Evidence map›Paper›PMID 33492238›Full record

ArticleJournal of medical Internet research2021

Adherence of Internet-Based Cancer Risk Assessment Tools to Best Practices in Risk Communication: Content Analysis.

Erika A Waters, Jeremy L Foust, Laura D Scherer, Amy McQueen, Jennifer M Taber

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Testing Explanations for Skepticism of Personalized Risk Information.Medical decision making : an international journal of the Society for Medical Decision Making · 2023
    Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Erika A WatersWashington University School of Medicine, Saint Louis, MO, United States.ORCID 0000-0001-7402-0133
Jeremy L FoustKent State University, Kent, OH, United States.ORCID 0000-0002-5386-7746
Laura D SchererUniversity of Colorado School of Medicine, Denver, CO, United States.ORCID 0000-0002-8660-7115
Amy McQueenWashington University School of Medicine, Saint Louis, MO, United States.ORCID 0000-0003-0332-3983
Jennifer M TaberKent State University, Kent, OH, United States.ORCID 0000-0003-3285-4871

Funding

COMMUNICATING MULTIPLE DISEASE RISKS: A TRANSLATION OF RISK PREDICTION SCIENCER01CA190391 · NCI · WASHINGTON UNIVERSITY · PI WATERS, ERIKA A · 2015 to 2018
$1.4M
NCI NIH HHS R01 CA190391
6 · The paper itself

Abstract

backgroundInternet-based risk assessment tools offer a potential avenue for people to learn about their cancer risk and adopt risk-reducing behaviors. However, little is known about whether internet-based risk assessment tools adhere to scientific evidence for what constitutes good risk communication strategies. Furthermore, their quality may vary from a user experience perspective.

objectiveThis study aims to understand the extent to which current best practices in risk communication have been applied to internet-based cancer risk assessment tools.

methodsWe conducted a search on August 6, 2019, to identify websites that provided personalized assessments of cancer risk or the likelihood of developing cancer. Each website (N=39) was coded according to standardized criteria and focused on 3 categories: general website characteristics, accessibility and credibility, and risk communication formats and strategies.

resultsSome best practices in risk communication were more frequently adhered to by websites. First, we found that undefined medical terminology was widespread, impeding comprehension for those with limited health literacy. For example, 90% (35/39) of websites included technical language that the general public may find difficult to understand, yet only 23% (9/39) indicated that medical professionals were their intended audience. Second, websites lacked sufficient information for users to determine the credibility of the risk assessment, making it difficult to judge the scientific validity of their risk. For instance, only 59% (23/39) of websites referenced the scientific model used to calculate the user's cancer risk. Third, practices known to foster unbiased risk comprehension, such as adding qualitative labels to quantitative numbers, were used by only 15% (6/39) of websites.

conclusionsLimitations in risk communication strategies used by internet-based cancer risk assessment tools were common. By observing best practices, these tools could limit confusion and cultivate understanding to help people make informed decisions and motivate people to engage in risk-reducing behaviors.

Indexed as

CommunicationHumansInternet-Based InterventionNeoplasmsRisk Assessmenthealth communicationinternetpersonalized medicinerisk assessment

Identifiers

PMID33492238
PMCPMC7870349

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.