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Suicide is one of the most critical public health concerns in the world and the second cause of death among young people in many countries. However, to date, no study can diagnose suicide ideation/behavior among university students in the Middle East and North Africa (MENA) region using a machine learning approach. Therefore, stability feature selection and stacked ensembled decision trees were employed in this classification problem. A total of 573 university students responded to a battery of questionnaires. Three-fold cross-validation with a variety of performance indices was sued. The proposed diagnostic system had excellent balanced diagnosis accuracy (AUC = 0.90 [CI 95%: 0.86–0.93]) with a high correlation between predicted and observed class labels, fair discriminant power, and excellent class labeling agreement rate. Results showed that 23 items out of all items could accurately diagnose suicide ideation/behavior. These items were psychological problems and how to experience trauma, from the demographic variables, nine items from Post-Traumatic Stress Disorder Checklist (PCL-5), two items from Post Traumatic Growth (PTG), two items from the Patient Health Questionnaire (PHQ), six items from the Positive Mental Health (PMH) questionnaire, and one item related to social support. Such features could be used as a screening tool to identify young adults who are at risk of suicide ideation/behavior.

Suicidal ideation and behavior are common in those suffering from Posttraumatic Stress Disorder (PTSD). The present study investigated factors buffering the association between PTSD symptoms and suicidal ideation/behavior. A total of 571 Iranian students and 421 German students took part in the investigation. Social support and positive mental health (PMH) were considered as resilience factors moderating the association between PTSD symptoms and suicide ideation/behavior within both samples. PMH moderated the impact of PTSD symptoms on suicidal ideation/behavior in Iranian and German students. Social support moderated the impact of PTSD symptoms on suicidal ideation/behavior in Iranian students only. Positive mental health and perceived social support seem to confer resilience and should be taken into account, when assessing individuals for suicide risk.

Background Positive mental health (PMH) is a factor of far-reaching salutogenetic importance. The present study aimed at validating the Persian version of the Positive Mental Health Scale (PMH-Scale). Methods Reliability and validity of the Persian version of the PMH-Scale were established in an Iranian student sample (N = 573). Internal consistency, convergent and discriminant validity were investigated, and exploratory factor analysis was conducted. Furthermore, it was assessed how PMH scores moderate the association between depressive symptoms and suicide ideation/behavior. Results The Persian version of the PMH-Scale  was shown to have a unidimensional structure with excellent internal consistency, as well as good convergent and divergent validity. PMH differentiated between participants with higher vs. lower suicide risk. Furthermore, PMH proved to moderate the association between depressive symptoms and suicide ideation/behavior. Conclusions The results suggest that the PMH-Scale is a brief, reliable, and valid measure of subjective and psychological well-being that can be used in Iranian student samples and research settings.