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Health Communication Research Measures


Do Kyun Kim and James W. Dearing

This volume presents state-of-the-art reporting on how to measure many of the key variables in health communication. While the focus is on quantitative measures, the editors argue that these measures are centrally important to the study of health communication. The chapters emphasize constructs, scales, and up-to-date reports and evidence about key social science constructs and ways of measuring them, whether your interest is in patient-provider dyadic communication, uncertainty management, self-efficacy, disclosure, social norms, social support, risk perception, health care team performance, message design and effects, health and numerical literacy, communication satisfaction, social influence and persuasion, stigma, health campaigns, reactance, or other topics. Students, researchers, and policymakers will find this book an accessible resource for planning and reviewing research studies and proposals.
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17. Psychological Reactance


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17. Psychological Reactance

BRIAN L. QUICK,University of Illinois at Urbana-Champaign& TOBIAS REYNOLDS-TYLUS,University of Illinois at Urbana-Champaign

Described as an aversive motivational state following a threatened or eliminated freedom, psychological reactance emerged onto the scene as a popular construct more than five decades ago for explaining resistance to persuasion (for a review, see Brehm, 1966; Brehm & Brehm, 1981). Despite the popularity of psychological reactance theory, the operationalization of reactance both as a psychological state and as an individual difference variable remained underdeveloped until recently. In the current chapter we set out to offer readers a validated conceptualization and operationalization of psychological reactance both as a state and trait. Additionally, evidence in support of recent operationalizations will also be provided. We begin with an overview of psychological reactance theory followed by scale development with respect to reactance as both a psychological state and an individual difference variable. We conclude the chapter by highlighting opportunities for scale application and modification in the future.

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