Modeling Complex Mechanisms Underlying Oral Health Disparities in Young Children and Their Caregivers

我们建议使用复杂系统科学方法来理解社会联系如何影响 幼儿及其照顾者对牙科护理的利用。我们研究计划的总体目标是 解决儿童早期龋齿（ECC）的差异，因为它仍然是影响儿童健康的最普遍的疾病。 儿童，其后果可能是严重和持久的。 社会影响是疾病原因、疾病的人群分布（例如， 差异），以及通过社交网络改变与健康相关的行为。理解社会影响力的作用 提供了一个强有力的观点，为什么只针对个人的行为干预往往失败， 产生有意义的结果。由于这些原因，对社交网络干预发展的兴趣已经 增长，但许多必要的信息，以制定和适当调整干预措施，以基本的 严重缺乏导致疾病产生的机制，特别是对面临疾病威胁的人口而言。 最大的疾病负担。 复杂系统科学方法，如基于代理的建模和社会网络分析，可以 对造成健康差距的机制提供重要见解。然而， 对口腔健康的应用是最小的。我们建议应用复杂系统科学的方法来理解 ECC的种群分布机制。我们提出以下具体目标： (1)描述照顾者的社会联系与个人层面互动的途径 口腔健康状况，行为和牙科保健实践的看法，以塑造ECC的人口模式。 (2)评估幼儿照顾者的社会网络结构和组成， 波士顿公共住房居民样本中的水平牙科保健利用行为。 (3)确定和测试旨在改变社会行为和龋齿风险的假设干预措施 通过使用计算机模拟实验的机制（即，模拟）。 我们的研究结果将为设计针对复杂系统的有针对性的干预措施提供信息。 受健康差距影响的人口动态。ECC的患病率和严重程度与 来自弱势群体（包括穷人和某些种族/族裔少数群体）的儿童的比例更高。 重要的是，ECC是美国儿童最大的未满足的医疗保健需求之一， 存在护理使用。公屋居民是研究贫富差距的高影响人群。作为 这些地区的特点是贫困和健康状况不佳的空间聚集， 对于拟议的工作。我们的研究结果有望对相互作用的强度产生重要的见解 负责产生行为模式及其后果，并提供必要的数据， 利用社会关系作为干预措施的潜在杠杆点，以改善口腔健康。

We propose to use complex systems science methods to understand how social connectedness influences the utilization of dental care by young children and their caregivers. The overall goal of our research program is to address disparities in Early Childhood Caries (ECC) as it remains the most prevalent disease afflicting children, the consequences of which can be serious and long lasting. Social influence is an important moderator of the causes of disease, the population distribution of disease (e.g. disparities), and health-related behavior change via social networks. Understanding the role of social influence provides a potent perspective on why behavioral interventions aimed solely at individuals have often failed to produce meaningful results. For these reasons, interest in the development of social network interventions has grown, but much of the information necessary to develop and adequately tailor interventions to the underlying mechanisms responsible for disease production is severely lacking, especially for populations facing the greatest burdens of disease. Complex systems science approaches, such as agent-based modeling and social network analysis, can provide critical insights into the mechanisms responsible for the production of health disparities. Yet, applications to oral health are minimal. We propose to apply complex systems science methods to understand the mechanisms underlying population distributions of ECC. We propose the following specific aims: (1) Characterize the pathways by which social connectedness of caregivers interacts with individual-level perceptions of oral health status, behaviors and dental care practices to shape population patterns of ECC. (2) Evaluate social network structure and composition of caregivers of young children in relation to individual- level dental care utilization behaviors among a sample of Boston public housing residents. (3) Identify and test hypothetical interventions aimed at modifying the social-behavioral and caries risk mechanisms through the use of in silico experimentation (i.e., simulations). Outcomes of our research will inform the design of targeted interventions that respond to complex system dynamics of populations affected by health disparities. ECC prevalence and severity are disproportionately higher among children from disadvantaged groups, including the poor and certain racial/ethnic minority groups. Importantly, ECC is one of the largest unmet healthcare needs of children in the US, and significant disparities in care utilization exist. Public housing residents are a high impact population for the study of disparities. As a population group, they are characterized by spatial clustering of poverty and poor health and are ideally suited for the proposed work. Our results are expected to yield important insights into the strength of the interactions responsible for producing behavioral patterns and their consequences, and provided the necessary data for using social relationships as potential leverage points for interventions to improve oral health.