key: cord-0795714-m9tjv2r3
authors: Staccini, Pascal; Lau, Annie Y. S.
title: Consumer Informatics and COVID-19 Pandemics: Challenges and Opportunities for Research: Findings from the Yearbook 2020 Section on Education and Consumer Health Informatics
date: 2021-09-03
journal: Yearb Med Inform
DOI: 10.1055/s-0041-1726532
sha: 66ea6e84012fb290bf8a06fe574388d3dfbdc2f0
doc_id: 795714
cord_uid: m9tjv2r3

Objective: To summarise the state of the art during the year 2020 in consumer health informatics and education, with a special emphasis on “Managing Pandemics with Health Informatics - Successes and Challenges”. Methods: We conducted a systematic search of articles published in PubMed using a predefined set of queries, which identified 147 potential articles for review. These articles were screened according to topic relevance and 15 were selected for consideration of best paper candidates, which were then presented to a panel of international experts for full paper review and scoring. The top five papers were discussed in a consensus meeting. Three papers received the highest score from the expert panel, and these papers were selected to be representative papers on consumer informatics for managing pandemics in the year 2020. Results: Bibliometrics analysis conducted on words found in abstracts of the candidate papers revealed 4 clusters of articles, where the clustering outcomes explained 77.04% of the dispersion. The first cluster composed of articles related to the use of mobile apps for video consultation and telehealth during the pandemic. The second revealed studies reporting the lived experience of healthcare workers and patients during COVID-19. The third focused on ways people used the internet to seek for health information during the pandemic and the dissemination of fake news. The last cluster composed of articles reporting the use of social listening methods (e.g., via tweet hashtags) to explore the spread of the virus around the world. Conclusions: The pandemic outbreak of the novel coronavirus disease (COVID-19) constitutes a grave risk to the global community and sparks a significant increase in public interest and media coverage, especially on social media. Consumers are facing a new set of challenges that were not considered before COVID-19, often finding themselves in a world that is constantly changing—blended with facts and fake information—and unable to decide what to do next. Despite most people understanding the good will behind public health policies, one must not forget it is individuals we are supporting and that their personal circumstances may affect how they perceive and comply with these policies. Consumers more than ever need help to make sense of the uncertainty and their situation and we need to help them navigate the best option in a world that is constantly evolving.

For this 30 th edition of the Yearbook of Medical Informatics, the topic of "Managing Pandemics with Health Informatics -Successes and Challenges" comes at dark times when massive populations face the spread of a mortal infectious disease (the coronavirus disease 2019 (COVID-19)) around the world. For clinicians, researchers, public health officials and political representatives, time is pressing to find solution to identify and care for vulnerable patients, to establish policies to slow down virus diffusion, and to monitor the impact of lock down policy, sanitary rules compliance, as well as vaccination campaigns. public health purposes. Since the beginning of COVID19 pandemics, numerous opensource datasets and statistical online tools have emerged compiling and modelling by country the number of deaths and the number of hospitalized patients with moderate or severe clinical symptoms requiring intensive care. A recent study showed that the main source of data comes from social media and Internet search engines [3] , raising the possibility of whether social media listening can be implemented in-real-time to support these predictive analyses on scale.

In this paper, we will explore the literature to explore the role of consumer informatics in the COVID-19 pandemics. Specifically,

Objective: To summarise the state of the art during the year 2020 in consumer health informatics and education, with a special emphasis on "Managing Pandemics with Health Informatics -Successes and Challenges". Methods: We conducted a systematic search of articles published in PubMed using a predefined set of queries, which identified 147 potential articles for review. These articles were screened according to topic relevance and 15 were selected for consideration of best paper candidates, which were then presented to a panel of international experts for full paper review and scoring. The top five papers were discussed in a consensus meeting. Three papers received the highest score from the expert panel, and these papers were selected to be representative papers on consumer informatics for managing pandemics in the year 2020.

Results: Bibliometrics analysis conducted on words found in abstracts of the candidate papers revealed 4 clusters of articles, where the clustering outcomes explained 77.04% of the dispersion. The first cluster composed of articles related to the use of mobile apps for video consultation and telehealth during the pandemic. The second revealed studies reporting the lived experience of healthcare workers and patients during COVID-19. The third focused on ways people used the internet to seek for health information during the pandemic and the dissemination of fake news. The last cluster composed of articles reporting the use of social listening methods (e.g., via tweet hashtags) to explore the spread of the virus around the world. Conclusions: The pandemic outbreak of the novel coronavirus disease (COVID-19) constitutes a grave risk to the global community and sparks a significant increase in public interest and media coverage, especially on social media. Consumers are facing a new set of challenges that were not considered before COVID-19, often finding themselves in a world that is constantly changing-blended with facts and fake information-and unable to decide what to do next. Despite most people understanding the good will behind public health policies, one must not forget it is individuals we are supporting and that their personal circumstances may affect how they perceive and comply with these policies. Consumers more than ever need help to make sense of the uncertainty and their situation and we need to help them navigate the best option in a world that is constantly evolving. Regarding the topic "management pandemics" recall back in 2009, Google Flu Trends (GFT), a digital disease detection system that uses the volume of selected Google search terms to predict influenza-like illnesses (ILI) activity, was identified by many as one of the first examples of how big data would transform traditional statistical predictive analysis [1] . Despite the development of these more refined and accurate predictive algorithms [2] , Google announced in May 2015 that GFT would be discontinued and that their raw data would be made accessible to selected scientific teams. These initiatives have laid the foundation for crunching publicly available online-generated data for we will identify how research in the past year have addressed: 1) innovative uses of social media listening for disease monitoring and public health purposes; 2) the lived experience of COVID as reported online; 3) the spread of 'fake information' and ways to determine quality in online information related to the pandemics; and 4) how people used telehealth and other technologies to maintain contact with their healthcare team.

We used PubMed to conduct our search, capturing papers on consumer-using technologies and emerging disease concerned published in the year 2020. The search strategy was based on the PICO framework ((P-Population/ Problem, I-Intervention, C-Comparison, O-Outcome), where 'Population' refers to patient, client, consumer, 'Problem' refers to the COVID-19 disease and clinical symptoms, 'Intervention' refers to social media and information technology. 'Comparison' and 'Outcome were not included as we were looking for innovative usage and we did not want to constrain the query with prespecified comparison or outcome measures. We started from a core query adopted in previous work.

Step 

To understand the state of the literature, we applied various bibliometrics tools onto the original set of articles returned from the search query. The "Bibliometrix" package from R [5] was used on the citation set of retrieved articles. We reported frequency of keywords. We illustrated the analysis of abstracts (measure of word frequency) by a word cloud drawing. We analysed keywords to uncover links between concepts through co-occurrences network. We also plotted a thematic map to analyse these clusters according to the quadrant in which they are placed [6] . Themes in the upper-right quadrant are both well-developed and important for the structuring of a research field. They are known as the motor-themes of the specialty given that they present strong centrality and high density. Themes in the upper-left quadrant have well-developed internal ties but unimportant external ties and so are of only marginal importance to the field. These themes are very specialized and peripheral in character. Themes in the lower-left quadrant are both weakly-developed and marginal. The themes of this quadrant have low density and low centrality, mainly representing either emerging or disappearing themes. Themes in the lower-right quadrant are important for a research field but are not as well-developed. Each theme is represented as a sphere, its volume being proportional to the number of documents associated with the theme.

A descriptive analysis of 147 articles was conducted, analysing the frequency of keywords, and the frequency of words in titles and abstracts. 703 distinct keywords were used, 640 distinct words in titles and 4302 words in abstracts. Figure 1 lists the 50 most cited keywords ranked according to decreasing frequency. Table 1 shows how the most cited keywords (10 or more occurrences) can be reorganised to describe the structure of the initial query. Figure 2 shows a triangle-shaped words cloud created from the analysis of abstracts. Along the tip of the triangle, we can see keywords such as "coronavirus, study, pandemic, health, covid"; and along the base of the triangle, we can see keywords such as "social media, patients" and "associated factors and risk reported". Regarding the conceptual structure of the set of 147 articles, Figure 3 shows the co-occurrences of keywords. It identifies the relationships between keywords in accordance to the groups reported in Figure 2 . Regarding thematic maps of keywords found in Figure 4 , clusters according to centrality (relevance degree) and density (development degree) are reported in each quadrant. Most common themes found across papers are related to covid infection as a human disease. Next set of frequently reported themes focus on "epidemiology, prevention and control". Niche themes revealed by this analysis are represented by two clusters: first, mobile applications and covid epidemiology, second, clinical epidemiology studies to describe the severity of illness. The cluster "attitude to health" is in central and neutral position. 

To identify the 15 candidate papers, co-editors independently assessed the 147 retrieved papers using the Rayyan web-tool [4] , followed by discussion. Elements that were considered in the screening decision include: 1) level of relevance regarding the 2021 Yearbook topic "Managing Pandemics with Health Informatics"; 2) whether the study was focused only on patients and consumers; 3) nature of the issues addressed; and 4) level of innovative approach. Section co-editors' agreement was measured with Cohen's kappa coefficient: κ=0.474 95%CI [0.098 ; 0.7168] (moderate agreement). The 15 articles were then presented to a panel of international experts for full paper review and scoring according to the IMIA Yearbook best paper selection process. The final selection of three best papers is completed after discussions at the annual IMIA Yearbook board meeting. Figure 5 shows the factorial map of papers, based on words in abstracts (400 terms), revealing four clusters. The result clustering explains 77.04% of the dispersion. This clustering was blinded to the reviewers. Cluster 1 is composed of articles relating to the use of mobile apps for video consultation with healthcare professionals. Sabrir et al. [7] investigated the effects of WhatsApp video consultation on patient admission and discharge times in comparison to bedside consultation during the pandemic. Consultation via WhatsApp was reported to have reduced both contact time with patients with COVID-19 and that the number of medical staffs contacting patients. Furthermore, the study reported reducing length of stay in the emergency department. Xu et al. [8] built a system based on a popular social media smartphone app called WeChat; the app was used to establish two-way communication between a multidisciplinary team with home-quarantined individuals including those diagnosed with COVID-19. The system requires few staff to manage a large cohort of patients. They found this telemedicine system reduces the risks of delayed hospitalisation due to better management of disease progression, optimising usage of resources, and preventing cross-infections among medical workers and patients.

Cluster 2 is composed of studies reporting the lived experience of patients and health workers during the pandemic [9] [10] [11] [12] [13] . El-Awaisi et al. [9] used social listening technique to explore unfiltered public perceptions during the COVID-19 pandemic and to elaborate on the emotional reactions in response to an online social media post about healthcare professionals. The post asked who do you think works in hospitals versus who really works in hospitals? Despite the word 'Heroes' being commonly used, the post brought considerable attention to the role of the interprofessional team and generated Bennett et al. [10] study aimed to gain better understanding of the experiences and concerns of front-line National Health Service (NHS) workers while caring for patients with COVID-19. Key findings highlighted that while healthcare workers shared intensely positive experiences, caring for COVID-19 patients brought a significant emotional toll, and strained relationships between immediate front-line staff, their families, management and even government. There was a sense that at the beginning of the pandemic, staff were driven by adrenalin and optimism; but over time this has dissipated and is replaced by exhaustion, numbness, and dreaded expectation of a 'second wave'. Healthcare workers could reasonably be considered as 'second victims' of COVID-19.

Cluster 3 composed of articles exploring how people used the internet to seek health information during the pandemic [14] [15] [16] [17] [18] and the dissemination of fake news [19] . Zhao et al. [15] found that a high proportion of Chinese female users were seeking health information and help for their parents or for older adults at home. The most searched information included accessing medical treatment, managing self-quarantine, as well as offline to online support. Li et al. [16] explored the predictive role of social media use on public preventive behaviors in China during the COVID-19 pandemic. They also found that different social media types differed in predicting an individual's preventive behaviors during COVID-19.

Cluster 4 composed of articles reporting the use of social listening methods (e.g., tweet hashtags) to explore the spread of the virus around the world (i.e., infoveillance) [20] [21] . See Appendix for more information.

Finally, three papers were selected to be best papers after discussions at a consensus meeting at the April 30 th 2021 IMIA Yearbook editorial meeting. They are listed in table 2. See Appendix to read the description of the studies and the main results.

The pandemic outbreak of the novel coronavirus (COVID-19) constitutes a grave risk to the global community and sparks a significant increase in public interest and media coverage, especially on social media. Consumers are facing a new set of challenges that were not conceived before COVID-19, often finding themselves in a world that is constantly changing, blended with facts and fake information, and many consumers unable to decide what to do next. Despite most people understanding the good will behind public health policies, one must not forget it is individuals we are supporting and that their personal circumstances may affect how they perceive and comply with these policies. Consumers more than ever need help to make sense of the uncertainty and their situation and help them navigate the best option in a world that is constantly evolving. Interestingly, tweet volumes in Turkey seemed to be higher than in surrounding countries. This study demonstrates how COVID-19-related tweets can be analyzed for a certain region (Europe). With the continuous progression of the pandemic situation, which is to be expected in the next months worldwide, further regions should be analyzed in-depth.

Google uses searches to track flu's spread. NY Times

Accurate estimation of influenza epidemics using Google search data via ARGO

Big data analytics as a tool for fighting pandemics: a systematic review of literature

Rayyan -a web and mobile app for systematic reviews

Bibliometrix: An R-tool for comprehensive science mapping analysis

Co-word analysis as a tool for describing the network of interactions between basic and technological research-the case of polymer chemistry

Use of WhatsApp for Polyclinic Consultation of Suspected Patients With COVID-19: Retrospective Case Control Study

Monitoring and Management of Home-Quarantined Patients With COVID-19 Using a WeChat-Based Telemedicine System: Retrospective Cohort Study

Perceptions of who is in the healthcare team? A content analysis of social media posts during COVID-19 pandemic

COVID-19 confessions: a qualitative exploration of healthcare workers experiences of working with COVID-19

Attitudes of the Public to Receiving Medical Care during Emergencies through Remote Physician-Patient Communications

When Going Digital Becomes a Necessity: Ensuring Older Adults' Needs for Fig 4 Thematic map of clusters of keywords. Information, Services, and Social Inclusion During COVID-19

Social Listening as a Rapid Approach to Collecting and Analyzing COVID-19 Symptoms and Disease Natural Histories Reported by Large Numbers of Individuals

Trends and Predictors of COVID-19 Information Sources and Their Relationship With Knowledge and Beliefs Related to the Pandemic: Nationwide Cross-Sectional Study

Online Health Information Seeking Using "#COVID-19 Patient Seeking Help" on Weibo in Wuhan, China: Descriptive Study

Social Media Use, eHealth Literacy, Disease Knowledge, and Preventive Behaviors in the COVID-19 Pandemic: Cross-Sectional Study on Chinese Netizens

Mobile Fotonovelas Within a Text Message Outreach: An Innovative Tool to Build Health Literacy and Influence Behaviors in Response to the COVID-19 Pandemic

YouTube as a Source of Medical and Epidemiological Information During COVID-19 Pandemic: A Cross-Sectional Study of Content Across Six Languages Around the Globe

Fake News and Covid-19 in Italy: Results of a Quantitative Observational Study

Social Media Data Analytics on Telehealth During the COVID-19 Pandemic

Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19-Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study

During the rapid escalation of the COVID-19 pandemic in March and April 2020, the authors conducted an online survey on the sources of information used and trusted by US adults for acquiring COVID-19 information and ascertained how these sources varied according to key sociodemographic characteristics. They also assessed how differences in information sources were associated with variation in beliefs and levels of knowledge related to COVID-19. The sample was a self-selected nonprobability sample of social media users on Facebook and its affiliated platforms that was recruited through an on-platform advertisement campaign. Participants were sampled in two rounds about one month apart, from March 20 th to 30 th , and from April 16 th to 21 th , 2020. Eligible participants included US residents aged ≥18 years. The survey was based on the Health Belief Model, which has been previously utilized in recent surveys on other viral outbreaks. Participants were asked whether or not they used any of the 11 predetermined sources to find information about COVID-19. A variable indicating the total number of sources used by each participant was created by summing the number of "yes" responses for each of the information sources. They were asked to identify the information source they trusted the most. A total of 13,201 respondents were eligible to participate, of whom 11,242 provided data on their sources of COVID-19 information. Males were significantly less likely than fe-