TY - JOUR
T1 - Specifying Future Behavior When Assessing Risk Perceptions
T2 - Implications for Measurement and Theory
AU - Waters, Erika A.
AU - Ackermann, Nicole
AU - Wheeler, Courtney S.
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by pilot funding from the Washington University Transdisciplinary Research on Energetics and Cancer (TREC) Center at Washington University in St. Louis with funding from grant U54CA155496 from the National Cancer Institute (NCI) of the National Institutes of Health (NIH). Funding was also provided by the Washington University Institute of Clinical and Translational Sciences grant UL1TR002345 from the National Center for Advancing Translational Sciences (NCATS) of NIH. The content is solely the responsibility of the authors and does not necessarily represent the official view of the NIH.
Funding Information:
Waters Erika A. Department of Surgery, Division of Public Health Sciences, School of Medicine, Washington University in St. Louis, Saint Louis, MO, USA Ackermann Nicole Department of Surgery, Division of Public Health Sciences, School of Medicine, Washington University in St. Louis, Saint Louis, MO, USA Wheeler Courtney S. Department of Surgery, Division of Public Health Sciences, School of Medicine, Washington University in St. Louis, Saint Louis, MO, USA Erika A. Waters, PhD, MPH, Department of Surgery, Division of Public Health Sciences, School of Medicine, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8100, Saint Louis, MO 63110, USA ( waterse@wustl.edu ). 10 2019 0272989X19879704 31 10 2018 10 9 2019 © The Author(s) 2019 2019 Society for Medical Decision Making Background . Many theories assert that high perceived risk motivates health behavior change; the empirical literature shows mixed findings. Purpose . To determine whether, for whom, and under what circumstances specifying a future behavior when assessing perceived risk (i.e., “conditioning” risk perception items on behavior) improves data quality and strengthens the perceived risk-intentions/behavior relationship. Methods . Internet panel participants ( N = 787, 58.8% no college experience, 44.4% racial/ethnic minority, 43.7% men, 67.3% aged 18–49 years, 59.0% nonadherent to physical activity guidelines) answered 8 colon cancer perceived risk items in a within-subjects design. Participants answered 4 types of risk perception items: absolute and comparative perceived likelihood and absolute and comparative feelings of risk. Participants answered each type of item twice: once conditioned on not engaging in physical activity and once unconditioned. Results . Compared to unconditioned items, conditioned items elicited fewer “don’t know” (DK) responses (OR = 0.80; 95% CI, 0.68–0.93), higher risk perceptions ( b = 0.55; 95% CI, 0.49–0.61) and stronger positive correlations with intentions ( z Steiger = 5.46, P < 0.001) and behavior ( z Steiger = 5.10, P < 0.001). The effect of conditioning was more pronounced for perceived likelihood than feelings of risk items (OR = 2.21; 95% CI, 1.63–3.01 and b = 0.14; 95% CI, 0.08–0.20 for DK responding and risk perception magnitude, respectively). The effect on risk perception magnitude (except absolute feelings of risk) was higher among people with higher health literacy (χ 2 (3) = 8.11, P = 0.04). Conclusions . Researchers who examine whether perceived risk motivates precautionary behavior should consider conditioning risk perception items on behavior to increase the validity of the statistical conclusions they draw and to gain insight into the nature of perceived risk and its relation to behavior. health behavior theory measurement risk perception survey methods edited-state corrected-proof The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by pilot funding from the Washington University Transdisciplinary Research on Energetics and Cancer (TREC) Center at Washington University in St. Louis with funding from grant U54CA155496 from the National Cancer Institute (NCI) of the National Institutes of Health (NIH). Funding was also provided by the Washington University Institute of Clinical and Translational Sciences grant UL1TR002345 from the National Center for Advancing Translational Sciences (NCATS) of NIH. The content is solely the responsibility of the authors and does not necessarily represent the official view of the NIH. Ethical Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed Consent Informed consent was obtained from all individual participants included in the study. Supplemental Material Supplemental material for this article is available online.
Publisher Copyright:
© The Author(s) 2019.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - Background. Many theories assert that high perceived risk motivates health behavior change; the empirical literature shows mixed findings. Purpose. To determine whether, for whom, and under what circumstances specifying a future behavior when assessing perceived risk (i.e., “conditioning” risk perception items on behavior) improves data quality and strengthens the perceived risk-intentions/behavior relationship. Methods. Internet panel participants (N = 787, 58.8% no college experience, 44.4% racial/ethnic minority, 43.7% men, 67.3% aged 18–49 years, 59.0% nonadherent to physical activity guidelines) answered 8 colon cancer perceived risk items in a within-subjects design. Participants answered 4 types of risk perception items: absolute and comparative perceived likelihood and absolute and comparative feelings of risk. Participants answered each type of item twice: once conditioned on not engaging in physical activity and once unconditioned. Results. Compared to unconditioned items, conditioned items elicited fewer “don’t know” (DK) responses (OR = 0.80; 95% CI, 0.68–0.93), higher risk perceptions (b = 0.55; 95% CI, 0.49–0.61) and stronger positive correlations with intentions (zSteiger = 5.46, P < 0.001) and behavior (zSteiger = 5.10, P < 0.001). The effect of conditioning was more pronounced for perceived likelihood than feelings of risk items (OR = 2.21; 95% CI, 1.63–3.01 and b = 0.14; 95% CI, 0.08–0.20 for DK responding and risk perception magnitude, respectively). The effect on risk perception magnitude (except absolute feelings of risk) was higher among people with higher health literacy (χ2(3) = 8.11, P = 0.04). Conclusions. Researchers who examine whether perceived risk motivates precautionary behavior should consider conditioning risk perception items on behavior to increase the validity of the statistical conclusions they draw and to gain insight into the nature of perceived risk and its relation to behavior.
AB - Background. Many theories assert that high perceived risk motivates health behavior change; the empirical literature shows mixed findings. Purpose. To determine whether, for whom, and under what circumstances specifying a future behavior when assessing perceived risk (i.e., “conditioning” risk perception items on behavior) improves data quality and strengthens the perceived risk-intentions/behavior relationship. Methods. Internet panel participants (N = 787, 58.8% no college experience, 44.4% racial/ethnic minority, 43.7% men, 67.3% aged 18–49 years, 59.0% nonadherent to physical activity guidelines) answered 8 colon cancer perceived risk items in a within-subjects design. Participants answered 4 types of risk perception items: absolute and comparative perceived likelihood and absolute and comparative feelings of risk. Participants answered each type of item twice: once conditioned on not engaging in physical activity and once unconditioned. Results. Compared to unconditioned items, conditioned items elicited fewer “don’t know” (DK) responses (OR = 0.80; 95% CI, 0.68–0.93), higher risk perceptions (b = 0.55; 95% CI, 0.49–0.61) and stronger positive correlations with intentions (zSteiger = 5.46, P < 0.001) and behavior (zSteiger = 5.10, P < 0.001). The effect of conditioning was more pronounced for perceived likelihood than feelings of risk items (OR = 2.21; 95% CI, 1.63–3.01 and b = 0.14; 95% CI, 0.08–0.20 for DK responding and risk perception magnitude, respectively). The effect on risk perception magnitude (except absolute feelings of risk) was higher among people with higher health literacy (χ2(3) = 8.11, P = 0.04). Conclusions. Researchers who examine whether perceived risk motivates precautionary behavior should consider conditioning risk perception items on behavior to increase the validity of the statistical conclusions they draw and to gain insight into the nature of perceived risk and its relation to behavior.
KW - health behavior theory
KW - measurement
KW - risk perception
KW - survey methods
UR - http://www.scopus.com/inward/record.url?scp=85074532493&partnerID=8YFLogxK
U2 - 10.1177/0272989X19879704
DO - 10.1177/0272989X19879704
M3 - Article
C2 - 31646937
AN - SCOPUS:85074532493
SN - 0272-989X
VL - 39
SP - 986
EP - 997
JO - Medical Decision Making
JF - Medical Decision Making
IS - 8
ER -