Risk perceptions – or an individual’s perceived susceptibility to a threat – are a key component of many health behavior change theories. Risk perceptions are often targeted in health behavior change interventions, and recent meta-analytic evidence suggests that interventions that successfully engage and change risk perceptions produce subsequent increases in health behaviors. Here, we review recent literature on risk perceptions and health behavior, including research on the formation of risk perceptions, types of risk perceptions (including deliberative, affective, and experiential), accuracy of risk perceptions, and associations and interactions among types of risk perceptions. Taken together, existing research suggests that disease risk perceptions are a critical determinant of health behavior, although the nature of the association among risk perceptions and health behavior may depend on the profile of different types of risk perceptions and the accuracy of such perceptions.

Uncertainty is a pervasive and important problem that has attracted increasing attention in health care, given the growing emphasis on evidence-based medicine, shared decision making, and patient-centered care. However, our understanding of this problem is limited, due in part to the absence of a unified, coherent concept of uncertainty. There are multiple meanings and varieties of uncertainty in health care, which are not often distinguished or acknowledged although each may have unique effects or warrant different courses of action. The literature on uncertainty in health care is thus fragmented, and existing insights have been incompletely translated to clinical practice. In this paper we attempt to address this problem by synthesizing diverse theoretical and empirical literature from the fields of communication, decision science, engineering, health services research, and psychology, and developing a new integrative conceptual taxonomy of uncertainty. We propose a three-dimensional taxonomy that characterizes uncertainty in health care according to its fundamental sources, issues, and locus. We show how this new taxonomy facilitates an organized approach to the problem of uncertainty in health care by clarifying its nature and prognosis, and suggesting appropriate strategies for its analysis and management.

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(2016) The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: a meta-analysis. Health Psychology, 35 (11). pp. 1178-1188 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/58976/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. CHANGING HEALTH BEHAVIORS 1The Impact of Changing Attitudes, Norms, and Self-Efficacy on Health-Related Intentions and Behavior: A Meta-Analysis CHANGING HEALTH BEHAVIORS 2 AbstractObjective: Several health behavior theories converge on the hypothesis that attitudes, norms, and self-efficacy are important determinants of intentions and behavior. Yet inferences regarding the relation between these cognitions and intention or behavior rest largely on correlational data that preclude causal inferences. To determine whether changing attitudes, norms, or self-efficacy leads to changes in intentions and behavior, investigators need to randomly assign participants to a treatment that significantly increases the respective cognition relative to a control condition, and test for differences in subsequent intentions or behavior. The present review analyzed findings from 204 experimental tests that met these criteria. Methods: Studies were located using computerized searches and informal sources and meta-analyzed using STATA Version 11.Results: Experimentally induced changes in attitudes, norms, and self-efficacy all led to mediumsized changes in intention (d+ = .48, .49, and .51, respectively), and engendered small to medium-sized changes in behavior (attitudes-d+ = .38; norms-d+ = .36; self-efficacy-d+ = .47).These effect sizes generally were not qualified by the moderator variables examined (e.g., study quality, theoretical basis of the intervention, methodological characteristics, features of the targeted behavior), although effects were larger for interventions designed to increase (vs. decrease) behavioral performance. Conclusion: The present review lends novel, experimental support...

The ubiquitous social media landscape has created an information ecosystem populated by a cacophony of opinion, true and false information, and an unprecedented quantity of data on many topics. Policy makers and the social media industry grapple with the challenge of curbing fake news, disinformation, and hate speech; and the field of medicine is similarly confronted with the spread of false, inaccurate, or incomplete health information. 1 From the discourse on the latest tobacco products, alcohol, and alternative therapies to skepticism about medical guidelines, misinformation on social media can have adverse effects on public health. For example, the social media rumors circulating during the Ebola outbreak in 2014 created hostility toward health workers, posing challenges to efforts to control the epidemic. 2 Another example is the increasingly prevalent antivaccine social media posts that seemingly legitimize debate about vaccine safety and could be contributing to reductions in vaccination rates and increases in vaccine-preventable disease. 3 The spread of health-related misinformation is exacerbated by information silos and echo chamber effects. Social media feeds are personally curated and tailored to individual beliefs, partisan bias, and identity. Consequently, information silos are created in which the likelihood for exchange of differing viewpoints