Sunyoung Kim1, Beatrice Trinidad2, Lisa Mikesell3, Mark Aakhus4. 1. School of Communication and Information, Rutgers University, United States. Electronic address: sunyoung.kim@rutgers.edu. 2. School of Communication and Information, Rutgers University, United States. Electronic address: beatrice.trinidad@gmail.com. 3. School of Communication and Information, Rutgers University, United States. Electronic address: lisa.mikesell@rutgers.edu. 4. School of Communication and Information, Rutgers University, United States. Electronic address: aakhus@rutgers.edu.
Abstract
BACKGROUND: The understanding and processing of numerical prognostic information can be challenging for patients who suffer from disease and the stress of a diagnosis. OBJECTIVE: This paper investigates how patients diagnosed with Leukemia respond to different graph representations of prognosis information. METHODS: We conducted a user-centered design process, for which three experimental prototypes (vertical, horizontal, and pie charts) with and without animation were developed. Twelve patients diagnosed with Leukemia were recruited to evaluate the prototypes using a think-aloud interview protocol. RESULTS: The results showed a preference for vertical bar charts over horizontal and pie charts. In addition, we found that animating the charts to "fill-up" generally conveyed a subtle sense of positivity even when diagnosis information was negative. The value of explicitly indicating numeric values and scale varied but the results suggest that what matters to participants is having control over when such details would be seen. The results also point out that making sense of prognostic information involves balancing the tension between information utility and patient judgments about authenticity and credibility of prognosis information. CONCLUSION: Our findings are important for the design and implementation of representations of prognostic information. They suggest that an appropriate visual format can reduce potential negative effects in conveying prognosis information, as well as helping patients stay positive and motivated for cure in the delivery of prognosis information.
BACKGROUND: The understanding and processing of numerical prognostic information can be challenging for patients who suffer from disease and the stress of a diagnosis. OBJECTIVE: This paper investigates how patients diagnosed with Leukemia respond to different graph representations of prognosis information. METHODS: We conducted a user-centered design process, for which three experimental prototypes (vertical, horizontal, and pie charts) with and without animation were developed. Twelve patients diagnosed with Leukemia were recruited to evaluate the prototypes using a think-aloud interview protocol. RESULTS: The results showed a preference for vertical bar charts over horizontal and pie charts. In addition, we found that animating the charts to "fill-up" generally conveyed a subtle sense of positivity even when diagnosis information was negative. The value of explicitly indicating numeric values and scale varied but the results suggest that what matters to participants is having control over when such details would be seen. The results also point out that making sense of prognostic information involves balancing the tension between information utility and patient judgments about authenticity and credibility of prognosis information. CONCLUSION: Our findings are important for the design and implementation of representations of prognostic information. They suggest that an appropriate visual format can reduce potential negative effects in conveying prognosis information, as well as helping patients stay positive and motivated for cure in the delivery of prognosis information.
Authors: Julie C Lauffenburger; Thomas Isaac; Lorenzo Trippa; Punam Keller; Ted Robertson; Robert J Glynn; Thomas D Sequist; Dae H Kim; Constance P Fontanet; Edward W B Castonguay; Nancy Haff; Renee A Barlev; Mufaddal Mahesri; Chandrashekar Gopalakrishnan; Niteesh K Choudhry Journal: Implement Sci Date: 2021-01-07 Impact factor: 7.327
Authors: George D Farmer; Mike Pearson; William J Skylark; Alexandra L J Freeman; David J Spiegelhalter Journal: Cancer Med Date: 2021-06-21 Impact factor: 4.711