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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 24, 2020
Date Accepted: Sep 22, 2020

The final, peer-reviewed published version of this preprint can be found here:

The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias

Han L, Boniface ER, Han L, Albright J, Doty N, Darney BG

The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias

J Med Internet Res 2020;22(10):e20619

DOI: 10.2196/20619

PMID: 33104002

PMCID: 7652681

Warning: This is an author submission that is not peer-reviewed or edited.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.

The abortion web ecosystem: an analysis of trustworthiness and bias

  • Leo Han; 
  • Emily R Boniface; 
  • Lisa Han; 
  • Jonathan Albright; 
  • Nora Doty; 
  • Blair G Darney

ABSTRACT

Background:

People use the internet as a primary source to learn about medical procedures and their associated safety and risks. Although abortion is one of the most common procedures among reproductive women in the world, it is controversial and highly politicized. Substantial scientific evidence demonstrates that abortion as safe and does not increase a woman’s future risk for depression disorders or infertility. The extent to which information found on the internet reflect these medical facts in a trustworthy and unbiased manner is not known.

Objective:

The purpose of this study was to collate and describe the trustworthiness and political slant or bias of web-based information about abortion safety and risks of depression and infertility.

Methods:

We performed a cross sectional study of internet websites on three search topics: is abortion safe?; 2) does abortion cause infertility?; and 3) does abortion cause depression? We used the Google Adwords tool to identify the most associated search terms with those topics and Google’s search engine to generate databases of websites related to each topic. We then classified and rated each website in terms of content slant (pro-choice, neutral, anti-choice), clarity of the slant (easy/medium/difficult to tell), trustworthiness (scale 1-5, 5=most trustworthy), type (forum, feature, scholarly article, resource page, or news article), and top-level domain (.com, .net, .org, edu., .gov or international domain). We compared website characteristics by search topic (safety, depression, or infertility) using bivariate tests. We summarized trustworthiness, using the median and interquartile range (IQR). We used box plots to visually compare trustworthiness by slant and by domain type.

Results:

Our search methods yielded a total of 111, 120 and 85 unique sites for safety, depression, and infertility respectively. For all sites (n=316), 57% were neutral, 35% anti-choice and 7% pro-choice. The median trustworthiness was 2.7 (IQR 1.7-3.7) and not significantly different across topics (P=.409). Anti-choice sites were less trustworthy (median trustworthiness=1.3, IQR 1.0-1.7) compared to neutral (3.3, IQR 2.7-4.0) and pro-choice sites (3.7, IQR 3.3-4.3). Anti-choice sites were also more likely to have slant clarity that was “difficult to tell” (36.6%) compared to neutral (13.8%) or pro-choice sites (17.4%, P-value < .001). A negative search term used in the topic of safety such as “risks” resulted in sites with lower trustworthiness scores than search terms with the word “safety” (median trustworthiness 1.7 vs 3.7; P-value <.001)

Conclusions:

People seeking information about the safety and potential risks of abortion are likely to encounter substantial amounts of untrustworthy and slanted/biased abortion information. Anti-choice sites are prevalent, often difficult to identify as anti-choice, and less trustworthy than neutral or pro-choice sites. Web searches may lead the public to believe abortion is riskier than it is.


 Citation

Please cite as:

Han L, Boniface ER, Han L, Albright J, Doty N, Darney BG

The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias

J Med Internet Res 2020;22(10):e20619

DOI: 10.2196/20619

PMID: 33104002

PMCID: 7652681

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