Making sense of cancer risk calculators on the web

Disinformation: A Bibliometric Review

OBJECTIVES

This paper aimed to provide a systematic review of relevant articles from the perspectives of literature distribution, research hotspots, and existing results to obtain the frontier directions in the field of disinformation.

METHODS

We analyzed disinformation publications published between 2002 and 2021 using bibliometric methods based on the Web of Science. There were 5666 papers analyzed using Derwent Data Analyzer (DDA).

RESULTS

The result shows that the USA was the most influential country in this area, while Ecker and Lewandowsky from the University of Western Australia published the largest volumes of papers. Keywords such as "social media", "COVID-19", and "vaccination" have gained immense popularity recently.

CONCLUSIONS

We summarized four themes that are of the biggest concern to scholars: group heterogeneity of misinformation in memory, disinformation mechanism in social media, public health related to COVID-19, and application of big data technology in the infodemic. The future agenda of disinformation is summarized from three aspects: the mechanism of disinformation, social media users, and the application of algorithms. This work can be a meaningful resource for researchers' study in the area of disinformation.

Review of interactive digital solutions improving health literacy of personal cancer risks in the general public

BACKGROUND

Health literacy is crucial in understanding the many risk factors for cancer. Low health literacy is associated with low adherence to medication, poor health status, and increased health care costs. Modern technology allows us to educate the general public on their risks. We focus herein on the available mobile applications and online web tools for the evaluation of cancer risk in the general public.

METHODS

A systematic search was performed for cancer risk calculators mobile applications on both Google Play and the App Store and for online cancer risk calculators using Google, Bing, Yahoo! and Baidu.

RESULTS

For mobile applications, out of 250 different apps found on GooglePlay, 16 Android applications were retained for evaluation in this review and for the AppStore, out of 10 different apps, 7 Android applications were retained for evaluation in this review. Only three apps were available for both Android and iOS systems. For web tools, a list of 20 tools was retained and evaluated.

CONCLUSION

This review presents the most popular and prominent tools and their strengths and possible weaknesses are evaluated. We discuss not only its current state as it relates to general knowledge about cancer risks, but also barriers and future directions. It is imperative that as developers continue to create and improve such tools, health care providers remain aware of these efforts in order to properly guide patients towards appropriate resources and educate them on both their usefulness and limitations.

Informed Choice and Nudging in Mammography Screening: A Discourse Analysis of Australian and Scandinavian Webpages

The tension between providing adequate information and achieving sufficiently high participation in population-based screening programmes, such as mammography, represents an ongoing challenge for health authorities. The theory of nudge illuminates how individuals may be nudged towards healthy behaviours without restricting individual freedom of choice. We analyse information provided on health authority webpages and uncover the subject positions available to healthy women deciding whether to participate in screening. We do so by comparing different policy contexts where women must opt in to screening (Australia) or opt out (Scandinavia).

We conclude that information is used to nudge women towards screening. Alongside focus on the ease of being screened, tensions exist in simultaneously portraying women as being at risk of breast cancer and providing reassurance of their healthy state. We identify persuasive devices that emphasise responsibility to participate in screening and conclude that webpages play a dynamic role in authorities’ attempts to, on one hand, achieve high participation in screening, and on the other, promote mammography screening as an individual choice.

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

BACKGROUND

Internet-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.

OBJECTIVE

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

METHODS

We 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.

RESULTS

Some 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.

CONCLUSIONS

Limitations 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.

"Mini Dial-A-Nurses" and "Good Brands": What Are the Desirable Features of Online HIV/STI Risk Calculators?

A wide variety of risk calculators estimate individuals' risk for HIV/sexually transmitted infections (STI) online. These tools can help target HIV/STI screening and optimize clinical decision-making. Yet, little evidence exists on suitable features for these tools to be acceptable to end-users. We investigated the desirable characteristics of risk calculators among STI clinic clients and testing service providers. Participants interacted with online HIV/STI risk calculators featuring varied target audiences, completion lengths, and message outputs. Thematic analysis of focus groups identified six qualities that would make risk calculators more appealing for online client use: providing personalized risk assessments based on users' specific sexual behaviors and HIV/STI-related concerns; incorporating nuanced risk assessment and tailored educational information; supplying quantifiable risk estimates; using non-stigmatizing and inclusive framing; including explanations and next steps; and developing effective and appropriate branding. Incorporating these features in the design of online HIV/STI risk calculators may improve their acceptability among end-users.

Translating Cancer Risk Prediction Models into Personalized Cancer Risk Assessment Tools: Stumbling Blocks and Strategies for Success

Cancer risk prediction models such as those published in Cancer Epidemiology, Biomarkers, and Prevention are a cornerstone of precision medicine and public health efforts to improve population health outcomes by tailoring preventive strategies and therapeutic treatments to the people who are most likely to benefit. However, there are several barriers to the effective translation, dissemination, and implementation of cancer risk prediction models into clinical and public health practice. In this commentary, we discuss two broad categories of barriers. Specifically, we assert that the successful use of risk-stratified cancer prevention and treatment strategies is particularly unlikely if risk prediction models are translated into risk assessment tools that (i) are difficult for the public to understand or (ii) are not structured in a way to engender the public's confidence that the results are accurate. We explain what aspects of a risk assessment tool's design and content may impede understanding and acceptance by the public. We also describe strategies for translating a cancer risk prediction model into a cancer risk assessment tool that is accessible, meaningful, and useful for the public and in clinical practice.

Chinese primary knee osteoarthritis progression cohort (CPKOPC) to evaluate the progression of knee osteoarthritis in the Beijing population: a prospective cohort study protocol

INTRODUCTION

Millions of patients are currently suffering from pain and dysfunction caused by osteoarthritis (OA), and billions of dollars have been invested into treatment. Because there is no effective treatment that can reverse the progression of knee OA, it is important to determine the risk factors that may influence the progression. However, although there are many studies that examine risk factors for progression, there are only a few that specifically focus on the impact of each risk factor for predicting progression of knee OA. This study aimed to develop a cohort of patients with primary knee OA in the Beijing area to establish models that identify the influence of each risk factor on the prediction of knee OA progression.

METHODS AND ANALYSIS

This is a prospective, multicentre, hospital-based cohort study. The study population comprises 2000 patients with primary knee OA from the Beijing area. The recruitment and baseline visits started in December 2017 and will finish in November 2018. After baseline visits, the patients will be followed for 3 years or until the occurrence of primary outcomes. Demographic variables will be collected during the baseline visit. Influencing factors including occupational exposures, family history and treatment will be collected at baseline and each follow-up visit. The primary outcome measure is a comprehensive index which will be combined with clinical WOMAC score, imaging K-L grade and clinical outcomes. These data will also be collected at baseline and each follow-up visit.

ETHICS AND DISSEMINATION

This study protocol has been approved by Peking University Third Hospital Medical Science Research Ethics Committee. All the eligible participants will give written informed consent. The findings will be published in peer-reviewed journals and presented at national or international conferences. Besides, the results will be disseminated to all participants via the social software 'WeChat'.

TRIAL REGISTRATION NUMBER

ChiCTR-ROC-17013790; preresults.

The Pink Underside: The Commercialization of Medical Risk Assessment and Decision-Making Tools for Hereditary Breast Cancer Risk

The growth of the Internet since the millennium has opened up a myriad of opportunities for education, particularly in medicine. Although those looking for health care information used to have to turn to a face-to-face doctor's visit, an immense library of medical advice is now available at their fingertips. The BRCA genetic predispositions (mutations of the BRCA1 and BRCA2 breast cancer genes) which expose men and women to greater risk of breast, ovarian, and other cancers can be researched extensively online. Several nonprofit organizations now offer online risk assessment and decision-making tools meant to supplement conversation with medical professionals, which in actuality are quickly replacing it. We argue here through a critical qualitative template analysis of several such tools that the discursive frameworks utilized are prone to fearmongering, commercialization, and questionable validity. Left unchecked, these assessment tools could do more harm than good in driving young women especially to take unnecessary extreme surgical action.

Randomized Controlled Trial of an Educational Intervention Using an Online Risk Calculator for Knee Osteoarthritis: Effect on Risk Perception

OBJECTIVE

Young adults, in general, are not aware of their risk of knee osteoarthritis (OA). Understanding risk and risk factors is critical to knee OA prevention. We tested the efficacy of a personalized risk calculator on accuracy of knee OA risk perception and willingness to change behaviors associated with knee OA risk factors.

METHODS

We conducted a randomized controlled trial of 375 subjects recruited using Amazon Mechanical Turk. Subjects were randomized to either use a personalized risk calculator based on demographic and risk-factor information (intervention), or to view general OA risk information (control). At baseline and after the intervention, subjects estimated their 10-year and lifetime risk of knee OA and responded to contemplation ladders measuring willingness to change diet, exercise, or weight-control behaviors.

RESULTS

Subjects in both arms had an estimated 3.6% 10-year and 25.3% lifetime chance of developing symptomatic knee OA. Both arms greatly overestimated knee OA risk at baseline, estimating a 10-year risk of 26.1% and a lifetime risk of 47.8%. After the intervention, risk calculator subjects' perceived 10-year risk decreased by 12.9 percentage points to 12.5% and perceived lifetime risk decreased by 19.5 percentage points to 28.1%. Control subjects' perceived risks remained unchanged. Risk calculator subjects were more likely to move to an action stage on the exercise contemplation ladder (relative risk 2.1). There was no difference between the groups for diet or weight-control ladders.

CONCLUSION

The risk calculator is a useful intervention for knee OA education and may motivate some exercise-related behavioral change.

Development and feasibility of a personalized, interactive risk calculator for knee osteoarthritis

Background

The incidence of knee osteoarthritis (OA) is rising. While several risk factors have been associated with the development of knee OA, this information is not readily accessible to those at risk for osteoarthritis. Risk calculators have been developed for several prevalent chronic conditions but not for OA. Using published evidence on established risk factors, we developed an interactive, personalized knee OA risk calculator (OA Risk C) and conducted a pilot study to evaluate its acceptability and feasibility.

Methods

We used the Osteoarthritis Policy (OAPol) Model, a validated, state-transition simulation of the natural history and management of OA, to generate data for OA Risk C. Risk estimates for calculator users were based on a set of demographic and clinical factors (age, sex, race/ethnicity, obesity) and select risk factors (family history of knee OA, occupational exposure, and history of knee injury). OA Risk C presents personalized risk of knee OA in several ways to maximize understanding among a wide range of users. We conducted a study of 45 subjects in a primary care setting to establish the feasibility and acceptability of the OA risk calculator. Pilot study participants were asked several questions regarding ease of use, clarity of presentation, and clarity of the graphical representation of their risk. These questions used a five-level agreement scale ranging from strongly disagree to strongly agree.

Results

OA Risk C depicts information about users’ risk of symptomatic knee OA in 5 year intervals. Study participants estimated their lifetime risk at 38 %, while their actual lifetime risk, as estimated by OA Risk C, was 25 %. Eighty-four percent of pilot study participants reported that OA Risk C was easy to understand, and 89 % agreed that the graphs depicting their risk were clear and comprehensible.

Conclusions

We have developed a personalized, computer-based OA risk calculator that is easy to use. OA Risk C may be utilized to estimate individuals’ knee OA risk and to deliver educational and behavioral interventions focused on osteoarthritis risk reduction.

Directing the public to evidence-based online content

To direct online users searching for gynecologic cancer information to accurate content, the Centers for Disease Control and Prevention's (CDC) 'Inside Knowledge: Get the Facts About Gynecologic Cancer' campaign sponsored search engine advertisements in English and Spanish. From June 2012 to August 2013, advertisements appeared when US Google users entered search terms related to gynecologic cancer. Users who clicked on the advertisements were directed to relevant content on the CDC website. Compared with the 3 months before the initiative (March-May 2012), visits to the CDC web pages linked to the advertisements were 26 times higher after the initiative began (June-August 2012) (p<0.01), and 65 times higher when the search engine advertisements were supplemented with promotion on television and additional websites (September 2012-August 2013) (p<0.01). Search engine advertisements can direct users to evidence-based content at a highly teachable moment--when they are seeking relevant information.

Risk prediction tools in surgical oncology

Healthcare has increasingly focused on patient engagement and shared decision-making. Decision aids can promote engagement and shared decision making by providing patients and their providers with care options and outcomes. This article discusses decision aids for surgical oncology patients. Topics include: short-term risk prediction following surgery, long-term risk prediction of survival and recurrence, the combination of short- and long-term risk prediction to help guide treatment choice, and decision aid usability, transparency, and accessibility.

An information-centric framework for designing patient-centered medical decision aids and risk communication

Risk communication is a major challenge in productive patient-physician communication. Patient decision making responsibilities come with an implicit assumption that patients are sufficiently educated and confident in their abilities to make decisions about their care based on evidence based treatment recommendations. Attempts to improve health literacy in patients by way of graphical decision aids have met with success. Such decision aids typically have been designed for a general population and evaluated based on whether or not users of the decision aid can accurately report the data points in isolation. To classify decision aids, we present an information-centric framework for assessing the content delivered to patients. We provide examples of our framework from a literature survey and suggest ways improvements can be made by considering all dimensions of our framework.

Meaningful use in practice using patient-specific risk in an electronic health record for shared decision making

Quantitative risk (QR) formulas have been developed for multiple conditions but are not routinely used in clinical practice. Tests were made of the feasibility of an automated clinical care process for using QR in routine primary care. Several modifications were made to the Framingham Risk Score (FRS) and it was applied to routine care in three areas: (1) for risk-stratification, (2) patient education about care options, and (3) guidance on optimizing choice of care options. Evidence-based methods were used to convert the smoking status variable from a binary- to a continuous-scale format and to add variables for alcohol use and HbA1c. An automated protocol tested in 2008-2010 was successful for all three applications. At-risk patients (defined according to criteria from the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure [JNC]-7 or the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults [adult treatment panel/ATP-III]) were automatically identified during routine encounters. Patient-reported data were obtained (n = 1826) by touchscreen questionnaire and automatically used with electronic health record (EHR) data to calculate risks on 1068 patients who had complete data. Patients were risk-stratified. Higher-risk patients viewed an interactive web-based tool and chose options to modify risk factors. Feasibility was successful for use of the FRS in the interactive web tool.

The potential of the Internet for health communication: the use of an interactive on-line tool for diabetes risk prediction

OBJECTIVE

The aim of the study is to assess the use of a web-based tool to calculate the 5-year risk of developing type 2 diabetes mellitus, the German Diabetes Risk Score (DRS), in a real-life setting.

METHODS

Recorded web server log information and user entered data (n=24,495) was analyzed. To distinguish information seeking behavior between high- and low-risk DRS records, a sub-sample was created to compare data entries of the highest and lowest risk quintile (n=5046). To learn more on the information seeking behavior of DRS users we created a dataset on the characteristics of those who calculate more than one DRS (n=11,902).

RESULTS

Most users (61%) entered the DRS without a referring website. Forty percent of users did not know their waist circumference. Visit duration among high-risk DRS records was almost 1.5 min longer compared to low-risk DRS records (p-value<0.001). Those who calculated multiple DRS were associated with a higher first DRS and male gender.

CONCLUSION

Understanding users' website utilization is an important step to evaluate risk calculator websites.

PRACTICE IMPLICATIONS

A range of media should be used conjointly to raise type 2 diabetes mellitus risk awareness. Risk websites should be linked to patient information pages.

A clustering approach to segmenting users of internet-based risk calculators

BACKGROUND

Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates.

OBJECTIVE

To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information.

METHODS

A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement.

RESULTS

Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions.

CONCLUSIONS

Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

What is my cancer risk? How internet-based cancer risk assessment tools communicate individualized risk estimates to the public: content analysis

Background

Internet-based cancer risk assessment tools have the potential to inform the public about cancer risk and promote risk-reducing behaviors. However, poorly communicated information on these websites may result in unintended adverse health outcomes.

Objective

This study examined whether: (1) Internet-based cancer risk assessment tools use risk communication formats that facilitate comprehension and reduce bias (as identified by the empirical literature); (2) the use of these formats varies by website affiliation; and (3) the websites provided information necessary to evaluate the quality of the risk estimate.

Methods

A content analysis of Internet-based cancer risk assessment tools was conducted. The terms calculate cancer risk, cancer risk calculator, estimate cancer risk, assess cancer risk, and cancer risk assessment were searched using three search engines. We identified 47 risk assessment tools and coded each according to standardized criteria. We calculated simple frequencies on all coding categories and performed crosstabulations but did not conduct formal statistical analysis due to small cell sizes.

Results

Use of risk communication formats that facilitate comprehension and reduce bias varied widely (eg, 30% of websites [14/47] provided absolute and comparative risk information but 83% [39/47] provided safety messages). Use of formats that facilitate comprehension varied by website affiliation and communication strategy (eg, only 8.3% [1/12] websites affiliated with the health care industry provided absolute and comparative risk information, but 83% [5/6] of websites affiliated with a governmental organization did so). Only 53% (25/47) of websites provided information about the statistical model or the peer-reviewed literature that was used to calculate the risk estimate.

Conclusion

Internet-based cancer risk assessment tools varied in their use of risk communication formats that facilitate comprehension and reduce bias. Formats that are difficult to understand may cause people to misperceive their cancer risk and consequently take inappropriate action.