Abstract
Online websites have become an important source of information in all domains. Health has become one of the most Internet-dependent domains for information for the common users and experts alike. However, health information can be a critical determinant of human health and false information may cause real harm to Internet users. In this research, we aim to develop a model that evaluates the degree of trust in websites that provide health information. We conducted a quasi-experiment to assess the factors that affect user trust in health information providing websites. The experiment was conducted on pre-selected websites that provided information on Covid-19, ranging from official sources to those reported as providing misinformation. Participants had to assess the websites and determine factors that affected their level of trust. A total of 30 participated in the quasi-experiment, including both common users (46%) and health experts (56%). As a result, we identified the user-perceived importance weight of each of the studied factors that affect user trust in the studied websites. Using the identified importance weights of the factors, we developed a trust model and algorithm to evaluate the degree of trust in websites that provide health information. To evaluate the scalability of the developed model and algorithm, they were additionally applied on a set of pre-identified websites. The results were compared to the manually assessed scores conducted by health expert participants. The developed model achieved an error rate between 15%–19%, depending on the type and nature of the information-providing websites.
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References
Internet users in the world 2021 | Statista. https://www.statista.com/statistics/617136/digital-population-worldwide/. Accessed 29 Dec 2021
Sbaffi, L., Rowley, J.: Trust and credibility in web-based health information: a review and agenda for future research. J. Med. Internet Res. 19(6), e218 (2017). https://doi.org/10.2196/jmir.7579
Health websites are notoriously misleading: So we rated their reliability. https://www.statnews.com/2019/07/26/health-websites-are-notoriouslymisleading-so-we-rated-their-reliability/. Accessed 02 Jan 2022
Brady, E., Segar, J., Sanders, C.: ‘You get to know the people and whether they’re talking sense or not’: negotiating trust on health-related forums. Soc. Sci. Med. 162, 151–157 (2016). https://doi.org/10.1016/J.SOCSCIMED.2016.06.029
Islam, M.S., et al.: COVID-19–related infodemic and its impact on public health: a global social media analysis. Am. J. Trop. Med. Hyg. 103(4), 1621–1629 (2020). https://doi.org/10.4269/AJTMH.20-0812
Baldwin, R., Weder, B., Mauro, D.: Economics in the Time of COVID-19. www.cepr.org. Accessed 15 Dec 2021
Fighting misinformation in the time of COVID-19, one click at a time. https://www.who.int/news-room/feature-stories/detail/fighting-misinformation-in-the-time-of-covid-19-one-click-at-a-time. Accessed 15 Dec 2021
Daraz, L., et al.: Readability of online health information: a meta-narrative systematic review. Am. J. Med. Qual. 33(5), 487–492 (2018). https://doi.org/10.1177/1062860617751639
Patwa, P., et al.: Fighting an Infodemic: COVID-19 Fake News Dataset. https://doi.org/10.1007/978-3
Sillence, E., Blythe, J.M., Briggs, P., Moss, M.: A revised model of trust in internet-based health information and advice: cross-sectional questionnaire study. J. Med. Internet Res. 21(11), e11125 (2019). https://doi.org/10.2196/11125
Eysenbach, G., Köhler, C.: How do consumers search for and appraise health information on the world wide web? Qualitative study using focus groups, usability tests, and in-depth interviews. BMJ 324(7337), 573–577 (2002). https://doi.org/10.1136/BMJ.324.7337.573
Kim, H., Park, S.-Y., Bozeman, I.: Online health information search and evaluation: observations and semi-structured interviews with college students and maternal health experts. https://doi.org/10.1111/j.1471-1842.2011.00948.x
Alsem, M.W., Ausems, F., Verhoef, M., Jongmans, M.J., Meily-Visser, J.M.A., Ketelaar, M.: Information seeking by parents of children with physical disabilities: an exploratory qualitative study. Res. Dev. Disabil. 60, 125–134 (2017). https://doi.org/10.1016/j.ridd.2016.11.015
Benedicta, B., Caldwell, P.H.Y., Scott, K.M.: How parents use, search for and appraise online health information on their child’s medical condition: a pilot study. J. Paediatr. Child Health 56(2), 252–258 (2020). https://doi.org/10.1111/JPC.14575
van Velsen, L., Flierman, I., Tabak, M.: The formation of patient trust and its transference to online health services: the case of a Dutch online patient portal for rehabilitation care. BMC Med. Inf. Dec. Making 21(1) (2021). https://doi.org/10.1186/s12911-021-01552-4
Peddie, K.A., Kelly-Campbell, R.J.: How people with hearing impairment in New Zealand use the Internet to obtain information about their hearing health. Comput. Hum. Behav. 73, 141–151 (2017). https://doi.org/10.1016/j.chb.2017.03.037
Marshall, L.A., Williams, D.: Health information: does quality count for the consumer? J. Librariansh. Inf. Sci. 38(3), 141–156 (2006). https://doi.org/10.1177/0961000606066575
Cunningham, A., Johnson, F.: Exploring trust in online health information: a study of user experiences of patients.co.uk. Heal. Inf. Libr. J. 33(4), 323–328 (2016). https://doi.org/10.1111/HIR.12163
Diviani, N., van den Putte, B., Meppelink, C.S., van Weert, J.C.M.: Exploring the role of health literacy in the evaluation of online health information: insights from a mixed-methods study. Patient Educ. Couns. 99(6), 1017–1025 (2016). https://doi.org/10.1016/J.PEC.2016.01.007
Sun, Y., Zhang, Y., Gwizdka, J., Trace, C.B.: Consumer evaluation of the quality of online health information: systematic literature review of relevant criteria and indicators. J. Med. Internet Res. 21(5), e12522 (2019). https://doi.org/10.2196/12522
Health websites are notoriously misleading. So we rated their reliability. https://www.statnews.com/2019/07/26/health-websites-are-notoriously-misleading-so-we-rated-their-reliability/. Accessed 2 Jan 2022
Stephens-davidowitz, S.: Everybody Lies : What The Internet Can Tell us About Who We Really Are. Bloomsbury Publishing (2018)
Seckler, M., Heinz, S., Forde, S., Tuch, A.N., Opwis, K.: Trust and distrust on the web: user experiences and website characteristics. Comput. Human Behav. 45, 39–50 (2015). https://doi.org/10.1016/J.CHB.2014.11.064
Fisher, R., Chu, S.Z.: Initial online trust formation: the role of company location and web assurance. Manag. Audit. J. 24(6) 542–563 (2009). https://doi.org/10.1108/02686900910966521/FULL/PDF
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Alajramy, L., Taweel, A. (2022). User Perception Based Trust Model of Online Sources: A Case Study of Misinformation on COVID-19. In: Spezzano, F., Amaral, A., Ceolin, D., Fazio, L., Serra, E. (eds) Disinformation in Open Online Media. MISDOOM 2022. Lecture Notes in Computer Science, vol 13545 . Springer, Cham. https://doi.org/10.1007/978-3-031-18253-2_1
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