A considerable body of research has rapidly accumulated with respect to the validity of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) dimensional trait model as it is assessed by the Personality Inventory for Diagnostic and Statistical Manual of Mental Disorders (PID-5; Krueger et al., 2012). This research though has not focused specifically on discriminant validity, although allusions to potentially problematic discriminant validity have been raised. The current study addressed discriminant validity, reporting for the first time the correlations among the PID-5 domain scales. Also reported are the bivariate correlations of the 25 PID-5 maladaptive trait scales with the personality domain scales of the NEO Personality Inventory-Revised (Costa & McCrae, 1992), the International Personality Item Pool-NEO (Goldberg et al., 2006), the Inventory of Personal Characteristics (Almagor et al., 1995), the 5-Dimensional Personality Test (van Kampen, 2012), and the HEXACO Personality Inventory-Revised (Lee & Ashton, 2004). The results are discussed with respect to the implications of and alternative explanations for potentially problematic discriminant validity. (PsycINFO Database Record

Download full-text PDF

Source
http://dx.doi.org/10.1037/per0000118DOI Listing

Publication Analysis

Top Keywords

discriminant validity
16
personality inventory
8
diagnostic statistical
8
statistical manual
8
manual mental
8
mental disorders
8
problematic discriminant
8
correlations pid-5
8
domain scales
8
personality inventory-revised
8

Similar Publications

Purpose: Heart failure (HF) is a disease that leads to approximately 300,000 fatalities annually in Europe and 250,000 deaths each year in the United States. Type 2 Diabetes Mellitus (T2DM) is a significant risk factor for HF, and testing for N-terminal (NT)-pro hormone BNP (NT-proBNP) can aid in early detection of HF in T2DM patients. We therefore developed and validated the HFriskT2DM-HScore, an algorithm to predict the risk of HF in T2DM patients, so guiding NT-proBNP investigation in a primary care setting.

View Article and Find Full Text PDF
Article Synopsis
  • Depression treatment effectiveness differs greatly among individuals, highlighting the need for objective biomarkers that can accurately predict therapy outcomes to improve treatment efficiency.
  • This study used functional near-infrared spectroscopy (fNIRS) combined with clinical assessments to explore whether machine learning techniques could forecast treatment responses in patients with major depressive disorder (MDD).
  • Findings revealed that changes in total hemoglobin levels in a specific brain region (dlPFC) correlated significantly with treatment response, and the fNIRS-only model demonstrated better predictive accuracy compared to a model that also included clinical data.
View Article and Find Full Text PDF

Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.

Med Image Anal

January 2025

Nuffield Department of Medicine, University of Oxford, Oxford, UK; Department of Engineering Science, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Oxford, UK. Electronic address:

Predicting disease-related molecular traits from histomorphology brings great opportunities for precision medicine. Despite the rich information present in histopathological images, extracting fine-grained molecular features from standard whole slide images (WSI) is non-trivial. The task is further complicated by the lack of annotations for subtyping and contextual histomorphological features that might span multiple scales.

View Article and Find Full Text PDF

A novel method for detecting genetic biomarkers in blood-based liquid biopsies using surface plasmon resonance imaging and magnetic beads shows promise in cancer diagnosis and monitoring.

Talanta

January 2025

Department of Chemical Sciences, University of Catania, Viale Andrea Doria 6, 95122, Catania, Italy; INBB, Istituto Nazionale di Biostrutture e Biosistemi, Viale delle Medaglie d'Oro, 305, 00136, Roma, Italy. Electronic address:

Directly detecting biomarkers in liquid biopsy for diagnosis and personalized treatment plays a crucial role in managing cancer relapse and increasing survival rates. Typically, the standard analysis of circulating tumour DNA requires lengthy isolation, extraction, and amplification steps, leading to sample contamination, longer turnaround time and higher assay costs. Surface plasmon resonance is an emerging and promising technology for rapid and real-time dynamic biomarker monitoring in liquid biopsy.

View Article and Find Full Text PDF

In this study, we developed and validated a novel microhaplotype (MH) panel, the FGID Microhaplotype Kit, which contains 232 loci and was specifically designed for forensic kinship analysis. The performance of the panel was evaluated through rigorous testing that included sensitivity, species specificity, inhibitor resistance, uniformity, stability, accuracy and mixture deconvolution. The results showed that the kit is capable of reliably detecting all loci with minimal DNA input.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!