Jackie Zhanbiao Li , Janet Yuen-Ha Wong , Doreen Wing-Han Au , Yiyao Chen , Yingqian Lao , Mengmeng Zhang
{"title":"社交媒体报道对护士工作满意度的影响:横断面调查","authors":"Jackie Zhanbiao Li , Janet Yuen-Ha Wong , Doreen Wing-Han Au , Yiyao Chen , Yingqian Lao , Mengmeng Zhang","doi":"10.1016/j.chbr.2024.100529","DOIUrl":null,"url":null,"abstract":"<div><div>This study aims to examine the impact of social media reports (SMR) on nurses' job satisfaction (NJS) and investigate the moderating effect of nurse manager overconfidence (NMO). Focusing on nurses in tertiary public hospitals in Guilin, China, we constructed an analytical dataset using survey data from January to June 2024 and social media comments collected through web scraping technology. Results reveal a significant positive correlation between SMR and NJS, indicating that increases in social media reports are associated with higher job satisfaction among nurses. However, when NMO acts as a moderating factor, the positive effect of SMR on NJS is attenuated, suggesting that overconfidence among nurse managers may diminish the influence of social media feedback. Furthermore, the study employs robustness tests, including the Replace Variables Method, Entropy Balancing Method, Instrumental Variable Method (IV-2LS), and Other Methods, effectively addressing endogeneity issues and confirming the reliability of these findings. This research offers theoretical support for enhancing hospital management and extends the literature on the moderating role of managerial characteristics on job satisfaction, providing practical insights for promoting high-quality hospital development.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100529"},"PeriodicalIF":4.9000,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of social media reports on nurses’ job satisfaction: A cross-section suvery\",\"authors\":\"Jackie Zhanbiao Li , Janet Yuen-Ha Wong , Doreen Wing-Han Au , Yiyao Chen , Yingqian Lao , Mengmeng Zhang\",\"doi\":\"10.1016/j.chbr.2024.100529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study aims to examine the impact of social media reports (SMR) on nurses' job satisfaction (NJS) and investigate the moderating effect of nurse manager overconfidence (NMO). Focusing on nurses in tertiary public hospitals in Guilin, China, we constructed an analytical dataset using survey data from January to June 2024 and social media comments collected through web scraping technology. Results reveal a significant positive correlation between SMR and NJS, indicating that increases in social media reports are associated with higher job satisfaction among nurses. However, when NMO acts as a moderating factor, the positive effect of SMR on NJS is attenuated, suggesting that overconfidence among nurse managers may diminish the influence of social media feedback. Furthermore, the study employs robustness tests, including the Replace Variables Method, Entropy Balancing Method, Instrumental Variable Method (IV-2LS), and Other Methods, effectively addressing endogeneity issues and confirming the reliability of these findings. This research offers theoretical support for enhancing hospital management and extends the literature on the moderating role of managerial characteristics on job satisfaction, providing practical insights for promoting high-quality hospital development.</div></div>\",\"PeriodicalId\":72681,\"journal\":{\"name\":\"Computers in human behavior reports\",\"volume\":\"16 \",\"pages\":\"Article 100529\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in human behavior reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2451958824001623\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in human behavior reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451958824001623","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
The impact of social media reports on nurses’ job satisfaction: A cross-section suvery
This study aims to examine the impact of social media reports (SMR) on nurses' job satisfaction (NJS) and investigate the moderating effect of nurse manager overconfidence (NMO). Focusing on nurses in tertiary public hospitals in Guilin, China, we constructed an analytical dataset using survey data from January to June 2024 and social media comments collected through web scraping technology. Results reveal a significant positive correlation between SMR and NJS, indicating that increases in social media reports are associated with higher job satisfaction among nurses. However, when NMO acts as a moderating factor, the positive effect of SMR on NJS is attenuated, suggesting that overconfidence among nurse managers may diminish the influence of social media feedback. Furthermore, the study employs robustness tests, including the Replace Variables Method, Entropy Balancing Method, Instrumental Variable Method (IV-2LS), and Other Methods, effectively addressing endogeneity issues and confirming the reliability of these findings. This research offers theoretical support for enhancing hospital management and extends the literature on the moderating role of managerial characteristics on job satisfaction, providing practical insights for promoting high-quality hospital development.