Journal of psychopathology and clinical science最新文献

This article contends that many of the chief complaints about the Diagnostic and Statistical Manual of Mental Disorders can be obviated by a set-theoretic, combinatorial approach. Arbitrary cutoffs, polythetic criteria, and category heterogeneity can be avoided by using a data-driven approach that assesses whether particular symptom combinations represent sufficient conditions for clinical benchmarks at an acceptable level of conditional probability. Using data from the National Comorbidity Survey-Replication, this study employed generalized anxiety disorder, major depressive disorder, posttraumatic stress disorder, and the union of major depressive disorder and generalized anxiety disorder as exemplars and set a target probability threshold of p ≥ .90 for sufficiency. All possible symptom combinations were generated for each subsample, with sample sizes of N = 1,948, N = 2,285, N = 777, and N = 3,129, respectively. Sufficient sets were identified for diagnosis, clinical distress, and functional impairment. Establishing sufficiency reduced the number of possible symptom combinations by at least 94% (M = 98.7%, SD = 1.79%). Finally, in a large, randomly split-halved subsample (N = 6,656), sufficient sets were identified at p ≥ .90 and tested in the holdout data. Results yielded an average conditional probability of .91 (SD = .03), reinforcing the robustness and generalizability of the current methods. These results suggest that a large amount of the heterogeneity in symptom combinations in internalizing disorders may be nested and reducible. Thus, much of the combinatorial information in the symptom presentations of these disorders may be overlapping and there may be core features of psychopathology that are sufficient to produce fidelity without requiring additional complexity. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Anxiety and shame are central, elevated emotions in body dysmorphic disorder (BDD) that are implicated as risk factors for suicide in suicide theories and are associated with suicide risk in cross-sectional BDD studies. Given that emotions are transient and suicide risk can increase quickly, risk prediction in BDD may be enhanced by measuring momentary anxiety and shame. In 87 adults with moderate to severe, clinician-diagnosed BDD, we collected ecological momentary assessment-rated anxiety and shame 3 times daily for two 14-day periods (28 days). We used generalized linear mixed models to estimate associations of concurrent or next-observation ecological momentary assessment-rated (a) intensity of desire to die by suicide and (b) intention (absent/present) to attempt suicide, above baseline clinician-assessed suicide ideation (SI) severity (Columbia-Suicide Severity Rating Scale). Higher within-person deviations from one's average anxiety and shame were significantly related to greater concurrent and next-observation suicide desire and concurrent intent, above baseline clinician-assessed SI severity. Only baseline clinician-assessed SI predicted next-observation suicide intent. Altogether, results showed that our ability to detect and predict suicide risk in BDD was improved beyond baseline clinician assessment when a person's current anxiety and shame levels were also considered. When someone with BDD experiences elevated anxiety or shame compared to their own norm, these elevations are associated with concurrent and short-term increases in suicide desire and concurrent suicide intent. This is the first prospective study of shame and anxiety as risk factors for SI in BDD. Results underscore the importance of these emotions as assessment and intervention targets. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

The personalization of psychopathology through the use of personalized symptom networks appears to be a promising approach for gaining deeper insights into the development and maintenance of mental disorders. One way to create such networks is by using the perceived causal networks (PECAN) method. In this method, respondents are systematically asked to quantify how their symptoms are causally linked. Answers are then visualized, either for the individual or aggregated for a group, as a directed network. PECAN can represent causal relations irrespective of their timescales and requires no data-hungry estimations. The following guidelines are intended to assist clinicians and researchers in the creation of personalized networks using the PECAN method. These networks can facilitate case conceptualization and personalization of treatments for individual patients and the description of groups of patients, revealing recurring feedback loops and central symptoms. Additionally, recommendations are provided regarding the procedures to be employed in the selection of nodes, assessment of edges, and visualization of the data. Furthermore, the potential for evaluating the reliability, validity, and clinical usefulness, as well as strengths, limitations, and future challenges of PECAN, is discussed. We conclude with an overview of the challenges of PECAN and a research agenda that highlights opportunities to improve the still very young method and implement it in clinical research and practice. (PsycInfo Database Record (c) 2025 APA, all rights reserved).