OBJECTIVE: To explore laypersons' understanding of individualized cancer risk estimates, and to identify conceptual problems that may limit this understanding. BACKGROUND: Risk prediction models are increasingly used to provide people with information about their individual risk of cancer and other diseases. However, laypersons may have difficulty understanding individualized risk information, because of conceptual as well as computational problems. DESIGN: A qualitative study was conducted using focus groups. Semi-structured interviews explored participants' understandings of the concept of risk, and their interpretations of a hypothetical individualized colorectal cancer risk estimate. SETTING AND PARTICIPANTS: Eight focus groups were conducted with 48 adults aged 50-74 years residing in two major US metropolitan areas. Participants had high school or greater education, some familiarity with information technology, and no personal or family history of cancer. RESULTS: Several important conceptual problems were identified. Most participants thought of risk not as a neutral statistical concept, but as signifying danger and emotional threat, and viewed cancer risk in terms of concrete risk factors rather than mathematical probabilities. Participants had difficulty acknowledging uncertainty implicit to the concept of risk, and judging the numerical significance of individualized risk estimates. The most challenging conceptual problems related to conflict between subjective and objective understandings of risk, and difficulties translating aggregate-level objective risk estimates to the individual level. CONCLUSIONS: Several conceptual problems limit laypersons' understanding of individualized cancer risk information. These problems have implications for future research on health numeracy, and for the application of risk prediction models in clinical and public health settings.
OBJECTIVE: To explore laypersons' understanding of individualized cancer risk estimates, and to identify conceptual problems that may limit this understanding. BACKGROUND: Risk prediction models are increasingly used to provide people with information about their individual risk of cancer and other diseases. However, laypersons may have difficulty understanding individualized risk information, because of conceptual as well as computational problems. DESIGN: A qualitative study was conducted using focus groups. Semi-structured interviews explored participants' understandings of the concept of risk, and their interpretations of a hypothetical individualized colorectal cancer risk estimate. SETTING AND PARTICIPANTS: Eight focus groups were conducted with 48 adults aged 50-74 years residing in two major US metropolitan areas. Participants had high school or greater education, some familiarity with information technology, and no personal or family history of cancer. RESULTS: Several important conceptual problems were identified. Most participants thought of risk not as a neutral statistical concept, but as signifying danger and emotional threat, and viewed cancer risk in terms of concrete risk factors rather than mathematical probabilities. Participants had difficulty acknowledging uncertainty implicit to the concept of risk, and judging the numerical significance of individualized risk estimates. The most challenging conceptual problems related to conflict between subjective and objective understandings of risk, and difficulties translating aggregate-level objective risk estimates to the individual level. CONCLUSIONS: Several conceptual problems limit laypersons' understanding of individualized cancer risk information. These problems have implications for future research on health numeracy, and for the application of risk prediction models in clinical and public health settings.
Authors: Victor G Vogel; Joseph P Costantino; D Lawrence Wickerham; Walter M Cronin; Reena S Cecchini; James N Atkins; Therese B Bevers; Louis Fehrenbacher; Eduardo R Pajon; James L Wade; André Robidoux; Richard G Margolese; Joan James; Scott M Lippman; Carolyn D Runowicz; Patricia A Ganz; Steven E Reis; Worta McCaskill-Stevens; Leslie G Ford; V Craig Jordan; Norman Wolmark Journal: JAMA Date: 2006-06-05 Impact factor: 56.272
Authors: David E Nelson; Gary L Kreps; Bradford W Hesse; Robert T Croyle; Gordon Willis; Neeraj K Arora; Barbara K Rimer; K V Viswanath; Neil Weinstein; Sara Alden Journal: J Health Commun Date: 2004 Sep-Oct
Authors: Mark Harrison; Paul K J Han; Borsika Rabin; Madelaine Bell; Hannah Kay; Luke Spooner; Stuart Peacock; Nick Bansback Journal: Patient Educ Couns Date: 2018-12-12
Authors: Paul K J Han; William M P Klein; Tom Lehman; Bill Killam; Holly Massett; Andrew N Freedman Journal: Med Decis Making Date: 2010-07-29 Impact factor: 2.583
Authors: Zsofia K Stadler; Peter Thom; Mark E Robson; Jeffrey N Weitzel; Noah D Kauff; Karen E Hurley; Vincent Devlin; Bert Gold; Robert J Klein; Kenneth Offit Journal: J Clin Oncol Date: 2010-06-28 Impact factor: 44.544
Authors: Marc T Kiviniemi; Jennifer L Hay; Aimee S James; Isaac M Lipkus; Helen I Meissner; Michael Stefanek; Jamie L Studts; John F P Bridges; David R Close; Deborah O Erwin; Resa M Jones; Karen Kaiser; Kathryn M Kash; Kimberly M Kelly; Simon J Craddock Lee; Jason Q Purnell; Laura A Siminoff; Susan T Vadaparampil; Catharine Wang Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-11 Impact factor: 4.254
Authors: K Viswanath; Rebekah H Nagler; Cabral A Bigman-Galimore; Michael P McCauley; Minsoo Jung; Shoba Ramanadhan Journal: Cancer Epidemiol Biomarkers Prev Date: 2012-10 Impact factor: 4.254