Empirically identified networks of healthcare providers for adults with mental illness

Background Policies target networks of providers who treat people with mental illnesses, but little is known about the empirical structures of these networks and related variation in patient care. The goal of this paper is to describe networks of providers who treat adults with mental illness in a multi-payer database based medical claims data in a U.S. state. Methods Provider networks were identified and characterized using paid inpatient, outpatient and pharmacy claims related to care for people with a mental health diagnosis from an all-payer claims dataset that covers both public and private payers. Results Three nested levels of network structures were identified: an overall network, which included 21% of providers (N = 8256) and 97% of patients (N = 476,802), five communities and 24 sub-communities. Sub-communities were characterized by size, provider composition, continuity-of-care (CoC), and network structure measures including mean number of connections per provider (degree) and average number of connections who were connected to each other (transitivity). Sub-community size was positively associated with number of connections (r = .37) and the proportion of psychiatrists (r = .41) and uncorrelated with network transitivity (r = −.02) and continuity of care (r = .00). Network transitivity was not associated with CoC after adjustment for provider type, number of patients, and average connection CoC (p = .85). Conclusions These exploratory analyses suggest that network analysis can provide information about the networks of providers that treat people with mental illness that is not captured in traditional measures and may be useful in designing, implementing, and studying interventions to improve systems of care. Though initial results are promising, additional empirical work is needed to develop network-based measures and tools for policymakers

Age and gender differences in narcissism: A comprehensive study across eight measures and over 250,000 participants

Age and gender differences in narcissism have been studied often. However, considering the rich history of narcissism research accompanied by its diverging conceptualizations, little is known about age and gender differences across various narcissism measures. The present study investigated age and gender differences and their interactions across eight widely used narcissism instruments (i.e., Narcissistic Personality Inventory, Hypersensitive Narcissism Scale, Dirty Dozen, Psychological Entitlement Scale, Narcissistic Personality Disorder Symptoms from the Diagnostic and Statistical Manual of Mental Disorders, Version IV, Narcissistic Admiration and Rivalry Questionnaire-Short Form, Single-Item Narcissism Scale, and brief version of the Pathological Narcissism Inventory). The findings of Study 1 (N = 5,736) revealed heterogeneity in how strongly the measures are correlated. Some instruments loaded clearly on one of the three factors proposed by previous research (i.e., Neuroticism, Extraversion, Antagonism), while others cross-loaded across factors and in distinct ways. Cross-sectional analyses using each measure and meta-analytic results across all measures (Study 2) with a total sample of 270,029 participants suggest consistent linear age effects (random effects meta-analytic effect of r = -.104), with narcissism being highest in young adulthood. Consistent gender differences also emerged (random effects meta-analytic effect was -.079), such that men scored higher in narcissism than women. Quadratic age effects and Age × Gender effects were generally very small and inconsistent. We conclude that despite the various conceptualizations of narcissism, age and gender differences are generalizable across the eight measures used in the present study. However, their size varied based on the instrument used. We discuss the sources of this heterogeneity and the potential mechanisms for age and gender differences

Les progrès dans la réalisation de la classification quantitative de la psychopathologie

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level'' dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity'' by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach. (C) 2020 Published by Elsevier Masson SAS

Considering Predictive Factors in the Diagnosis of Clinically Significant Prostate Cancer in Patients with PI-RADS 3 Lesions

The use of multi-parametric magnetic resonance imaging (mpMRI) in conjunction with the Prostate Imaging Reporting and Data System (PI-RADS) is standard practice in the diagnosis, surveillance, and staging of prostate cancer. The risk associated with lesions graded at a PI-RADS score of 3 is ambiguous. Further characterization of the risk associated with PI-RADS 3 lesions would be useful in guiding further work-up and intervention. This study aims to better characterize the utility of PI-RADS 3 and associated risk factors in detecting clinically significant prostate cancer. From a prospectively maintained IRB-approved dataset of all veterans undergoing mpMRI fusion biopsy at the Southeastern Louisiana Veterans Healthcare System, we identified a cohort of 230 PI-RADS 3 lesions from a dataset of 283 consecutive UroNav-guided biopsies in 263 patients from October 2017 to July 2020. Clinically significant prostate cancer (Gleason Grade ≥ 2) was detected in 18 of the biopsied PI-RADS 3 lesions, representing 7.8% of the overall sample. Based on binomial analysis, PSA densities of 0.15 or greater were predictive of clinically significant disease, as was PSA. The location of the lesion within the prostate was not shown to be a statistically significant predictor of prostate cancer overall (p = 0.87), or of clinically significant disease (p = 0.16). The majority of PI-RADS 3 lesions do not represent clinically significant disease; therefore, it is possible to reduce morbidity through biopsy. PSA density is a potential adjunctive factor in deciding which patients with PI-RADS 3 lesions require biopsy. Furthermore, while the risk of prostate cancer for African-American men has been debated in the literature, our findings indicate that race is not predictive of identifying prostate cancer, with comparable Gleason grade distributions on histology between races

E-Cigarette-Associated Endothelial Damage: A Potential Mechanism for Erectile Dysfunction

Electronic cigarettes (e-cigs) have increased in popularity as a potentially less harmful alternative to tobacco smoking; however, the literature suggests “vaping” can cause endothelial damage, which can adversely affect erectile function. While there is a known link between smoking cigarettes and erectile dysfunction (ED), the effect of e-cigs on erectile function has been understudied. To review the evidence for e-cig use causing endothelial dysfunction, to explore endothelial dysfunction as a potential mechanism for ED, and to determine if there is literature to support e-cigs as a cause of ED. A literature review was performed to identify publications pertaining to e-cig consumption and ED. Publications regarding e-cig consumption and vascular or endothelial damage were also included. The search was conducted through PubMed, MEDLINE database, the Cochrane Library Central Search, Web of Science, and Google Scholar. We identified 40+ publications for review, including 6 clinical trials and 3 basic science studies. The literature suggests that e-cig use induces oxidative stress, including the direct formation of reactive oxygen species and hydroxyl radicals, leading to endothelial damage. Endothelial dysfunction is a potential mechanism for ED, but there is a paucity of studies evaluating the relationship between e-cig use and ED. E-cig use may cause ED in men, but more studies, specifically clinical trials, are needed to establish a relationship between e-cigs and ED. E-cig-induced endothelial dysfunction is a potential mechanism for ED that is worth exploring further. J Pincus, V Sandoval, B Dick, et al. E-Cigarette-Associated Endothelial Damage: A Potential Mechanism for Erectile Dysfunction. Sex Med Rev 2021;XX:XXX–XXX