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The triarchic model of psychopathy posits that three distinct trait dispositions-disinhibition, meanness, and boldness-contribute to the interpersonal, affective, and impulsive-unrestrained features of this condition and is represented to varying degrees in all conceptualizations and measures of psychopathy. Using data for incarcerated males ( = 273) and females ( = 83) from 10 different prisons in Italy, we specified a latent variable model of the triarchic trait constructs in which scale measures of disinhibition, meanness, and boldness composed of items from the following inventories served as indicators: Triarchic Psychopathy Measure, Psychopathic Personality Inventory-Revised, Minnesota Multiphasic Personality Inventory-2 Restructured Form, and NEO Five Factor Inventory. A correlated three-factor solution evidenced adequate model fit, with individual triarchic trait scales loading strongly onto their target factors. The model exhibited comparable fit and factor loadings when specified using data for males only, and its factors showed expected relations with pertinent criterion variables, including measures of normative personality and clinical dysfunction along with staff ratings of prison behavior and release prognosis. Extending prior research with nonclinical participants from the U.S., present study results demonstrate the viability of a latent variable model of the triarchic traits in an incarcerated offender sample from a separate culture (Italy). The significance of this work lies in the potential of the triarchic traits to serve as conceptual-empirical points of reference for integrating findings across studies of psychopathy employing diverse samples and assessment measures. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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http://dx.doi.org/10.1037/pas0001158 | DOI Listing |
Behav Res Methods
September 2025
Wilhelm-Wundt Institute for Psychology, Leipzig University, Neumarkt 9-19, 04109, Leipzig, Germany.
The study of time-dependent within-person dynamics has gained popularity in recent years through the use of multilevel (latent) time-series models. However, due to the complexity of the models, model applications are usually limited with respect to the inclusion of time-varying moderating factors on the longitudinal within-person relations between variables. That is, in common applications of multilevel time-series models, the within-person dynamics of constructs over time are regarded as being insensitive to changes in other time-varying factors or changes in contexts.
View Article and Find Full Text PDFCrit Care Explor
September 2025
Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Objective: To identify distinct phenotypes of acute respiratory distress syndrome (ARDS) developing after hematopoietic cell transplantation (HCT), using routinely available clinical data at ICU admission.
Design: Multicenter retrospective cohort study using latent class analysis.
Setting: ICUs across three Mayo Clinic campuses (Minnesota, Florida, and Arizona).
Asian Nurs Res (Korean Soc Nurs Sci)
September 2025
Department of cardiovascular medicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Purpose: This study aimed to explore health literacy profiles in patients with heart failure and identify heterogeneous subgroups within the chronic heart failure population. Through investigating the health literacy of heart failure patients, we analyzed the factors influencing patients' health literacy levels, aiming to provide evidence-based guidance for improving health literacy in this patient population.
Methods: This study employed a cross-sectional design.
J Med Internet Res
September 2025
The Hong Kong Jockey Club Centre for Suicide Research and Prevention, University of Hong Kong, 5 Sassoon Rd, Sandy Bay, Hong Kong, 999077, China (Hong Kong), 852 2831 5232.
Background: Online text-based counseling services are becoming increasingly popular. However, their text-based nature and anonymity pose challenges in tracking and understanding shifts in help-seekers' emotional experience within a session. These characteristics make it difficult for service providers to tailor interventions to individual needs, potentially diminishing service effectiveness and user satisfaction.
View Article and Find Full Text PDFFront Public Health
September 2025
School of Statistics, University of International Business and Economics, Beijing, China.
The advent of electronic storage of medical records and the internet has led to an increase in the use of online medical records, thereby enhancing doctor-patient communication and facilitating medical treatment. Based on demographic and personal behavioral characteristics from the National Cancer Institute's 2019-2020 National Trends in Health Information Survey data, this study explored the characteristics and factors influencing the frequent use of online medical records and compared them with those that do not. By combining traditional statistical tests and two machine learning algorithms, eight variables were identified as key variables in the frequent use of online medical records.
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