Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Dec 20, 2020
Date Accepted: Sep 21, 2021
Date Submitted to PubMed: Nov 24, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Obesity Communication with Etiology and Disease: Automated Content Analysis of Digital News, 2010-2019
ABSTRACT
Background:
The fact that the number of population suffering from obesity has increased worldwide calls into question on media efforts for informing the public. This research attempts to determine the ways in which the mainstream digital news covers the etiology of obesity and diseases associated with the burden of obesity.
Objective:
The dual objectives of this study are to obtain an understanding of what the news says about obesity and to explore meanings in data by extending preconceived grounded theory.
Methods:
We propose an automatic content analysis tool, DiVoMiner. This computer-aided platform is designed to organize and filter large sets of data based on patterns of word occurrence and latent topics. Another programming language Python 3 is employed to explore connections and patterns created by the aggregated interactions. The 10 years of news text compared the development of obesity coverage and its potential impact on perception in Mainland China, Hong Kong, and Taiwan. Digital news stories covering obesity along with affliction and consequence inferences in nine newspapers were sampled.
Results:
A total of 30,968 news stories were identified with increasing attention since 2016. The highest intensity of newspaper coverage of obesity communication was found in Taiwan. Overall, a stronger focus on two shared causative attributes of obesity are on stress (n = 4,483, 33.0%) and tobacco use (n = 3143, 23.2.0%). Similar to the previous studies, the discourse between the obesity epidemic and personal afflictions is the most emphasized approach (n = 13,587, 80.0%). Additionally, the burden of obesity and cardiovascular diseases are implied the most (n = 8,477, 42.2%) despite the aggregated interaction of edge centrality shows the highest link between the use of “obesity” and “cancer”. The discussion indicated that the inclination of blaming personal attributes for health afflictions potentially limits social and governmental responsibility for addressing this issue. The strategy of various obesity communication for news gatekeepers, health communication researchers, and policy-makers are noted.
Conclusions:
This study goes beyond traditional journalism studies by extending the framework of computational and customizable online texts. This could set a norm for researchers and practitioners who work on the data projects largely for a different and innovative attempt. However, challenges of methods should be faced, including the lack of standards of automated content measures. Clinical Trial: not available.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.