Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS).

Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.

Sleep and Women's Mental Health.

Women have increased risks for both sleep disturbances and disorders and for mental health issues throughout their lives, starting in adolescence. Women have a higher prevalence of insomnia disorder and restless legs syndrome (RLS) versus men, and obstructive sleep apnea (OSA) is more likely as women age. Hormonal transitions are important to consider in women's sleep. For women, insomnia, OSA, and RLS are predictive of depression, and insomnia and sleep-disordered breathing are predictive of Alzheimer disease. These findings underscore the importance of assessment, treatment, and future research examining sleep and mental health in women, given their unique and increased vulnerability.