Mental Disorders and Socioeconomic Status: Impact on Population Risk of Attempted Suicide in Australia

The population attributable risk (PAR) of mental disorders compared to indicators of socioeconomic status (SES) for attempted suicide was estimated for Australia. For mental disorders, the highest PAR% for attempted suicide was for anxiety disorders (males 28%; females 36%). For SES, the highest PAR% for attempted suicide in males was for occupation (males 31%; females 16%) and education level (males 19%; females 8%), following adjustment for age and mental disorders. The study results suggest that one third of suicide attempts in both males and females are attributable to anxiety disorders, the same proportion attributable to low educational or occupational status.     

Suicide and Its Association with Individual,Family, Peer,and School Factors in an Adolescent Population in Southern Taiwan

A representative sample of 10,233 adolescent students was recruited to examine the rate of suicidal attempt and its correlates in the adolescents living in southern Taiwan. Five questions from the Kiddie Schedule for Affective Disorders and Schizophrenia (Kiddie‐SADS‐E) were used to inquire about the participants' suicidality. The associations between suicidal attempt and multidimensional factors were examined by using logistic regression analysis: 9.1% of the participants reported a suicidal attempt in the preceding year. Female gender, low self‐esteem, weekly alcohol use, illicit drugs use, depression, high family conflict, low maternal education level, poor family function, low connectedness to school, low rank, poor feeling in peer group, and drop out from school were associated with adolescent suicidal attempt. The rate of suicidal attempt was found to be high in Taiwanese adolescents, and multidimensional factors were correlated to adolescent suicidal attempt.     

Short-term clinical risk assessment and management: Comparing the Brockville Risk Checklist and Hamilton Anatomy of Risk Management

The current article aims to examine the performance of two brief, dynamic risk measures – the Brockville Risk Checklist (BRC4) and one of two versions of the Hamilton Anatomy of Risk Management [HARM-FV and electronic HARM-FV (eHARM-FV)] – scored at regular clinical case conferences for forensic psychiatric patients in two different settings. The eHARM represents a first-in-class dynamic risk assessment tool using data analytics. Two studies are presented from two forensic psychiatric hospitals in Ontario, Canada. The first study compared the HARM-FV, scored by trained research staff, with the BRC4, scored concurrently by clinical teams, on 36 forensic inpatients. In the second study, trained research staff scored both the BRC4 and the eHARM-FV on 55 forensic inpatients. Both studies demonstrated that the BRC4 and both HARM-FV tools were moderately and positively correlated with each other, with higher agreement for similar domains and items. In both samples, the risk measures performed better at identifying individuals who engaged in repeated or more serious problematic behavior. The HARM-FV and eHARM-FV produced higher area under the curve values for subsequent behavior compared with the BRC4. All three tools were effective at detecting future aggression and adverse incidents. We did not directly compare the HARM-FV and eHARM-FV.     

Empirical Support for an Evolutionary Model of Self‐Destructive Motivation

We tested predictions generated from an evolutionary account of self‐destructive motivation in two survey studies of 18–24‐year‐old university students. As hypothesized, hierarchical regressions showed that the positive relationship between perceived burden to family and suicide ideation was amplified for participants with low measured health and romantic relationship satisfaction, and for participants with relatively young mothers. The moderating effect of maternal age was also observed in logistic regressions of suicide attempts. These effects occurred independently of depression, hopelessness, and other relevant extraneous variables. Results have implications for understanding self‐destructive motivation, assessing suicide risk, and preventing suicidal thinking and behavior.