Information Pollution in Virtual Organizations and Solution Suggestions
Abstract views: 117 / PDF downloads: 68
DOI:
https://doi.org/10.5281/zenodo.13151413Keywords:
Information pollution, virtual organization, celiac disease, digital literacy, health information managementAbstract
This study examines the effects of information pollution in virtual organizations on celiac patients and how this pollution can be managed. Virtual organizations are defined as flexible and dynamic structures where geographically dispersed individuals coordinate through digital communication tools. Information pollution refers to the issue of making access to accurate and reliable information difficult due to the spread of false, misleading, or incomplete information. The study identifies that while the internet and social media platforms are primary sources for celiac patients to access information, doubts about the accuracy of the information on these platforms make it difficult for patients to obtain correct information.
Using qualitative analysis methods, themes such as lack of information, accuracy of information, similarity of information, inconsistency of information, and reliability of information sources were emphasized. According to the research results, information pollution makes it challenging for celiac patients to access accurate information, thereby negatively impacting their health. Misleading and incomplete information on social media platforms, in particular, can lead patients to adopt incorrect treatment methods or harmful diet practices.
Various strategies are suggested to prevent information pollution and ensure celiac patients have access to accurate information. These strategies include developing information verification protocols, providing digital literacy training, encouraging reliable information sources, utilizing artificial intelligence and data analytics, and collaborating with health professionals. Information verification protocols involve systematically evaluating the accuracy of information circulating on the internet, while digital literacy training helps patients recognize information pollution and distinguish correct information.
Furthermore, promoting reliable information sources and ensuring health professionals provide accurate information to patients play a crucial role in reducing information pollution. Artificial intelligence and data analytics offer effective tools for detecting misleading information and providing quick access to accurate information. Implementing these strategies will help celiac patients make healthy and informed decisions, thereby minimizing the effects of information pollution in virtual organizations.
Downloads
References
Agarwal, R., & Lau, F. (2010). Digital communication tools: Their impact on decision-making in healthcare organizations. Journal of Medical Systems, 34(6), 943-954.
Barnatt, C. (1995). Cyber business: Mindsets for a wired age. John Wiley & Sons.
Brossard, D., & Scheufele, D. A. (2013). Science, new media, and the public. Science, 339(6115), 40-41.
Creswell, J. W. (2013). Nitel araştırma yöntemleri (M. Bütün ve S. Ş. Demir, Çev. Ed.). 3. Baskı, Siyasal Kitapevi.
Davidow, W. H., & Malone, M. S. (1992). The virtual corporation: Structuring and revitalizing the corporation for the 21st century. HarperBusiness.
DeSanctis, G., & Monge, P. (1998). Communication processes for virtual organizations. LEA.
Dowling, G. R. (2001). Creating corporate reputations: Identity, image, and performance. Oxford University Press.
Edmonds, B. (1999). Capturing social embeddedness: A constructivist approach. Adaptive Behavior, 7, 323-347. https://doi.org/10.1177/105971239900700307
Fallis, D. (2009). Misinformation and the ethics of belief. The Journal of Philosophy, 106(4), 197-219.
Floridi, L. (2011). The philosophy of information. Oxford University Press.
Gibbs, G. (2008). Analyzing qualitative data. Sage.
Greenberg, L. (2008). Case management implications of celiac disease. Professional Case Management, 13(4), 211-217.
Hedberg, B., Dahlgren, G., Hansson, J., & Olve, N. G. (1997). Virtual organizations and beyond: Designing and implementing virtual organizations. John Wiley & Sons.
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
Khalifa, M. (2014). The importance of accurate medical information for patient safety in healthcare organizations. Procedia Computer Science, 37, 174-180.
LeCompte, M. (1982). Problems of reliability and validity in ethnographic research. Review of Educational Research, 52(1), 31-60.
Lewandowsky, S., Ecker, U. K., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest, 13(3), 106-131.
Lipnack, J., & Stamps, J. (1997). Virtual teams: Reaching across space, time, and organizations with technology. John Wiley & Sons.
Ludvigsson, J. F., Card, T. R., Kaukinen, K., Bai, J., Zingone, F., Sanders, D. S., & Murray, J. A. (2015). Support for patients with celiac disease: A literature review. United European Gastroenterology Journal, 3(5), 1-16.
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734.
McCright, A. M., & Dunlap, R. E. (2011). Cool dudes: The denial of climate change among conservative white males in the United States. Global Environmental Change, 21(4), 1163-1172.
Merriam, S. B. (2013). Nitel araştırma: Desen ve uygulama için bir rehber (S. Turan, Çev.). Nobel Yayıncılık.
Meskó, B., Drobni, Z., Bényei, É., Gergely, B., & Győrffy, Z. (2015). Digital literacy in the medical curriculum: A course with social media tools and gamification. JMIR Medical Education, 1(2), e8.
Miles, M., & Huberman, A. (1994). Qualitative data analysis: An expanded sourcebook (2. Baskı). Sage.
Norman, C. D., & Skinner, H. A. (2006). eHealth literacy: Essential skills for consumer health in a networked world. Journal of Medical Internet Research, 8(2), e9.
Rubin, V. L. (2001). Information overload revisited. IEEE Professional Communication Society Newsletter, 45(5), 1-8.
Sondhi, P., Bhowmick, P., Mitra, P., & Brusilovsky, P. (2012). Reliability prediction of webpages in the medical domain. Proceedings of the 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 453-457.
Southwell, B. G., Thorson, E. A., Sheble, L., & Perrault, E. K. (2020). Roles of health care professionals in addressing patient-held misinformation: A perspective from health communication. Health Communication Research, 36(3), 256-270.
Speier, C., Valacich, J. S., & Vessey, I. (1999). The influence of task interruption on individual decision making: An information overload perspective. Decision Sciences, 30(2), 337-361.
Şahin, C., & Demir, S. (2015). The impact of unreliable information sources on healthcare quality. Health Information Management Journal, 44(3), 144-151.
Townsend, A. M., DeMarie, S. M., & Hendrickson, A. R. (1998). Virtual teams: Technology and the workplace of the future. Academy of Management Perspectives, 12(3), 17-29.
Yıldırım, A., & Şimşek, H. (2016). Sosyal bilimlerde nitel araştırma yöntemleri (10. Baskı). Seçkin Yayıncılık.
Walambe, R., Srivastava, A., Yagnik, B. D., Hasan, M. M. U., Saiyed, Z., Joshi, G., & Kotecha, K. (2022). Explainable misinformation detection across multiple social media platforms. ArXiv. https://arxiv.org/abs/2203.11724
Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic literature review on the spread of health-related misinformation on social media. Journal of Public Health, 41(2), 123-130.
Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe.
World Health Organization (WHO). (2020). Infodemic management: A key component of the COVID-19 global response. World Health Organization.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Premium e-Journal of Social Science (PEJOSS)
This work is licensed under a Creative Commons Attribution 4.0 International License.