Christine M Gunn1, Barbara Bokhour, Victoria A Parker, Patricia A Parker, Sarah Blakeslee, Hanna Bandos, Christine Holmberg. 1. Author Affiliations: Women's Health Unit, Section of General Internal Medicine, Boston University School of Medicine (Dr Gunn); Department of Health Law, Policy and Management, Boston University School of Public Health (Drs Gunn, Bokhour, and V.A. Parker), Massachusetts; Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, New York (Dr P.A. Parker); NRG Oncology, and The University of Pittsburgh, Pittsburgh, Pennsylvania (Dr Bandos); and Institute of Public Health, Charité-Universitätsmedizin, Berlin, Germany (Dr Holmberg and Ms Blakeslee).
Abstract
BACKGROUND: Explanatory models represent patient understanding of etiology, pathophysiology, illness, symptoms, and treatments, but little attention has been paid to how they are used by patients "at risk" for future disease. OBJECTIVE: The aims of this study were to elucidate what constitutes an explanatory model of risk and to describe explanatory models of risk related to developing breast cancer. METHODS: Thirty qualitative interviews with women identified as at an increased risk for breast cancer were conducted. Interviews were coded to identify domains of explanatory models of risk using a priori codes derived from the explanatory model of illness framework. Within each domain, a grounded thematic analysis described participants' explanatory models related to breast cancer risk. RESULTS: The domains of treatment and etiology remained similar in a risk context compared with illness, whereas course of illness, symptoms, and pathophysiology differed. We identified a new, integrative concept relative to other domains within explanatory models of risk: social comparisons, which was dominant in risk perhaps due to the lack of physical experiences associated with being "at risk." CONCLUSIONS: Developing inclusive understandings of risk and its treatment is key to developing a framework for the care of high-risk patients that is both evidence based and sensitive to patient preferences. IMPLICATIONS FOR PRACTICE: The concept of "social comparisons" can assist healthcare providers in understanding women's decision making under conditions of risk. Ensuring that healthcare providers understand patient perceptions of risk is important because it relates to patient decision making, particularly due to an increasing focus on risk assessment in cancer.
BACKGROUND: Explanatory models represent patient understanding of etiology, pathophysiology, illness, symptoms, and treatments, but little attention has been paid to how they are used by patients "at risk" for future disease. OBJECTIVE: The aims of this study were to elucidate what constitutes an explanatory model of risk and to describe explanatory models of risk related to developing breast cancer. METHODS: Thirty qualitative interviews with women identified as at an increased risk for breast cancer were conducted. Interviews were coded to identify domains of explanatory models of risk using a priori codes derived from the explanatory model of illness framework. Within each domain, a grounded thematic analysis described participants' explanatory models related to breast cancer risk. RESULTS: The domains of treatment and etiology remained similar in a risk context compared with illness, whereas course of illness, symptoms, and pathophysiology differed. We identified a new, integrative concept relative to other domains within explanatory models of risk: social comparisons, which was dominant in risk perhaps due to the lack of physical experiences associated with being "at risk." CONCLUSIONS: Developing inclusive understandings of risk and its treatment is key to developing a framework for the care of high-risk patients that is both evidence based and sensitive to patient preferences. IMPLICATIONS FOR PRACTICE: The concept of "social comparisons" can assist healthcare providers in understanding women's decision making under conditions of risk. Ensuring that healthcare providers understand patient perceptions of risk is important because it relates to patient decision making, particularly due to an increasing focus on risk assessment in cancer.
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Authors: Christine M Gunn; Barbara G Bokhour; Victoria A Parker; Tracy A Battaglia; Patricia A Parker; Angela Fagerlin; Worta McCaskill-Stevens; Hanna Bandos; Sarah B Blakeslee; Christine Holmberg Journal: Med Decis Making Date: 2019-02-25 Impact factor: 2.583
Authors: Christine Holmberg; Hanna Bandos; Angela Fagerlin; Therese B Bevers; Tracy A Battaglia; D Lawrence Wickerham; Worta J McCaskill-Stevens Journal: Cancer Prev Res (Phila) Date: 2017-10-04
Authors: Ariel Maschke; Michael K Paasche-Orlow; Nancy R Kressin; Mara A Schonberg; Tracy A Battaglia; Christine M Gunn Journal: J Health Commun Date: 2021-01-17