Department of Statistical Science, Duke University, Durham, NC, USA.
Int J Methods Psychiatr Res. 2010 Jun;19 Suppl 1(Suppl 1):88-98. doi: 10.1002/mpr.315.
Information about the prevalence of serious mental illness (SMI) among adults or serious emotional disturbance (SED) among youth in small domains such as counties, states, or schools is valuable for mental health policy planning purposes, but prohibitively expensive to collect with semi-structured surveys. Commonly used synthetic estimation methods yield imprecise estimates. An improved method is described here that combines information about socio-demographic covariates with screening scale scores obtained from a sample of individuals, using a prediction equation derived from a Bayesian multilevel regression model with bivariate outcomes fitted to a larger population survey. This method is illustrated using K6 screening scale scores to predict school-level prevalence of SED in the sample of 282 schools that participated in the National Comorbidity Survey Replication Adolescent Supplement. Respondents completed a diagnostic interview that was used to define DSM-IV SED. SED prevalence varied significantly across schools and was strongly correlated with aggregate K6 scores (rho = 0.70). Calculations suggest that near-maximum precision of school-level SED prevalence estimates could be attained with K6 samples of 200 students per school. This modeling approach holds great promise for generating accurate estimates of SMI/SED in small-area planning units based on K6 scores collected in ongoing health tracking surveys.
有关成年人中严重精神疾病（SMI）或年轻人中严重情绪障碍（SED）在小区域（如县、州或学校）的患病率的信息，对于心理健康政策规划目的非常有价值，但使用半结构化调查收集这些信息非常昂贵。常用的综合估计方法产生的估计结果不够精确。本文描述了一种改进的方法，该方法结合了社会人口学协变量的信息和从个体样本中获得的筛查量表评分，使用从具有双变量结果的贝叶斯多层回归模型得出的预测方程，并拟合到更大的人群调查中。该方法使用 K6 筛查量表评分来预测参与国家共病调查再版青少年补充调查的 282 所学校样本中的 SED 在校级的流行率。受访者完成了一项诊断访谈，用于定义 DSM-IV SED。SED 的流行率在学校之间差异显著，与总 K6 评分呈强相关（rho = 0.70）。计算表明，通过每所学校 200 名学生的 K6 样本，可以获得 SED 在校级的精确估计。这种建模方法为基于正在进行的健康跟踪调查中收集的 K6 评分，在小区域规划单元中生成 SMI/SED 的准确估计提供了巨大的希望。
