The DSM-5 Section III alternative model for personality disorders (AMPD) is a personality disorder (PD) nosology based on severity of personality dysfunction and pathological traits. We examined the degree to which the personality constructs identified by McAdams and Pals (2006; dispositional traits, characteristic adaptations, narrative identity) and the paradigms of personality assessment described by Wiggins (2003; psychodynamic, interpersonal, personological, multivariate, empirical) are represented within the AMPD. Nine raters expert with the AMPD and personality evaluated elements of Criterion A and the 25 trait facets of Criterion B for presence of type and degree of personality constructs and paradigms, as well as level of inference. Criterion B showed higher rater agreement compared to Criterion A. Criteria A and B reflect different configurations of construct, paradigm, and level of inference. The characteristic adaptation construct and interpersonal paradigm were strongly reflected in both Criteria A and B. The psychodynamic and personological paradigms and the narrative identity construct were highly correlated, and the multivariate, empirical, and dispositional traits variables were highly correlated. Results illustrate differential conceptual emphases as well as areas of overlap with Criteria A and B. This characterization highlights that PD nosology rests on personality theory and suggests implications for integrative PD assessment.
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http://dx.doi.org/10.1080/00223891.2018.1477787 | DOI Listing |
Cell Mol Life Sci
January 2025
Department of Anesthesiology, Shenzhen Children's Hospital, Yitian Road 7019, Shenzhen, 518000, China.
Hair follicle (HF) development and pigmentation are complex processes governed by various signaling pathways, such as TGF-β and FGF signaling pathways. Nestin + (neural crest like) stem cells are also expressed in HF stem cells, particularly in the bulge and dermal papilla region. However, the specific role and differentiation potential of these Nestin-positive cells within the HF remain unclear, especially regarding their contribution to melanocyte formation and hair pigmentation.
View Article and Find Full Text PDFBMC Geriatr
January 2025
Department of Cardiology, The Second Hospital & Clinical Medical School, Lanzhou University, No. 82 Cuiyingmen, Lanzhou, 730000, China.
Objective: Constructing a predictive model for the occurrence of heart disease in elderly hypertensive individuals, aiming to provide early risk identification.
Methods: A total of 934 participants aged 60 and above from the China Health and Retirement Longitudinal Study with a 7-year follow-up (2011-2018) were included. Machine learning methods (logistic regression, XGBoost, DNN) were employed to build a model predicting heart disease risk in hypertensive patients.
BMC Pulm Med
January 2025
Medical Research Center, Affiliated Hospital of Jining Medical University, Jining Medical University, 89 Guhuai Road, Jining, Shandong Province, 272029, PR China.
Background: Lung cancer is a leading cause of morbidity and mortality globally. Despite advances in targeted and immunotherapies, overall survival (OS) rates remain suboptimal. Cyclin-A2 (CCNA2), known for its upregulation in various tumors and role in tumorigenesis, has an undefined function in non-small cell lung cancer (NSCLC).
View Article and Find Full Text PDFBMC Pediatr
January 2025
Department of Psychology, University of South Dakota, 414 E. Clark St, Vermillion, SD, USA.
Background: Competing definitions of posttraumatic stress disorder (PTSD) have been proposed by ICD-11 and DSM-5; it is unclear which diagnostic model works best for children and adolescents. Although other studies have predicted the impact of these models by approximating the criteria using older measures, this study advances the research by comparing measures designed to assess ICD-11 and DSM-5 criteria in hurricane-exposed youth. This study evaluates ICD-11 and DSM-5 (both the standard and preschool-age) diagnostic models by identifying diagnostic rates, evaluating diagnostic concordance, investigating the predictive value of constructs associated with PTSD (demographics, disaster threat and exposure, functional impairment), and examining model fit.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orthopaedics, Traditional Chinese Medical Hospital of Gansu Province, Qilihe District, Guazhou Street 418, Lanzhou, 730050,, Gansu, China.
Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning techniques. Clinical data from 2594 samples were obtained and stratified into training and validation datasets in a 7:3 ratio.
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