Classification and prediction of suicide attempts in high-risk groups is important for preventing suicide. The purpose of this study was to investigate whether the information from multiple clinical scales has classification power for identifying actual suicide attempts. Patients with depression and anxiety disorders (N = 573) were included, and each participant completed 31 self-report psychiatric scales and questionnaires about their history of suicide attempts. We then trained an artificial neural network classifier with 41 variables (31 psychiatric scales and 10 sociodemographic elements) and ranked the contribution of each variable for the classification of suicide attempts. To evaluate the clinical applicability of our model, we measured classification performance with top-ranked predictors. Our model had an overall accuracy of 93.7% in 1-month, 90.8% in 1-year, and 87.4% in lifetime suicide attempts detection. The area under the receiver operating characteristic curve (AUROC) was the highest for 1-month suicide attempts detection (0.93), followed by lifetime (0.89), and 1-year detection (0.87). Among all variables, the Emotion Regulation Questionnaire had the highest contribution, and the positive and negative characteristics of the scales similarly contributed to classification performance. Performance on suicide attempts classification was largely maintained when we only used the top five ranked variables for training (AUROC; 1-month, 0.75, 1-year, 0.85, lifetime suicide attempts detection, 0.87). Our findings indicate that information from self-report clinical scales can be useful for the classification of suicide attempts. Based on the reliable performance of the top five predictors alone, this machine learning approach could help clinicians identify high-risk patients in clinical settings.
Objective Individual differences in attachment insecurity are important in a broad range of mental health problems. However, few empirical studies have examined the clinical factors that contribute to individual differences in attachment style. This study examines the nature of interrelationships among adult attachment styles, sensitivities of behavioral activation system/behavioral inhibition system (BIS/BAS), and childhood trauma in patients with depressive disorders.Methods Patients with depressive disorders (n=294) completed self-report questionnaires evaluating adult attachment style, childhood trauma, and BIS/BAS sensitivity. We performed multiple regression analyses to examine the associations between attachment style and other clinical factors, including childhood trauma and BIS/BAS sensitivity. We also conducted hierarchical regression analyses and simple slope analyses to examine the interaction between BIS/BAS sensitivity and childhood trauma.Results The BAS sensitivity was negatively associated with attachment avoidance. The higher was the BIS/BAS sensitivity, the higher was the level of attachment anxiety. Among childhood trauma, emotional neglect contributed to both dimensions of insecure attachment. The interaction between BAS sensitivity and emotional neglect is significantly associated with attachment anxiety.Conclusion This study used data regarding the interrelationship of childhood trauma and basic motivational systems to contribute to the understanding of adult insecure attachment behaviors, a risk factor for depression.
Objective The present study aimed to explore how the patterns of interaction between stress and positive resources differ according to the severity of depression and which resources play the most important role among the various positive resources.Methods The study included 1,806 people who had visited a health screening center for a mental health check-up to evaluate the levels of perceived stress, positive resources, and depressive symptoms. The participants were divided into a depressive group (n=1,642, mean age 50.60, female 68%) and a non-depressive group (n=164, mean age 48.42, female 66.6%). We conducted hierarchical regression analyses and simple slope analyses to examine the interaction between perceived stress and positive resources.Results The interaction between perceived stress and optimism was significantly associated with depression in non-depressive groups. In depressive groups, the interactions between five types of positive resources (optimism, purpose in life, self-control, social support and care) and perceived stress were all significantly related to depression.Conclusion Interventions that promote optimism can be helpful for preventing inevitable stress from leading to depression. A deficiency in positive resources may be a factor in aggravating depression in stressful situations for people reporting moderate to severe depressive symptoms.
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