Where does attention-deficit/hyperactivity disorder fit in the psychopathology hierarchy? A symptom-focused analysis.

Modern psychopathology classification systems position attention-deficit/hyperactivity disorder (ADHD) with different groups of conditions, either with externalizing or neurodevelopmental. As such, the optimal placement of ADHD in modern classification systems remains unclear. We advanced the literature by mapping ADHD symptoms onto three transdiagnostic psychopathology spectra-externalizing, neurodevelopmental, and internalizing-and their symptoms.

Haves and have-nots: socioeconomic position improves accuracy of machine learning algorithms for predicting high-impact chronic pain.

Lower socioeconomic position (SEP) is associated with increased risk of developing chronic pain, experiencing more severe pain, and suffering greater pain-related disability. However, SEP is a multidimensional construct; there is a dearth of research on which SEP features are most strongly associated with high-impact chronic pain, the relative importance of SEP predictive features compared to established chronic pain correlates, and whether the relative importance of SEP predictive features differs by race and sex. This study used 3 machine learning algorithms to address these questions among adults in the 2019 National Health Interview Survey.

Clustering methods: To optimize or to not optimize?

Many clustering problems are associated with a particular objective criterion that is sought to be optimized. There are often several methods that can be used to tackle the optimization problem, and one or more of them might guarantee a globally optimal solution. However, it is quite possible that, relative to one or more suboptimal solutions, a globally optimal solution might be less interpretable from the standpoint of psychological theory or be less in accordance with some known (i.

Locating triarchic model constructs in the hierarchical structure of a comprehensive trait-based psychopathy measure: Implications for research and clinical assessment.

The triarchic model posits that distinct trait constructs of boldness, meanness, and disinhibition underlie psychopathy. The triarchic model traits are conceptualized as biobehavioral dimensions that can be assessed using different sets of indicators from alternative measurement modalities; as such, the triarchic model would hypothesize that these traits are not confined to any one item set. The present study tested whether the triarchic model dimensions would emerge from a hierarchical-structural analysis of the facet scales of the Elemental Psychopathy Assessment (EPA), an inventory designed to comprehensively index psychopathy according to the five-factor personality model.

Good Fit Is Weak Evidence of Replication: Increasing Rigor Through Prior Predictive Similarity Checking.

Replication provides a confrontation of psychological theory, not only in experimental research, but also in model-based research. Goodness of fit (GOF) of the original model to the replication data is routinely provided as meaningful evidence of replication. We demonstrate, however, that GOF obscures important differences between the original and replication studies.

"Emotional stress is more detrimental than the virus itself": A qualitative study to understand HIV testing and pre-exposure prophylaxis (PrEP) use among internal migrant men in South Africa.

Introduction: South Africa has one of the highest rates of internal migration on the continent, largely comprised of men seeking labour in urban centres. South African men who move within the country (internal migrants) are at higher risk than non-migrant men of acquiring HIV yet are less likely to test or use pre-exposure prophylaxis (PrEP). However, little is known about the mechanisms that link internal migration and challenges engaging in HIV services.

Improving the Walktrap Algorithm Using -Means Clustering.

The walktrap algorithm is one of the most popular community-detection methods in psychological research. Several simulation studies have shown that it is often effective at determining the correct number of communities and assigning items to their proper community. Nevertheless, it is important to recognize that the walktrap algorithm relies on hierarchical clustering because it was originally developed for networks much larger than those encountered in psychological research.

Methods for quantifying the heterogeneity of psychopathology.

Objectives: Specifiers for a major depressive disorder (MDE) are supposed to reduce diagnostic heterogeneity. However, recent literature challenges the idea that the atypical and melancholic specifiers identify more homogenous or coherent subgroups. We introduce the usage of distance metrics to characterize symptom heterogeneity.

Alcohol use disorder conceptualizations and diagnoses reflect their sociopolitical context.

The present paper highlights how alcohol use disorder (AUD) conceptualizations and resulting diagnostic criteria have evolved over time in correspondence with interconnected sociopolitical influences in the United States. We highlight four illustrative examples of how DSM-defined alcoholism, abuse/dependence, and AUD have been influenced by sociopolitical factors. In doing so, we emphasize the importance of recognizing and understanding such sociopolitical factors in the application of AUD diagnoses.

Psychopathology as dynamic markers of alcohol initiation across development: A three-year longitudinal examination.

Sipping, an early form of alcohol initiation, is associated with aspects of psychopathology and personality that reflect long-term risk for harmful alcohol use. In the Adolescent Brain and Cognitive Development cohort ( = 11,872), sipping by age 9-10 was concurrently associated with impulsivity, other aspects of externalizing, and prodromal schizophrenia symptoms. Still, these associations were cross-sectional in nature, leaving open the possibility that these features of psychopathology and personality might not reflect long-term risk for alcohol consumption and related harm across development.

Factor analysis in personality disorders research: Modern issues and illustrations of practical recommendations.

The development of factor analysis is uniquely situated within psychology, and the development of many psychological theories and measures are likewise tethered to the common use of factor analysis. In this article, we review modern methodological controversies and developments of factor analytic techniques through concrete demonstrations that span the exploratory-confirmatory continuum. Also, we provide recommendations for working through common challenges in personality disorders research.

Alcohol use disorder criteria exhibit different comorbidity patterns.

Background And Aims: Alcohol use disorder is comorbid with numerous other forms of psychopathology, including externalizing disorders (e.g. conduct disorder) and, to a lesser extent, internalizing conditions (e.

The Basic Psychological Need Satisfaction and Frustration Scales probably do not validly measure need frustration.

In basic psychological needs theory (BPNT), the separable constructs of need satisfaction and need frustration are theorized as pivotally related to psychopathology and broader aspects of well-being. The Basic Psychological Need Satisfaction and Frustration Scales (BPNSFS; Chen et al., 2015) have rapidly emerged as the dominant self-report measure in the BPNT domain, with translated versions available in a wide range of languages and a plethora of versions adapted for specific populations and life contexts.

A broad internalizing dimension accounts for the genetic associations between personality and individual internalizing disorders.

Much research has demonstrated that psychopathology can be described in terms of broad dimensions, representing liability for multiple psychiatric disorders. Broad spectra of psychopathology (e.g.

A comparison of logistic regression methods for Ising model estimation.

The Ising model has received significant attention in network psychometrics during the past decade. A popular estimation procedure is IsingFit, which uses nodewise l-regularized logistic regression along with the extended Bayesian information criterion to establish the edge weights for the network. In this paper, we report the results of a simulation study comparing IsingFit to two alternative approaches: (1) a nonregularized nodewise stepwise logistic regression method, and (2) a recently proposed global l-regularized logistic regression method that estimates all edge weights in a single stage, thus circumventing the need for nodewise estimation.

On maximization of the modularity index in network psychometrics.

The modularity index (Q) is an important criterion for many community detection heuristics used in network psychometrics and its subareas (e.g., exploratory graph analysis).

New approaches to deep phenotyping in addictions.

Objective: The causes of substance use disorders (SUDs) are largely unknown and the effectiveness of their treatments is limited. One crucial impediment to research and treatment progress surrounds how SUDs are classified and diagnosed. Given the substantial heterogeneity among individuals diagnosed with a given SUD (e.

How Robust Is the p Factor? Using Multitrait-Multimethod Modeling to Inform the Meaning of General Factors of Youth Psychopathology.

We used multitrait-multimethod (MTMM) modeling to examine general factors of psychopathology in three samples of youth (s = 2119, 303, 592) for whom three informants reported on the youth's psychopathology (e.g., child, parent, teacher).

Model fit is a fallible indicator of model quality in quantitative psychopathology research: A reply to Bader and Moshagen.

As evidenced by our exchange with Bader and Moshagen (2022), the degree to which model fit indices can and should be used for the purpose of model selection remains a contentious topic. Here, we make three core points. First, we discuss the common misconception about fit statistics' abilities to identify the "best model," arguing that mechanical application of model fit indices contributes to faulty inferences in the field of quantitative psychopathology.

A comparison of spectral clustering and the walktrap algorithm for community detection in network psychometrics.

Spectral clustering is a well-known method for clustering the vertices of an undirected network. Although its use in network psychometrics has been limited, spectral clustering has a close relationship to the commonly used walktrap algorithm. In this article, we report results from simulation experiments designed to evaluate the ability of spectral clustering and the walktrap algorithm to recover underlying cluster (or community) structure in networks.

A modified approach to fitting relative importance networks.

Most researchers have estimated the edge weights for relative importance networks using a well-established measure of general dominance for multiple regression. This approach has several desirable properties including edge weights that represent ² contributions, in-degree centralities that correspond to ² for each item when using other items as predictors, and strong replicability. We endorse the continued use of relative importance networks and believe they have a valuable role in network psychometrics.