Using a Short Screening Scale for Small-Area Estimation of Mental Illness Prevalence for Schools

We use data collected in the National Comorbidity Survey-Adolescent (NCS-A) to develop a methodology to estimate the small-area prevalence of serious emotional distress (SED) in schools in the United States, exploiting the clustering of the main NCS-A sample by school. The NCS-A instrument includes both a short screening scale, the K6, and extensive diagnostic assessments of the individual disorders and associated impairment that determine the diagnosis of SED. We fitted a Bayesian bivariate multilevel regression model with correlated effects for the probability of SED and a modified K6 score at the individual and school levels. Our results provide evidence for the existence of variation in the prevalence of SED across schools and geographical regions. Although the concordance between the modified K6 scale and SED is only modest for individuals, the school-level random effects for the two measures are strongly correlated. Under this model we obtain a prediction equation for the rate of SED based on the mean K6 score and covariates. This finding supports the feasibility of using short screening scales like the K6 as an alternative to more comprehensive lay assessments in estimating school-level rates of SED. These methods may be applicable to other studies aiming at small-area estimation for geographical units.

[1]  Danny Pfeffermann,et al.  Small Area Estimation , 2011, International Encyclopedia of Statistical Science.

[2]  R. Fay,et al.  Estimates of Income for Small Places: An Application of James-Stein Procedures to Census Data , 1979 .

[3]  Nathaniel Schenker,et al.  Combining Information From Two Surveys to Estimate County-Level Prevalence Rates of Cancer Risk Factors and Screening , 2007 .

[4]  R. Kessler,et al.  Final Versions of our Non-Specific Psychological Distress Scale , 1994 .

[5]  C. G. Hudson.  Validation of a model for estimating state and local prevalence of serious mental illness , 2009, International journal of methods in psychiatric research.

[6]  Jiming Jiang,et al.  Mixed model prediction and small area estimation , 2006 .

[7]  David Alan Marker,et al.  Small area estimation: A Bayesian perspective. , 1995 .

[8]  S. Chib,et al.  Bayesian analysis of binary and polychotomous response data , 1993 .

[9]  R. Kessler,et al.  National comorbidity survey replication adolescent supplement (NCS-A): I. Background and measures. , 2009, Journal of the American Academy of Child and Adolescent Psychiatry.

[10]  J. Barendregt,et al.  Global burden of disease , 1997, The Lancet.

[11]  Ronald C Kessler,et al.  Design and field procedures in the US National Comorbidity Survey Replication Adolescent Supplement (NCS‐A) , 2009, International journal of methods in psychiatric research.

[12]  Adrian F. M. Smith,et al.  Sampling-Based Approaches to Calculating Marginal Densities , 1990 .

[13]  Daniel R. Jeske,et al.  Mean Squared Error of Estimation or Prediction under a General Linear Model , 1992 .

[14]  Alan D. Lopez,et al.  The global burden of disease: a comprehensive assessment of mortality and disability from diseases injuries and risk factors in 1990 and projected to 2020. , 1996 .

[15]  Subir Ghosh,et al.  Multivariate analysis, design of experiments, and survey sampling , 2000 .

[16]  D. Rubin,et al.  Inference from Iterative Simulation Using Multiple Sequences , 1992 .

[17]  C. Desouza,et al.  An Approximate Bivariate Bayesian Method for Analyzing Small Frequencies , 1992 .

[18]  Malay Ghosh,et al.  Estimation of Median Income of Four-Person Families: A Bayesian Approach , 1996 .

[19]  Rachel M. Harter,et al.  The multivariate components of variance model for small area estimation , 1986 .

[20]  Xiao-Li Meng,et al.  Modeling covariance matrices in terms of standard deviations and correlations, with application to shrinkage , 2000 .

[21]  R. Kessler,et al.  Improving the K6 short scale to predict serious emotional disturbance in adolescents in the USA , 2010, International journal of methods in psychiatric research.

[22]  Bradley P. Carlin,et al.  Generalized Linear Models for Small-Area Estimation , 1998 .

[23]  T. Maiti,et al.  MULTIVARIATE BAYESIAN SMALL AREA ESTIMATION : AN APPLICATION TO SURVEY ANDSATELLITE DATA , 1998 .

[24]  N. Breslow,et al.  Approximate inference in generalized linear mixed models , 1993 .

[25]  William J Browne,et al.  MCMC Estimation in MLwiN (Version 2.13) Centre for Multilevel Modelling, University of Bristol , 2009 .

[26]  Xiao-Li Meng,et al.  POSTERIOR PREDICTIVE ASSESSMENT OF MODEL FITNESS VIA REALIZED DISCREPANCIES , 1996 .

[27]  Rachel M. Harter,et al.  An Error-Components Model for Prediction of County Crop Areas Using Survey and Satellite Data , 1988 .

[28]  Malay Ghosh,et al.  Small Area Estimation: An Appraisal , 1994 .

[29]  R. Kessler,et al.  Estimating prevalence of serious emotional disturbance in schools using a brief screening scale , 2010, International journal of methods in psychiatric research.