Dimensional Taxonomy Research Articles

Integrating "Lumpers" versus "Splitters" Perspectives: Toward a Hierarchical Dimensional Taxonomy of Eating Disorders from Clinician Ratings.

This study describes a hierarchical dimensional model of eating-disorder (ED) classification based on the Hierarchical Taxonomy of Psychopathology (HiTOP). Participants were community-recruited adults with an ED (N=252; 81.9% female). We used a modified version of Goldberg's (2006) method, which involved sequentially extracting latent factors using exploratory structural equation modeling, resulting in a 10-factor hierarchical-dimensional model. Dimensions predicted 92.4% and 58.7% of the variance in recovery outcomes at six-month and one-year, respectively. Compared to other illness indicators (e.g., DSM diagnoses, dimensional ED impairment scores, weight/shape overvaluation, and DSM ED severity specifiers), hierarchical dimensions predicted .88 to 334 times more variance in ED behaviors at baseline and 1.95 to 80.8 times more variance in psychiatric impairment at one-year follow-up. Results suggest that reducing within-disorder heterogeneity for EDs within the broader context of internalizing symptoms provides a powerful framework from which to predict outcomes and understand symptoms experienced by those with EDs.

Differentiating Abnormal, Normal, and Ideal Personality Profiles in Multidimensional Spaces

Abstract: Current dimensional taxonomies of personality disorder (PD) establish that intense traits do not suffice to diagnose a disorder, and additional constructs reflecting dysfunction are required. However, traits appear able to predict maladaptation by themselves, which might avoid duplications and simplify diagnosis. On the other hand, if trait-based diagnoses are feasible, it is the whole personality profile that should be considered, rather than individual traits. This takes us into multidimensional spaces, which have their own particular – but poorly understood – logic. The present study examines how profile-level differences between normal and disordered subjects can be used for diagnosis. The Dimensional Assessment of Personality Pathology – Basic Questionnaire (DAPP-BQ) and the Personality Inventory for DSM-5 (PID-5) were administered to a community and a clinical sample each (total n = 1,925 and 3,543 respectively). Intense traits proved to be common in the general population, so empirically-based thresholds are indispensable not to take as abnormal what is at most unideal. Profile-level parameters such as Euclidean and Mahalanobis distances outperformed individual traits in predicting mental problems and equaled the performance of published measures of dysfunction or severity. Personality profiles can play a more central role in identifying disorders than is currently acknowledged, provided that adequate metrics are used.

An Exploratory Study of MMPI-2-RF Personality and Psychopathology Profiles of Adults with Autism Spectrum Disorder without Intellectual Disability.

More empirical research is needed to disentangle the phenotypes of autism spectrum disorder (ASD) and cluster C personality symptomatology (CCPD), as both show similarities in their clinical presentation. We explored personality and psychopathology dimensions as conceptualized in contemporary dimensional taxonomies (i.e., hierarchical taxonomy of psychopathology; HiTOP) in adults with ASD without intellectual disability operationalized by the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF). Applying secondary analytic processes using clinical data, we cross-examined the MMPI-2-RF profiles of adults with ASD (n = 28) compared to adults with Cluster C personality disorders (CCPD; n = 28) and a control group (n = 28) by conducting nonparametric tests and assessing effect sizes. The profiles of the ASD and CCPD groups evidenced to be similar, and both average clinical profiles diverged from the average control group profiles by elevated levels of demoralization, internalizing, and somatization symptomatology. There were small differences between the average profiles of adults with ASD and adults with CCPD. Additional research using dimensional measures of psychopathology could elucidate the dimensional phenotypes of ASD and CCPD. Based on the results in this study, the MMPI-2-RF may not meaningfully discriminate between the two clinical presentations, with the exception of various externalizing scales.

Computational Predictions for OCD Pathophysiology and Treatment: A Review.

Obsessive compulsive disorder (OCD) can manifest as a debilitating disease with high degrees of co-morbidity as well as clinical and etiological heterogenity. However, the underlying pathophysiology is not clearly understood. Computational psychiatry is an emerging field in which behavior and its neural correlates are quantitatively analyzed and computational models are developed to improve understanding of disorders by comparing model predictions to observations. The aim is to more precisely understand psychiatric illnesses. Such computational and theoretical approaches may also enable more personalized treatments. Yet, these methodological approaches are not self-evident for clinicians with a traditional medical background. In this mini-review, we summarize a selection of computational OCD models and computational analysis frameworks, while also considering the model predictions from a perspective of possible personalized treatment. The reviewed computational approaches used dynamical systems frameworks or machine learning methods for modeling, analyzing and classifying patient data. Bayesian interpretations of probability for model selection were also included. The computational dissection of the underlying pathology is expected to narrow the explanatory gap between the phenomenological nosology and the neuropathophysiological background of this heterogeneous disorder. It may also contribute to develop biologically grounded and more informed dimensional taxonomies of psychopathology.

Investigating the Transdiagnostic Value of Subjective Emptiness

It is common for people with mental health problems to report feelings of emptiness. However, the association of subjective emptiness with specific disorders and its unique role within dimensional taxonomies of personality pathology is not well understood. The present study assesses the transdiagnostic value of subjective emptiness using a recently developed self-report measure in a mixed sample of 157 participants. The authors investigated the associations of emptiness with clinically relevant variables, including borderline personality disorder symptoms, depression, anxiety, suicidal ideation, and suicide attempts. Subjective emptiness showed strong positive relationships with all criteria. Regression models controlling for impairments of personality functioning, maladaptive personality traits, and current symptom distress supported the incremental validity of emptiness for specific disorder constructs and suicidality. These findings indicate that emptiness represents a facet of psychopathology that can be particularly useful for the classification of mental disorders, and in particular internalizing disorders involving self-dysfunction and detachment.

Assessment of HiTOP Constructs Across the Population: A Commentary on the HiTOP Measure Development Project.

The set of articles in this issue demonstrates the promise of the HiTOP collaborative effort in advancing a viable alternative dimensional taxonomy of psychopathology. Besides transcending the limitations of our current taxonomic system and categorical diagnoses, the potential contributions of HiTOP should extend to also critically examining long-standing notions of psychopathology and mental wellness, evaluating the ability of symptom measures to capture the various manifestations of disorder in the population, and questioning the emphasis on predominant Western cultural norms as a basis for our definitions of psychopathology and their measurement. This commentary addresses the extent to which the implementation of the measurement studies featured in the special issue centered these goals, drawing on the work of scholars from within and outside the fields of psychiatry and clinical psychology, some who have taken a critical view of these fields. The hope is that we work to challenge some basic assumptions and increase self-reflection, with an eye toward reducing bias and mental health disparities.

Focusing the Lens to See More Clearly: Overcoming Definitional Challenges and Identifying New Directions in Racial Microaggressions Research

Despite significant advances in research on racial microaggressions, key challenges remain regarding how to define and classify them. Resolving these challenges is necessary to reduce misunderstanding and the subsequent minimization of racial microaggression research. Our goals in this article are to discuss the definitional challenges, to discuss implications for the creation of taxonomies, and to offer directions for how a revised definition and corresponding taxonomies can be used to further racial microaggression research. Regarding our first aim, we assert that racial microaggressions are observable events that occur independently of intention (i.e., regardless of whether they are intentional or unintentional) or impact (i.e., regardless of how they are perceived by recipients). Moreover, we assert that racial microaggressions are most validly defined by people of color and can have different meanings on the basis of situational context. The second aim is to propose a refinement and expansion of racial microaggression taxonomies. Sue and colleagues’ taxonomy has been invaluable, yet other ways of classifying microaggressions and moving toward dimensional taxonomies are needed to advance scholarship. We highlight key dimensions related to the experience, perpetration, characteristics, and sociopolitical function of racial microaggressions that may be useful for future taxonomies. Overall, overcoming definitional challenges and expanding taxonomies holds potential to advance the literature on racial microaggression.

A dimensional taxonomy of perceived characteristics of major life events.

Major life events (MLEs) are studied in many different areas in psychology such as personality development, clinical psychology, or posttraumatic growth. In all of these areas, a common finding is that MLEs differ in their effects on psychological outcomes. However, a framework that allows a systematic examination of these differences is still absent. This article presents a systematic literature review and 4 empirical studies (Ns between 226 and 449, total N = 1,477) in which we developed and evaluated a dimensional taxonomy of 9 perceived characteristics of MLEs: valence, impact, predictability, challenge, emotional significance, change in worldviews, social status changes, external control, and extraordinariness. These event characteristics can be measured reliably with the Event Characteristics Questionnaire (ECQ). Perceived event characteristics predicted individual differences in changes in subjective well-being in both retrospective and longitudinal data after MLEs over and above established predictors of subjective well-being such as personality and demographic characteristics. A comparison between the ECQ and established taxonomies of situation characteristics such as the DIAMONDS (Rauthmann et al., 2014) showed high conceptual and empirical convergence between some ECQ subscales (e.g., valence, challenge) with characteristics of situations, whereas other ECQ subscales (e.g., social status changes, external control) were conceptually and empirically distinct from situation characteristics. In sum, including measures of perceived event characteristics in studies on MLEs may enhance our understanding of why MLEs differ in the direction, strength, and duration of their effects on psychological outcomes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Dimensional Taxonomy of Data Visualization: A Proposal From Communication Sciences Tackling Complexity.

This article consists of a conceptual analysis—from the perspective of communication sciences—of the relevant aspects that should be considered during operational steps in data visualization. The analysis is performed taking as a reference the components that integrate the communication framework theory—the message, the form, the encoder, the context, the channel, and the decoder—which correspond to six elements in the context of data visualization: content, graphic representation, encoding setup, graphic design and approach, media, and user. The study is focused accordingly on the dimensions that these elements describe: the degrees of abstraction of the information, the functionalities of the tool for the graphical representation, the specifications for the setup of the visualization, the approach modes to the context by the graphic design, the levels of communication efficiency in the media, and the requirements of the visualization perceived as values from the user experience side. The unfolding of these dimensions is undertaken following a common pattern of six organizational layers of complexity—basic, extended, synthetic, dynamic, interactive, and integrative—according to the analytical criteria. The results of the detailed study, based on an extensive scientific literature review, allow the design of a dimensional taxonomy of data visualization built on a matrix structure where these elements act as factors of completeness and the layers act as factors of complexity. As a conclusion, an object-centered model constituted by an ordered series of phases and achievements is proposed as a guide to complete a systematic process of data visualization.

A third hierarchical level of narrower traits for the Dimensional Assessment of Personality Pathology-Basic Questionnaire.

Current dimensional taxonomies of personality disorder show a stronger empirical grounding than categories, but may lack the necessary level of detail to make accurate predictions and case formulations. We need to further develop the lower levels of the hierarchy until reaching the building blocks of personality pathology. The Dimensional Assessment of Personality Pathology-Basic Questionnaire (DAPP-BQ) is well-suited to this purpose due to its multilayered structure and its agreement with the official dimensional classifications. We disaggregated the 18 DAPP-BQ mid-level facets through exploratory and confirmatory factor analysis in a sample of 3233 community subjects and outpatients. We obtained a set of 72 clinically relevant, narrower subfacets, which were reliable, well-fitted to the data, and invariant between clinical and community subjects and between the sexes. This third level of abstraction increases by 4.7% the capacity to predict DSM categorical personality disorders, gives a particular advantage in capturing dependent, histrionic, paranoid, obsessive, and schizoid features and can provide the detailed information that clinical decisions demand.

Integration of the ICD-11 and DSM-5 Dimensional Systems for Personality Disorders Into a Unified Taxonomy With Non-overlapping Traits.

The promise of replacing the diagnostic categories of personality disorder with a better-grounded system has been only partially met. We still need to understand whether our main dimensional taxonomies, those of the International Classification of Diseases, 11th Revision (ICD-11) and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), are the same or different, and elucidate whether a unified structure is possible. We also need truly independent pathological domains, as they have shown unacceptable overlap so far. To inquire into these points, the Personality Inventory for DSM-5 (PID-5) and the Personality Inventory for ICD-11 (PiCD) were administered to 677 outpatients. Disattenuated correlation coefficients between 0.84 and 0.93 revealed that both systems share four analogous traits: negative affectivity, detachment, dissociality/antagonism, and disinhibition. These traits proved scalar equivalence too, such that scores in the two questionnaires are roughly interchangeable. These four domains plus psychoticism formed a theoretically consistent and well-fitted five-factor structure, but they overlapped considerably, thereby reducing discriminant validity. Only after the extraction of a general personality disorder factor (g-PD) through bifactor analysis, we could attain a comprehensive model bearing mutually independent traits.

Investigating the Transdiagnostic Value of Subjective Emptiness.

It is common for people with mental health problems to report feelings of emptiness. However, the association of subjective emptiness with specific disorders and its unique role within dimensional taxonomies of personality pathology is not well understood. The present study assesses the transdiagnostic value of subjective emptiness using a recently developed self-report measure in a mixed sample of 157 participants. The authors investigated the associations of emptiness with clinically relevant variables, including borderline personality disorder symptoms, depression, anxiety, suicidal ideation, and suicide attempts. Subjective emptiness showed strong positive relationships with all criteria. Regression models controlling for impairments of personality functioning, maladaptive personality traits, and current symptom distress supported the incremental validity of emptiness for specific disorder constructs and suicidality. These findings indicate that emptiness represents a facet of psychopathology that can be particularly useful for the classification of mental disorders, and in particular internalizing disorders involving self-dysfunction and detachment.

Hierarchical models of psychopathology: empirical support, implications, and remaining issues.

There is an ongoing revolution in psychology and psychiatry that will likely change how we conceptualize, study and treat psychological problems.- Many theorists now support viewing psychopathology as consisting of continuous dimensions rather than discrete diagnostic categories. Indeed, recent papers have proposed comprehensive taxonomies of psychopathology dimensions to replace the DSM and ICD taxonomies of categories. The proposed dimensional taxonomies, which portray psychopathology as hierarchically organized correlated dimensions, are now well supported at phenotypic levels. Multiple studies show that both a general factor of psychopathology at the top of the hierarchy and specific factors at lower levels predict different functional outcomes. Our analyses of data on a large representative sample of child and adolescent twins suggested the causal hypothesis that phenotypic correlations among dimensions of psychopathology are the result of many familial influences being pleiotropic. That is, most genetic variants and shared environmental factors are hypothesized to non-specifically influence risk for multiple rather than individual dimensions of psychopathology. In contrast, person-specific experiences tend to be related to individual dimensions. This hierarchical causal hypothesis has been supported by both large-scale family and molecular genetic studies. Current research focuses on three issues. First, the field has not settled on a preferred statistical model for studying the hierarchy of causes and phenotypes. Second, in spite of encouraging progress, the neurobiological correlates of the hierarchy of dimensions of psychopathology are only partially described. Third, although there are potentially important clinical implications of the hierarchical model, insufficient research has been conducted to date torec-ommend evidence-based clinical practices.

Supplemental Material for A Dimensional Taxonomy of Perceived Characteristics of Major Life Events

Supplemental Material for A Dimensional Taxonomy of Perceived Characteristics of Major Life Events

Integrating Philosophical and Psychological Accounts of Happiness and Well-Being

Philosophers have been interested in happiness and well-being since the Hellenic period. More recently, psychologists have begun to study how happy people are and what makes people’s lives go well. Today, these fields begin to converge, as philosophers and psychologists are interested in integrating the two disciplines. A central challenge for any interdisciplinary research is that disciplines often differ in their terminology. In this paper, we offer a novel approach to integrating philosophical and psychological accounts of happiness and well-being by describing these accounts on two independent continuous dimensions: degree of stability (from transient to stable) and psychological process (from affective to cognitive). This dimensional taxonomy highlights similarities and differences among the accounts and allows researchers to assess where philosophical and psychological accounts overlap and where they diverge. We first describe the methodological approach we used to develop our two-dimensional taxonomy, and then demonstrate how this taxonomy can be applied to a large number of existing theoretical accounts of happiness and well-being. We conclude the paper with a discussion of the strengths and limitations of the dimensional approach and implications for future theoretical and empirical research.

Developing an integrative level-dimensional taxonomy model for rehabilitation psychology research and practice.

The present article concerns the development of a taxonomy model for organizing and classifying all aspects of rehabilitation psychology from an integrative level-dimensional conceptualization. This conceptualization is presented as an alternative to a primarily categorical approach to classification. It also assumes a continuity perspective for all aspects of behavior and experience. Development of this taxonomy model involves organizing information relevant to levels/domains of all aspects of behavior and experience, and to constructs describing their underlying components conceptually as well as dimensions which constitute the measurable basis of constructs. A taxonomy model with levels/domains, representative examples of constructs and dimensions is presented as a foundation for development of the present taxonomy model, with specific relevance to rehabilitation psychology. This integrative level-dimensional taxonomy model provides a structure for organizing all aspects of rehabilitation psychology relevant to understanding, assessing, and influencing the rehabilitation process. Suggestions for development and research are provided for the taxonomy model. (PsycINFO Database Record

Using a Local Framework Combining Principal Component Regression and Monte Carlo Simulation for Uncertainty and Sensitivity Analysis of a Domestic Energy Model in Sub-City Areas

Domestic energy modelling is complex, in terms of user input and the approach used to define the model; therefore, there is an increase in the sources of uncertainties. Previous efforts to perform sensitivity and uncertainty analyses have focused on national energy models, while in this research, the objective is to extend traditional sensitivity analysis and use a local framework combining principal component regression and Monte Carlo Simulation. Therefore, in our method the total amount of the energy output’s variance is decomposed, in relative terms, according to the contribution of the different predictor parameters. Our framework provides compelling evidence that local area characteristics are important in energy modelling and those national and regional indexes and values may not properly reflect the local conditions, resulting in programmes and interventions that will be sub-optimal. Furthermore, our uncertainty methodology uses a three dimensional integrative taxonomy and a concept map. The concept map identified concrete terminal causes of uncertainty within the taxonomic framework of sources, issues, sub-issues and a further abstraction of those quantities in terms of accuracy and precision. Understanding uncertainties in this way provides a possible framework for modellers, policy makers and data collectors to improve practice in key areas and to reduce uncertainty.

Personality Disorders Are Not as We Thought: Hierarchical Factor Structure at the Criterion Level

ABSTRACTThe use of personality disorder (PD) categories persists, despite the evidence against them. An often overlooked reason for this is the fact that the true structure underlying the Diagnostic and Statistical Manual of Mental Disorders (DSM) taxonomy is still unknown: We cannot be certain which disorders are valid, and which ones are arbitrary mixtures of heterogeneous traits. To address this gap, we factor analyzed the Personality Diagnostic Questionnaire (PDQ–4+; Hyler, 1994) at the criterion level in a mixed clinical and nonclinical sample of 2,519 individuals. The resulting structure was more similar to current dimensional taxonomies than to the DSM classification at all hierarchical levels. Whereas paranoid and antisocial PDs—and to a lesser extent avoidant, dependent, depressive, and schizoid PDs—were fairly homogeneous, all other disorders turned out to be combinations of 2 or 3 unrelated dimensions. Our results strongly support the structure of empirically based dimensional taxonomies and relocate DSM criteria within this emerging framework, thus contributing to preserving much of the knowledge accumulated to date.

How temperament and character affect our career, relationships, and mental health

BackgroundOn the way toward an agreed dimensional taxonomy for personality disorders (PD), several pivotal questions remain unresolved. We need to know which dimensions produce problems and in what domains of life; whether impairment can be found at one or both extremes of each dimension; and whether, as is increasingly advocated, some dimensions measure personality functioning whereas others reflect style. MethodTo gain this understanding, we administered the Temperament and Character Inventory to a sample of 862 consecutively attended outpatients, mainly with PDs (61.2%). Using regression analysis, we examined the ability of personality to predict 39 variables from the Life Outcome Questionnaire concerning career, relationships, and mental health. ResultsPersistence stood out as the most important dimension regarding career success, with 24.2% of explained variance on average. Self-directedness was the best predictor of social functioning (21.1%), and harm avoidance regarding clinical problems (34.2%). Interpersonal dimensions such as reward dependence and cooperativeness were mostly inconsequential. In general, dimensions were detrimental only in one of their poles. ConclusionsAlthough personality explains 9.4% of life problems overall, dimensions believed to measure functioning (character) were not better predictors than those measuring style (temperament). The notion that PD diagnoses can be built upon the concept of “personality functioning” is unsupported.

Have changes in business practices and reporting standards changed the taxonomy of financial ratios?

Purpose – Prior research established a seven dimensional taxonomy of financial ratios. The purpose of this paper is to identify the extent to which the previously identified relationships have changed, and if appropriate, to establish an entirely new taxonomy of manufacturing industry financial ratios. Design/methodology/approach – The authors used principle component analysis (PCA) to identify factor patterns for 58 financial ratios over the ten-year period 2004-2013. The validity of employing PCA was confirmed using the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett’s test of sphericity. Findings – This study identified four additional financial analysis factors beyond the seven established by prior research. Notably, a separate cash flow factor did not surface as was the case in earlier work but an entirely new factor (current position) was identified. Research limitations/implications – This paper leaves to future research to establish the precise causes for the changes to the taxonomy of financial ratios and how to best utilize the new set of factors for financial analysis research. Practical implications – This paper identifies changes in financial ratio relationships to guide future researchers in selecting appropriate ratios for their studies. Originality/value – This study substantially improves and extends prior work in two areas. First, it utilizes advanced statistical methodologies and computing technologies that were unavailable to previous researchers. Second, it investigates not only the current taxonomy of manufacturing industry financial ratios, but also its stability over a recent ten-year period.