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https://orcid.org/0000-0003-0984-1474
Abstract
Abstract
Objective
During the COVID-19 pandemic, Americans have increasingly relied on internet versus television news. The extent to which this change in health news consumption practice impacts health knowledge is not known. This study investigates the relationship between most trusted information source and COVID-19 knowledge.
Methods
A cross-sectional online survey was sent to a convenience sample from a list of adults on a central Pennsylvania health system’s marketing database 25–31 March 2020. Respondents were grouped by their trusted news sources and comparison of respondent COVID-19 knowledge was made between these groups for 5948 respondents.
Results
Those who selected government health websites as their most trusted source were more likely to answer COVID-19 questions correctly than those who selected other internet news sources or television news (OR 1.21, p < .05; 1.08, p > .05; and 0.87, p < .05, respectively). Those who used Facebook as an additional source of news in any way were less likely to answer COVID-19 questions correctly than those who did not (OR 0.93, p < .05).
Conclusions
COVID-19 knowledge correlates with trusted news source. To increase public knowledge of COVID-19 in order to maximize information dissemination and compliance with COVID-19-related public health recommendations, those who provide health information should consider use of the public’s most trusted sources of information, as well as monitoring and correcting misinformation presented by other sources. Independent content review for accuracy in media may be warranted in public health emergencies to improve knowledge.
Introduction
The COVID-19 pandemic has become a global tragedy. Worldwide, 124.3 million cases have been reported and over 2,736,668 have lost their lives as of March 24, 20211. As nations continue to address this pandemic, effective communication between healthcare experts and national populations is paramount to public health2–7. Past pandemics have shown that ineffective messaging may result in public misconceptions, poor compliance with precautionary measures, overuse of health services, and facilitate inadequate health and public policy decisions8–11. For health messaging to be effective, it must be received, understood and believed by the public. Therefore, understanding public information sources is an important component of health messaging campaigns, and understanding their relationship to knowledge informs how to approach addressing public misconceptions.
In 2003, 80% of adult internet users searched for at least one of 16 major health topics online12. In 2009, 61% of Americans searched online for health information13. In 2017, 50% of Americans got their news primarily from television, 43% primarily from the internet and 66% got at least some of their news from social media14. Information sources for COVID-19 appear to be quite different. The single most trusted news sources about COVID-19 for central Pennsylvania adults are government websites (42.8%), television (27.2%) and health system communications (9.3%)15. This change in information sources may play a significant role in how the public has understood and acted (or not acted) upon public health messaging, and may partially explain the public misconception and poor compliance already reported during the COVID-19 pandemic15–18.
The extent to which preferred information sources relate to knowledge and behavior during the COVID-19 pandemic is a small, but growing, area of research. A political survey found that Americans appear to have maintained similar news habits19. One large study of social media users evaluated information sources and knowledge related to COVID-19 and found that traditional media was the most frequently utilized source of information (91.2%), and that the most trusted source of information was government websites (45.2%)20. That study also found that the use of social media information may not be associated with significantly different awareness about an emerging health crisis like COVID-19, but the authors note that because their sample was a nonprobability convenience sample of Facebooki (and affiliated platforms used), their results may not be generalizable20. To overcome potential biases inherent to political and nonprobability social medial platform surveys, this COVID-19 study explores relationships between information sources and knowledge in an apolitical survey of a patient population. Detailed understanding of public information consumption and knowledge will inform community outreach and health messaging strategies necessary to improve compliance with public health recommendations, and give insights into the generalizability of current research in the field.
Methods
The development, design and implementation of the survey used are described in detail elsewhere15. Briefly, a cross-sectional online survey was sent to a convenience sample from a list of adults on a central Pennsylvania health system’s marketing database 25–31 March 2020. From a database of 121,573 unique, valid email addresses, 5948 respondents completed the survey (73.7% of all those who opened the survey, 50.9% of those who opened the survey link, 11.1% of those who opened the email and 4.8% of the entire email address list recipients). This study focuses on associations between knowledge, information sources and demographic characteristics.
The Pennsylvania State University College of Medicine Institutional Review Board approved the study protocol. This study adhered to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).
Knowledge questions were scored as incorrect or correct, and each had an associated 5 point confidence score (1 = Extremely confident, 5 = Not at all confident [just guessing]). Simple imputation was used for skipped or missed confidence levels for questions answered. Binary knowledge answers were analyzed via a generalized linear mixed-effects model (GLMM) with a logistic link function and a random effect for the participant, modeling the probability of a correct response. The logarithm of the estimated odds ratios from the GLMM were transformed to probability estimates, with 95% confidence intervals (CIs). To report adjusted p values, the false-discovery rate was applied. SAS Version 9.4 was used.
Results
As previously reported, respondents were primarily older, white, educated, females, whose most trusted sources of information regarding COVID-19 were internet government websites (CDC/NIH/WHO; 42.8%, N = 2547), television news (27.2%, N = 1620) and health system communications (9.3%, N = 550)15. Preferred sources were similar by gender, but markedly difference by age category with those over 50 far more likely to trust television news and less likely to trust internet news than those under 50 (Table 1).
Table 1. Top four single most trusted news sources among central Pennsylvania adults, March 2020.
Respondents with different single most preferred sources had substantial, significant differences in COVID-19 knowledge, which were similar for both the 8-item basic knowledge set and the full 15-item set. Table 2 summarizes odds ratios for knowledge comparisons based on the single most trusted source as well as a comparison of those who used or did not use Facebook as an additional information source.
Table 2. Knowledge by preferred information sources.
Those whose single most trusted information source was internet news were similar in overall knowledge compared to those with other trusted sources (OR 1.08, 95% CI 1.00, 1.17; Table 2). Those whose single most trusted information source was television news were less likely to answer questions correctly than those with other trusted sources (OR 0.87, 95% CI 0.83, 0.91). Those whose single most trusted information source was government internet news were much more likely to answer knowledge questions correctly than those with other trusted sources (OR 1.21, 95% CI 1.16, 1.26). Respondents who selected “Facebook” as either their single most trusted source or as an additional information source were less likely to answer knowledge questions correctly (OR 0.93, 95% CI 0.88, 0.97) than respondents who reported a different primary source and did not to use Facebook as an additional information source.
Discussion
Participants who used government health websites were more likely to correctly answer COVID-19 questions than other groups. This is similar to Ali et al., who reported that use of government websites resulted in significantly better knowledge for 3 of their 7 COVID-19 questions (with no difference in the other questions)20.
Those who relied on television news as a primary source, or who used Facebook as an additional news source generally, were less likely to answer COVID-19 questions correctly than other groups. This is concerning, as half of Americans report using television as a source of news14,15 and 66% of Americans use social media such as Facebook as a news source14. This finding differs from that reported by Ali et al.20, which may be a reflection of their sampling method (derived from Facebook advertising). Further evaluation of knowledge across multiple social media sites, and the impact of Facebook’s efforts at “fact-checking” in part due to misinformation reported during COVID-19, is indicated. Lower knowledge in these groups is consistent with a 2018 study that found an inverse relationship between health literacy and using television or social media as a source of information21. Whether these relationships are due to misinformation, a lack of good information or re-enforcement of false beliefs is unknown but, given these associations, it would behoove health communicators to monitor these venues to correct misinformation when it appears.
Our study has several strengths. It is one of the largest pandemic information studies reported to date. The survey was rapidly disseminated amidst the early weeks of the pandemic, offering insight into the public use of information in the midst of a national emergency. Further, we elicited both the single most trusted source as well as secondary sources, which may offer a better indication of primary information source influence over behavior.
Our study is limited by a lack of racial diversity or urban representation. Also, during the survey period, the central Pennsylvania area had not directly experienced significant impacts of COVID-19, thus responses from populations with greater burden may be different. These limitations may decrease the generalizability of these findings. Further, selection bias may contribute to the relatively high knowledge scores, as those who chose to respond to the survey may be more attentive to COVID-19-related issues. The survey was cross-sectional and results may not be generalizable over time.
Conclusions
In summary, adults whose most trusted information source is government health websites are more likely to correctly answer questions about COVID-19 than those with another most trusted source. Individuals whose most trusted source is television news and those who use Facebook as an additional source of news are less likely to correctly answer COVID-19 questions. Effective public health emergency responsiveness requires that effective information dissemination and public compliance with precautionary measures occur8–11. To increase public knowledge of COVID-19 in order to maximize information dissemination and compliance with COVID-19 related public health recommendations, those who provide health information should consider use of the public’s most trusted sources of information, as well as monitoring and correcting misinformation presented by other sources.
| Demographic | Top four single most trusted source of COVID-19 information | |||
|---|---|---|---|---|
| Government website (CDC/NIH/WHO) (%) | Television news (%) | Health system communication (%) | Internet news (%) | |
| Overall (N = 5948) | 42.8* | 27.2* | 9.2* | 7.4* |
| Gender | ||||
| Female (N = 4006) | 46.5 | 25.8 | 9.0 | 7.0 |
| Male (N = 1883) | 35.1 | 30.5 | 9.9 | 8.0 |
| Age | ||||
| 18–35 (N = 723) | 61.4 | 11.9 | 5.0 | 7.3 |
| 36–50 (N = 1297) | 49.7 | 17.8 | 9.3 | 9.1 |
| >50 (N = 3900) | 37.2 | 33.1 | 10.0 | 6.8 |
| Race | ||||
| Nonwhite (N = 271) | 43.5 | 22.5 | 8.9 | 11.4 |
| White (N = 5473) | 42.9 | 27.6 | 9.2 | 7.1 |
| Education | ||||
| Higher education (bachelor’s degree or higher) (N = 3523) | 48.3 | 22.0 | 7.7 | 8.4 |
| Profession | ||||
| Healthcare worker (N = 946) | 55.0 | 15.9 | 13.1 | 3.6 |
*Previously reported15.
| Question (correct answer†) (missing knowledge response and confidence weight (N)‡) | Modeling probability of correct response stratified by single most trusted sourceǁ | Modeling probability of correct response stratified by other information source§ | ||
|---|---|---|---|---|
| OR (95% CL) Gov’t websites (N = 2547) vs. any other source (N = 3382) | OR (95% CL) TV news (N = 1620) vs. any other source (N = 4309) | OR (95% CL) Internet news (N = 439) vs. any other source (N = 5490) | OR (95% CL) Facebook (N = 1157) vs. No Facebook (N = 4677) | |
| *Treatments for the symptoms of COVID-19 are available without a prescription. (True) (19) | 1.28 (1.12, 1.47) | 0.73 (0.62, 0.85) | 1.04 (0.80, 1.35) | 1.04 (0.88, 1.24) |
| *Most hospitalized patients with COVID-19 should be treated in an ICU. (False) (25) | 1.21 (1.04, 1.41) | 0.85 (0.72, 1.00) | 1.37 (1.01, 1.86) | 0.76 (0.63, 0.92) |
| The CDC recommends using corticosteroids for COVID-19 patients with acute respiratory distress syndrome (ARDS). (False) (176) | 0.99 (0.82, 1.18) | 1.20 (0.98, 1.47) | 0.84 (0.59, 1.20) | 0.83 (0.66, 1.04) |
| COVID-19 is the first coronavirus to cause disease in humans. (False) (27) | 1.50 (1.13, 1.98 | 0.60 (0.45, 0.79) | 1.25 (0.72, 2.18) | 0.74 (0.54, 1.01) |
| *Patients with shortness of breath, fever and cough should call the emergency room prior to arrival. (True) (21) | 1.41 (1.15, 1.74) | 0.74 (0.60, 0.91) | 0.97 (0.66, 1.41) | 1.59 (1.20, 2.11) |
| Patients whose first (early) symptoms are severe are more likely to die from COVID-19 than those whose first (early) symptoms are less severe. (False) (47) | 0.92 (0.77, 1.11) | 1.08 (0.87, 1.32) | 1.09 (0.75, 1.57) | 0.88 (0.70, 1.11) |
| *Children ages 5 and under are at higher risk of death from COVID-19. (False) (33) | 1.28 (1.04, 1.57) | 0.95 (0.75, 1.19) | 1.07 (0.72, 1.58) | 0.77 (0.60, 0.98) |
| In someone who has not received the measles vaccine, measles is more contagious than COVID-19. (True) (62) | 1.16 (0,99, 1.35) | 0.76 (0.64, 0.90) | 1.18 (0.88, 1.59) | 0.97 (0.80, 1.19) |
| The incubation period for the coronavirus that causes COVID-19 is up to 21 days. (False) (39) | 1.01 (0.88, 1.17) | 1.09 (0.92, 1.28) | 0.97 (0.73, 1.28) | 0.93 (0.77, 1.11) |
| *Healthy people should wear facemasks to help prevent the spread of COVID-19. (False†) (20) | 1.54 (1.28, 1.84) | 0.87 (0.72, 1.05) | 0.91 (0.66, 1.26) | 0.75 (0.61, 0.93) |
| *A vaccine for COVID-19 should be available within approximately 3 months. (False) (26) | 1.57 (1.23, 1.99) | 0.78 (0.61, 1.00) | 1.49 (0.90, 2.44) | 0.60 (0.46, 0.78) |
| CDC recommends the use of alcohol-based hand sanitizers with greater than 60% ethanol or 70% isopropanol. (True) (34) | 1.32 (1.02, 1.73) | 0.75 (0.57, 0.98) | 0.98 (0.60, 1.60) | 1.52 (1.05, 2.19) |
| Currently, the CDC recommends that everyone with COVID-19 symptoms should get tested. (False) (28) | 1.45 (1.26, 1.67) | 0.74 (0.64, 0.87) | 1.07 (0.82, 1.39) | 1.09 (0.91, 1.29) |
| *Everyone who tests positive for COVID-19 should be treated with hydroxychloroquine (Plaquenil)ii or chloroquine. (False) (39) | 2.19 (1.62, 2.97) | 0.74 (0.55, 0.99) | 1.06 (0.62, 1.79) | 0.53 (0.39, 0.72) |
| *COVID-19 testing is not recommended for individuals with no symptoms, even if they were exposed to someone with confirmed COVID-19 within the past 2 weeks. (True) (20) | 1.05 (0.90, 1.23) | 1.05 (0.88, 1.24) | 1.05 (0.78, 1.41) | 0.95 (0.78, 1.16) |
| 15-item (616) | 1.21 (1.16, 1.26) | 0.87 (0.83, 0.91) | 1.08 (1.00, 1.17) | 0.93 (0.88, 0.97) |
| 8-item (616) | 1.28 (1.21, 1.35) | 0.85 (0.80, 0.91) | 1.09 (0.98, 1.22) | 0.89 (0.83, 0.95) |
Abbreviations. OR, Odds ratio; CL, Confidence limits.
Statistically significant comparisons are bolded (adjusted p < .05 for individual items; p < .05 for 8- and 15-item composites).
‡The statistical model used to calculate weighted predicted probabilities of correct responses (and corresponding 95% confidence limits) while accounting for the corresponding confidence in the response excluded N = 616 missing knowledge response questions and N = 616 missing weight values. Note that N = 616 reflects the number of items, not the number of patient respondents. Simple imputation was used for confidence items where respondents answered the knowledge component but skipped the corresponding confidence component (N = 170 imputed confidence level values). After imputing confidence levels, any item missing a knowledge response was also missing a confidence level, and vice versa.
*Item belongs to selected 8-item subset of “basic knowledge”, not requiring detailed or nuanced medical knowledge.
†Correct response according to information publicly available from the Centers for Disease Prevention and Control website as of the date the survey was distributed (25 March 2020).
ǁCurrent single most trusted source is defined by the question: “What is your current, single most trusted source for information about health issues like COVID-19? (Please pick one)”. N = 19 respondents were missing values for current single most trusted source (excluded N = 19 respondents; N = 285 missing fixed [subject] effects). N = 5929 patient respondents were included in the analysis for a total of N = 88,323 observations used. Note that comparisons shown in this table are not mutually exclusive. For example, those who selected Internet: government websites (CDC, NIH, WHO) are included in the “any other source” group when comparing television news channels to any other source and internet: news websites to any other source.
§Other information source is defined by the question: “What other information sources do you use for information about health issues like COVID-19? Select all that apply”. “No Facebook” includes any combination of the following selections: family and friends, Instagram, Internet: government websites (CDC, NIH, WHO), Internet: news websites, Penn State Health Communications, podcasts, print news, television news channels, Twitter, radio, other internet sites, other social media and other. N = 114 respondents did not select any of the options provided, and thus were treated as missing values, as it is unknown if the respondent skipped the question or if none of the options available to select applied to them (excluded N = 114 respondents; N = 1710 missing fixed [subject] effects). N = 5834 patient respondents were included in the analysis for a total of N = 86,912 observations used.
Acknowledgements
Without the assistance of the following individuals and groups, the scope and scale of this project would not have been possible. We thank Stacy Beers, Amy Peiffer and the Penn State Health and Penn State College of Medicine Marketing teams, Susan Chobanoff, Neal Thomas, Leslie Parent, Sarah Bronson, Heather Stuckey-Peyrot and the Penn State Qualitative Mixed Methods Core.
Transparency
Declaration of funding
Funding was provided by the Huck Institutes of the Life Sciences and the Social Science Research Institute of Pennsylvania State University (under Grant 7601), and the Pennsylvania State College of Medicine Department of Family and Community Medicine (DFCM) (under Grant 7601-M). The DFCM faculty was involved in study design and manuscript production. No other funders were involved in data collection, analysis, interpretation or any aspect of manuscript production.
Declaration of financial/other relationships
S.M.S. and J.C.G. have disclosed that they are medical students at Penn State College of Medicine. L.J.V.S., E.L.M., B.S., E.W., V.M.C. and R.P.L. have disclosed that they are employees of Penn State College of Medicine. CMRO peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Author contributions
Conception and design: R.P.L., L.J.V.S., E.L.M., B.S. Analysis and interpretation: R.P.L., E.W., V.M.C., S.M.S. Drafting or revising for intellectual content: S.M.S., R.P.L., E.W. Final approval: S.M.S., L.J.V.S., J.C.G., E.L.M., B.S., E.W., V.M.C., R.P.L. All authors agree to be accountable for all aspects of the work.
Data availability statement
The data that support the findings of this study are available from the corresponding author, R.P.L., upon reasonable request.
Notes
i Facebook is a registered trademark of Facebook, Inc., Menlo Park, CA, USA.
ii Plaquenil is a registered trademark of Concordia Pharmaceuticals Inc., Luxembourg city, Luxembourg.
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