The purpose of this rejoinder is to emphasize several important areas of future research that were mentioned by one or both commentaries. First, the authors discuss issues related to multi-source assessment, such as the importance of further research on informant bias, andargue that the information gleaned from multiple sources is worth the added assessment burden. Second, they underscore the importance of longitudinal assessment both in capturing the treatment-relevant within-person processes through which personality pathology unfolds, as well as tracking therapeutic progress. They assert that a given measure’s ability to reliably and validly measure change over time should be considered when evaluating its clinical utility. Finally, they emphasize the need for greater attention to clinical utility of dimensional PD assessment measures.

Over the past twenty years, several taxonomies of personality and psychopathology have been developed. More recently, many studies have compared dimensional models of personality pathology to categorical diagnoses of personality disorders. Altogether, this proliferation of research suggests the value of articulating the desirable properties of a good taxonomic system. Here, the authors extend basic research in cognitive science on the limitations of representational capacity, which suggests that humans need to compress complex clinical presentations to make good judgments. With this in mind, the authors propose that information compression and information fidelity are two principles that are essential to good taxonomy. The principle of information compression is that taxonomies should prune the complexities of a detailed clinical presentation to focus on important sources of covariation. The principle of information fidelity is that a good taxonomy should maintain essential features that reasonably approximate the structure of an individual or the population. They conclude with the claim that the overarching goal of taxonomic science in classifying personality pathology is to provide clinicians and researchers with empirically based informative priors that help to bias thinking toward useful clinical distinctions.

In their chapter, Bach and Presnall-Shvorin (this volume) introduce guidelines for incorporating empirically-driven trait models of personality pathology, codified in the DSM-5 and ICD-11, into therapeutic practice. Though the authors of this commentary are supportive of the effort to bridge research with clinical practice, they suggest that a mechanistic model which accounts for personality processes underlying descriptive traits could offer greater precision than traits alone. Furthermore, they argue that clinical dysfunction can only be meaningfully defined and treated with an understanding of dynamic, contextualized aspects of personality. To illustrate how a mechanistic model could complement and extend Bach and Presnall’s recommendations, the authors present a case conceptualization using cybernetic theory. Finally, they review how idiographic data gleaned from ambulatory assessment methods provide insight into pathological processes ideal for therapeutic intervention. To achieve a generalizable approach flexible enough to adapt to the individual, they encourage the development of treatment models that go beyond traits to mechanistically link stable and dynamic personality features into a unified framework.

This commentary on Sharp and De Clerq’s chapter (this volume) describes potential benefits of integrating and synthesizing research conducted primarily predominantly with adults from a personality pathology perspective with the increasingly robust body of research conducted with children and adolescents from a developmental psychopathology perspective. Both perspectives view psychopathology as emerging from an interplay of biologically-based vulnerabilities and risk and protective factors at multiple levels of social ecological systems (e.g., individual, family, community, and culture). Both attempt to understand developmental pathways and trajectories that may evolve into more durable and distinctive patterns of thoughts, emotions, and behaviors that may be categorized as a personality disorder or other mental disorder. Both perspectives hope to identify effective interventions that may prevent more severe and chronic disorders among at-risk individuals. The authors argue that the integration of personality pathology and developmental psychopathology perspectives may contribute to the development of more sophisticated transdiagnostic approaches that inform clinical case formulation and treatment planning for children and adolescents.

The authors of this commentary aim to expand on particular points covered in the chapter by Evans, Williams and Simms, and discuss other issues that were not covered there. First, they discuss future research directions for, and the potential utility of, multisource assessments of personality pathology. Second, they emphasize the need for aspects of clinical utility within some of the reviewed measures (e.g., norms, validity scales). Third, they discuss the need for further examinations into the feasibility and utility of longitudinal assessments of personality pathology (e.g., dynamics in the context of treatment). Fourth, they describe two recent measures of personality pathology that warrant further validation. Lastly, they emphasize the need for a conceptual and measurement-based consensus regarding the multidimensional nature of personality pathology as a whole.

The purpose of this chapter is to review the current state of the dimensional assessment of personality disorder (PD). The first part of the chapter serves as a review of the most well-established and commonly used measures of maladaptive personality traits. Measures that assess the psychosocial impairment associated with personality pathology also are reviewed. Areas of discontinuity among these measures (e.g., theoretical origin, method of scale construction, degree of correspondence with well-known trait dimensions, attention received in the empirical literature, degree of bipolarity of underlying dimensions) are emphasized, and the clinical utility of measures is evaluated. The second part of the chapter focuses on several controversial issues with which the field of dimensional PD assessment now is grappling. These issues include (a) the psychometric distinction of personality traits from personality functioning, (b) the incremental utility of adaptive trait assessment, (c) the question of maladaptive trait bipolarity, (d) facet-level differences versus domain-level similarity across competing PD trait models, and (e) the value of multi-source assessment.

This comment concurs with Miller and Widiger’s review on the five-factor model’s potential to describe personality pathology. Remaining challenges are the definition of the domain that one wants to cover and how to separate personality description from dysfunction.

Evans et al. (this volume) reviewed prominent dimensional measures of personality, discussed the clinical usefulness of these measures, and provided an overview of personality assessment issues. This commentary focuses on the clinical utility and applications of personality traits and assessment, as well as factors relevant to bridging the research-to-practice gap. In order to adequately disseminate and implement evidence-based personality assessments into practice, personality pathology researchers should be taking active steps to move the empirical base (e.g., validated models of personality, evidence-based assessments, aspects of clinical utility) into application. The process of translating these traits and measures into practice may include assessing barriers to use among practitioners, addressing matters of acceptability and feasibility, and providing training and consultation to practitioners. The authors review benefits of including adaptive traits in assessment and practice (e.g., assist with collaborative treatment planning, decrease stigma), provide commentary on the incremental utility of dysfunction including the use of external correlates, and outline the importance of bipolarity of dimensional trait measures.