Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

This article synthesizes what is known about the relationship between social disadvantage and measures of health literacy (HL), and reviews the research examining whether low HL is an explanatory factor connecting social disadvantage, health outcomes, and health disparities. Written from a United States perspective, this article offers a novel conceptual framework that presents how the social determinants of health might interact with HL to result in health disparities. The framework articulates relationships that reflect public health pathways and health care pathways, which include their related health literacies. The article continues with several cautionary statements based on the inherent limitations of current HL research, including problems and concerns specific to the attribution of HL as an explanatory factor for extant socioeconomic and racial/ethnic health disparities. The article closes with recommendations regarding future research directions. [ HLRP: Health Literacy Research and Practice . 2021;5(3):e233–e243.] Plain Language Summary: Socially disadvantaged populations have worse health and health literacy compared to privileged populations. Scientists, health care providers, and policymakers are interested in the possible role health literacy plays in explaining health differences. The article reviews our current understandings of whether and how population characteristics and related exposures to risk interact with low health literacy to generate worse health to inform interventions.

Despite the ubiquity of health-related communications via social media, no consensus has emerged on whether this medium, on balance, jeopardizes or promotes public health. During the COVID-19 pandemic, social media has been described as the source of a toxic “infodemic” or a valuable tool for public health. No conceptual model exists for examining the roles that social media can play with respect to population health. We present a novel framework to guide the investigation and assessment of the effects of social media on public health: the SPHERE (Social media and Public Health Epidemic and REsponse) continuum. This model illustrates the functions of social media across the epidemic–response continuum, ranging across contagion, vector, surveillance, inoculant, disease control, and treatment. We also describe attributes of the communications, diseases and pathogens, and hosts that influence whether certain functions dominate over others. Finally, we describe a comprehensive set of outcomes relevant to the evaluation of the effects of social media on the public’s health.

We sought to identify interest in different modes of self-management support among diabetes patients cared for in public hospitals, and to assess whether demographic or disease-specific factors were associated with patient preferences. We explored the possible role of a perceived communication need in influencing interest in self-management support. Telephone survey of a random sample of 796 English and Spanish-speaking diabetes patients (response rate 47%) recruited from four urban US public hospital systems. In multivariate models, we measured the association of race/ethnicity, primary language, self-reported health literacy, self-efficacy, and diabetes-related factors on patients' interest in three self-management support strategies (telephone support, group medical visits, and Internet-based support). We explored the extent to which patients believed that better communication with providers would improve their diabetes control, and whether this perception altered the relationship between patient factors and self-management support acceptance. Sixty-nine percent of respondents reported interest in telephone support, 55% in group medical visits, and 42% in Internet. Compared to Non-Hispanic Whites, Spanish-speaking Hispanics were more interested in telephone support (OR 3.45, 95% CI 1.97-6.05) and group medical visits (OR 2.45, 95% CI 1.49-4.02), but less interested in Internet self-management support (OR 0.56, 95% CI 0.33-0.93). African-Americans were more interested than Whites in all three self-management support strategies. Patients with limited self-reported health literacy were more likely to be interested in telephone support than those not reporting literacy deficits. Forty percent reported that their diabetes would be better controlled if they communicated better with their health care provider. This perceived communication benefit was independently associated with interest in self-management support (p<0.001), but its inclusion in models did not alter the strengths of the main associations between patient characteristics and self-management support preferences. Many diabetes patients in safety-net settings report an interest in receiving self-management support, but preferences for modes of delivery of self-management support vary by race/ethnicity, language proficiency, and self-reported health literacy. Public health systems should consider offering a range of self-management support services to meet the needs of their diverse patient populations. More broad dissemination and implementation of self-management support may help address the unmet need for better provider communication among diabetes patients in these settings.

This chapter synthesizes what is known about the relationship between social disadvantage and measures of low health literacy (LHL), and reviews the research examining whether LHL is an explanatory factor connecting social disadvantage, health outcomes, and health disparities. Written from a U.S. perspective, the chapter then offers a novel conceptual framework that presents how the social determinants of health might interact with LHL to result in health disparities. The framework articulates relationships that reflect public health pathways and healthcare pathways, which include their related health literacies. In addition, the chapter highlights as an exemplar one important potential causal mechanism in the healthcare pathway by exploring the communication model in outpatient care, as communication has been very well-studied with respect to both health disparities and HL. The chapter then, provides two examples of HL interventions aligned with the conceptual framework, one of which addresses the health care literacy pathway, and the other addresses the public health literacy pathway. The chapter continues with a number of cautionary statements based on the inherent limitations of current HL research, including problems and concerns specific to the attribution of HL as an explanatory factor for extant socioeconomic and racial/ethnic health disparities. The chapter closes with recommendations regarding future research directions.

Individuals with severe mental illness (e.g., schizophrenia, bipolar disorder) die 10–25 years earlier than the general population, primarily from premature cardiovascular disease (CVD). Contributing factors are complex, but include systemic-related factors of poorly integrated primary care and mental health services. Although evidence-based models exist for integrating mental health care into primary care settings, the evidence base for integrating medical care into specialty mental health settings is limited. Such models are referred to as “reverse” integration. In this paper, we describe the application of an implementation science framework in designing a model to improve CVD outcomes for individuals with severe mental illness (SMI) who receive services in a community mental health setting. Using principles from the theory of planned behavior, focus groups were conducted to understand stakeholder perspectives of barriers to CVD risk factor screening and treatment identify potential target behaviors. We then applied results to the overarching Behavior Change Wheel framework, a systematic and theory-driven approach that incorporates the COM-B model (capability, opportunity, motivation, and behavior), to build an intervention to improve CVD risk factor screening and treatment for people with SMI. Following a stepped approach from the Behavior Change Wheel framework, a model to deliver primary preventive care for people that use community mental health settings as their de facto health home was developed. The CRANIUM (cardiometabolic risk assessment and treatment through a novel integration model for underserved populations with mental illness) model focuses on engaging community psychiatrists to expand their scope of practice to become responsible for CVD risk, with significant clinical decision support. The CRANIUM model was designed by integrating behavioral change theory and implementation theory. CRANIUM is feasible to implement, is highly acceptable to, and targets provider behavior change, and is replicable and efficient for helping to integrate primary preventive care services in community mental health settings. CRANIUM can be scaled up to increase CVD preventive care delivery and ultimately improve health outcomes among people with SMI served within a public mental health care system.