Printer Friendly

FAKE NEWS, HEALTH LITERACY, AND MISINFORMED PATIENTS: THE FATE OF SCIENTIFIC FACTS IN THE ERA OF DIGITAL MEDICINE.

1. Introduction

Fabrication and erroneousness of health news in social media represent an unrealized menace to the public health. Inspecting social media leading distributed news may be instrumental in detection of top fake medical information wrongly educating the society (Orazulike, 2018; Petcu, 2017; Pilkington, 2017; Sternadori, 2017; Tulloch, 2016) and may galvanize authorities to put alerts on predisposed domains or accurately assess those producing fake health news. (Waszak, Kasprzycka-Waszak, and Kubanek, 2018) Exploiting the panics and vulnerabilities of consumers, companies employ unscrupulous marketing strategies to mislead the public and prosper. (Haithcox-Dennis, 2018)

2. Literature Review

Health policy is shaped by determined persons who cut down elaborate notions to snippets that back their viewpoint and that may be contingent on unreliable information (Benedikter, Siepmann, and Reymann, 2017; Caruso et al., 2017; Farber, 2017; Gutu, 2018; Mihaila, 2017) but, as the individuals circulating those sound bites know, they are adequate in accomplishing their policy objectives. (Mainous III, 2018) Just as it is beneficial to suspect scientific falsehoods, unfounded connections and unconfirmed assertions in health care, patients should be circumspect so as to put an end to unsubstantiated contentions, established practices and acceptances in medical education. (Hodges, 2017)

3. Methodology

Using data from Morning Consult and Pew Research Center, I performed analyses and made estimates regarding percentage of online news consumers who get news online from news organizations/people they are close with/people they are not particularly close with often/sometimes (of those who get news online from each, percentage who say that the news they get from news organizations/people they are close with/people they are not particularly close with is very/somewhat near to their interests), percentage of each social networking website's users who ever get news on the site, percentage of social media news consumers who click on links to news stories/"like" news stories/share or repost news stories/comment on news stories/post links to news stories themselves/discuss issues in the news on the site/post their own photos or videos of a news event, percentage of news instances through each pathway in which a/no follow-up action was taken, percentage of Facebook news consumers who regularly see news on Facebook about entertainment/people and events in their communities/sports/national government and politics/crime/health and medicine/local government and politics/local weather and traffic/international news/science and technology/business, and percentage of U.S. adults who say they shared a political news story online they later found out/knew at the time was made up.

4. Results and Discussion

Any individual can have access to the internet, but few patients have the comprehension to precisely decipher outcomes of medical research. Plausibly, fake news headlines attract the curiosity of persons worried about a medical condition, and the ensuing clickbait may lead the potential customer to a website or source purposed to make money on the ultimate endorser of the narrative, thus entailing the purchase of remedies, enhancements, tests and procedures not thus far proved to be advisable in such cases. (Bolton and Yaxley, 2017) A flawlessly cognizant public is indispensable to designing prudent substance utilization, prevention, and treatment policies. (Arndt and Jones, 2018) (Figures 1-6)
Figure 1 Percentage of online news consumers who get news online
from... often/sometimes

                            Often  Sometimes  Net

News organizations          39%    44%        83%
People they are close with  17%    57%        74%
People they are not          9%    31%        40%
particulary close with

Of those who get news online from each percentage who say that the news
they get from...is very/somewhat near to their interests

                            Very  Somewhat  Net

News organizations          13%   64%       77%
People they are close with  17%   62%       79%
People they are not          7%   41%       48%
particulary close with

Sources: Pew Research Center; my survey among 2,900 individuals
conducted June 2018.

Note: Table made from bar graph.

Figure 2 Percentage of news instances through each pathway in which...

                               No follow-up     A follow-up action
                             action was taken        was taken

Family or friend email/text        29%                  71%
Search engine                      39%                  61%
Social media                       48%                  52%
News org email/text/alert          52%                  42%
News org website/app               53%                  47%

Sources: Pew Research Center; my survey among 2,900 individuals
conducted June 2018.

Note: Table made from bar graph.

Figure 3 Percentage of each social networking website's users who ever
get news on the site

Reddit          66%
Twitter         55%
Facebook        50%
Google Plus     32%
Tumblr          31%
YouTube         22%
Myspace         16%
Linkedln        15%
Instagram       15%
Vine            12%
Pinterest        6%

Sources: Pew Research Center; my survey among 2,900 individuals
conducted June 2018.

Note: Table made from bar graph.

Figure 4 Percentage of social media news consumers who...

                                 Often   Sometimes   Net

Click on links to news stories   27%     52%         79%
"Like" news stories              17%     44%         61%
Share or repost news stories     12%     40%         52%
Comment on news stories           9%     30%         39%
Post links to news stories        7%     31%         38%
themselves
Discuss issues in the news on     6%     28%         34%
the site
Post their own photos or          4%     18%         22%
videos of a news event

Sources: Pew Research Center; my survey among 2,900 individuals
conducted June 2018.

Note: Table made from bar graph.

Figure 5 Percentage of Facebook news consumers who regularly see news
on Facebook about...

Entertainment                      77%
People & events in my community    68%
Sports                             60%
National gov't & politics          58%
Crime                              54%
Health & medicine                  48%
Local gov't & politics             46%
Local weather & traffic            44%
International news                 41%
Science & technology               39%
Business                           34%

Sources: Pew Research Center; my survey among 2,900 individuals
conducted June 2018.

Note: Table made from bar graph.

Figure 6 Percentage of U.S. adults who say they... Shared a political
news story online they later found out was made up

Shared a political news story online   19%
they later found out was made up
Shared a political news story online   17%
they knew at the time was made up
Did either/both of these               27%

Sources: Pew Research Center; my survey among 2,900 individuals
conducted June 2018.

Note: Table made from bar graph.


5. Conclusions

The stream of healthcare and scientific news to the public may be polluted at diverse points along a contaminated flow of information. (Schwitzer, 2017) Unconfirmed therapies may give rise to deceptive expectations in patients with grave medical conditions, faulty claims may add perturbation to already deep-rooted clinical protocols, and inaccurate information regarding adverse side effects or undocumented risks may impede treatment or cause persons to decline relevant preventive health interventions. (Wiederhold, 2017)

Acknowledgments

This paper was supported by Grant GE-1824624 from the Social Science Research Unit at CLI, Washington, DC.

Author Contributions

The author confirms being the sole contributor of this work and approved it for publication.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

REFERENCES

Arndt, S., and D. S. Jones (2018). "Preventing Sensationalistic Science and Fake News about Substance Use," BioMed Central 13: 11.

Benedikter, R., K. Siepmann, and A. Reymann (2017). "'Head-Transplanting' and 'Mind-Uploading:' Philosophical Implications and Potential Social Consequences of Two Medico-Scientific Utopias," Review of Contemporary Philosophy 16: 38-82.

Bolton, D. M., and J. Yaxley (2017). "Fake News and Clickbait - Natural Enemies of Evidence-Based Medicine," BJU International 119(S5): 8-9.

Caruso, R., C. Arrigoni, A. Magon, F. Pittella, F. Dellafiore, A. M. Grugnetti, D. Ausili, and F. Auxilia (2017). "Health Determinants in Italian Type 2 Diabetes Mellitus (T2DM) Patients: A Critical Gender Differences Analysis," Journal of Research in Gender Studies 7(2): 93-108.

Farber, M. (2017). "The Future of Journalistic Labor in the Age of Digital Narratives: The Algorithmic Authority of Automated News as a Legitimate Knowledge Producer," Psychosociological Issues in Human Resource Management 5(2): 199-204.

Gutu, G. (2018). "Interferential Creativity: The Case of Paul Celan," Creativity 1(2): 113-135.

Haithcox-Dennis, M. (2018). "Reject, Correct, Redirect: Using Web Annotation to Combat Fake Health Information - A Commentary," American Journal of Health Education 49(4): 206-209.

Hodges, B. D. (2017). "Rattling Minds: The Power of Discourse Analysis in a Post-Truth World," Medical Education 51(3): 235-237.

Mainous III, A. G. (2018). "Perspectives in Primary Care: Disseminating Scientific Findings in an Era of Fake News and Science Denial," Annals of Family Medicine 16(6): 490-491.

Mihaila, R. (2017). "The Lying Epidemic," Educational Philosophy and Theory 49(6): 580-581.

Orazulike, U. (2018). "Post-Brexit Threats to Work Safety and Health Standards and Good Working Conditions in the UK," Psychosociological Issues in Human Resource Management 6(1): 63-95.

Petcu, C. (2017). "Democratic Sexuality and Alienated Capitalism in Houellebecq's Novels," Contemporary Readings in Law and Social Justice 9(2): 81-87.

Pilkington, O. A. (2017). "Structural Complexity of Popular Science Narratives of Discovery as an Indicator of Reader-awareness: A Labov-inspired Approach," Linguistic and Philosophical Investigations 16: 7-28.

Schwitzer, G. (2017). "Pollution of Health News: Time to Drain the Swamp," The BMJ 356: j1262.

Sternadori, M. (2017). "Empathy May Curb Bias: Two Studies of the Effects of News Stories on Implicit Attitudes toward African Americans and Native Americans," Contemporary Readings in Law and Social Justice 9(2): 11-27.

Tulloch, L. (2016). "An Auto-Ethnography of Vegan Praxis and Encounters with the Meat-Eating Cyborg," Review of Contemporary Philosophy 15: 28-45.

Waszak, P. M., W. Kasprzycka-Waszak, and A. Kubanek (2018). "The Spread of Medical Fake News in Social Media - The Pilot Quantitative Study," Health Policy and Technology 7(2): 115-118.

Wiederhold, B. K. (2017). "Don't Tweet False Hope to Patients Desperate for a Cure," Cyberpsychology, Behavior, and Social Networking 20(3): 141.

doi:10.22381/AM1720186

SOFIA BRATU

sofiabratu@yahoo.com

Spiru Haret University, Bucharest

How to cite: Bratu, Sofia (2018). "Fake News, Health Literacy, and Misinformed Patients: The Fate of Scientific Facts in the Era of Digital Medicine," Analysis and Metaphysics 17: 122-127.

Received 18 August 2018 * Received in revised form 12 October 2018

Accepted 20 October 2018 * Available online 11 December 2018
COPYRIGHT 2018 Addleton Academic Publishers
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2018 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Bratu, Sofia
Publication:Analysis and Metaphysics
Article Type:Report
Date:Jan 1, 2018
Words:1648
Previous Article:REGULATION OF AUTOMATED INDIVIDUAL DECISION-MAKING AND ARTIFICIALLY INTELLIGENT ALGORITHMIC SYSTEMS: IS THE GDPR A POWERFUL ENOUGH MECHANISM TO...
Next Article:BIG DATA LEARNING ANALYTICS AND ALGORITHMIC DECISION-MAKING IN DIGITAL EDUCATION GOVERNANCE.
Topics:

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters