Background: Psychotic experiences (PEs) are not exclusive to psychotic disorders and highly correlated with mood episodes. In this representative general population-based study, longitudinal bidirectional associations between the extended psychosis phenotype and mood episodes were investigated, accounting for other possible causes.
Methods: Households were contacted in a multistage clustered probability sampling frame covering 11 districts and 302 neighbourhoods at baseline (n = 4011) and at 6-year follow-up (n = 2185). Participants were interviewed with the relevant sections of the composite international diagnostic interview both at baseline and at follow-up. Sociodemographic, familial and environmental risk factors associated with the extended psychosis phenotype and mood episodes were assessed. Logistic regression and cross-lagged panel correlation models were used for the associations between the extended psychosis phenotype and mood episodes.
Results: PEs were associated with subsequent depressive and manic episodes. There was bidirectionality in that mood episodes were associated with subsequent PEs, and PEs were associated with subsequent mood episodes. The associations occurred in a sub-additive pattern. There were substantial synchronous and cross-lagged correlations between these psychopathology domains, with reciprocally similar cross-lagged correlations. Familial risk and adverse life events were associated with both psychopathology domains, whereas some sociodemographic risk factors and alcohol/cannabis use were associated with only one domain.
Conclusion: The sub-additive bidirectional associations between PEs and mood episodes over time and the similarity of cross-lagged correlations are suggestive of mutually causal connections between affective and psychotic domains of psychopathology.
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http://dx.doi.org/10.1007/s00127-018-1641-8 | DOI Listing |
J Affect Disord
January 2025
School of Medicine, Faculty of Health Sciences, Universidad Técnica de Manabí, Portoviejo, Manabí, Ecuador; Research Institute, Universidad Técnica de Manabí, Portoviejo, Manabí, Ecuador. Electronic address:
Background: Sociodemographic characteristics and limited mental health care access may contribute to higher depression rates in low- and middle-income countries. Aim This study aimed to analyze nationwide depressive disorder hospitalizations in Ecuador.
Methods: We assessed the sociodemographic characteristics, severity, recurrence, and duration of hospitalizations for depressive disorders.
Introduction: Research has consistently shown that the prevalence of burnout symptoms (such as emotional and physical exhaustion, cynicism, or lack of interest in schoolwork, the sense of incompetence, or the feeling that you cannot be effective) in medical students is greater than the prevalence in the general population. Students with preexisting anxiety, depression, mood disorder or other psychological distress are more vulnerable to burnout. It is estimated that at least half of U.
View Article and Find Full Text PDFPsychol Addict Behav
January 2025
Department of Biobehavioral Health, Bennett Pierce Prevention Research Center, Pennsylvania State University.
Objective: Drinking intention is a predictor of heavy-drinking episodes and could serve as a real-time target for preventive interventions. However, the association is inconsistent and relatively weak. Considering the affective context when intentions are formed might improve results by revealing conditions in which intention-behavior links are strongest and the predictive power of intentions is greatest.
View Article and Find Full Text PDFJ Voice
January 2025
Department of Surgery, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, Belgium; Division of Laryngology and Bronchoesophagology, Department of Otolaryngology Head Neck Surgery, EpiCURA Hospital, Baudour, Belgium; Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, UFR Simone Veil, Université Versailles Saint-Quentin-en-Yvelines (Paris Saclay University), Paris, France; Department of Otolaryngology, Elsan Hospital, Paris, France. Electronic address:
Background: Voice analysis has emerged as a potential biomarker for mood state detection and monitoring in bipolar disorder (BD). The systematic review aimed to summarize the evidence for voice analysis applications in BD, examining (1) the predictive validity of voice quality outcomes for mood state detection, and (2) the correlation between voice parameters and clinical symptom scales.
Methods: A PubMed, Scopus, and Cochrane Library search was carried out by two investigators for publications investigating voice quality in BD according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements.
J Affect Disord
January 2025
Department of Psychiatry and Psychotherapy, University of Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), University of Marburg, Germany.
Background: Major depressive disorder (MDD) comes along with an increased risk of recurrence and poor course of illness. Machine learning has recently shown promise in the prediction of mental illness, yet models aiming to predict MDD course are still rare and do not quantify the predictive value of established MDD recurrence risk factors.
Methods: We analyzed N = 571 MDD patients from the Marburg-Münster Affective Disorder Cohort Study (MACS).
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