Journal of Genetic Counseling

, Volume 26, Issue 3, pp 469–479 | Cite as

A Qualitative Study of Anticipated Decision Making around Type 2 Diabetes Genetic Testing: the Role of Scientifically Concordant and Discordant Expectations

  • Alicia G. Carmichael
  • Bailey B. Hulswit
  • Emily J. Moe
  • Toby Epstein Jayaratne
  • Beverly M. Yashar
Original Research


Type 2 diabetes mellitus (T2DM) genetic testing is undergoing clinical trials to measure the efficacy of genetic counseling for behavior-based risk reduction. The expectations patients bring to the testing process may play an important role in individual outcomes. We conducted a qualitative exploration of anticipated decision-making and expectations around T2DM genetic testing. Semi-structured interviews were completed with Mexican Americans (n = 34), non-Hispanic Black Americans (n = 39), and non-Hispanic White Americans (n = 39) at risk for T2DM. Transcripts were analyzed for themes. Most participants would accept T2DM genetic testing in order to motivate risk-reducing behaviors or apprise family members of their risk. Participants who would decline testing wished to avoid emotional distress or believed the test would not reveal new risk information. Non-Hispanic Whites and those with college education declined genetic testing more often than other groups. Those without college education were more likely to have testing expectations that were discordant with current science, such as conflating genetic testing with common ‘blood tests.’ Understanding expectations and decision-making factors around T2DM genetic testing will better prepare healthcare professionals to counsel their patients. This may lead to a higher efficacy of T2DM genetic testing and counseling.


Diabetes Genetic testing Decision-making Qualitative research 



The authors thank Hannah M. Curtis and Alix H. Bernholtz for assistance with qualitative coding, and Ji Qi for help with data management. This project was funded by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number R01DK083347 (to T.E.J.). Additional support was provided by the Michigan Center for Diabetes Translational Research under award number P30DK092926 from the National Institute of Diabetes and Digestive and Kidney Diseases. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Compliance with Ethical Standards

Conflict of Interest

Alicia Carmichael, Bailey Hulswit, Emily Moe, Toby Jayaratne, and Beverly Yashar declare that they have no conflict of interest.

Human Studies and Informed Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all patients for being included in the study.

Animal Studies

No animal studies were carried out by the authors for this article.


  1. Almgren, P., Lehtovirta, M., Isomaa, B., Sarelin, L., Taskinen, M. R., Lyssenko, V., Tuomi, T., & Groop, L. (2011). Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia study. Diabetologia, 54, 2811–2819.CrossRefPubMedGoogle Scholar
  2. American Diabetes Association (2015). Standards of medical care in diabetes—2015. Diabetes Care, 38(Supplement 1), S5–S7.CrossRefGoogle Scholar
  3. Becker, F., van El, C. G., Ibarreta, D., Zika, E., Hogarth, S., Borry, P., Cambon-Thomsen, A., Cassiman, J.J., Evers-Kiebooms, G., Hodgson, S., Janssens, A.C., Kaariainen, H., Krawczak, M., Kristoffersson, U., Lubinski, J., Patch, C., Penchaszadeh, V.B., Read, A., Rogowski, W., Sequeiros, J., Tranebjaerg, L., van Langen, I.M., Wallace, H., Zimmern, R., Schmidtke, J., & Cornel, M.C. (2011). Genetic testing and common disorders in a public health framework: how to assess relevance and possibilities. Background document to the ESHG recommendations on genetic testing and common disorders. European Journal of Human Genetics, 19, S6-S44.Google Scholar
  4. Cameron, L. D., & Jago, L. (2008). Emotion regulation interventions: a common-sense model approach. British Journal of Health Psychology, 13, 215–221.CrossRefPubMedGoogle Scholar
  5. Cardona-Morrell, M., Rychetnik, L., Morrell, S. L., Espinel, P. T., & Bauman, A. (2010). Reduction of diabetes risk in routine clinical practice: are physical activity and nutrition interventions feasible and are the outcomes from reference trials replicable? A systematic review and meta-analysis. BMC Public Health, 10(653), 1–17.Google Scholar
  6. Centre d’Etudes et de Recherche pour l’Intensification du Traitement du Diabète. (2012). Validation of a Predictive Risk Equation for Type 2 Diabetes in Families With Risk (DESCENDANCE). In: Bethesda (MD): - [cited 2016 Feb 2]. Available from: NLM Identifier: NCT01727349.
  7. Christensen, K. D., Jayaratne, T. E., Roberts, J. S., Kardia, S. L., & Petty, E. M. (2010). Understandings of basic genetics in the United States: results from a national survey of black and white men and women. Public Health Genomics, 13, 467–476.CrossRefPubMedPubMedCentralGoogle Scholar
  8. David Grant U.S. Air Force Medical Center, Duke University. (2013). Genetic risk and health coaching for type 2 diabetes and coronary heart disease. In: Bethesda (MD): - [cited 2016 Feb 2]. Available from: NLM Identifier: NCT01884545.
  9. de Miguel-Yanes, J. M., Shrader, P., Pencina, M. J., Fox, C. S., Manning, A. K., Grant, R. W., Dupuis, J., Florez, J. C., D’Agostino, R. B., Cupples, L. A., & Meigs, J. B. (2011). Genetic risk reclassification for type 2 diabetes by age below or above 50 years using 40 type 2 diabetes risk single nucleotide polymorphisms. Diabetes Care, 34, 121–125.CrossRefPubMedGoogle Scholar
  10. Grant, R. W., Hivert, M., Pandiscio, J. C., Florez, J. C., Nathan, D. M., & Meigs, J. B. (2009). The clinical application of genetic testing in type 2 diabetes: a patient and physician survey. Diabetologia, 52, 2299–2305.CrossRefPubMedGoogle Scholar
  11. Grant, R. W., O’Brien, K. E., Waxler, J. L., Vassy, J. L., Delahanty, L. M., Bissett, L. G., Green, R. C., Stember, K. G., Guiducci, C., Park, E. R., Florez, J. C., & Meigs, J. B. (2013). Personalized genetic risk counseling to motivate diabetes prevention: a randomized trial. Diabetes Care, 36, 13–19.CrossRefPubMedGoogle Scholar
  12. Haga, S. B., Barry, W. T., Mills, R., Ginsburg, G. S., Svetkey, L., Sullivan, J., & Willard, H. F. (2013). Public knowledge of an attitudes toward genetics and genetic testing. Genetic Testing and Molecular Biomarkers, 17, 327–335.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15, 1277–1288.CrossRefPubMedGoogle Scholar
  14. International Diabetes Federation. (2013). IDF Diabetes Atlas, 6th edn. Brussels, Belgium: International Diabetes Federation; Retrieved from:
  15. Klitzman, R. L. (2010). Misunderstandings concerning genetics among patients confronting genetic disease. Journal of Genetic Counseling, 19, 430–446.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Kuczmarski, M. F., Kuczmarski, R. J., & Najjar, M. (2001). Effects of age on validity of self-reported height, weight, and body mass index: findings from the third National Health and nutrition examination survey, 1988–1994. Journal of the American Dietetic Association, 101, 28–34.Google Scholar
  17. Lanie, A. D., Jayaratne, T. E., Sheldon, J. P., Kardia, S. L., Anderson, E. S., Feldbaum, M., & Petty, E. M. (2004). Exploring the public understanding of basic genetic concepts. Journal of Genetic Counseling, 13, 305–320.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Lea, D. H., Kaphingst, K. A., Bowen, D., Lipkus, I., & Hadley, D. W. (2011). Communicating genetic and genomic information: health literacy and numeracy considerations. Public Health Genomics, 14, 279–289.CrossRefPubMedGoogle Scholar
  19. Lombard, M., Snyder-Duch, J., & Bracken, C. C. (2002). Content analysis in mass communication: assessment and reporting of intercoder reliability. Human Communication Research, 28, 1468–2958.CrossRefGoogle Scholar
  20. MacQueen, K. M., McLellan, E., Kay, K., & Milstein, B. (1998). Codebook development for team-based qualitative analysis. Field Methods, 10, 31–36.CrossRefGoogle Scholar
  21. Markowitz, S. M., Park, E. R., Delahanty, L. M., O’Brien, K. E., & Grant, R. W. (2011). Perceived impact of diabetes genetic risk testing among patients at high phenotypic risk for type 2 diabetes. Diabetes Care, 34, 568–573.CrossRefPubMedPubMedCentralGoogle Scholar
  22. McAndrew, L. M., Musumeci-Szabó, T. J., Mora, P. A., Vileikyte, L., Burns, E., Halm, E. A., Leventhal, E. A., & Leventhal, H. (2008). Using the common sense model to design interventions for the prevention and management of chronic illness threats: From description to process. British Journal of Health Psychology, 12, 195–204.CrossRefGoogle Scholar
  23. Meigs, J. B., Shrader, P., Sullivan, L. M., McAteer, J. B., Fox, C. S., Dupuis, J., Manning, A. K., Florez, J. C., Wilson, P. W. F., D’Agostino, R. B., & Cupples, L. A. (2008). Genotype score in addition to common risk factors for prediction of type 2 diabetes. The New England Journal of Medicine, 359, 2208–2219.CrossRefPubMedPubMedCentralGoogle Scholar
  24. Mills, R., Powell, J., Barry, W., & Haga, S. B. (2015). Information-seeking and sharing behavior following genomic testing for diabetes risk. Journal of Genetic Counseling, 24, 58–66.CrossRefPubMedGoogle Scholar
  25. Nishigaki, M., Kobayashi, K., Hitomi, T., Yokomura, T., Yokoyama, M., Seki, N., & Kazuma, K. (2007). Perception of offspring risk for type 2 diabetes among patients with type 2 diabetes and their adult offspring. Diabetes Care, 30, 3033–3034.CrossRefPubMedGoogle Scholar
  26. Nishigaki, M., Sato, E., Ochiai, R., Shibayama, T., & Kazuma, K. (2011). Impact of a booklet about diabetes genetic susceptibility and its prevention on attitudes towards prevention and perceived behavioral change in patients with type 2 diabetes and their offspring. Advances in Preventive Medicine, 2011, 1–7.Google Scholar
  27. Nishigaki, M., Tokunaga-Nakawatase, Y., Nishida, J., & Kazuma, K. (2014). The effect of genetic counseling for adult offspring of patients with type 2 diabetes on attitudes toward diabetes and its heredity: a randomized controlled trial. Journal of Genetic Counseling, 23, 762–769.CrossRefPubMedGoogle Scholar
  28. O’Daniel, J. M. (2010). The prospect of genome-guided preventive medicine: a need and opportunity for genetic counselors. Journal of Genetic Counseling, 19, 315–327.CrossRefPubMedGoogle Scholar
  29. Persky, S., Kaphingst, K. A., Condit, C. M., & McBride, C. M. (2007). Assessing hypothetical scenario methodology in genetic susceptibility testing analog studies: a quantitative review. Genetics in Medicine, 9, 727–738.CrossRefPubMedGoogle Scholar
  30. Proove Bioscience, Inc. (2015). A Study of the Impact of Genetic Testing on Clinical Decision Making and Patient Care (REVOLUTION). In: Bethesda (MD): - [cited 2016 Feb 2]. Available from: NLM Identifier: NCT02487888.
  31. Schellenberg, E. S., Dryden, D. M., Vandermeer, B., Ha, C., & Korownyk, C. (2013). Lifestyle interventions for patients with and at risk for type 2 diabetes: a systematic review and meta-analysis. Annals of Internal Medicine, 159, 543–551.CrossRefPubMedGoogle Scholar
  32. Tessaro, I., Smith, S. L., & Rye, S. (2005). Knowledge and perceptions of diabetes in an Appalachian population. Preventing Chronic Disease, 2(2), 1–9.Google Scholar
  33. U.S. Department of Health and Human Services. (2008). 2008 Physical Activity Guidelines for Americans. (Report No. U0036). Retrieved from
  34. Vassy, J. L., Donelan, K., Hivert, M. F., Green, R. C., & Grant, R. W. (2013). Genetic susceptibility testing for chronic disease and intention for behavior change in healthy young adults. Journal of Community Genetics, 4, 263–271.CrossRefPubMedPubMedCentralGoogle Scholar
  35. Vassy, J. L., O’Brien, K. E., Waxler, J. L., Park, E. R., Delahanty, L. M., Florez, J. C., Meigs, J. B., & Grant, R. W. (2012). Impact of literacy and numeracy on motivation for behavior change after diabetes genetic risk testing. Medical Decision Making, 32, 606–615.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Voils, C. I., Coffman, C. J., Grubber, J., Edelman, D., Sadeghpour, A., Maciejewski, M. L., Bolton, J., Cho, A., Ginsburg, G. S., & Yancy Jr., W. S. (2015). Does type 2 diabetes genetic testing and counseling reduce modifiable risk factors? A randomized controlled trial of veterans. Journal of General Internal Medicine, 30, 1591–1598.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Waxler, J. L., O’Brien, K. E., Delahanty, L. M., Meigs, J. B., Florez, J. C., Park, E. R., Pober, B. R., & Grant, R. W. (2012). Genetic counseling as a tool for type 2 diabetes prevention: a genetic counseling framework for common polygenetic disorders. Journal of Genetic Counseling, 21, 684–691.CrossRefPubMedGoogle Scholar
  38. Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender bahaviour change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132, 249–268.CrossRefPubMedGoogle Scholar
  39. WHO Department of Health Statistics and Information Systems. (2013). Global health estimates summary tables: YLLs by cause, Age, and sex. In: GHE_YLL_Global_2000_2011.xls, editor. Geneva, Switzerland: World Health Organization.Google Scholar
  40. Wright, C. F., & Kroese, M. (2009). Evaluation of genetic tests for susceptibility to common complex diseases: why, when and how? Human Genetics, 127, 125–134.CrossRefPubMedGoogle Scholar
  41. Yates, T., Davies, M., & Khunti, K. (2009). Preventing type 2 diabetes: Can we make the evidence work? Postgraduate Medicine Journal, 85, 475–480.CrossRefGoogle Scholar

Copyright information

© National Society of Genetic Counselors, Inc. 2016

Authors and Affiliations

  • Alicia G. Carmichael
    • 1
  • Bailey B. Hulswit
    • 2
  • Emily J. Moe
    • 3
  • Toby Epstein Jayaratne
    • 4
  • Beverly M. Yashar
    • 5
  1. 1.BioSocial Methods Collaborative, Research Center for Group Dynamics, Institute for Social ResearchUniversity of MichiganAnn ArborUSA
  2. 2.Center for Molecular Medicine and GeneticsWayne State UniversityDetroitUSA
  3. 3.Genetics and Genomics ProgramChildren’s Hospital of WisconsinMilwaukeeUSA
  4. 4.Department of Health Behavior and Health Education, School of Public HealthUniversity of MichiganAnn ArborUSA
  5. 5.Department of Human GeneticsUniversity of MichiganAnn ArborUSA

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