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Communication Science and Online Risk Assessment Tools

In March 2012, the Division of Cancer Control and Population Sciences (DCCPS) at NCI hosted a webinar on communication science and online risk assessment tools. A panel of distinguished speakers shared best practices from the field, reviewed the latest empirical data on communicating disease risk using online tools, presented key considerations in communicating risk, and identified knowledge gaps and research directions for the field.

The webinar provided a unique opportunity for a diverse array of practitioners to interface. The spectrum of presenters included those focused on 1) risk prediction model development, 2) the goals and content of online risk assessment tools, 3) tool implementation for use in clinical practice and public education, and 4) standards creation for risk model development and dissemination.

Help us keep the conversation going! You can start by considering the following questions:

  • What are your thoughts/experiences with risk prediction models and online risk assessment tools, and what best practices or probable pitfalls do you want to share with colleagues?
  • Given that existing risk prediction models may have limited accuracy and discrimination for clinical decision making, especially for use at the individual level, what are the possibilities for developing better methods to refine and "approve" risk assessment models?
  • How can the research community promote more collaboration and transdisciplinary team science to produce better risk prediction models?
  • What standards should be used to determine if a risk assessment tool is ready to be implemented in clinical practice and/or disseminated to a broad public audience? 
  • What are the best ways to optimize the usefulness of a risk prediction number based on a person's ability not only to know what the number is, but also to understand what it means? Specifically: What are the best formats to represent and communicate risk prediction information, and what contextual information is optimal to ensure people understand risk assessments?
  • What are the prospects for building consensus on practices and processes for the implementation of risk prediction models?

We look forward to continuing the conversation and to learning together!

This was a terrific webinar!  Thanks for the very useful combination of talks and insights.

I wanted to comment on the talk given by Drs. Woloshin and Schwartz.

Drs. Woloshin and Schwartz discussed their Know Your Chances website which provides context for risk (e.g., comparisons to different causes of death, to smoking vs not smoking, etc.).  They’re working with SEER to present it on an NCI website that will allow users to construct charts of mortality/survival risks from top causes or for specific cancers that are more personalized for them (e.g., gender, time frame, number format, ethnicity).  The purpose of the tool is to give people data and let them make their own value judgments. The website is in process now. It's fairly complex at the moment and has not yet been studied with patients.  As a result, it's a terrific research opportunity to take what we know about risk communication and apply it to an important endeavor!

For example, in Q&A, Dr. Bill Klein asked a question about whether there was a “sweet spot” for how much context was provided versus the notion of “Less is More;” in other research, this notion was particularly important for less numerate (e.g., Peters, Dieckmann, Dixon, Hibbard, & Mertz, 2007)) and may be for older individuals as well.  Another research question could be whether patients and consumers are able to understand the meaning of information (e.g., its affect or how good or bad a risk is for the individual) as well as its precise form (e.g., 9.1%).

I'll be curious what others think.

 Ellen Peters

 

 

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