Highlighting psychological pain avoidance and decision‐making bias as key predictors of suicide attempt in major depressive disorder—A novel investigative approach using machine learning

Abstract

Objective Predicting suicide is notoriously difficult and complex, but a serious public health issue. An innovative approach utilizing machine learning (ML) that incorporates features of psychological mechanisms and decision‐making characteristics related to suicidality could create an improved model for identifying suicide risk in patients with major depressive disorder (MDD). Method Forty‐four patients with MDD and past suicide attempts (MDD_SA, N = 44); 48 patients with MDD but without past suicide attempts (MDD_NS, N = 48–42 of whom with suicide ideation [MDD_SI, N = 42]), and healthy controls (HCs, N = 51) completed seven psychometric assessments including the Three‐dimensional Psychological Pain Scale (TDPPS), and one behavioral assessment, the Balloon Analogue Risk Task (BART). Descriptive statistics, group comparisons, logistic regressions, and ML were used to explore and compare the groups and generate predictors of suicidal acts. Results MDD_SA and MDD_NS differed in TDPPS total score, pain arousal and avoidance subscale scores, suicidal ideation scores, and relevant decision‐making indicators in BART. Logistic regression tests linked suicide attempts to psychological pain avoidance and a risk decision‐making indicator. The resultant key ML model distinguished MDD_SA/MDD_NS with 88.2% accuracy. The model could also distinguish MDD_SA/MDD_SI with 81.25% accuracy. The ML model using hopelessness could classify MDD_SI/HC with 94.4% accuracy. Conclusion ML analyses showed that motivation to avoid intolerable psychological pain, coupled with impaired decision‐making bias toward under‐valuing life's worth are highly predictive of suicide attempts. Analyses also demonstrated that suicidal ideation and attempts differed in potential mechanisms, as suicidal ideation was more related to hopelessness. ML algorithms show useful promises as a predictive instrument.

Risk factors for suicidal attempt in patients with the melancholic subtype of depressive disorder: Implication for nursing care

“…When they are depressive, they cannot get outside support well or cannot make effective use of support. [ 30 , 31 ] The results of previous studies [ 32 – 34 ] have shown that depression patients with low levels of social support increase the risk of suicide, which is more consistent with the results of this study. Therefore, for female patients with depression who live alone, attention should be paid to giving care and special attention.…”

Potential neuropsychological mechanism involved in the transition from suicide ideation to action – a resting-state fMRI study implicating the insula

“…Our study’s finding that the SA group had higher psychological pain avoidance than the HSI group is consistent with those reported by Li and colleagues [25, 49]. In terms of risk decision-making, our finding that the SA group had greater loss aversion than the HSI group is similar to those from Liu and colleagues using similar methodology [44], and others employing different decision tasks or models [26, 50]. Furthermore, the SA group showed a lower estimation of the probability of balloon explosion than the HSI group, which is consistent with the results of Liu et.…”

Decision‐making biases in suicide attempters with major depressive disorder: A computational modeling study using the balloon analog risk task (BART)

“…Finally, the Three-Dimensional Psychological Pain theory proposed by Li and colleagues, based on the Psychological Pain theory (Shneidman, 1993), separates psychological pain into three dimensions-painful feelings, pain arousal and pain avoidance, to measure the experience, cognitive and motivation aspects of psychological pain (Li et al, 2014). Related research has found that psychological painful feelings and pain arousal were both related to suicidal ideation, while psychological pain avoidance was related to suicidal behavior (Ji et al, 2021(Ji et al, , 2022.…”

“…Informed by these theories, a number of recent studies have focused on the process of suicide decision making, and found that after the generation of suicidal ideation, individuals often need to make repeated decisions on whether to carry out suicide (Bryan et al, 2020; Ji et al, 2021, 2022). The researchers and others have proposed that there are distinct MDD‐associated and suicidality‐associated decision‐making processes, such that there may exist unique decision biases associated with the ultimate production of suicidal behaviour, and constitute as risk factors for suicide (Ackerman et al, 2015; Gifuni et al, 2020; Perrain et al, 2021).…”