In the 19th century, Western medicine spread widely worldwide and ultimately diffused into Japan. It had a significant impact on previous Japanese medical practice and education; it is, effectively, the foundation of contemporary Japanese medicine. Although Western medicine seems universal, its elements and origins as it has spread to other countries show localized differences, depending on the context and time period. Cultural fusion theory proposes that the culture of a host and influence of a newcomer conflict, merge, or transform each other. It could shed light on how Japanese medicine and medical education have been influenced by and coevolved with Western medicine and culture. Cultural fusion is not assimilation or adaptation; it has numerous churning points where the traditional and the modern, the insider (indigenous) and the outsider (immigrant), mix and compete. In Japan, medicine has a long history, encountering medical practices from neighboring countries, such as China and Korea in ancient times, and Western countries in the Modern period. The most drastic changes happened in the 19th century with strong influence from Germany before World War II and in the 20th century from the impact of the United States after World War II. Recently, the pressure of globalization could be added as one influence. Since cultural fusion is ubiquitous in Japanese medical fields, examples showing how the host and newcomers interact and merge can be found among many aspects of Japanese medicine and medical education, such as curricula, languages, systems, learning styles, assessment methods, and educational materials. In addition, cultural fusion is not limited to influence from the West but extends to and from neighboring Asian countries. Examining cases and previous studies on cultural fusion in Japanese medicine and medical education could reveal how the typical notion that Japan pursued Westernization of its medicine and medical education concealed the traditions and the growth of the local education system. The people involved in medicine in the past and the present have struggled to integrate the new system with their previous ideals to improve their methods, which could be further researched.
Mariko Morishita and Miho Iwakuma
Roxanne L. Parrott, Amber K. Worthington, Rachel A. Smith, and Amy E. Chadwick
The public, including lay members who have no personal or familial experience with genetic testing or diagnosis, as well as individuals who have had such experiences, face many intrinsic decisions relating to understanding genetics. With the sequencing of the human genome and genetic science discoveries relating genes to cancer, heart disease, and diabetes, the scope of such decisions broadened from prenatal genetic testing related to reproductive choices to genetic testing for contributors to common causes of morbidity and mortality. The decision about whether to seek genetic testing encompasses concerns about stigma and discrimination. These issues lead some who can afford the cost to seek screening through online direct-to-consumer sites rather than in clinical settings. Many who may benefit from genetic testing lack awareness of family health history that could guide physicians to recommend these diagnostic tests. Families may not discuss health history due to genetic illiteracy, with the public’s genetic illiteracy increasing their illness uncertainty and decreasing the likelihood that physicians will engage in conversations about personalized medicine with their patients. Physicians may nonetheless order genetic tests based on patients’ symptoms, during preoperative workups, or as part of opportunistic screening and assessment associated with a specific genetic workup. Family members who receive positive genetic test results may not disclose them to life partners, other family members, or insurance companies based on worries and anxiety related to their own identity, as well as a lack of understanding about their family members’ risk probability. For many, misguided beliefs that genes absolutely determine health and disease status arise from media translations of genetic science. These essentialist beliefs negatively relate to personal actions to limit genetic expression, including failure to seek medical care, while contributing to stereotypes and stigma communication. As medical science continues to reveal roles for genes in health across a broad spectrum, communicating about the relationships that genes have for health will be increasingly complex. Policy associated with registering, monitoring, and controlling the activities of those with genetic mutations may be coercive and target individuals unable to access health care or technology. Communicating about genes, health, and risk will thus challenge health communicators throughout the 21st century.
Teresa L. Thompson and Kelly Haskard-Zolnierek
Patient adherence (sometimes referred to as patient compliance) is the extent to which a patient’s health behavior corresponds with the agreed-upon recommendations of the healthcare provider. The term patient compliance is generally synonymous with adherence but suggests that the patient played a more passive role in the healthcare professional’s prescription of treatment, whereas the term adherence suggests that the patient and healthcare professional have come to an agreement on the regimen through a collaborative, shared decision-making process. Another term related to the concept of adherence is persistence (i.e., taking a medication for the recommended duration). Some patients are purposefully or intentionally nonadherent, whereas others are unintentionally nonadherent due to forgetfulness or poor understanding of the regimen. Patients may be intentionally nonadherent because of a belief that the costs of the regimen outweigh the benefits, for example. Nonadherence behaviors in medication taking include never filling a prescription, taking too much or too little medication, or taking a medication at incorrect time intervals. Patient adherence is relevant not only in medication-taking behaviors, but also in health behaviors such as following a specific dietary regimen, maintaining an exercise program, attending follow-up appointments, getting recommended screenings or immunizations, and smoking cessation, among others. A number of factors predict patient adherence to treatment, but the relationship between provider-patient communication and adherence to treatment will be stressed. Focusing on recent research, the article examines the concept of patient adherence, describes how provider-patient communication can enhance patient adherence, explains what elements of communication are relevant for adherence, and illustrates how interventions to improve communication can improve adherence.
Wayne A. Beach, Kyle Gutzmer, and Chelsea Chapman
Beginning with phone calls to an emergency psychiatric hospital and suicide prevention center, the roots of Conversation Analysis (CA) are embedded in systematic analyses of routine problems occurring between ordinary persons facing troubling health challenges, care providers, and the institutions they represent. After more than 50 years of research, CA is now a vibrant and robust mode of scientific investigation that includes close examination of a wide array of medical encounters between patients and their providers. Considerable efforts have been made to overview CA and medicine as a rapidly expanding mode of inquiry and field of research. Across a span of 18 years, we sample from 10 of these efforts to synthesize important priorities and findings emanating from CA investigations of diverse interactional practices and health care institutions. Key topics and issues are raised that provide a unique opportunity to identify and track the development and maturity of CA approaches to medical encounters. Attention is also given to promising new modes of research, and to the potential and challenges of improving medical practices by translating basic and rigorous empirical findings into innovative interventions for medical education. A case is made that increasing reliance on CA research can positively impact training and policies shaping the delivery of humane and quality medical care.
Jennifer A. Malkowski, J. Blake Scott, and Lisa Keränen
Rhetoric, commonly understood as the art, practice, and analysis of persuasion, has longstanding connections to medicine and health. Rhetorical scholars, or rhetoricians, have increasingly applied rhetorical theories, concepts, and methods to the texts, contexts, discourses, practices, materials, and digital and visual artifacts related to health and medicine. As an emerging interdisciplinary subfield, the rhetoric of health and medicine seeks to uncover how symbolic patterns shape thought and action in health and medical texts, discourses, settings, and materials. In practice, rhetoricians who study health and medicine draw from the standard modes of rhetorical analysis, such as rhetorical criticism and rhetorical historiography, as well as from social science methods—including participant observation, interviewing, content analysis, and visual mapping—in order to deepen understanding of how language functions across health and medical objects, issues, and discussions. The objects of analysis for rhetorical studies of health and medicine span medical research, education, and clinical practice from laboratory notes to provider–patient interaction; health policymaking and practice from draft policies through standards of care; public health texts and artifacts; consumer health practices and patient advocacy on- and offline; public discourses about disease, death, bodies, illness, wellness, and health; online and digital health information; popular entertainments and medical dramas; and alternative and complementary medicine. Despite its methodological breadth, rhetorical approaches to science and medicine consistently involve the systematic examination and production of symbolic exchanges occurring across interactional, institutional, and public contexts to determine how individuals and groups create knowledge, meanings, identities, understandings, and courses of action about health and illness.
Bradford William Hesse
The presence of large-scale data systems can be felt, consciously or not, in almost every facet of modern life, whether through the simple act of selecting travel options online, purchasing products from online retailers, or navigating through the streets of an unfamiliar neighborhood using global positioning system (GPS) mapping. These systems operate through the momentum of big data, a term introduced by data scientists to describe a data-rich environment enabled by a superconvergence of advanced computer-processing speeds and storage capacities; advanced connectivity between people and devices through the Internet; the ubiquity of smart, mobile devices and wireless sensors; and the creation of accelerated data flows among systems in the global economy. Some researchers have suggested that big data represents the so-called fourth paradigm in science, wherein the first paradigm was marked by the evolution of the experimental method, the second was brought about by the maturation of theory, the third was marked by an evolution of statistical methodology as enabled by computational technology, while the fourth extended the benefits of the first three, but also enabled the application of novel machine-learning approaches to an evidence stream that exists in high volume, high velocity, high variety, and differing levels of veracity. In public health and medicine, the emergence of big data capabilities has followed naturally from the expansion of data streams from genome sequencing, protein identification, environmental surveillance, and passive patient sensing. In 2001, the National Committee on Vital and Health Statistics published a road map for connecting these evidence streams to each other through a national health information infrastructure. Since then, the road map has spurred national investments in electronic health records (EHRs) and motivated the integration of public surveillance data into analytic platforms for health situational awareness. More recently, the boom in consumer-oriented mobile applications and wireless medical sensing devices has opened up the possibility for mining new data flows directly from altruistic patients. In the broader public communication sphere, the ability to mine the digital traces of conversation on social media presents an opportunity to apply advanced machine learning algorithms as a way of tracking the diffusion of risk communication messages. In addition to utilizing big data for improving the scientific knowledge base in risk communication, there will be a need for health communication scientists and practitioners to work as part of interdisciplinary teams to improve the interfaces to these data for professionals and the public. Too much data, presented in disorganized ways, can lead to what some have referred to as “data smog.” Much work will be needed for understanding how to turn big data into knowledge, and just as important, how to turn data-informed knowledge into action.