Literature DB >> 17237451

Further insight into the perception of quantitative information: judgments of gist in treatment decisions.

Deb Feldman-Stewart1, Michael D Brundage, Vladimir Zotov.   

Abstract

PURPOSE: To compare relative accuracy and relative response times (RTs) as well as impact of foreground and background colors in a treatment decision context of judging larger/smaller when the following elements are added to the graphics studied previously: 1) a number (the displayed percentage), 2) a referent scale, and 3) a number and a referent scale.
METHOD: An experiment compared pie charts, vertical bars, horizontal bars, digits, systematic ovals, and random ovals. On each trial, participants saw 2 percentages (in 1 format) and were asked to choose the larger chance of survival or the smaller chance of side effects. Outcomes were errors and RT. Formats were either black and white or blue and yellow; background color was either white or blue. Participants were 216 volunteers from the community older than 50 years.
RESULTS: Formats with a number produced the same relative errors and relative RT as the formats with a number and scale. Formats with only a scale, however, shifted relative performance: Errors increased with more difficult formats (pie charts and random ovals by 3%-4% v. approximately 1% with other formats), but RT decreased with easier formats (vertical bars, horizontal bars, and systematic ovals decreased 100-200 ms v. an increase of 0-300 ms with other formats). Vertical bars with scales were the fastest and most accurately processed. Neither foreground nor background color had any impact on either outcome.
CONCLUSIONS: For supporting older people's judgments of relative extent, risk information is best presented using vertical bars with a scale; the format systematic ovals with a scale are among the next most easily processed.

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Mesh:

Year:  2007        PMID: 17237451     DOI: 10.1177/0272989X06297101

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  36 in total

1.  Visual presentations of efficacy data in direct-to-consumer prescription drug print and television advertisements: A randomized study.

Authors:  Helen W Sullivan; Amie C O'Donoghue; Kathryn J Aikin; Dhuly Chowdhury; Rebecca R Moultrie; Douglas J Rupert
Journal:  Patient Educ Couns       Date:  2015-12-22

2.  Helping patients decide: ten steps to better risk communication.

Authors:  Angela Fagerlin; Brian J Zikmund-Fisher; Peter A Ubel
Journal:  J Natl Cancer Inst       Date:  2011-09-19       Impact factor: 13.506

3.  The effect of format on parents' understanding of the risks and benefits of clinical research: a comparison between text, tables, and graphics.

Authors:  Alan R Tait; Terri Voepel-Lewis; Brian J Zikmund-Fisher; Angela Fagerlin
Journal:  J Health Commun       Date:  2010-07

4.  Tables or bar graphs? Presenting test results in electronic medical records.

Authors:  Noel T Brewer; Melissa B Gilkey; Sarah E Lillie; Bradford W Hesse; Stacey L Sheridan
Journal:  Med Decis Making       Date:  2012-04-03       Impact factor: 2.583

5.  Health providers' perceptions of novel approaches to visualizing integrated health information.

Authors:  T Le; B Reeder; H Thompson; G Demiris
Journal:  Methods Inf Med       Date:  2013-02-28       Impact factor: 2.176

Review 6.  Clinical implications of numeracy: theory and practice.

Authors:  Wendy Nelson; Valerie F Reyna; Angela Fagerlin; Isaac Lipkus; Ellen Peters
Journal:  Ann Behav Med       Date:  2008-08-02

7.  Integrated data visualisation: an approach to capture older adults' wellness.

Authors:  Thai Le; Katarzyna Wilamowska; George Demiris; Hilaire Thompson
Journal:  Int J Electron Healthc       Date:  2012

8.  Communicating Numerical Risk: Human Factors That Aid Understanding in Health Care.

Authors:  Priscila G Brust-Renck; Caisa E Royer; Valerie F Reyna
Journal:  Rev Hum Factors Ergon       Date:  2013-10

9.  Informing the uninformed: optimizing the consent message using a fractional factorial design.

Authors:  Alan R Tait; Terri Voepel-Lewis; Vijayan N Nair; Naveen N Narisetty; Angela Fagerlin
Journal:  JAMA Pediatr       Date:  2013-07       Impact factor: 16.193

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

Authors:  Erika A Waters; Helen W Sullivan; Wendy Nelson; Bradford W Hesse
Journal:  J Med Internet Res       Date:  2009-07-31       Impact factor: 5.428

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