Using Community Participation to Improve the Health System in South India

描述(申请人提供)：耻辱是一个主要的社会问题，阻碍了控制传染病的努力。医学和社会科学以前的大部分研究都集中在个人遭受耻辱的经历上，而很少关注耻辱是如何发展的以及为什么会发展。这项拟议的研究采用了一种新的方法，将耻辱概念化为一种社区层面的现象。借鉴经济学的最新进展，发展了一种结构理论(目标1)，该理论认为，至少在最初，污名通过减少感染的传播而造福于社区。一旦开发出一种治疗方法，污名仍然在一些社区持续存在，导致动态低效，而在另一些社区则消失了。 这一理论将使用来自印度农村的独特的初级和行政数据进行验证，印度农村是一项正在进行的由国家卫生研究院资助的研究(HD 058831)的所在地，该研究正在评估社区志愿者(村庄或种姓成员)对结核病患者坚持治疗的影响。实证分析的第一步将是确定社区的定义(村庄、种姓或 (村里的种姓)，这与印度的污名分析有关(目标2)。第二步将是确定耻辱是一种社区一级的现象，而不是个人一级的现象(目标3)。该理论表明，一旦开发出一种治疗方法，社区要么保持污名化平衡，要么转向非污名化平衡，这取决于它们的基本特征。财富或教育水平高于门槛的社区，如果拥有健康的成员，就会不成比例地受益，很容易变得不受羞辱。获得医疗服务的门槛水平以上的社区也将成为非污名化社区，这将降低治疗成本。然而，污名标准将在低于这些门槛的社区中持续存在。经验分析的第三步将是从统计上确定社区从污名化向非污名化平衡不连续转变的阈值(目标4)。最后一步将是审查健康结果--检测延迟和不坚持治疗结核病--是否在相同的阈值上不连续地变化，这将为污名和这些健康结果之间的理论和因果关系提供支持(目标5)。拟议分析的大部分数据已经收集完毕，例如，一系列污名措施、社区特征和治疗结果。补充项目将从整个研究区域的中心收集更多的结核病检测数据。总体而言，这项创新研究为污名的分析带来了一种全新的基于社区的理论视角和最先进的非线性计量经济学技术。除了对基础社会科学的贡献外，研究结果还将为未来寻求减少耻辱和改善健康结果的政策干预措施提供信息，方法是：(1)表明这些干预措施的最佳设计应在社区(而不是个人)一级进行；(2)确定最容易从污名化走向非污名化平衡的特定社区。

DESCRIPTION (provided by applicant): Stigma is a major social problem that hinders efforts to control communicable diseases. Much of the previous research from the medical and social sciences focuses on individual experiences with stigma and pays little attention to how and why stigma develops. The proposed research takes a new approach and conceptualizes stigma as a community-level phenomenon. Drawing on recent advances in economics, a structural theory is developed (Aim 1) which argues that, at least initially, stigma serves to benefit the community by reducing the spread of infection. Once a treatment has been developed, stigma nevertheless persists in some communities, giving rise to a dynamic inefficiency, while it dissipates in others. This theory will be tested using unique primary and administrative data from rural India, the site of an ongoing NIH-funded study (HD 058831) that is evaluating the impact of community volunteers (village or caste members) on adherence to treatment among TB patients. The first step in the empirical analysis will be to establish the definition of community (village, caste, or caste within village) that is relevant for the analysis of stigma in the Indian context (Aim 2). Th second step will be to establish that stigma is a community-level rather than individual-level phenomenon (Aim 3). The theory indicates that once a treatment is developed, communities will either remain in the stigmatizing equilibrium or move to a non-stigmatizing equilibrium, depending on their fundamental characteristics. Communities above a threshold level of wealth or education, which benefit disproportionately from having healthy members, will readily become non-stigmatizing. Communities above a threshold level of access to health services, which lowers the cost of treatment, will also become non- stigmatizing. However, the stigma norm will persist in communities below these thresholds. The third step in the empirical analysis will be to statistically identify the threshold at which communities switch discontinuously from the stigmatizing to the non-stigmatizing equilibrium (Aim 4). The final step will be to examine whether health outcomes - testing delays and non-adherence to treatment for TB - change discontinuously at the same threshold, which would provide support for the theory and the causal relationship between stigma and those health outcomes (Aim 5). Much of the data for the proposed analysis is already being collected, e.g., a range of stigma measures, community characteristics, and treatment outcomes. The supplemental project will collect additional TB testing data from centers throughout the study area. Overall, this innovative research brings a fresh community-based theoretical perspective and state-of-the-art non-linear econometric techniques to the analysis of stigma. Apart from the contribution to basic social science, the results will inform future policy interventions that seek to reduce stigma and improve health outcomes by (1) showing that the optimal design of these interventions should be at the community (rather than individual) level and (2) identifying specific communities that could most easily be pushed from the stigmatizing to the non-stigmatizing equilibrium.