A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial

Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological markers related to suicide, computer science provides opportunities to understand suicide thought markers. In this novel prospective, multimodal, multicenter, mixed demographic study, we used machine learning to measure and fuse two classes of suicidal thought markers: verbal and nonverbal. Machine learning algorithms were used with the subjects’ words and vocal characteristics to classify 379 subjects recruited from two academic medical centers and a rural community hospital into one of three groups: suicidal, mentally ill but not suicidal, or controls. By combining linguistic and acoustic characteristics, subjects could be classified into one of the three groups with up to 85% accuracy. The results provide insight into how advanced technology can be used for suicide assessment and prevention.     

10 Suicidality Among Acculturating Mexican Americans: Current Knowledge and Directions for Research

Despite the dramatic increase in Mexican-American immigration over the past two decades, the acculturative experience and its relationship to suicide risk have received little attention within the field of suicidology. This paper summarizes findings from community-based studies that have explored suicide and risk factors among immigrant and Mexican-American groups, and suggests directions for future research. Most of these studies have been epidemiologic, and relatively few have addressed risk and protective factors within well-defined acculturating groups. Further study of the full continuum of suicidal thoughts and behaviors that examines precise cultural risk factors, and uses methodologies that combine quantitative and qualitative data, may improve our understanding of suicide risk among acculturating Mexican Americans.     

Spiritual health locus of control and breast cancer beliefs among urban African American women.

The present study examined the relationship between spiritual health locus of control, breast cancer beliefs, and mammography utilization among a sample of 1,227 African American women from urban public health centers. Spiritual health locus of control was conceptualized as having an active and passive dimension, empowering individuals in their health beliefs and behaviors or rendering them to rely on a higher power (e.g., God) to determine their health outcomes, respectively. The active dimension was negatively associated with perceived benefits of mammography and positively associated with perceived barriers to mammography. The active and passive spiritual dimensions are distinct from internal and external health locus of control. Further study of their associations with other health-related beliefs and behaviors is warranted.     

Self‐Efficacy to Avoid Suicidal Action: Factor Structure and Convergent Validity among Adults in Substance Use Disorder Treatment

Individuals with substance use disorders (SUDs) are at high risk of suicidal behaviors, highlighting the need for an improved understanding of potentially influential factors. One such domain is self‐efficacy to manage suicidal thoughts and impulses. Psychometric data about the Self‐Efficacy to Avoid Suicidal Action (SEASA) Scale within a sample of adults seeking SUD treatment (N = 464) is provided. Exploratory factor analysis supported a single self‐efficacy construct. Lower SEASA scores, or lower self‐efficacy, were reported in those with more severe suicidal ideation and those with more suicide attempts, providing evidence for convergent validity. Implications of measuring self‐efficacy in the context of suicide risk assessment are discussed.