Literature DB >> 17678683

The image of the nurse on the internet.

Beatrice J Kalisch1, Suzanne Begeny, Sue Neumann.   

Abstract

The media image of the nurse is a source of concern because of its impact on: recruitment into the profession; the decisions of policy makers who enact legislation that defines the scope and financing of nursing services; the use of nursing services by consumers; and the self-image of the nurse. This article reports on the results of a study of the image of nursing on the Internet utilizing content analysis methodology. A total of 144 Websites were content-analyzed in 2001 and 152 in 2004. Approximately 70% of the Internet sites showed nurses as intelligent and educated and 60% as respected, accountable, committed, competent, and trustworthy. Nurses were also shown as having specialized knowledge and skills in 70% (2001) and 62% (2004) of the Websites. Scientific/research-oriented, competent, sexually promiscuous, powerful, and creative/innovative increased from 2001-2004 while committed, attractive/well groomed, and authoritative images decreased. Doctoral-prepared nurses were evident in 19% of the Websites in 2001 and doubled in 2004. The results of this study suggest that there are important opportunities to use the Internet to improve the image of the nurse.

Mesh:

Year:  2007        PMID: 17678683     DOI: 10.1016/j.outlook.2006.09.002

Source DB:  PubMed          Journal:  Nurs Outlook        ISSN: 0029-6554            Impact factor:   3.250


  3 in total

1.  Does student orientation improve nursing image and positively influence the enrolment of nursing students in the University? An observational study.

Authors:  Ivan Rubbi; Gianandrea Pasquinelli; Valeria Cremonini; Flavio Fortunato; Lorenzo Gatti; Federica Lepanto; Giovanna Artioli; Antonio Bonacaro
Journal:  Acta Biomed       Date:  2019-07-08

2.  Chinese nurses' self-expression media image during COVID-19 pandemic: A qualitative media image analysis.

Authors:  Huili Cao; Yangjie Chen; Xingyue He; Yejun Song; Qiaohong Wang; Hui Yang
Journal:  Nurs Open       Date:  2022-01-14

3.  The Drivers of Acceptance of Artificial Intelligence-Powered Care Pathways Among Medical Professionals: Web-Based Survey Study.

Authors:  Lisa Cornelissen; Claudia Egher; Vincent van Beek; Latoya Williamson; Daniel Hommes
Journal:  JMIR Form Res       Date:  2022-06-21
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.