Background Disease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients... Show moreBackground Disease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients would enable personalized management of these patients. This study aimed to predict recovery from anxiety disorders within 2 years applying a machine learning approach. Methods In total, 887 patients with anxiety disorders (panic disorder, generalized anxiety disorder, agoraphobia, or social phobia) were selected from a naturalistic cohort study. A wide array of baseline predictors (N = 569) from five domains (clinical, psychological, sociodemographic, biological, lifestyle) were used to predict recovery from anxiety disorders and recovery from all common mental disorders (CMDs: anxiety disorders, major depressive disorder, dysthymia, or alcohol dependency) at 2-year follow-up using random forest classifiers (RFCs). Results At follow-up, 484 patients (54.6%) had recovered from anxiety disorders. RFCs achieved a cross-validated area-under-the-receiving-operator-characteristic-curve (AUC) of 0.67 when using the combination of all predictor domains (sensitivity: 62.0%, specificity 62.8%) for predicting recovery from anxiety disorders. Classification of recovery from CMDs yielded an AUC of 0.70 (sensitivity: 64.6%, specificity: 62.3%) when using all domains. In both cases, the clinical domain alone provided comparable performances. Feature analysis showed that prediction of recovery from anxiety disorders was primarily driven by anxiety features, whereas recovery from CMDs was primarily driven by depression features. Conclusions The current study showed moderate performance in predicting recovery from anxiety disorders over a 2-year follow-up for individual patients and indicates that anxiety features are most indicative for anxiety improvement and depression features for improvement in general. Show less
Psychological problems like procrastination, perfectionism, low self-esteem, test anxiety and stress are common among college students. There are evidence-based interventions available for these... Show morePsychological problems like procrastination, perfectionism, low self-esteem, test anxiety and stress are common among college students. There are evidence-based interventions available for these problems that not only have direct effects on these problems, but also indirect effects on mental disorders such as depression and anxiety disorders. Targeting these psychological problems may offer new opportunities to prevent and treat mental disorders in a way that is less stigmatizing to students. In this study we examined the association of five psychological problems with five common mental disorders (panic, generalized anxiety, bipolar, major depressive, and substance use disorder) in a sample of 2,449 students from two Dutch universities. Psychological problems were measured with one item for each problem and mental disorders were measured with the Composite International Diagnostic Interview Screening Scales. Associations were examined with Poisson regression models as relative risks (RR) of the disorders as a function of the psychological problems. The population attributable fraction (PAF) indicates by what percentage the prevalence of the mental disorder would be reduced if the psychological problem was addressed successfully by an intervention. Especially generalized anxiety disorder was strongly associated with psychological problems (strong associations with stress and low self-esteem and moderately with test anxiety). The group with three or more psychological problems had a strongly increased risk for generalized anxiety (RR = 11.25; 95% CI: 7.51-16.85), and a moderately increase risk for major depression (RR = 3.22; 95% CI: 2.63-3.95), panic disorder (RR = 3.19; 95% CI: 1.96-5.20) and bipolar disorder (RR = 3.66; 95% CI: 2.40-5.58). The PAFs for having any of the psychological problems (one or more) were considerable, especially for generalized anxiety (60.8%), but also for panic disorder (35.1%), bipolar disorder (30.6%) and major depression (34.0%). We conclude that common psychological problems are associated with mental disorders and with each other. After adjustment, psychological problems are associated with different patterns of mental disorders. If the impact of the psychological problems could be taken away, the prevalence of several mental disorders would be reduced considerably. The psychological problems may provide a promising target to indirectly prevent and intervene in psychopathology in hard to reach college students with mental disorders. Show less
Pesce, L.; Veen, T. van; Carlier, I.; Noorden, M.S. van; Wee, N.J.A. van der; Hemert, A.M. van; Giltay, E.J. 2016
