Personalized risk communication for personalized risk assessment: Real world assessment of knowledge and motivation for six mortality risk measures from an online life expectancy calculator

References

• Weinstein ND, Atwood K, Puleo E, Fletcher R, Colditz G, Emmons K. Colon cancer: risk perceptions and risk communication. Journal of Health Communication. 2004;9(1):53–65.
   PubMed Web of Science ®Google Scholar
• Harle CA, Downs JS, Padman R. Effectiveness of personalized and interactive health risk calculators: a randomized trial. Medical Decision Making. 2012;32(4):594–605.
   PubMed Web of Science ®Google Scholar
• Edwards AG, Naik G, Ahmed H, Elwyn GJ, Pickles T, Hood K, et al. Personalised risk communication for informed decision making about taking screening tests. The Cochrane Database of Systematic Reviews. 2013;2:Cd001865.
   Google Scholar
• Ahmed H, Naik G, Willoughby H, Edwards AG. Communicating risk. BMJ. 2012;344:e3996.
   PubMed Web of Science ®Google Scholar
• Waldron CA, van der Weijden T, Ludt S, Gallacher J, Elwyn G. What are effective strategies to communicate cardiovascular risk information to patients? A systematic review. Patient Education Counseling. 2011;82(2):169–181.
   PubMed Web of Science ®Google Scholar
• Edwards A, Elwyn G, Covey J, Matthews E, Pill R. Presenting risk information–a review of the effects of “framing” and other manipulations on patient outcomes. Journal of Health Communication. 2001;6(1):61–82.
   PubMed Web of Science ®Google Scholar
• Zipkin DA, Umscheid CA, Keating NL, Allen E, Aung K, Beyth R, et al. Evidence-based risk communication: a systematic review. Annals of Internal Medicine. 2014;161(4):270–280.
   PubMed Web of Science ®Google Scholar
• Edwards A, Elwyn G. Understanding risk and lessons for clinical risk communication about treatment preferences. Quality in Health Care. 2001;10(suppl 1):i9–i13.
   PubMedGoogle Scholar
• Fagerlin A, Zikmund-Fisher BJ, Ubel PA. “If I’m better than average, then I’m ok?”: comparative information influences beliefs about risk and benefits. Patient Education Counseling. 2007; 69 (1–3): 140–144.
   PubMed Web of Science ®Google Scholar
• Malenka DJ, Baron JA, Johansen S, Wahrenberger JW, Ross JM. The framing effect of relative and absolute risk. Journal of General Internal Medicine. 1993;8(10):543–548.
   PubMed Web of Science ®Google Scholar
• Moxey A, O’Connell D, McGettigan P, Henry D. Describing treatment effects to patients. Journal of General Internal Medicine. 2003;18(11):948–959.
   PubMed Web of Science ®Google Scholar
• Fagerlin A, Zikmund-Fisher BJ, Ubel PA. Helping patients decide: ten steps to better risk communication. Journal of the National Cancer Institute. 2011;103(19):1436–1443.
   PubMedGoogle Scholar
• Trevena LJ, Zikmund-Fisher BJ, Edwards A, et al. Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Medical Informatics and Decision Making.; 2013;13(Suppl 2):S7. doi:10.1186/1472-6947-13-S2-S7
   Google Scholar
• Trevena LJ, Zikmund-Fisher BJ, Edwards A, Gaissmaier W, Galesic M, Han PK, et al. Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Medical Informatics and Decision Making. 2013;13(Suppl 2):S7.
   PubMed Web of Science ®Google Scholar
• Bonner C, Jansen J, Newell BR, Irwig L, Glasziou P, Doust J, et al. I don’t believe it, but i’d better do something about it: patient experiences of online heart age risk calculators. Journal of Medical Internet Research. 2014;16(5):e120.
   PubMed Web of Science ®Google Scholar
• Harle CA, Downs JS, Padman R. A clustering approach to segmenting users of internet-based risk calculators. Methods of Information in Medicine. 2011;50(3):244–252.
   PubMed Web of Science ®Google Scholar
• Lopez-Gonzalez AA, Aguilo A, Frontera M, Bennasar-Veny M, Campos I, Vicente-Herrero T, et al. Effectiveness of the Heart Age tool for improving modifiable cardiovascular risk factors in a Southern European population: a randomized trial. European Journal of Preventive Cardiology 2015;22(3):389–96.
   Google Scholar
• Nolan T, Dack C, Pal K, Ross J, Stevenson FA, Peacock R, et al. Patient reactions to a web-based cardiovascular risk calculator in type 2 diabetes: a qualitative study in primary care. The British Journal of General Practice: the Journal of the Royal College of General Practitioners. 2015;65(632):e152–e160.
   PubMed Web of Science ®Google Scholar
• Price HC, Griffin SJ, Holman RR. Impact of personalized cardiovascular disease risk estimates on physical activity-a randomized controlled trial. Diabetic Medicine: a Journal of the British Diabetic Association. 2011;28(3):363–372.
   PubMed Web of Science ®Google Scholar
• Soureti A, Hurling R, Murray P, van Mechelen W, Cobain M. Evaluation of a cardiovascular disease risk assessment tool for the promotion of healthier lifestyles. European journal of Cardiovascular Prevention and Rehabilitation: Official Journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology. 2010;17(5):519–523.
   PubMedGoogle Scholar
• Neiger BL, Thackeray R, Burton SH, Giraud-Carrier CG, Fagen MC. Evaluating social media’s capacity to develop engaged audiences in health promotion settings: use of Twitter metrics as a case study. Health Promotion Practice. 2013;14(2):157–162.
   PubMedGoogle Scholar
• Neiger BL, Thackeray R, Van Wagenen SA, Hanson CL, West JH, Barnes MD, et al. Use of social media in health promotion: purposes, key performance indicators, and evaluation metrics. Health Promotion Practice. 2012;13(2):159–164.
   PubMedGoogle Scholar
• Schulte JM, Rothaus CS, Adler JN. Starting statins — polling results. New England Journal of Medicine. 2014;371(4):e6.
   PubMed Web of Science ®Google Scholar
• Manuel DG, Perez R, Bennett C, Rosella L, Taljaard M, Roberts M, et al. Seven more years: the impact of smoking, alcohol, diet, physical activity and stress on health and life expectancy in Ontario. Toronto: Institute for Clinical Evaluative Sciences and Public Health Ontario; 2012.
   Google Scholar
• O’Connor AM, Cranney A. User manuel - acceptability. Ottawa: Ottawa Hospital Research Institute; 1996. p. 5.
   Google Scholar
• Eysenbach G. Improving the quality of Web surveys: the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). Journal of MEDICAL INTERNET RESEARCH. 2004;6(3):e34.
   PubMed Web of Science ®Google Scholar
• McCartney M. How do we know whether medical apps work? BMJ. 2013;346:f1811.
   PubMed Web of Science ®Google Scholar
• Marceglia S, Bonacina S, Zaccaria V, Pagliari C, Pinciroli F. How might the iPad change healthcare? Journal of the Royal Society of Medicine. 2012;105(6):233–241.
   PubMed Web of Science ®Google Scholar
• Huckvale K, Morrison C, Ouyang J, Ghaghda A, Car J. The evolution of mobile apps for asthma: an updated systematic assessment of content and tools. BMC Medicine. 2015;13:58.
   PubMed Web of Science ®Google Scholar
• Visvanathan A, Hamilton A, Brady RR. Smartphone apps in microbiology–is better regulation required? Clinical Microbiology and Infection. 2012;18(7):E218–E220.
   PubMed Web of Science ®Google Scholar
• Demidowich AP, Lu K, Tamler R, Bloomgarden Z. An evaluation of diabetes self-management applications for Android smartphones. Journal of Telemedicine and Telecare. 2012;18(4):235–238.
   PubMed Web of Science ®Google Scholar
• Bonacina S, Marceglia S, Pinciroli F. A pictorial schema for a comprehensive user-oriented identification of medical Apps. Methods of Information in Medicine. 2014;53(3):208–224.
   PubMed Web of Science ®Google Scholar
• Brick JM. The future of survey sampling. Public Opinion Quarterly. 2011;75(5):872–888.
   Web of Science ®Google Scholar
• Rivers D, editor Sampling for web surveys. Joint Statistical Meetings 2007. http://www.amstat.org/meetings/jsm/2007/
   Google Scholar
• Vavreck L, D. Rivers The 2006 cooperative congressional election study. Journal of Elections, Public Opinion and Parties. 2008;18(4):355–366.
   Google Scholar