Structure as cause and representation: Implications of descriptivist inference for structural modeling across multiple levels of analysis

What is a psychopathology dimension?

Coherence in the science and practice of mental health assessment depends upon a tight connection between psychopathology concepts that are used and the way those concepts are operationalized and defined. In contrast, the use of the same word to mean more than one thing contributes to incoherence, inefficiency, and confusion. In this paper, we review three possible meanings of the word "dimension" as it relates to the assessment of psychopathology and describe how the indiscriminate use of this word has caused confusion in the general context of the transition to a more evidence-based approach to mental health diagnosis. We attempt to disambiguate the term "dimension" by demarcating three concepts that can be distinguished based on different empirical standards: continuous variables, unidimensional dimensions, and distinct dimensions.

Empirically based assessment and taxonomy of psychopathology for ages 1½-90+ years: Developmental, multi-informant, and multicultural findings

BACKGROUND

Originating in the 1960s, the Achenbach System of Empirically Based Assessment (ASEBA) comprises a family of instruments for assessing problems and strengths for ages 1½-90+ years.

PURPOSE

To provide an overview of the ASEBA, related research, and future directions for empirically based assessment and taxonomy.

CONTENT

Standardized, multi-informant ratings of transdiagnostic dimensions of behavioral, emotional, social, and thought problems are hierarchically scored on narrow-spectrum syndrome scales, broad-spectrum internalizing and externalizing scales, and a total problems (general psychopathology) scale. DSM-oriented and strengths scales are also scored. The instruments and scales have been iteratively developed from assessments of clinical and population samples of hundreds of thousands of individuals. Items, instruments, scales, and norms are tailored to different kinds of informants for ages 1½-5, 6-18, 18-59, and 60-90+ years. To take account of differences between informants' ratings, parallel instruments are completed by parents, teachers, youths, adult probands, and adult collaterals. Syndromes and Internalizing/Externalizing scales derived from factor analyses of each instrument capture variations in patterns of problems that reflect different informants' perspectives. Confirmatory factor analyses have supported the syndrome structures in dozens of societies. Software displays scale scores in relation to user-selected multicultural norms for the age and gender of the person being assessed, according to ratings by each type of informant. Multicultural norms are derived from population samples in 57 societies on every inhabited continent. Ongoing and future research includes multicultural assessment of elders; advancing transdiagnostic progress and outcomes assessment; and testing higher order structures of psychopathology.

Evidence that psychopathology symptom networks have limited replicability

Network analysis is quickly gaining popularity in psychopathology research as a method that aims to reveal causal relationships among individual symptoms. To date, 4 main types of psychopathology networks have been proposed: (a) association networks, (b) regularized concentration networks, (c) relative importance networks, and (d) directed acyclic graphs. The authors examined the replicability of these analyses based on symptoms of major depression and generalized anxiety between and within 2 highly similar epidemiological samples (i.e., the National Comorbidity Survey-Replication [n = 9282] and the National Survey of Mental Health and Wellbeing [n = 8841]). Although association networks were stable, the 3 other types of network analysis (i.e., the conditional independence networks) had poor replicability between and within methods and samples. The detailed aspects of the models-such as the estimation of specific edges and the centrality of individual nodes-were particularly unstable. For example, 44% of the symptoms were estimated as the "most influential" on at least 1 centrality index across the 6 conditional independence networks in the full samples, and only 13-21% of the edges were consistently estimated across these networks. One of the likely reasons for the instability of the networks is the predominance of measurement error in the assessment of individual symptoms. The authors discuss the implications of these findings for the growing field of psychopathology network research, and conclude that novel results originating from psychopathology networks should be held to higher standards of evidence before they are ready for dissemination or implementation in the field. (PsycINFO Database Record