Undergraduate Students' Online Health Information-Seeking Behavior during COVID-19: Comparison
Please note this is a comparison between Version 2 by Yvaine Wei and Version 1 by Wan-Chen Hsu.

As the COVID-19 pandemic has swept across the world, the amount of health-related information available has skyrocketed. Individuals can easily access health information through the internet, which may influence their thoughts or behavior, causing potential technological risks that may affect their lives. 

  • health information
  • online health information
  • information-seeking behavior
  • undergraduate students
  • COVID-19

​1. Introduction​

The COVID-19 pandemic, caused by the novel Sars-CoV-2 coronavirus, has caused the death of millions of people and disrupted daily life worldwide. During this pandemic, individuals were restricted from going outside, and physical activities were reduced as a result of its impact. Consequently, people gathered, exchanged information, and entertained themselves via the internet, with online health information becoming an alternative to personal visits to physical hospitals and medical centers.

Online platforms have the potential to provide individuals with useful information, increase their engagement, and potentially revolutionize the patient–physician relationship [4][1]. Information seeking has become a focus of health communication scholarship, since individuals can now use a variety of platforms, such as the television, newspapers, the internet, and other interpersonal communication channels, to gain knowledge [5][2]. Chen and Lee [6][3] noted that people often have limited skills related to retrieving and evaluating the vast amount of information available from a variety of online sources with varying quality. This overwhelming availability of online health information highlights the importance of understanding the status and key influencing factors of its use among individuals.​

​Health information is defined as information that can assist individuals in promoting their health, making health-related decisions, and participating in the healthcare system [7][4]. Information seeking can be unintentional, passive, or active [8][5] and is often purposeful, with individuals seeking information to meet a personal need or goal [9][6]. Information-seeking behavior is the action of searching for and using information in any way, following an individual’s need. In particular, it relates to the behavior arising from an interaction with the information source when one needs information; it can range from passive attention to passive searching, active searching, and ongoing searches, all of which fall within the scope of information-seeking behavior [9][6]. Online health information-seeking behavior is dominated by active information seeking and passive information acquisition [7][4]. Health information-seeking behavior is a type of personal health promotion in which individuals obtain expertise from various sources, such as doctors, to inform their decisions, improve their food and nutrition intake, relieve stress, and reduce drug abuse [5][2]. In sum, online health information-seeking behavior involves individuals’ retrieval of health information from the internet, which can be actively or passively motivated, for the purpose of obtaining knowledge for personal health promotion and facilitating decision making.​

Regarding health information retrieval and health promotion theories, the social cognitive theory is one of the most widely used theoretical frameworks [10][7]. Bandura’s social cognitive theory provides a structure for interpreting the relevant results of individuals after retrieving information [11,12][8][9]. For example, how much confidence an individual has in finding quality health information, i.e., their self-efficacy in searching, is also related to the expected results after retrieval. Self-efficacy can be a powerful predictor of expected results regarding an individual’s online health information-seeking behavior [13][10]. The risk information seeking and processing model (RISP) is one of the representative theoretical models explaining online information seeking. It emphasizes that the behavior of individuals to retrieve online information is triggered by insufficient cognitive data (termed as information insufficiency hereafter); according to the model, a lack of information is the main factor directly driving information seeking, alongside other incidental social and psychological factors, such as emotional response (worry, anxiety) and subjective criticism of information. The RISP model thus provides a framework to explain the key influencing factors that individuals use to seek and process relevant risk information in a more systematic or deliberate manner. Brown, Skelly, and Chew-Graham [14][11] proposed a model, pointing out that individuals’ online health information retrieval is affected by their previous experience, health beliefs, and other personal background factors.

2. Is Information Literacy the Missing Part of Health Promotion among Undergraduate Students?​​

It was found that most of the keywords used by the participants in the search for health information were nouns, although some did use a mixture of nouns, adjectives, and adverbs. Few searched using Boolean logic, and they seldom limited the scope of their queries to narrow down the results, indicating that the undergraduate students had few relevant skills in searching for information.​

Information literacy is one of the multiple components of health literacy that adolescents are aware of, encompassing a range of skills and knowledge that are relevant to health behaviors and can reduce health risks​ [21][12]. When individuals are familiar with internet search methods, they can easily filter out useful information based on the purpose of the search and the source of the data. Conversely, users who are unfamiliar with these operations are easily distracted by irrelevant information, which affects the accuracy and usefulness of their information judgments. Furthermore, individuals who are exposed to a large amount of online health information and are unable to critique and make good use of this information may suffer negative effects, leading to feelings of anxiety that can cause emotional distress and even severe cyberchondria [27][13]. Joseph and Fleary [21][12] explored adolescents’ perceptions of health literacy and revealed that they involved more functional than critical literacy. Criticality involves reading, understanding, and acting upon health information, having potential effects and benefits for individuals and society. This highlights the importance of critical skill development and education for the youth in particular.

​3. What Is the Potential Risk of Self-Diagnosis Due to the Explosion of Health Information during the COVID-19 Pandemic?

​In fact, obtaining health-related information on the internet and diagnosing oneself based on it affects one’s health-related behaviors, decisions, and actions. Sturiale et al. [4][1] found that there was a correlation between those who used the internet for work and those who had knowledge of both symptoms and their likely diagnosis before consultation, among patients. Patients who used the internet daily were more likely to request a consultation within six months of symptom onset. Additionally, those with anorectal diseases were more likely to have knowledge of their disease and symptoms before the visit. Hsu et al. [3][14] surveyed a sample of undergraduate students to explore their experiences with online health information and found that they retrieved health information related to their needs from the internet in order to prevent or maintain their health conditions. However, the prescriptions they retrieved online only offered reference answers, and sometimes inner doubts still lingered in their minds. Using the flu as an example, Myrick employed a naturalistic experiment to test the emotions of 380 Americans after retrieving information online, exploring the theoretical models that shaped cognition and behavior [13][10]. It was found that the study participants had difficulty retrieving information when they had a dubious attitude. Myrick further tested how to improve the skills required for the online health information retrieval process, observing that individuals had multiple emotions (fear, hope, satisfaction, interest, and motivation) after retrieving information, and the mediating effect of “social cognitive factors” affected their subsequent attitudes and behaviors. The positive emotions of interest and hope experienced during the online health information-seeking process positively influenced individuals’ confidence and behavioral intentions.

The number of medical articles published on the internet increased significantly during the COVID-19 pandemic [28][15]; however, at the same time, the amount of fake news and disinformation skyrocketed to several dozen times the previous level [29][16]. As the internet booms and health information spreads, the World Wide Web has become a major source for the public to search for information about medical and health risks. In tandem with this boom, many health and disease-focused websites have emerged to provide the public with more immediate access to health information. Such sites provide information and resources for readers with medical conditions, assisting them with possible self-diagnostic references for certain symptoms and helping them decide whether to self-treat or consult a physician [30][17]. The use of the internet to retrieve health-related information is a behavioral manifestation of the individuals’ search for peace of mind. However, the information available on the internet is not always accurate and reliable; therefore, it is important to promote individuals’ online search skills to reduce uncertainty, worries, and anxiety, avoiding incorrect self-diagnosis. As individuals are exposed to the risks of online information technology, it is critical to understand how they use health information when they are inundated with it online [31][18]. A key strategy for managing health care surge is “forward triage”—the sorting of patients before they arrive at the emergency department (ED). Direct-to-consumer (or on-demand) telemedicine, a 21st-century approach to forward triage that allows individuals to be efficiently screened, is both patient-centered and conducive to self-quarantine, protecting patients, clinicians, and the community from exposure to any infectious disease, such as COVID-19. Furthermore, it allows physicians and patients to communicate using smartphones or webcam-enabled computers, which may be beneficial during situations such as the COVID-19 pandemic [32][19]. Telemedicine, however, may not always be the go-to approach for physicians in Italy. For example, the utilization of telemedicine for the diagnosis of common proctologic conditions (e.g., hemorrhoidal disease, anal abscess and fistula, anal condylomas, and anal fissure) and functional pelvic floor disorders was generally considered inappropriate. Teleconsultation was instead deemed appropriate only for the diagnosis and management of pilonidal disease, revealing the boundaries of telemedicine in Italy. Therefore, infrastructures, logistics, and legality related to telemedicine need to be standardized [33][20].​​​​​​​​​​​​​​​

References

  1. Sturiale, A.; Pata, F.; De Simone, V.; Pellino, G.; Campennì, P.; Moggia, E.; Manigrasso, M.; Milone, M.; Rizzo, G.; Morganti, R.; et al. Internet and social media use among patients with colorectal diseases (ISMAEL): A nationwide survey. Colorectal Dis. 2020, 22, 1724–1733.
  2. Moorman, C.; Matulich, E. A model of consumers’ preventive health behavior: The role of health motivation and health ability. J. Consum. Res. 1993, 20, 208–228.
  3. Chen, W.; Lee, K.H. More than search? Informational and participatory eHealth behavior. Comput. Hum. Behav. 2014, 30, 103–109.
  4. Liao, W.C.; Chiu, L.A.; Yueh, H.P. A study of rural elderly’s health information needs and seeking behavior. J. Libr. Inf. Stud. 2012, 10, 155–204.
  5. Case, D.O. Looking for Information: A Survey of Research on Information Seeking, Needs and Behavior; Academic Press: San Diego, CA, USA, 2002.
  6. Wilson, T.D. Human information behavior. Inf. Sci. 2000, 3, 49–55.
  7. Dawkins-Moultin, M.; Mcdonald, A.; Mckyer, E.L. Integrating the principles of socioecology and critical pedagogy for health promotion health literacy interventions. J. Health Commun. 2016, 21, 30–35.
  8. Bandura, A. The self system in reciprocal determinism. Am. Psychol. 1978, 33, 344–358.
  9. Bandura, A. Self-Efficacy: The Exercise of Control; W. H. Freeman and Company: New York, NY, USA, 1997.
  10. Myrick, J.G. The role of emotions and social cognitive variables in online health information seeking processes and effects. Comput. Hum. Behav. 2017, 68, 422–433.
  11. Brown, R.J.; Skelly, N.; Chew-Graham, C.A. Online health research and health anxiety: A systematic review and conceptual integration. Clin. Psychol. 2019, 27, e12299.
  12. Joseph, P.; Fleary, S.A. “The way you interpret health”: Adolescent definitions and perceptions of health literacy. J. Sch. Health 2021, 91, 599–607.
  13. Jokić-Begić, N.; Mikac, U.; Čuržik, D.; Jokić, D.S. The development and validation of the Short Cyberchondria Scale (SCS). J. Psychopathol. Behav. Assess. 2019, 41, 1–15.
  14. Hsu, W.C.; Chen, S.F.; Ho, C.J. Experience of using web health information among undergraduate students: An analysis from the health literacy perspective. J. Health Promot. Health Educ. 2011, 35, 1–22.
  15. Chrzanowski, J.; Sołek, J.; Fendler, W.; Jemielniak, D. Assessing public interest based on Wikipedia’s most visited medical articles during the SARS-CoV-2 outbreak: Search trends analysis. J. Med. Internet Res. 2021, 23, e26331.
  16. Mangono, T.; Smittenaar, P.; Caplan, Y.; Huang, V.S.; Sutermaster, S.; Kemp, H.; Sgaier, S.K. Information-seeking patterns during the COVID-19 pandemic across the United States: Longitudinal analysis of Google Trends data. J. Med. Internet Res. 2021, 23, e22933.
  17. Ryan, A.; Wilson, S. Internet healthcare: Do self-diagnosis sites do more harm than good? Expert Opin. Drug Saf. 2008, 7, 227–229.
  18. Zahnd, W.E.; Scaife, S.L.; Francis, M.L. Health literacy skills in rural and urban populations. Am. J. Health Behav. 2009, 33, 550–557.
  19. Hollander, J.E.; Carr, B.G. Virtually perfect? Telemedicine for COVID-19. N. Engl. J. Med. 2020, 382, 1679–1681.
  20. Gallo, G.; Grossi, U.; Sturiale, A.; Di Tanna, G.L.; Picciariello, A.; Pillon, S.; Mascagni, D.; Altomare, D.F.; Naldini, G.; Perinotti, R.; et al. E-consensus on telemedicine in proctology: A RAND/UCLA-modified study. Surgery 2021, 170, 405–411.
More
Video Production Service