The 54-item Social Adjustment Scale – Self-report (SAS-SR) is a measure of social functioning used in research studies and clinical practice. Two shortened versions were recently developed: the 24-item SAS-SR: Short and the 14-item SAS-SR: Screener. We briefly describe the development of the shortened scales and then assess their reliability and validity in comparison to the full SAS-SR in new analyses from two separate samples of convenience from a family study and from a primary care clinic.

Compared to the full SAS-SR, the shortened scales performed well, exhibiting high correlations with full SAS-SR scores (r values between 0.81 and 0.95); significant correlations with health-related quality of life as measured by the Short Form 36 Health Survey; the ability to distinguish subjects with major depression versus other psychiatric disorders versus no mental disorders; and sensitivity to change in clinical status as measured longitudinally with the Symptom Checklist-90 and Global Assessment Scale.

The SAS-SR: Short and SAS-SR: Screener retained the areas assessed by the full SAS-SR with fewer items in each area, and appear to be promising replacements for the full scale when a shorter administration time is desired and detailed information on performance in different areas is not required. Further work is needed to test the validity of the shortened measures.

Evaluations of assessment instruments using classical test theory typically rely on indices of internal consistency, test-retest reliability, and construct validity. However, the use of models from item response theory (IRT) allows comparison of instruments (and items) in terms of the information they provide and where they provide it along the continuum of severity of the construct being assessed. Such results help to identify the measures most appropriate for specific clinical and research contexts. The present study examined the functioning of the Beck Depression Inventory (BDI), the Center for Epidemiologic Studies – Depression Scale (CES-D), and the nine primary symptoms from the depression module of the Schedule for Affective Disorders and Schizophrenia – Children (K-SADS) using IRT methods. A large sample of adolescents (n = 1,709) completed the BDI, CES-D, and K-SADs. IRT calibration analyses demonstrated that the BDI and CES-D performed well in similar ranges of depressive severity (approximately −1 to +3 SDs), although the BDI provided more information at higher severity levels and the CES-D at lower severity levels. The K-SADS depression items, which are dichotomous and focused on clinical disorder, provided the least information that was restricted to the narrowest range (approximately +1 to +3 SDs). This work finds consistency between past rationale for the use of the BDI in clinical samples while using the CES-D in epidemiological studies. The results for the KSADs suggest that interview measures may benefit from increasing the number of items and/or response options to collect more psychometric information.

Research diagnostic interviews need to discriminate between closely related disorders in order to allow comorbidity among mental disorders to be studied reliably. Yet conventional studies of diagnostic validity generally focus on single disorders and do not examine discriminant validity. The current study examines the validity of fully-structured diagnoses of closely-related distress disorders (generalized anxiety disorder, post-traumatic stress disorder, major depressive episode, and dysthymic disorder) in the lay-administered Composite International Diagnostic Interview Version 3.0 (CIDI) with independent clinical diagnoses based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS) in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A). The NCS-A is a national survey of DSM-IV mental disorders among 10,148 adolescents. A probability subsample of 347 of these adolescents and their parents were administered blinded follow-up K-SADS interviews. Good concordance (AUC; area under the receiver operating characteristic curve) was found between diagnoses based on the CIDI and the K-SADS for generalized anxiety disorder (AUC = .78), post-traumatic stress disorder (AUC = .79), and major depressive episode/dysthymic disorder (AUC = .86). Further, the CIDI was able to effectively discriminate among different types of distress disorders in the sub-sample of respondents with any distress disorder.

Accurate information concerning alcohol consumption level and patterns is vital to formulating public health policy. The objective of this paper is to critically assess the extent to which survey design, response rate and alcohol consumption coverage obtained in random digit dialing, telephone-based surveys impact on conclusions about alcohol consumption and its patterns in the general population. Our analysis will be based on the Canadian Alcohol and Drug Use Monitoring Survey (CADUMS) 2008, a national survey intended to be representative of the general population. The conclusions of this paper are as follows: 1) ignoring people who are homeless, institutionalized and/or do not have a home phone may lead to an underestimation of the prevalence of alcohol consumption and related problems; 2) weighting of observations to population demographics may lead to a increase in the design effect, does not necessarily address the underlying selection bias, and may lead to overly influential observations; and 3) the accurate characterization of alcohol consumption patterns obtained by triangulating the data with the adult per capita consumption estimate is essential for comparative analyses and intervention planning especially when the alcohol coverage rate is low like in the CADUMS with 34%.

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 (ρ = .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.

Given the enormous influence of classification on the major clinical, research, and administrative activities of mental health professionals, understanding the true number and nature of disorders and the reasons for their comorbidity is an important public health priority. However, while studies of latent structure have yielded valuable information about disorder boundaries, their reliance on nonrepresentative samples and failure to evaluate the practical implications of structural findings has limited their ability to effect nosological change. Conversely, community epidemiology studies, which inform classification by assessing the implications of diagnostic criteria in representative samples, have been limited by their focus on mental disorders as they are currently conceptualized by the field rather than on correlates and consequences of these disorders as they actually exist in nature. I consider the potential value of integrating systematically the methods of structural research with the methods of epidemiological research, exploring five ways in which these largely independent traditions may profitably be combined to inform the next classifications of mental disorders. By capitalizing on the complementary strengths of structural and epidemiological research, an integrated approach has significant potential to advance understanding of the nature of psychopathology and improve the validity and utility of its diagnosis.

Validity of the adolescent version of the World Health Organization Composite International Diagnostic Interview (CIDI) Version 3.0, a fully-structured research diagnostic interview designed to be used by trained lay interviewers, is assessed in comparison to independent clinical diagnoses based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS). This assessment is carried out in the clinical reappraisal sub-sample (n = 347) of the US National Comorbidity Survey Adolescent Supplement (NCS-A), a large (n = 10,148) community epidemiological survey of the prevalence and correlates of adolescent mental disorders in the US. The diagnoses considered are panic disorder and phobic disorders (social phobia, specific phobia, agoraphobia). CIDI diagnoses are found to have good concordance with K-SADS diagnoses (AUC = .81–.94), although the CIDI diagnoses are consistency somewhat higher than the K-SADS diagnoses. Data are also presented on criterion-level concordance in an effort to pinpoint CIDI question series that might be improved in future modifications of the instrument. Finally, data are presented on the factor structure of the fears associated with social phobia, the only disorder in this series where substantial controversy exists about disorder subtypes.

With emergence of new technologies, there has been an explosion of basic and clinical research on the affective and cognitive neuroscience of face processing and emotion perception. Adult emotional face stimuli are commonly used in these studies. For developmental research, there is a need for a validated set of child emotional faces. This paper describes the development of the NIMH Child Emotional Faces Picture Set (NIMH-ChEFS), a relatively large stimulus set with high quality, color images of the emotional faces of children. The set includes 482 photos of fearful, angry, happy, sad and neutral child faces with two gaze conditions: direct and averted gaze. In this paper we describe the development of the NIMH-ChEFS and data on the set’s validity based on ratings by 20 healthy adult raters. Agreement between the a priori emotion designation and the raters’ labels was high and comparable with values reported for commonly used adult picture sets. Intensity, representativeness, and composite “goodness” ratings are also presented to guide researchers in their choice of specific stimuli for their studies. These data should give researchers confidence in the NIMH-ChEFS’s validity for use in affective and social neuroscience research.

The metric of disability-adjusted life years (DALYs) has become the global standard of measuring burden of disease. DALYs are comprised of years of life lost due to premature mortality and years of healthy life lost due to living with disability. In order to calculate the second part of the DALY equation, disease specific disability weights have to be established, i.e., measures for the decline of health associated with these disease states, which vary between 0 for perfect health and 1 for death. Although these disability weights are key for estimating DALYs, there have not been many comprehensive studies with empirical determinations of them. This article describes a systematic review on the state of the art with respect to empirically determining disability weights. Based on this review, a multi-method approach is outlined, which has also been implemented in a U.S. study to measure burden of disease. This approach involves the use of psychometric methodology as well as economic trade-off methods for determining the value of health states. It is conceptualized as a disaggregated approach, where the disability weight of any health state can be calculated if the attributes of this health state are known. The U.S. study received the collaboration of experts from more than 20 institutes of the National Institutes of Health and of the Centers for Disease Control and Prevention. First results will be available by the end of this year.

The performance of the short screening scale for DSM-IV posttraumatic stress disorder (PTSD), developed by Breslau et al. (1999), has not been assessed in an independent general population sample, although it has been used in epidemiological as well as clinical research. In this report we evaluate the short screening scale in the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a population-based survey of US household and group quarter residents. DSM-IV PTSD was assessed via symptom questions in the Alcohol Use Disorder and Associated Disabilities Interview Schedule–DSM-IV Version (AUDADIS-IV). Sensitivity, specificity, positive and negative predictive value, and percent correctly classified were calculated, using the interview-based diagnosis as the standard. Replicating findings from the initial report, a score of four or more on Breslau’s short screening scale identifies cases of PTSD with sensitivity of 78%, specificity of 97%, positive predictive value of 75%, and negative predictive value of 98%. The percentage of correctly classified respondents was 96%. The findings support the utility of the seven-item scale for screening PTSD in clinical and general population samples.

Attrition in longitudinal studies can lead to biased results. The study is motivated by the unexpected observation that alcohol consumption decreased despite of increased availability, which may be due to sample attrition of heavy drinkers. Several imputation methods have been proposed, but rarely compared in longitudinal studies of alcohol consumption. The imputation of consumption level measurements is computationally particularly challenging due to alcohol consumption being a semi-continuous variable (dichotomous drinking status and continuous volume among drinkers), and the non-normality of data in the continuous part. Data come from a longitudinal study in Denmark with four waves (2003–2006) and 1771 individuals at baseline. Five techniques for missing data are compared: Last value carried forward (LVCF) was used as a single, and Hotdeck, Heckman modelling, multivariate imputation by chained equations (MICE), and a Bayesian approach as multiple imputation methods. Predictive mean matching was used to account for non-normality, where instead of imputing regression estimates, “real” observed values from similar cases are imputed. Methods were also compared by means of a simulated dataset. The simulation showed that the Bayesian approach yielded the most unbiased estimates for imputation. The finding of no increase in consumption levels despite a higher availability remained unaltered.

Multivariate imputation by chained equations (MICE) has emerged as a principled method of dealing with missing data. Despite properties that make MICE particularly useful for large imputation procedures and advances in software development that now make it accessible to many researchers, many psychiatric researchers have not been trained in these methods and few practical resources exist to guide researchers in the implementation of this technique. This paper provides an introduction to the MICE method with a focus on practical aspects and challenges in using this method. A brief review of software programs available to implement MICE and then analyze multiply imputed data is also provided.

Objective

The clinician-rated (QIDS-C16) and self-report (QIDS-SR16) versions of the 16-item Quick Inventory of Depressive Symptomatology have been extensively examined in adult populations. This study evaluated both versions of the QIDS and the 17-item Children’s Depressive Rating Scale-Revised (CDRS-R) in an adolescent outpatient sample.

Method

Both the QIDS-C16 and QIDS-SR16 were completed for the adolescents. Three different methods were used to complete the QIDS-C16: (a) adolescents’ responses to clinician interviews; (b) parents’ responses to clinician interview; and (c) a composite score using the most pathological response from the two interviews. Both classical and item response theory methods were used. Factor analyses evaluated the dimensionality of each scale.

Results

The sample included 140 adolescent outpatients. All versions of the QIDS, save the parent interview, and the CDRS-R were very reliable (α ≥ 0.8). All four versions of the QIDS are reasonably effective and unidimensional. The CDRS-R was clearly at least two-dimensional. The CDRS-R was the most discriminating among low and extremely high levels of depression. The QIDS-SR16 was the most discriminating at moderate levels of depression. There was no relation between the QIDS scores and concurrent Axis III comorbidities.

Conclusion

The QIDS-C16 and the QIDS-SR16 are suitable for use in adolescents.

We present a case study using a multilevel modeling approach to determine whether depressive symptoms are affected by genetic factors. Existing studies examining this question have focused on twins. The present study built on the literature by conducting a preliminary study of the heritability of depressive symptoms within extended families. At the same time, this study assessed the need for adjustment of a heritability measure in a family study using a multigenerational sample. The sample consisted of 230 community-dwelling extended families that included 431 adult offspring, comprising full siblings, half siblings and cousins that participated in the University of Southern California Longitudinal Study of Generations. All participants filled out the Center for Epidemiologic Studies Depression (CES-D) scale. The multilevel analysis allowed us to model the natural hierarchy of the extended family. Results indicate that the proportion of the phenotypic variance for CES-D that occurs due to genetic differences is not significantly larger than zero among these participants [h2 = 8.6%, 95% confidence interval (CI) = 0–57%, p = 0.71]. Our findings suggest that future studies examining depressive symptoms in this sample can focus on non-genetic explanatory factors without the necessity to control for genetic variation. However, our study may be limited by measurement of prevalent depressive symptoms, which may not generalize to lifetime depressive symptoms.

Although needs assessment surveys are carried out after many large natural and man-made disasters, synthesis of findings across these surveys and disaster situations about patterns and correlates of need is hampered by inconsistencies in study designs and measures. Recognizing this problem, the US Substance Abuse and Mental Health Services Administration (SAMHSA) assembled a task force in 2004 to develop a model study design and interview schedule for use in post-disaster needs assessment surveys. The US National Institute of Mental Health subsequently approved a plan to establish a center to implement post-disaster mental health needs assessment surveys in the future using an integrated series of measures and designs of the sort proposed by the SAMHSA task force. A wide range of measurement, design, and analysis issues will arise in developing this center. Given that the least widely discussed of these issues concerns study design, the current report focuses on the most important sampling and design issues proposed for this center based on our experiences with the SAMHSA task force, subsequent Katrina surveys, and earlier work in other disaster situations.

This paper evaluates the internal consistency reliability and concurrent validity of the assessment of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) attention deficit hyperactivity disorder (ADHD) in the adolescent version of the World Health Organization (WHO) Composite International Diagnostic Interview Version 3.0 (CIDI). The CIDI is a lay-administered diagnostic interview that was carried out in conjunction with the US National Comorbidity Survey Adolescent Supplement, a US nationally representative survey of 10,148 adolescents and their parents. Internal consistency reliability was evaluated using factor and item response theory analyses. Concurrent validity was evaluated against diagnoses based on blinded clinician-administered interviews. Inattention and hyperactivity-impulsivity items loaded on separate but correlated factors, with hyperactivity and impulsivity items forming a single factor in parent reports but separate factors in youth reports. We were able to differentiate hyperactivity and impulsivity factors for parents as well by eliminating a subset who endorsed zero ADHD items from the factor analysis. Although concurrent validity was relatively weak, decomposition showed that this was due to low validity of adolescent reports. A modified CIDI diagnosis based exclusively on parent reports generated a diagnosis that had good concordance with clinical diagnoses [area under the curve (AUC) = 0.78]. Implications for assessing ADHD using the CIDI and the effect of different informants on measurement are discussed.

Introduction

A primary challenge in psychiatric genetics is the lack of a completely validated system of classification for mental disorders. Appropriate statistical methods are needed to empirically derive more homogenous disorder subtypes.

Methods

Using the framework of Robins & Guze’s (1970) five phases, latent variable models to derive and validate diagnostic groups are described. A process of iterative validation is proposed through which refined phenotypes would facilitate research on genetics, pathogenesis, and treatment, which would in turn aid further refinement of disorder definitions.

Conclusions

Latent variable methods are useful tools for defining and validating psychiatric phenotypes. Further methodological research should address sample size issues and application to iterative validation.

An overview is presented of the design and field procedures of the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A), a US face-to-face household survey of the prevalence and correlates of DSM-IV mental disorders. The survey was based on a dual-frame design that included 904 adolescent residents of the households that participated in the US National Comorbidity Survey Replication (85.9% response rate) and 9,244 adolescent students selected from a nationally representative sample of 320 schools (74.7% response rate). After expositing the logic of dual-frame designs, comparisons are presented of sample and population distributions on Census socio-demographic variables and, in the school sample, school characteristics. These document only minor differences between the samples and the population. The results of statistical analysis of the bias-efficiency trade-off in weight trimming are then presented. These show that modest trimming meaningfully reduces mean squared error. Analysis of comparative sample efficiency shows that the household sample is more efficient than the school sample, leading to the household sample getting a higher weight relative to its size in the consolidated sample relative to the school sample. Taken together, these results show that the NCS-A is an efficient sample of the target population with good representativeness on a range of socio-demographic and geographic variables.

Given recent adaptations of the World Health Organization Composite International Diagnostic Interview (WMH-CIDI), new methodological studies are needed to evaluate the concordance of CIDI diagnoses with clinical diagnostic interviews. This paper summarizes lessons learned from a clinical reappraisal study done with U. S. Latinos. We compare CIDI diagnoses with independent clinical diagnosis using the World Mental Health Structured Clinical Interview for DSM-IV (WMH SCID 2000). Three sub-samples stratified by diagnostic status (CIDI positive, CIDI negative, or CIDI subthreshold for a disorder) based on nine disorders were randomly selected for a telephone re-interview using the SCID. We calculated sensitivity, specificity, and weight-adjusted Cohen's kappa. Weighted 12 month prevalence estimates of the SCID are slightly higher than those of the CIDI for generalized anxiety disorder, alcohol abuse/dependence, and drug abuse/dependence. For Latinos, CIDI-SCID concordance at the aggregate disorder level is comparable, albeit lower, to other published reports. The CIDI does very well identifying negative cases and classifying disorders at the aggregate level. Good concordance was also found for major depressive episode and panic disorder. Yet, our data suggests that the CIDI presents problems for assessing PTSD and GAD. Recommendations on how to improve future versions of the CIDI for Latinos are offered.

This paper provides a rationale and overview of procedures used to develop the National Latino and Asian American Study (NLAAS). The NLAAS is nationally representative community household survey that estimates the prevalence of mental disorders and rates of mental health service utilization of Latinos and Asian Americans in the United States. The central aims of the NLAAS are to: 1) describe the lifetime and 12-month prevalence of psychiatric disorders and the rates of mental health services use for Latino and Asian American populations using nationwide representative samples of Latinos and Asian Americans, 2) assess the associations among social position, environmental context, and psychosocial factors with the prevalence of psychiatric disorders and utilization rates of mental health services, and 3) compare the lifetime and 12-month prevalence of psychiatric disorders, and utilization of mental health services of Latinos and Asian Americans with national representative samples of non-Latino whites (from the National Comorbidity Study-Replication; NCS-R) and African Americans (from the National Survey of American Life; NSAL). This paper presents new concepts and methods utilized in the development of the NLAAS to capture and investigate ethnic, cultural and environmental considerations that are often ignored in mental health research.

This paper describes the development, translation and adaptation of measures in the National Latino and Asian American Study (NLAAS). We summarize the techniques used to attain cultural relevance; semantic, content and technical equivalency; and internal consistency of the measures across languages and Latino sub-ethnic groups. We also discuss some of the difficulties and challenges encountered in doing this work. The following three main goals are addressed in this paper: (1) Attaining cultural relevance by formulating the research problem with attention to the fundamental cultural and contextual differences of Latinos and Asians as compared to the mainstream population; (2) Developing cultural equivalence in the standardized instruments to be used with these populations; and (3) Assessing the generalizability of the measures –i.e., that the measures do not fluctuate according to culture or translation. We present details of the processes and steps used to achieve these three goals in developing measures for the Latino population. Additionally, the integration of both the etic and emic perspectives in the instrument adaptation model is presented.

Although early use of alcohol during adolescence has been consistently associated with increased risk of alcoholism in adulthood, the specific mechanisms that underlie this association remain unclear. We describe a program of epidemiological twin-family research that shows that early use of alcohol is best conceptualized as an indicator of a more general propensity to engage in adolescent problem behavior. Adolescent problem behavior, in turn, is a risk factor for a broad range of adult externalizing disorders, of which alcoholism is but one manifestation. These findings are shown to be consistent with a dual-process model whereby early adolescent problem behavior is associated with increased risk of adult psychopathology because both are indicators of a common inherited liability and because early adolescent problem behavior increases the likelihood an adolescent is exposed to high-risk environments. We conclude with a discussion of the importance of cross-cultural research, which may be especially informative for identifying the consequences of early adolescent drinking.

Prevalence of extramedical opioid analgesic use in the United States is rising, yet little is known about the nature and extent of problems of dependence related to the use of these drugs. This study uses latent class analysis to empirically define classes of past-year extramedical opioid analgesic users based on observed clustering of DSM-IV defined clinical dependence features; multinomial logistic regression is used to describe differences across these groups. The 2002–2003 public data-files of the National Survey on Drug Use and Health were used to identify 7,810 extramedical opioid analgesic users in the past-year. The best-fitting four-class model identified classes that differed quantitatively and qualitatively, with 2% of the users in Class 4 (most severe) and 84% in Class 1 (least severe). Classes 2 and 3 had parallel symptom profiles, but those in Class 3 reported additional problems. Adolescents (12–17 year olds) were at higher odds of being in Class 3 vs. older age groups; Females were two times as likely to be in Classes 2 and 4, and those with mental health problems were at higher odds of belonging in the more severe classes. Differences by type of past year opioid users were also detected. This study sheds light on the classification and distribution of extramedical opioid analgesic dependence symptoms in the US general population, identifying subgroups that warrant immediate attention.

The validity of the 6-question World Health Organization Adult ADHD Self-Report Scale (ASRS) Screener was assessed in a sample of subscribers to a large health plan in the US. A convenience sub-sample of 668 subscribers was administered the ASRS Screener twice to assess test-retest reliability and then a third time in conjunction with a clinical interviewer for DSM-IV adult ADHD. The data were weighted to adjust for discrepancies between the sample and the population on socio-demographics and past medical claims. Internal consistency reliability of the continuous ASRS Screener was in the range .63–.72 and test-retest reliability (Pearson correlations) in the range .58–.77. A four-category version The ASRS Screener had strong concordance with clinician diagnoses, with an area under the receiver operating characteristic curve (AUC) of .90. The brevity and ability to discriminate DSM-IV cases from non-cases make the 6-question ASRS Screener attractive for use both in community epidemiological surveys and in clinical outreach and case-finding initiatives.

We evaluated the psychometric properties of the 12-item interviewer-administered screener version of the World Health Organization Disability Assessment Schedule – version II (WHODAS II) among older people living in seven low- and middle-income countries. Principal component analysis (PCA), confirmatory factor analysis (CFA) and Mokken analyses were carried out to test for unidimensionality, hierarchical structure, and measurement invariance across 10/66 Dementia Research Group sites.

PCA generated a one-factor solution in most sites. In CFA, the two-factor solution generated in Dominican Republic fitted better for all sites other than rural China. The two factors were not easily interpretable, and may have been an artefact of differing item difficulties. Strong internal consistency and high factor loadings for the one-factor solution supported unidimensionality. Furthermore, the WHODAS II was found to be a ‘strong’ Mokken scale. Measurement invariance was supported by the similarity of factor loadings across sites, and by the high between-site correlations in item difficulties.

The Mokken results strongly support that the WHODAS II 12-item screener is a unidimensional and hierarchical scale confirming to item response theory (IRT) principles, at least at the monotone homogeneity model level. More work is needed to assess the generalizability of our findings to different populations. Copyright © 2010 John Wiley & Sons, Ltd.