Laura D Scherer1, Tanner J Caverly2, James Burke2, Brian J Zikmund-Fisher3, Jeffrey T Kullgren2, Douglas Steinley4, Denis M McCarthy4, Meghan Roney5, Angela Fagerlin6. 1. Department of Psychological Sciences. 2. VA Center for Clinical Management Research, VA Ann Arbor Healthcare System. 3. Department of Internal Medicine, University of Michigan Medical School. 4. Department of Psychological Sciences, University of Missouri. 5. Center for Bioethics and Social Sciences in Medicine, University of Michigan. 6. Department of Population Health Sciences, University of Utah.
Abstract
OBJECTIVE: Medical over- and underutilization are central problems that stand in the way of delivering optimal health care. As a result, one important question is how people decide to take action, versus not, when it comes to their health. The present article proposes and validates a new measure that captures the extent to which individuals are "medical maximizers" who are predisposed to seek health care even for minor problems, versus "medical minimizers" who prefer to avoid medical intervention unless it is necessary. METHOD: Studies 1-3 recruited participants using Amazon's Mechanical Turk. Study 1 conducted exploratory factor analysis (EFA) to identify items relevant to the proposed construct. In Study 2 confirmatory factor analysis (CFA) was conducted on the identified items, as well as tests of internal, discriminant, and convergent validity. Study 3 examined test-retest reliability of the scale. Study 4 validated the scale in a non-Internet sample. RESULTS: EFA identified 10 items consistent with the proposed construct, and subsequent CFA showed that the 10 items were best understood with a bifactor model that assessed a single underlying construct consistent with medical maximizing-minimizing, with 3 of the 10 items cross-loading on another independent factor. The scale was distinct from hypochondriasis, distrust in medicine, health care access, and health status, and predicted self-reported health care utilization and a variety of treatment preferences. CONCLUSIONS: Individuals have general preferences to maximize versus minimize their use of health care, and these preferences are predictive of health care utilization and treatment preferences across a range of health care contexts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
OBJECTIVE: Medical over- and underutilization are central problems that stand in the way of delivering optimal health care. As a result, one important question is how people decide to take action, versus not, when it comes to their health. The present article proposes and validates a new measure that captures the extent to which individuals are "medical maximizers" who are predisposed to seek health care even for minor problems, versus "medical minimizers" who prefer to avoid medical intervention unless it is necessary. METHOD: Studies 1-3 recruited participants using Amazon's Mechanical Turk. Study 1 conducted exploratory factor analysis (EFA) to identify items relevant to the proposed construct. In Study 2 confirmatory factor analysis (CFA) was conducted on the identified items, as well as tests of internal, discriminant, and convergent validity. Study 3 examined test-retest reliability of the scale. Study 4 validated the scale in a non-Internet sample. RESULTS: EFA identified 10 items consistent with the proposed construct, and subsequent CFA showed that the 10 items were best understood with a bifactor model that assessed a single underlying construct consistent with medical maximizing-minimizing, with 3 of the 10 items cross-loading on another independent factor. The scale was distinct from hypochondriasis, distrust in medicine, health care access, and health status, and predicted self-reported health care utilization and a variety of treatment preferences. CONCLUSIONS: Individuals have general preferences to maximize versus minimize their use of health care, and these preferences are predictive of health care utilization and treatment preferences across a range of health care contexts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Authors: Stella K Kang; Laura D Scherer; Alec J Megibow; Leslie J Higuita; Nathanael Kim; R Scott Braithwaite; Angela Fagerlin Journal: AJR Am J Roentgenol Date: 2017-11-15 Impact factor: 3.959
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Authors: Joshua M Evron; David Reyes-Gastelum; Mousumi Banerjee; Laura D Scherer; Lauren P Wallner; Ann S Hamilton; Kevin C Ward; Sarah T Hawley; Brian J Zikmund-Fisher; Megan R Haymart Journal: J Clin Oncol Date: 2019-10-01 Impact factor: 50.717
Authors: Laura D Scherer; Daniel D Matlock; Larry A Allen; Chris E Knoepke; Colleen K McIlvennan; Monica D Fitzgerald; Vinay Kini; Channing E Tate; Grace Lin; Hillary D Lum Journal: MDM Policy Pract Date: 2021-07-02