Medical Maximizing-Minimizing Predicts Patient Preferences for High- and Low-Benefit Care

Author:

Scherer Laura D.12ORCID,Shaffer Victoria A.3ORCID,Caverly Tanner456,DeWitt Jeff67ORCID,Zikmund-Fisher Brian J.789ORCID

Affiliation:

1. Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, USA

2. VA Denver Center for Innovation (COIN), Denver, CO, USA

3. Department of Psychological Sciences, University of Missouri, Columbia, MO, USA

4. Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI, USA

5. Department of Medicine, University of Michigan, Ann Arbor, MI, USA

6. Center for Clinical Management Research (CCMR), Ann Arbor VA, Ann Arbor, MI, USA

7. Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, USA

8. Department of Health Behavior and Health Education, University of Michigan, Ann Arbor, MI, USA

9. Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA

Abstract

Purpose. People vary in their general preferences for more v. less health care, and the validated Medical Maximizing-Minimizing Scale (MMS) reliably measures this orientation. Medical maximizers (people scoring highly on the MMS) prefer to receive more health care visits, medications, tests, and treatments, whereas minimizers prefer fewer services. However, it is unclear how maximizing-minimizing preferences relate to willingness to pursue appropriate health care. We hypothesized that minimizers are at increased risk of rejecting evidence-based high-benefit care and that maximizers are at risk of wanting low-benefit care. Design. In total, 785 US adults recruited through an online panel expressed preferences to receive or forgo a health care intervention in 18 hypothetical scenarios. In 8 scenarios, the intervention was high benefit per evidence-based guidelines. In the remaining 10 scenarios, the intervention was low benefit. We assessed associations between participants’ MMS score and their preferences for medical intervention in each scenario using regression analyses that adjusted for hypochondriasis, health risk tolerance, health status, and demographic variables. Results. MMS score was significantly associated with preferences in all 18 scenarios after adjusting for other variables. The MMS uniquely explained 11% of the variance in preferences for high-benefit care and 29% of the variance in preferences for low-benefit care. Differences between strong minimizers (10th percentile) and strong maximizers (90th percentile) across the 18 scenarios ranged from 5.6 to 32.3 points on a 1 to 100 preference scale. Conclusions. The MMS reliably predicts people’s willingness to pursue appropriate care, both when appropriate care means taking high-benefit actions and when appropriate care means avoiding low-benefit actions. Targeting and tailoring messages according to maximizing-minimizing preferences might increase the effectiveness of both efforts to reduce overutilization of low-benefit services and campaigns to support uptake of high-benefit care.

Publisher

SAGE Publications

Subject

Health Policy

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