OBJECTIVE: To provide an explanation of perceived susceptibility judgment that accounts for both inconsistencies among commonly used measures of perceived susceptibility (i.e., absolute risk, direct comparative risk, and indirect comparative risk) and their inconsistent relationships to disease risk factors. Inconsistencies are attributed to differential processing of general versus personal risk factors, coupled with the method of computation of the risk measures. DESIGN AND MEASURES: Study 1 characterized risk factors as general versus personal. In Studies 2 and 3, community-residing adult women (ns = 432 and 147, respectively) rated perceived susceptibility to osteoporosis, breast cancer, heart disease, and diabetes, rated risk factors, and reported personal medical history. RESULTS: Correlations and regression analyses mainly supported our characterization of the source of inconsistencies among susceptibility measures and their relationships to risk factors. CONCLUSION: Perceived susceptibility measures are not interchangeable and can lead to opposite conclusions about correlates of perceived susceptibility. Researchers are cautioned against using indirect comparative measures, computed as difference scores, and are encouraged to use other methods to compel participants to consider the risk of others when making comparative judgments.
OBJECTIVE: To provide an explanation of perceived susceptibility judgment that accounts for both inconsistencies among commonly used measures of perceived susceptibility (i.e., absolute risk, direct comparative risk, and indirect comparative risk) and their inconsistent relationships to disease risk factors. Inconsistencies are attributed to differential processing of general versus personal risk factors, coupled with the method of computation of the risk measures. DESIGN AND MEASURES: Study 1 characterized risk factors as general versus personal. In Studies 2 and 3, community-residing adult women (ns = 432 and 147, respectively) rated perceived susceptibility to osteoporosis, breast cancer, heart disease, and diabetes, rated risk factors, and reported personal medical history. RESULTS: Correlations and regression analyses mainly supported our characterization of the source of inconsistencies among susceptibility measures and their relationships to risk factors. CONCLUSION: Perceived susceptibility measures are not interchangeable and can lead to opposite conclusions about correlates of perceived susceptibility. Researchers are cautioned against using indirect comparative measures, computed as difference scores, and are encouraged to use other methods to compel participants to consider the risk of others when making comparative judgments.
Authors: Annette R Kaufman; Amber R Koblitz; Alexander Persoskie; Rebecca A Ferrer; William M P Klein; Laura A Dwyer; Elyse R Park Journal: Nicotine Tob Res Date: 2015-05-10 Impact factor: 4.244
Authors: Annette R Kaufman; Jenny E Twesten; Jerry Suls; Kevin D McCaul; Jamie S Ostroff; Rebecca A Ferrer; Noel T Brewer; Linda D Cameron; Bonnie Halpern-Felsher; Jennifer L Hay; Elyse R Park; Ellen Peters; David R Strong; Erika A Waters; Neil D Weinstein; Paul D Windschitl; William M P Klein Journal: Nicotine Tob Res Date: 2020-10-29 Impact factor: 4.244
Authors: Lisa G Aspinwall; Jennifer M Taber; Wendy Kohlmann; Samantha L Leaf; Sancy A Leachman Journal: J Genet Couns Date: 2013-12-10 Impact factor: 2.537