LATE LIFE DEPRESSION OUTCOME & MEDICAL ILLNESS SEVERITY

描述：晚年抑郁症的公共卫生意义 在初级保健环境中的作用是公认的。特别是，横截面 抑郁症状的发病率不符合诊断标准的主要 抑郁症比单纯的重度抑郁症更严重。但不 如果不知道这种情况是否会持续下去， 或有其他长期的疾病。因此，修订后的R 01 应用程序提出了测试的假设， 定义的轻微/亚综合征抑郁症将有一个中间3-4年 结果（与非抑郁对照组和重度抑郁患者相比） 抑郁症）在以下领域：抑郁症状和诊断， 医学疾病严重程度、死亡率、功能状态和医疗保健 利用率和成本。此外，调查还将测试以下假设： 特定的理论变量与上述变量之间的关联 结果。这些预测因素涵盖了生物心理社会领域，包括 脑血管病危险因素，总体医疗负担，功能状态， 人格特质、社会支持、宗教信仰和 生活事件研究者将招募并随访1000名受试者，年龄 ≥ 65岁，来自纽约州门罗县的各种初级保健中心 人口研究评估将来自病历审查， HCFA数据以及使用经验证的 DSM-IV的结构化临床访谈和 纵向间隔随访评价。将使用协方差分析 来检验结果的群体差异。多元回归技术将 用于确定假设预测因子的独立关联 有结果。这些结果将直接为未来的研究提供信息，包括 确定干预的对象，并确定理论 抑郁症发病机制模型值得更明确的测试。

DESCRIPTION: The public health significance of later life depressive conditions in primary care settings is well recognized. In particular, the cross-sectional morbidity of depressive symptoms not meeting diagnostic criteria for major depression is greater than that of major depression alone. However, it is not known whether such conditions persist, lead to more severe depressive conditions, or have other long term morbidity. Accordingly, this revised R01 application proposes to test the hypothesis that patients with operationally defined minor/subsyndromal depression will have an intermediate 3-4 year outcome (as compared to non-depressed controls and to patients with major depression) in the following domains: depressive symptoms and diagnoses, medical illness severity, mortality, functional status, and health care utilization and costs. Also, the investigation will test hypotheses regarding the associations of specific theoretically based variables with the above outcomes. The predictors range across the biopsychosocial spectrum, including cerebrovascular risk factors, overall medical burden, functional status, the Five Factor Model of personality traits, social support, religiousness, and life events. The Study investigators Will recruit and follow 1000 subjects, age >= 65 years, from a variety of primary care sites serving the Monroe County, NY population. Study assessments will be derived from medical chart reviews and HCFA data as well as semi-structured patient interviews using validated measures such as the Structured Clinical Interview for DSM-IV and the Longitudinal Interval Follow-up Evaluation. Analysis of covariance will be used to examine group differences in outcomes. Multiple regression techniques will be used to determine the independent association of hypothesized predictors with outcomes. The results will directly inform future research, including identifying subjects for interventions as well as identifying theoretical models of depression pathogenesis that merit more definitive testing.