Introduction Much testing in medicine is aimed at healthy people to facilitate the early detection of health conditions. However, there is growing evidence that early detection is a double-edged sword that may cause harm in the form of overdiagnosis. The media can be seen as a major generator of consumer demand for health services. Previous research shows that media coverage tends to overstate the benefits and downplay the harms of medical interventions for the sick, and often fails to cover relevant conflicts of interest of those promoting those interventions. However, little is known about how the benefits and harms of testing the healthy are covered by media. This study will examine the media coverage of the benefits and harms of testing the healthy, and coverage of potential conflicts of interest of those promoting the testing.
Methods and analysis We will examine five tests: 3D mammography for the early detection of breast cancer; blood liquid biopsy for the early detection of cancer; blood biomarker tests for the early detection of dementia; artificial intelligence technology for the early detection of dementia; and the Apple Watch Series 4 electrocardiogram sensor for the early detection of atrial fibrillation. We will identify media coverage using Google News and the LexisNexis and ProQuest electronic databases. Sets of two independent reviewers will conduct story screening and coding. We will include English language media stories referring to any of the five tests from January 2016 to May 2019. We will include media stories if they refer to any benefits or harms of the test for our conditions of interest. Data will be analysed using categorical data analysis and multinomial logistic regression.
Ethics and dissemination No ethical approval is required for this study. Results will be presented at relevant scientific conferences and in peer-reviewed literature.
- testing the healthy
- media coverage
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
Contributors MO, RM, AB and CM have been primarily responsible for study conception, design and designing the data coding approach. MJ advised on statistical analysis. JZ and AF helped pilot the search strategy and coding tool. MO drafted the first version of this manuscript. All authors provided critical evaluation and revision of the manuscript and had given final approval of the manuscript accepting responsibility for all aspects.
Funding This study will not receive any specific funding. MO is supported by a European Union Marie Skłodowska-Curie postdoctoral fellowship. AB and RM are investigators on a National Health and Medical Research Council of Australia (NHMRC) funded CRE grant no 1104136. RM is supported by an NHMRC grant, #1124207. AF is a postdoctoral fellow on an Australian NHMRC project grant no1122332. CM is supported by an Australian NMHRC Research Fellowship. This specific study received no specific grant from any funding agency in public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.