Several theories construe risk appraisals as key determinants of decisions and actions, and this idea has been supported in correlational studies. However, correlational data cannot answer the question, “Does heightening risk appraisals change people’s intentions and behavior?” The present review meta-analyzed experimental evidence in order to address this issue. We identified 4 elements of risk appraisal—risk perception, anticipatory emotion, anticipated emotion, and perceived severity—and located experiments that (a) engendered a statistically significant increase in risk appraisal among treatment compared to control participants and (b) measured subsequent intention or behavior. Heightening risk appraisals had effects of d+ = .31 (k = 217) and d+ = .23 (k = 93) on intention and behavior, respectively. There was evidence that the elements of risk appraisal combined to influence outcomes. For instance, heightening risk perceptions had larger effects on outcomes when anticipatory emotions or perceived severity was also increased. Crucially, risk appraisal effects were augmented by coping appraisals: Risk appraisals had larger effects on outcomes when response efficacy and self-efficacy were enhanced or when response
costs were reduced. The largest effect sizes were observed when risk appraisals, response efficacy, and self-efficacy were simultaneously heightened (d+ = .98 and .45, for intention and behavior, respectively). These findings indicate that heightening risk appraisals changes intentions and behavior. However, the direct effects of risk appraisals were generally small. Exploiting synergies among the elements of risk appraisal, and between risk appraisals and coping appraisals, should make for more effective behavior change interventions.

Does heightening risk appraisals change people's intentions and behavior? A meta-analysis of experimental studies.

Machine learning is used increasingly in clinical care to improve diagnosis, treatment selection, and health system efficiency. Because machine-learning models learn from historically collected data, populations that have experienced human and structural biases in the past-called protected groups-are vulnerable to harm by incorrect predictions or withholding of resources. This article describes how model design, biases in data, and the interactions of model predictions with clinicians and patients may exacerbate health care disparities. Rather than simply guarding against these harms passively, machine-learning systems should be used proactively to advance health equity. For that goal to be achieved, principles of distributive justice must be incorporated into model design, deployment, and evaluation. The article describes several technical implementations of distributive justice-specifically those that ensure equality in patient outcomes, performance, and resource allocation-and guides clinicians as to when they should prioritize each principle. Machine learning is providing increasingly sophisticated decision support and population-level monitoring, and it should encode principles of justice to ensure that models benefit all patients.

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Ensuring Fairness in Machine Learning to Advance Health Equity.

Objective: The aim was to provide a scholarly review of the published literature on biological, clinical, and nonclinical contributors to race/ethnic and sex disparities in endocrine disorders and to identify current gaps in knowledge as a focus for future research needs. Participants in Development of Scientific Statement: The Endocrine Society's Scientific Statement Task Force (SSTF) selected the leader of the statement development group (S.H.G.). She selected an eight-member writing group with expertise in endocrinology and health disparities, which was approved by the Society. All discussions regarding the scientific statement content occurred via teleconference or written correspondence. No funding was provided to any expert or peer reviewer, and all participants volunteered their time to prepare this Scientific Statement. Evidence: The primary sources of data on global disease prevalence are from the World Health Organization. A comprehensive literature search of PubMed identified U.S. population-ba...

Health Disparities in Endocrine Disorders: Biological, Clinical, and Nonclinical Factors—An Endocrine Society Scientific Statement

The annual National Healthcare Quality and Disparities Reports document widespread and persistent racial and ethnic disparities. These disparities result from complex interactions between patient factors related to social disadvantage, clinicians, and organizational and health care system factors. Separate and unequal systems of health care between states, between health care systems, and between clinicians constrain the resources that are available to meet the needs of disadvantaged groups, contribute to unequal outcomes, and reinforce implicit bias. Recent data suggest slow progress in many areas but have documented a few notable successes in eliminating these disparities. To eliminate these disparities, continued progress will require a collective national will to ensure health care equity through expanded health insurance coverage, support for primary care, and public accountability based on progress toward defined, time-limited objectives using evidence-based, sufficiently resourced, multilevel quality improvement strategies that engage patients, clinicians, health care organizations, and communities.

https://www.annualreviews.org/doi/pdf/10.1146/annurev-publhealth-032315-021439

Racial and Ethnic Disparities in the Quality of Health Care

The Extended Parallel Process Model (EPPM; Communication Monographs, 59, 1992, 329) is a predominant message design theory in the social science fear appeal literature that provides a framework for effective communication of health-related information. This paper provides a review and update of the theory and the use of fear appeals in persuasion. First, a brief overview of the EPPM is provided. Then, Littlejohn and Foss (Theories of Human Communication, 2005, Belmont, CA: Thomson Wadsworth) criteria for evaluation of theory are used as a guide for reviewing research guided by the EPPM in terms of the consistency of data with theoretical predictions, how it has been adjusted and extended through research findings, and a discussion of future research to expand social scientific knowledge about fear appeals and persuasion. It is concluded that the EPPM has advanced our understanding of how fear appeals operate and continues to generate questions for research in risk messaging.

Fear appeals and persuasion: A review and update of the Extended Parallel Process Model.

Over the past decade, researchers have shifted their focus from documenting health care disparities to identifying solutions to close the gap in care Finding Answers: Disparities Research for Change, a national program of the Robert Wood Johnson Foundation, is charged with identifying promising interventions to reduce disparities Based on our work conducting systematic reviews of the literature, evaluating promising practices, and providing technical assistance to health care organizations, we present a roadmap for reducing racial and ethnic disparities in care The roadmap outlines a dynamic process in which individual interventions are just one part It highlights that organizations and providers need to take responsibility for reducing disparities, establish a general infrastructure and culture to improve quality, and integrate targeted disparities interventions into quality improvement efforts Additionally, we summarize the major lessons learned through the Finding Answers program We share best practices for implementing disparities interventions and synthesize cross-cutting themes from 12 systematic reviews of the literature Our research shows that promising interventions frequently are culturally tailored to meet patients’ needs, employ multidisciplinary teams of care providers, and target multiple leverage points along a patient’s pathway of care Health education that uses interactive techniques to deliver skills training appears to be more effective than traditional didactic approaches Furthermore, patient navigation and engaging family and community members in the health care process may improve outcomes for minority patients We anticipate that the roadmap and best practices will be useful for organizations, policymakers, and researchers striving to provide high-quality equitable care

Electronic supplementary material
The online version of this article (doi:101007/s11606-012-2082-9) contains supplementary material, which is available to authorized users

/pdf/a-roadmap-and-best-practices-for-organizations-to-reduce-2xiwy5gsmm.pdf

A Roadmap and Best Practices for Organizations to Reduce Racial and Ethnic Disparities in Health Care

The extended parallel process model was employed to increase intentions to use on-the-job hearing protection among agricultural workers. Brochures were designed to increase perceptions of the threat of hearing loss and the efficacy of hearing protection to avert hearing loss. Brochures were presented to one half of the sample in each population (farmers and landscapers), and a questionnaire was administered assessing perceptions of threat, efficacy, and intentions. The other half of each sample completed the questionnaire, and then received brochures. Results indicated that farmers were initially high in threat and efficacy perceptions, but brochure exposure resulted in higher intentions to use hearing protection. Landscapers perceived higher threat, efficacy, and intentions after being presented with the brochure. Results are discussed in terms of future research and practical application.

Nicole M. Keesecker

Papers

A Roadmap and Best Practices for Organizations to Reduce Racial and Ethnic Disparities in Health Care

Using the EPPM to Create and Evaluate the Effectiveness of Brochures to Increase the Use of Hearing Protection in Farmers and Landscape Workers