Year: 2022 Source: Crisis. (2021). 42(6): 405-410. SIEC No: 20220433

What makes people suicidal? Unfortunately, despite a century of suicide research and theorizing, the field of suicidology has yet to provide a sufficient answer to this foundational question. We have managed to identify a multitude of empirically and theoretically derived risk factors – spanning everything from social forces at the societal level (e.g., Durkheim, 1897/1951) to biological mechanisms at the microscopic level (e.g., Mann, 2013; Pedersen et al., 2012), and everywhere in between (see Turecki et al., 2019) – but “there is no evidence that any known risk factors – broad or specific – approach what many might define as clinical significance” (Franklin et al., 2016, p. 215). The inability of single or small sets of risk factors to adequately predict suicide risk has reinforced the highly complex nature of suicidal thoughts and behaviors (STBs) and prompted the use of machine-learning methods, which are better suited to model the types of complex dynamics that may be necessary to predict risk (Franklin et al., 2016; Ribeiro et al., 2016).