Shirley M. Moore, PhD, RN, is the Edward J. and Louise Mellen Professor of Nursing, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Carol M. Musil, PhD, RN, is the Marvin E. and Ruth Durr Denekas Professor of Nursing, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Anthony I. Jack, PhD, is Associate Professor, Department of Philosophy, Case Western Reserve University, Cleveland, Ohio. Megan L. Alder, BSN, RN, is PhD Student, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. David M. Fresco, PhD, is Professor, Department of Psychological Sciences, Kent State University, and Case Western Reserve University, Cleveland, Ohio. Alison Webel, PhD, RN, is Assistant Professor, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Kathy D. Wright, PhD, RN, CNS, is Assistant Professor, Chief Diversity Officer, The College of Nursing, The Ohio State University, Columbus. Abdus Sattar, PhD, is Associate Professor, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio. Patricia Higgins, PhD, RN, is Associate Professor, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio.
Nurs Res. 2019 Mar/Apr;68(2):127-134. doi: 10.1097/NNR.0000000000000331.
Although many of the proposed mediating processes of self-management interventions are operationally defined as cognitive processes (e.g., acquiring and using information, self-efficacy, motivation, and decision-making), little is known about their underlying brain mechanisms. Brain biomarkers of how people process health information may be an important characteristic on which to individualize health information to optimize self-management of chronic conditions.
We describe a program of research addressing the identification of brain biomarkers that differentially predict responses to two types of health information (analytic focused and emotion focused) designed to support optimal self-management of chronic conditions.
We pooled data from two pilot studies (N = 52) that included functional magnetic resonance imaging during a specially designed, ecologically valid protocol to examine brain activation (task differentiation) associated with two large-scale neural networks-the Analytic Network and the Empathy Network-and the ventral medial prefrontal cortex while individuals responded to different types of health information (analytic and emotional).
Findings indicate that analytic information and emotional information are processed differently in the brain, and the magnitude of this differentiation in response to type of information varies from person to person. Activation in the a priori regions identified in response to both analytic and emotion information was confirmed. The feasibility of obtaining brain imaging data from persons with chronic conditions also is demonstrated.
An understanding of brain signatures related to information processing has potential to assist in the design of more individualized, effective self-management interventions.
尽管自我管理干预措施的许多提出的中介过程在操作上被定义为认知过程（例如，获取和使用信息、自我效能、动机和决策），但人们对其潜在的大脑机制知之甚少。了解人们如何处理健康信息的大脑生物标志物可能是一个重要特征，可以根据个体特征来个性化健康信息，以优化慢性疾病的自我管理。
我们描述了一个研究计划，旨在确定大脑生物标志物，这些标志物可以预测两种类型的健康信息（分析型和情感型）的反应，这些信息旨在支持慢性疾病的最佳自我管理。
我们汇集了两项试点研究（N=52）的数据，这些研究包括在专门设计的、生态有效的协议中进行功能磁共振成像，以检查在个体对不同类型的健康信息（分析型和情感型）做出反应时，与两个大型神经网络（分析网络和同理心网络）和腹内侧前额叶皮层相关的大脑激活（任务分化）。
研究结果表明，大脑对分析信息和情感信息的处理方式不同，而且对信息类型的反应的这种分化程度因人而异。对分析和情感信息都有反应的先验区域的激活得到了证实。还证明了从患有慢性疾病的人获得大脑成像数据的可行性。
对与信息处理相关的大脑特征的理解有可能有助于设计更个体化、更有效的自我管理干预措施。
