and reports of their Twitter experiences offer insights into behavior on the web and the evolving role of cyberspace, and potentially problematic posts provide opportunities for teaching digital professionalism. Our study indicates that there is a continued need to provide students with guidance and training regarding the importance of maintaining a professional persona on the web.
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