Psychometric properties of the Brief Symptom Inventory support the hypothesis of a general psychopathological factor

Unravelling inter-relations within and between psychodynamic constructs and psychopathology using network analysis

Psychodynamic constructs and psychopathology are closely inter-related, but more detailed insight is needed. We investigated these complex inter-relations using network analysis. A Gaussian graphical model in a sample of N = 2232 psychotherapeutic inpatients was estimated. Self-administered questionnaires to assess interpersonal relations (Inventory of Interpersonal Problems-32), psychodynamic conflicts (Operationalized Psychodynamic Diagnosis-Conflict Questionnaire), personality functioning (Operationalized Psychodynamic Diagnosis-Structure Questionnaire-Short Form, Inventory of Personality Organization-Short Form), and psychopathology (Brief Symptom Inventory) were utilized. We investigated the network structure, identified the most inter-related psychodynamic constructs and the psychodynamic constructs with the strongest inter-relations to psychopathology, and explored the clustering of all included constructs. Active and passive conflict processing modes were negatively inter-related in most conflicts. Passive conflict processing modes were more strongly related to psychopathology than active ones in all conflicts, apart from the care versus autarky conflict. Identity diffusion shared the strongest inter-relations within psychodynamic constructs. The psychodynamic constructs that were most strongly related to psychopathology were impairments in self-perception and the passive self-worth conflict. Psychopathology and psychodynamic constructs formed distinct clusters. Our results emphasize the relevance of personality functioning within psychodynamic constructs and in relation to psychopathology.

Impacts of mental health in the sleep pattern of healthcare professionals during the COVID-19 pandemic in Brazil

BACKGROUND

After >2 years of the Coronavirus Disease-19 (COVID-19) pandemic, it is well established how sleep symptoms are rising, especially among healthcare workers (HCW). The aim of this study is to evaluate what features are associated with sleep disturbances in the HCW population.

METHODS

Cross-sectional and longitudinal analysis of social and clinical variables associated with sleep problems and insomnia incidence in HCW in a large, national-level cohort. The measurement of sleep problems was assessed by self-report using Jenkins Sleep Scale (JSS). A multivariate analysis was used in the cross-sectional design and generalized linear models were used in the longitudinal design.

RESULTS

10,467 HCW were analyzed in the cross-sectional analysis, 3313 participants were analyzed in the three timepoints of the study. Sex, previously diagnosed mental illness and frontline work with COVID-19 were associated with higher scores in JSS in the univariate analysis. In the multivariate analysis, only previous diagnosis of mental illness was related with sleep difficulties, especially previously diagnosed insomnia. The longitudinal analysis concluded that previous diagnosis of mental illnesses was associated with higher levels of insomnia development (OR = 11.62). The self-reported disorders found to be major risk factors were addiction (OR = 7.69), generalized anxiety disorder (OR = 3.67), social anxiety (OR = 2.21) and bipolar disorder (OR = 2.21).

LIMITATIONS

Attrition bias.

CONCLUSIONS

Previous diagnosis of mental illness was strongly related to insomnia development in HCW during the COVID-19 pandemic. Strategies that focus on this population are advised.