Background: Severe mental illness diagnoses have overlapping symptomatology and shared genetic risk, motivating cross-diagnostic investigations of disease-relevant quantitative measures. We analysed relationships between neurocognitive performance, symptom domains, and diagnoses in a large sample of people with severe mental illness not ascertained for a specific diagnosis (cases), and people without mental illness (controls) from a single, homogeneous population.
Methods: In this case-control study, cases with severe mental illness were ascertained through electronic medical records at Clínica San Juan de Dios de Manizales (Manizales, Caldas, Colombia) and the Hospital Universitario San Vicente Fundación (Medellín, Antioquía, Colombia). Participants were assessed for speed and accuracy using the Penn Computerized Neurocognitive Battery (CNB). Cases had structured interview-based diagnoses of schizophrenia, bipolar 1, bipolar 2, or major depressive disorder. Linear mixed models, using CNB tests as repeated measures, modelled neurocognition as a function of diagnosis, sex, and all interactions. Follow-up analyses in cases included symptom factor scores obtained from exploratory factor analysis of symptom data as main effects.
Findings: Between Oct 1, 2017, and Nov 1, 2019, 2406 participants (1689 cases [schizophrenia n=160; bipolar 1 disorder n=519; bipolar 2 disorder n=204; and major depressive disorder n=806] and 717 controls; mean age 39 years (SD 14); and 1533 female) were assessed. Participants with bipolar 1 disorder and schizophrenia had similar impairments in accuracy and speed across cognitive domains. Participants with bipolar 2 disorder and major depressive disorder performed similarly to controls, with subtle deficits in executive and social cognition. A three-factor model (psychosis, mania, and depression) best represented symptom data. Controlling for diagnosis, premorbid IQ, and disease severity, high lifetime psychosis scores were associated with reduced accuracy and speed across cognitive domains, whereas high depression scores were associated with increased social cognition accuracy.
Interpretation: Cross-diagnostic investigations showed that neurocognitive function in severe mental illness is characterised by two distinct profiles (bipolar 1 disorder and schizophrenia, and bipolar 2 disorder and major depressive disorder), and is associated with specific symptom domains. These results suggest the utility of this design for elucidating severe mental illness causes and trajectories.
Funding: US National Institute of Mental Health.
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http://dx.doi.org/10.1016/S2215-0366(20)30098-5 | DOI Listing |
J Neurosci Res
January 2025
Department of Psychology, University of Regensburg, Regensburg, Germany.
Anxiety and depression disorders show high prevalence rates, and stress is a significant risk factor for both. However, studies investigating the interplay between anxiety, depression, and stress regulation in the brain are scarce. The present manuscript included 124 law students from the LawSTRESS project.
View Article and Find Full Text PDFInt J Lang Commun Disord
January 2025
Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff, UK.
Background: There is a growing body of evidence showing the value of community singing-based rehabilitation on psychosocial well-being and communication for people with post-stroke communication impairment (PSCI). However, there has been little consideration of the potential value an inpatient aphasia-friendly choir may have through the perspective of the stroke multidisciplinary team (MDT).
Aims: To explore the experiences and views of the MDT on the role an established inpatient aphasia-friendly choir, at a stroke rehabilitation centre in South Wales, UK, may play in the rehabilitation of people with PSCI.
Health Promot Chronic Dis Prev Can
January 2025
Department of Psychology, University of Regina, Regina, Saskatchewan, Canada.
Introduction: This study provides a descriptive overview of the prevalence of posttraumatic stress disorder (PTSD) in Canada, across sociodemographic characteristics, mental health-related variables and negative impacts of the COVID-19 pandemic.
Methods: Data were obtained from cycles 1 and 2 of the Survey on COVID-19 and Mental Health (SCMH), collected in fall 2020 (N = 14 689) and spring 2021 (N = 8032). The prevalence of PTSD was measured using the PTSD Checklist for DSM-5 (PCL-5) Cross-sectional associations were quantified using logistic regression, while controlling for sociodemographic characteristics.
J Adv Nurs
January 2025
Independant Scholar.
Aim: To explore psychiatric and mental health nurses' perceptions of patients with co-occurring psychiatric and substance use disorders in psychiatric settings.
Design: An exploratory qualitative study design based on grounded theory, employing Straussian analytic procedures.
Method: Semi-structured interviews were conducted with 11 psychiatric and mental health nurses.
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