Harms of massage in persons with cancer or receiving treatment for cancer: A systematic review and meta-analysis.

University students worldwide are widely exposed to the risk of suicidal thoughts and behaviors (STB), including suicide death, suicidal ideation, and suicide attempts [, ]. The prevalence rates among university students are higher than those observed in the general adult population [, ]. Macalli et al., [], who analyzed data from 19 universities across eight countries, reported a 17.2% prevalence of suicidal ideation among university students. Furthermore, compared with North American students, Asian university students exhibit higher prevalence rates of STB []. Given that the suicide risk among college students reflects the interplay of multidimensional factors—psychological, interpersonal, and behavioral []—the development of suicide-related theories to explain individual causes of suicide, the construction of measurement tools and models to predict or diagnose individuals at high risk, and the identification of critical predictors have long been central concerns for psychologists and researchers. Recent integrative suicide-related theories have been proposed to systematically explain the stages and causes by which individuals develop STB. Three important multistage suicide theoretical models include the interpersonal–psychological theory of suicide (IPT; [, ]), the integrated motivational–volitional theory of suicide (IMV; []), and the three-step theory of suicide (3ST; [, ]). IPT posits that the interaction of thwarted belongingness, perceived burdensomeness, and acquired capability for suicide results in maximal suicide risk [, ]. IMV posits that the progression from suicidal ideation to suicidal behavior unfolds across three stages: (1) the premotivational phase, which involves any negative life event experienced by the individual; (2) the motivational phase, emphasizing the role of (e.g., autobiographical memory biases and rumination) and (e.g., thwarted belongingness and social support); and (3) the volitional phase, where volitional moderators determine the risk conditions for transitioning from suicidal intent to suicidal behavior [, ]. The 3ST explains the development of high suicide risk in stages on the basis of the individual’s experience of pain and hopelessness, connectedness to others, and ability to attempt suicide. Suicide-related theories focus on explanatory models for individuals’ STB, providing a foundation for and promoting the development of empirical research []. Conducted a meta-analysis of 365 suicide-related studies published between 1965 and 2015 and revealed that previous research focused primarily on risk factors for STB, such as externalizing psychopathology, normative personality traits, physical illness, treatment history, prior self-injurious thoughts or behaviors, and exposure to self-injurious thoughts and behaviors. The meta-analysis also revealed that earlier studies were limited by traditional statistical methods, which failed to adequately characterize the complex relationships between risk factors and STB, leading to poor predictive accuracy. Franklin et al. (2016) further emphasized the advantages of machine learning (ML) in (1) identifying optimal algorithms, (2) managing complex relationships among predictive variables, and (3) improving model generalizability, recommending that future research utilize ML to develop algorithms for STB.