Fig. 1: ROC analysis.
From: A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic
a ROC curves of FSQ-MIS total score and factor scores for discriminate patients and healthy controls. Total score for discrimination, AUC = 0.983 ± 0.002, p < 0.001, 95%CI [0.980, 0.986]. F1 for discrimination, AUC = 0.972 ± 0.002, p < 0.001, 95%CI [0.968, 0.977]. F2 for discrimination, AUC = 0.944 ± 0.004, p < 0.001, 95%CI [0.937, 0.952]. F3 for discrimination, AUC = 0.902 ± 0.004, p < 0.001, 95%CI [0.893, 0.911]. F4 for discrimination, AUC = 0.716 ± 0.007, p < 0.001, 95%CI [0.702, 0.731]. F5 for discrimination, AUC = 0.748 ± 0.008, p < 0.001, 95%CI [0.733, 0.763]. F6 for discrimination, AUC = 0.734 ± 0.008, p < 0.001, 95%CI [0.719, 0.750]. b ROC curves for measuring the performance of FSQ-MIS-Factors (F1, F3, F4, F5, F6) in identifying the mental disorders. F1 predicts anxiety and depression related diagnosis, AUC = 0.700 ± 0.010, p < 0.001, 95%CI [0.681, 0.720]; F3 predicts sleep disturbance related diagnosis, AUC = 0.791 ± 0.007, p < 0.001, 95%CI [0.777, 0.806]; F4 predicts psychosis related diagnosis, AUC = 0.820 ± 0.011, p < 0.001, 95%CI [0.799, 0.842]; F5 predicts obsessive-compulsive related diagnosis, AUC = 0.692 ± 0.012, p < 0.001, 95%CI [0.667, 0.716]; F6 predicts excitation symptom related diagnosis, AUC = 0.692 ± 0.013, p < 0.001, 95%CI [0.667, 0.717].
