Abstract
Background
Developments in genomics may improve patient consultations about weight management; however, optimal approaches for these communications are unstudied.
Purpose
We assessed the influence of receiving generic, genomic information and of physician communication approach on overweight females in simulated clinical weight counseling interactions.
Methods
Two hundred participants were randomized to receive information about genomic or behavioral underpinnings of body weight from a virtual reality-based physician who used either a supportive or directive communication approach. Participants completed post-test self-report questionnaires.
Results
Genomic explanations for body weight led patients to perceive less blame [F (1,196) = 47.68, p < .0001] and weight stigma [F (1,196) = 5.75, p = .017] in the consultation. They did not lead to negative outcomes in physician-patient interaction or affect health behavior-related attitudes and beliefs. Physician’s supportive or directive communication approach did not moderate these effects.
Conclusions
Integrating genomic concepts into health care has potential to positively influence the patient-provider relationship while addressing longstanding challenges in weight management. ClinicalTrials.gov number NCT01443910.
Similar content being viewed by others
References
Feero WG. Clinical application of whole-genome sequencing: Proceed with care. JAMA. 2014; 311(10): 1017-1019.
Manolio T, Chisholm R, Ozenberger B, et al. Implementing genomic medicine in the clinic: The future is here. Genet Med. 2013; 15(4): 258-267.
Loos R. Genetic determinants of common obesity and their value in prediction. Best Pract Res Clin Endocrinol Metab. 2012; 26(2): 211-226.
Haga S, Carrig M, O’Daniel J, et al. Genomic risk profiling: Attitudes and use in personal and clinical care of primary care physicians who offer risk profiling. J Gen Intern Med. 2011; 26(8): 834-840.
Agurs-Collins T, Khoury M, Simon-Morton D, Olster D, Harris J, Milner J. Public health genomics: Translating obesity genomics into population health benefits. Obesity. 2008; 16(S3): S85-S94.
El-Sayed Moustafa J, Froguel P. From obesity genetics to the future of personalized obesity therapy. Nat Rev Endocrinol. 2013; 9(7): 402-413.
Douketis J, Macie C, Thabane L, Williamson D. Systematic review of long-term weight loss studies in obese adults: Clinical significance and applicability to clinical practice. Int J Obes. 2005; 29(10): 1153-1167.
Anderson J, Konz E, Frederich R, Wood C. Long-term weight-loss maintenance: A meta-analysis of US studies. Am J Clin Nutr. 2001; 74(5): 579-584.
Kraschnewski J, Boan J, Esposito J, et al. Long-term weight loss maintenance in the United States. Int J Obes. 2010; 34(11): 1644-1654.
Chisholm A, Hart J, Lam V, Peters S. Current challenges of behavior change talk for medical professionals and trainees. Patient Educ Couns. 2012; 87(3): 389-394.
Kushner R. Barriers to providing nutrition counseling by physicians: A survey of primary care practitioners. Prev Med. 1995; 24(6): 546-552.
Ruelaz A, Diefenbach P, Simon B, Lanto A, Arterburn D, Shekelle P. Perceived barriers to weight management in primary care: Perspectives of patients and providers. J Gen Intern Med. 2007; 22(4): 518-522.
Friedman KE, Ashmore JA, Applegate KL. Recent experiences of weight-based stigmatization in a weight loss surgery population: Psychological and behavioral correlates. Obesity. 2008; 16(S2): S69-S74.
Safran D, Taira D, Rogers W, Kosinski M, Ware J, Tarlov A. Linking primary care performance to outcomes of care. J Fam Pract. 1998; 46(3): 213-220.
Stewart M, Brown J, Donner A, et al. The impact of patient-centered care on outcomes. J Fam Pract. 2000; 49(9): 796-804.
Suther S, Goodson P. Barriers to the provision of genetic services by primary care physicians. A systematic review of the literature. Genet Med. 2003; 5(2): 70-76.
Najafzadeh M, Davis J, Joshi P, Marra C. Barriers for integrating personalized medicine into clinical practice: A qualitative analysis. Am J Med Genet. 2013; 161A(4): 758-763.
Wilkes M. The case against marketing genetic tests to primary care doctors to promote test ordering. J Gen Intern Med. 2011; 26(8): 824-825.
Persky S, Sanderson S, Koehly L. Online communication about genetics and body weight: Implications for health behavior and internet-based education. J Health Commun. 2013; 18(2): 241-249.
Conradt M, Dierk J-M, Schlumberger P, et al. A consultation with genetic information about obesity decreases self-blame about eating and leads to realistic weight loss goals in obese individuals. J Psychosom Res. 2009; 66(4): 287-295.
Yoo J, Kim J. Obesity in the new media: A content analysis of obesity videos on YouTube. Health Commun. 2012; 27(1): 89-97.
Meisel S, Wardle J. ‘Battling my biology’: Psychological effects of genetic testing for risk of weight gain. J Genet Couns. 2014; 23(2): 179-186.
Weiner B, Perry R, Magnusson J. An attributional analysis of reactions to stigmas. J Pers Soc Psychol. 1998; 55(5): 736-748.
Crandall C. Prejudice against fat people: Ideology and self-interest. J Pers Soc Psychol. 1994; 66: 882-894.
Puhl RM, Moss-Racusin CA, Schwartz MB. Internalization of weight bias: Implications for binge eating and emotional well-being. Obesity. 2007; 15(1): 19-23.
Hall W, Matthews R, Morley K. Being more realistic about the public health impact of genomic medicine. PLoS Med. 2010; 7(10): e1000347.
Flinter F. Should we sequence everyone’s genome? No. Br Med J. 2013; 346: f31-f32.
Phelan JC. Genetic bases of mental illness—a cure for stigma? Trends Neurosci. 2002; 25(8): 430-431.
Angermeyer M, Holzinger A, Carta M, Schomerus G. Biogenetic explanations and public acceptance of mental illness: Systematic review of population studies. Br J Psychiatry. 2011; 199(5): 367-372.
Epstein RM, Street RL Jr. Patient-centered communication in cancer care: promoting healing and reducing suffering. Bethesda, MD: National Cancer Institute, NIH Publication No. 07-6225; 2007.
Grugaard PK, Finset A. Trait anxiety and reactions to patient-centered and doctor-centered styles of communication: An experimental study. Psychosom Med. 2000; 62: 33-39.
Kinmonth A, Woodcock A, Griffin S, Spiegal N, Campbell M. Randomised controlled trial of patient centred care of diabetes in general practice: Impact on current well-being and future disease risk. The Diabetes Care From Diagnosis Research Team. BMJ. 1998; 317(7167): 1202-1208.
Swenson S, Buell S, Zettler P, White M, Ruston D, Lo B. Patient-centered communication: Do patients really prefer it? J Gen Intern Med. 2004; 19(11): 1069-1079.
Bray S, Saville P, Brawley L. Determinants of clients’ efficacy in their interventionists and effects on self-perceptions for exercise in cardiac rehabilitation. Rehabil Psychol. 2013; 58(2): 185-195.
Graugaard P, Finset A. Trait anxiety and reactions to patient-centered and doctor-centered styles of communications: An experimental study. Psychosom Med. 2000; 62(1): 33-39.
Persky S. Employing immersive virtual environments for innovative experiments in health care communication. Patient Educ Couns. 2011; 82(3): 313-317.
Bailenson JN, Blascovich J, Beall AC, Loomis JM. Interpersonal distance in immersive virtual environments. Personal Soc Psychol Bull. 2003; 29: 1-15.
McCall C, Blascovich J. How, when, and why to use digital experimental virtual environments to study social behavior. Soc Personal Psychol Compass. 2009; 3: 1-15.
Blascovich J, Loomis J, Beall A, Swinth K, Hoyt C, Bailenson J. Immersive virtual environment technology as a research tool for social psychology. Psychol Inq. 2002; 13: 103-125.
Raij AB, Johnsen K, Dickerson RF, et al. Comparing interpersonal interactions with a virtual human to those with a real human. IEEE Trans Vis Comput Graph. 2007; 13(3): 1-15.
Tiggemann M, Rothblum ED. Gender differences in social consequences of perceived overweight in the United States and Australia. Sex Roles. 1988; 18: 75-86.
Puhl RM, Heuer CA. The stigma of obesity: A review and update. Obesity. 2009; 17(5): 941-964.
Esplen M, Stuckless N, Hunter J, et al. The BRCA self-concept scale: A new instrument to measure self-concept in BRCA1/2 mutation carriers. Psycho-Oncology. 2009; 18(11): 1216-1229.
Ogden J, Flanagan Z. Beliefs about the causes and solutions to obesity: A comparison of GPs and lay people. Patient Educ Couns. 2008; 71(1): 72-78.
Foster G, Wadden T, Markis A, et al. Primary care physicians’ attitudes about obesity and its treatment. Obes Res. 2003; 11(10): 1168-1177.
Jay M, Kalet A, Ark T, et al. Physicians’ attitudes about obesity and their associations with competency and specialty: A cross-sectional study. BMC Health Serv Res. 2009; 9: 106.
Budd G, Mariotti M, Graff D, Falkenstein K. Health care professionals’ attitudes about obesity: An integrative review. Appl Nurs Res. 2011; 24: 127-137.
Amy N, Aalborg A, Lyons P, Keranen L. Barriers to routine gynecological cancer screening for White and African-American obese women. Int J Obes. 2006; 30(1): 147-155.
Marteau T, French D, Griffin S, Prevost A, Sutton S, Watkinson C, et al. Does communicating DNA-based risk estimates motivatepeople to change their behaviour? Cochrane Database Syst Rev. 2010; 10: CD007275. doi:10.1002/14651858.CD007275
McBride C, Sanderson S, Kaphingst K, Koehly L. The behavioral response to personalized genetic information: Will genetic risk profiles motivate individuals and families to choose more healthful behaviors? Annu Rev Public Health. 2010; 31: 89.
Vartanian L, Shaprow J. Effects of weight stigma on exercise motivation and behavior: A preliminary investigation among college-aged females. J Health Psychol. 2008; 13(1): 131-138.
Major B, Hunger J, Bunyan D, Miller C. The ironic effects of weight stigma. J Exp Soc Psychol. 2014; 51: 74-80.
Brogan A, Hevey D. The structure of the causal attribution belief network of patients with obesity. Br J Health Psychol. 2009; 14: 35-48.
Parrott R, Silk K, Condit C. Diversity in lay perceptions of the sources of human traits: Genes, environments, and personal behaviors. Soc Sci Med. 2003; 56: 1099-1109.
American Medical Association. An ethical force program concensus report: Improving communication - improving care. Chicago: AMA; 2006.
Moyer V. Screening for and management of obesity in adults: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2012; 157(5): 373-378.
Acknowledgments
This research was supported by the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health. This work is based on data collected in the Immersive Virtual Environment Testing Area of the Social and Behavioral Research Branch, NHGRI, NIH. The authors thank Colleen McBride, Ph.D. and Howard Gordon, MD for advice and feedback during study development and editorial comments on a previous version of this manuscript. We thank Aanand Naik, MD for feedback during study development. We also acknowledge Peter Hanna, Stephanie Browning, and Maie Lee for assistance with data collection.
Authors’ Statement of Conflict of Interest and Adherence to Ethical Standards
Authors Susan Persky and Richard Street have no conflict of interest to report. All procedures, including the informed consent process, were conducted 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.
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Persky, S., Street, R.L. Evaluating Approaches for Communication About Genomic Influences on Body Weight. ann. behav. med. 49, 675–684 (2015). https://doi.org/10.1007/s12160-015-9701-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12160-015-9701-8