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Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

ObjectiveDiagnosis is a cornerstone of clinical practice for mental health care providers, yet traditional diagnostic systems have well-known shortcomings, including inadequate reliability, high comorbidity, and marked within-diagnosis heterogeneity. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a data-driven, hierarchically based alternative to traditional classifications that conceptualizes psychopathology as a set of dimensions organized into increasingly broad, transdiagnostic spectra. Prior work has shown that using a dimensional approach improves reliability and validity, but translating a model like HiTOP into a workable system that is useful for health care providers remains a major challenge.MethodThe present work outlines the HiTOP model and describes the core principles to guide its integration into clinical practice.ResultsPotential advantages and limitations of the HiTOP model for clinical utility are reviewed, including with respect to case conceptualization and treatment planning. A HiTOP approach to practice is illustrated and contrasted with an approach based on traditional nosology. Common barriers to using HiTOP in real-world health care settings and solutions to these barriers are discussed.ConclusionsHiTOP represents a viable alternative to classifying mental illness that can be integrated into practice today, although research is needed to further establish its utility. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.

Social anxiety is a common mental disorder with an average age of onset in early adolescence. Current theories focus largely on risk factors that are present from early in life, but reasons for onset of the disorder as youth move into adolescence are rarely discussed. We recently proposed a model of the onset of certain mental disorders during the adolescent years based on characteristics of adolescent development. While this model will require longitudinal testing, the current article establishes concurrent associations between relevant variables in a cohort of 528 preadolescents (M[subscript age] = 11.2 years) at baseline. Youth with social anxiety disorder differed significantly from other youth on measures of social comparison (including physical appearance comparisons, self-rated attractiveness, and negative peer comparisons on social media) as well as positive peer connections (including self-reported school belonging, number of friends, victimization, and peer affiliation). A structural equation model showed that symptom levels of social anxiety were directly related to social comparisons and peer connections, as well as indirectly associated with pubertal development and social comparisons. This pattern was not moderated by sex of youth.

Background: The DSM-5 features hundreds of diagnoses comprising a multitude of symptoms, and there is considerable repetition in the symptoms among diagnoses. This repetition undermines what we can learn from studying individual diagnostic constructs because it can obscure both disorder- and symptom-specific signals. However, these lost opportunities are currently veiled because symptom repetition in the DSM-5 has not been quantified. Method: This descriptive study mapped the repetition among the 1419 symptoms described in 202 diagnoses of adult psychopathology in section II of the DSM-5. Over a million possible symptom comparisons needed to be conducted, for which we used both qualitative content coding and natural language processing. Results: In total, we identified 628 distinct symptoms: 397 symptoms (63.2%) were unique to a single diagnosis, whereas 231 symptoms (36.8%) repeated across multiple diagnoses a total of 1022 times (median 3 times per symptom; range 2–22). Some chapters had more repetition than others: For example, every symptom of every diagnosis in the bipolar and related disorders chapter was repeated in other chapters, but there was no repetition for any symptoms of any diagnoses in the elimination disorders , gender dysphoria or paraphilic disorders. The most frequently repeated symptoms included insomnia, difficulty concentrating, and irritability – listed in 22, 17 and 16 diagnoses, respectively. Notably, the top 15 most frequently repeating diagnostic criteria were dominated by symptoms of major depressive disorder. Conclusion: Overall, our findings lay the foundation for a better understanding of the extent and potential consequences of symptom overlap. [ABSTRACT FROM AUTHOR]

Our consumer-driven culture has negative impacts for individuals who are vulnerable to clinical hoarding and compulsive shopping. Because of this, there is an ever-present need to have standardized tools to assess why we acquire and save things we might not need. In this article, we present the development of the Acquiring Motives Questionnaire (AMQ) and Saving Motives Questionnaire (SMQ), which were written based on a thorough literature review and consultation with 22 experts in the field. After piloting with two large nonclinical samples, we administered the measures to another large nonclinical sample (N = 535; Mage = 24.4, 74.2% female, 54.6% White) and then a community sample of individuals with hoarding disorder and/or compulsive buying–shopping disorder and controls without any mental health diagnoses (N = 159; Mage = 42.54, 85.5% female, 59.7% White). Confirmatory factor analyses supported a 14-factor model for the AMQ and a 14-factor model for the SMQ. All subscales demonstrated good internal consistency (ω = 0.81–0.96), 2-week test–retest reliability (intraclass correlation coefficient = 0.67–0.83), and convergent, divergent, and criterion validity. The measures also distinguished between controls and individuals with hoarding and/or compulsive buying diagnoses. Findings highlight that acquiring and saving behaviors are both motivated by the pursuit of positive emotions and the avoidance of negative emotions, which is consistent with our theoretical understanding of these clinical issues. Based on our findings, we make suggestions for psychological interventions. Public Significance Statement: Current levels of overconsumption, particularly in capitalist societies, are environmentally unsustainable and have negative consequences for individuals vulnerable to compulsive shopping and hoarding. This is because many consumers buy too many nonessential products, often due to psychological reasons rather than actual needs. This article developed a new measure for the psychological motivations that drive the excessive acquisition and saving of possessions. [ABSTRACT FROM AUTHOR]

The present study examined high-risk personality traits and associations with psychopathology across multiple levels of a hierarchical-dimensional model of psychopathology in a large adolescent, general population sample. Confirmatory factor analyses were run using data from two randomized controlled trials of Australian adolescents (N = 8,654, mean age = 13.01 years, 52% female). A higher-order model – comprised of general psychopathology, fear, distress, alcohol use/harms, and conduct/inattention dimensions – was selected based on model fit, reliability, and replicability. Indirect-effects models were estimated to examine the unique associations between high-risk personality traits (anxiety sensitivity, negative thinking, impulsivity, and sensation seeking) and general and specific dimensions and symptoms of psychopathology. All personality traits were positively associated with general psychopathology. After accounting for general psychopathology, anxiety sensitivity was positively associated with fear; negative thinking was positively associated with distress; impulsivity was positively associated with conduct/inattention; and sensation seeking was positively associated with alcohol use/harms and conduct/inattention, and negatively associated with fear. Several significant associations between personality traits and individual symptoms remained after accounting for general and specific psychopathology. These findings contribute to our understanding of the underlying structure of psychopathology among adolescents and have implications for the development of personality-based prevention and early intervention programs. [ABSTRACT FROM AUTHOR]

Confirmatory factor analysis (CFA) and its bifactor models are popular in empirical investigations of the factor structure of psychological constructs. CFA offers straightforward hypothesis testing but has notable pitfalls, such as the imposition of strict assumptions (i.e., simple structure) that obscure unmodeled complexity. Due to the limitations of bifactor CFAs, they have yielded anomalous results across samples and studies that suggest model misspecification (e.g., evaporating specific factors and unexpected loadings). We propose the use of exploratory factor analysis (EFA) to evaluate the structural validity of CFA solutions--either before or after the estimation of more restrictive CFA models--to (a) identify model misspecifications that may drive anomalous estimates and (b) confirm CFA models by examining whether hypothesized structures emerge with limited researcher input. We evaluated the degree to which predominant factor structures were invariant across contexts along the exploratory-confirmatory continuum and demonstrate how poor methodological choices can distort results and impede theory development. All CFA models fit well, but there were numerous differences in replicability and substantive interpretability. Several similarities emerged between bifactor CFA and EFA models, including evidence of overextraction, the collapse of specific factors onto the general factor, and subsequent shifts in how the general factor was defined. We situate these methodological shortcomings within the broader literature on structural models of psychopathology, articulate implications for theories (such as the p-factor) that are borne out of factor analysis, outline several remedies for problems encountered when performing exploratory bifactor analysis, and propose alternative specifications for confirmatory bifactor models. Confirmatory factor analysis (CFA) is the most popular method in model comparison studies involving bifactor structures of psychological constructs. However, notable pitfalls are associated with myopic approaches to building and testing bifactor CFA models, which can distort results, limit generalizability, and impede theory development. The overarching aims of this study are to provide applied researchers with a conceptually clear roadmap for evaluating latent factor structures, present a comprehensive accounting of theoretical and methodological challenges that arise in both confirmatory and exploratory factor analytic scenarios, and highlight the benefits of their combined use. These general issues are illustrated in an applied example featuring a frequently used dataset in the field of quantitative psychopathology. Several statistical and conceptual similarities emerged across bifactor CFA and EFA models. Results are situated within the broader literature on structural models of psychopathology, and implications for p-factor theories are discussed. The historical narrative that is woven into this study traces recurring themes of the century-old general factor debate to caution readers against the development of theories on the basis of a single factor analytic solution. [ABSTRACT FROM AUTHOR]

Given the now well-recognized limitations of traditional classification systems for research, this editorial proposes to advance mental health science by focusing research efforts on studying fine-grained elements of mental health and illness such as symptoms, mechanisms, and processes. Our own perspectives are informed by three approaches in particular that have gained traction over the last decade: the Hierarchical Taxonomy of Psychopathology, the network or systems approach, and the National Institute of Mental Health Research Domain Criteria. Drawing on these and other perspectives as well as the diverse views of the author teams that contributed to this Special Section, we summarize the state of the field and propose an ambitious plan for the way ahead. Specifically, we propose that embracing pluralistic, multimethod, and multisystem approaches offers a way forward. This will require strategies to reduce research waste and much stronger channels for communication to identify confluence, discoveries, and dead ends within and between disciplines. We are optimistic this will lead to a better understanding of the mechanisms underpinning psychopathology and ultimately to more effective interventions. General Scientific Summary: In this editorial, we introduce a Special Section focused on investigating fine-grained elements of mental health and illness such as individual symptoms, symptom clusters, or detailed mechanisms and processes. We summarize a variety of viewpoints reflected in the Special Section and propose paths forward. [ABSTRACT FROM AUTHOR]