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In the last decade, suicidality has been increasingly theorized as a distinct phenomenon from major depressive disorder (MDD), with unique psychological and neural mechanisms, rather than being mostly a severe symptom of MDD. Although decision-making biases have been widely reported in suicide attempters with MDD, little is known regarding what components of these biases can be distinguished from depressiveness itself.Ninety-three patients with current MDD (40 with suicide attempts [SA group] and 53 without suicide attempts [NS group]) and 65 healthy controls (HCs) completed psychometric assessments and the balloon analog risk task (BART). To analyze and compare decision-making components among the three groups, we applied a five-parameter Bayesian computational modeling.Psychological assessments showed that the SA group had greater suicidal ideation and psychological pain avoidance than the NS group. Computational modeling showed that both MDD groups had higher risk preference and lower ability to learn and adapt from within-task observations than HCs, without differences between the SA and NS patient groups. The SA group also had higher loss aversion than the NS and HC groups, which had similar loss aversion.Our BART and computational modeling findings suggest that psychological pain avoidance and loss aversion may be important suicide risk factor that are distinguishable from depression illness itself.

Background Patients with major depressive disorder (MDD) exhibit a diminished ability to think or concentrate, indecisiveness, and altered sensitivity to reward and punishment. These impairments can influence complex risk-related decision-making in dynamic environments. The neurophysiological mechanisms mediating MDD effects on decision-making behavior are not well understood. Methods Patients with MDD (N=50) and healthy controls (HC, N=40) were enrolled. They completed a series of psychometric tests. Event-related potentials (ERPs) were recorded during the performance of a well-validated modified version of Balloon Analogue Risk Task (BART). Results BART behavior data were similar across the two groups except the MDD patients showed more stability of risk aversion. Neurophysiologically, BART losses generated larger P3 amplitudes than wins, and MDD patients had larger feedback-related negativity (FRN) components than HCs in response to negative feedback (losses). Greater FRN amplitudes in response to losses correlated with higher levels of depressiveness, psychological pain, and anhedonia. A longer FRN latency in MDD patients was associated with more severe suicidal ideation. Limitations The findings are based on cross-sectional data, which are not powerful enough to make causal inferences. Conclusion MDD patients exhibit enhanced FRNs in the frontocentral region after receiving negative feedback in a risky decision-making task. FRN magnitude is associated with depressive symptom severity. Punishment hypersensitivity may contribute to the maintenance of depressive symptoms in MDD patients, and FRN may be a useful index of such hypersensitivity.

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.

Background A motivation dimension of the core psychiatric symptom anhedonia additional has been suggested. The Temporal Experience of Pleasure Scale (TEPS) has been reported to assess anticipatory and consummatory pleasure separately in multiple factor-structure models. This study explored the factor structure of a Chinese version of the 18-item TEPS and further explored the measurement invariance of the TEPS across sex and clinical status (non-clinical, psychiatric). Methods Best-fit factor structure of the TEPS was examined in a non-clinical cohort of 7410 undergraduates, randomized into sample 1 (N = 3755) for exploratory factor analysis (EFA) and sample 2 (N = 3663) for confirmatory factor analysis (CFA). Additionally, serial CFA was conducted to evaluate measurement invariance across sex and between clinical (N = 313) and non-clinical (N = 341) samples. Results EFA supported a new four-factor structure with a motivation component, based on the original two-factor model (consummatory pleasure with/without motivation drive, anticipatory pleasure with/without motivation drive). CFA confirmed the four-factor model as the best-fit structure and revealed a second-order hierarchy in non-clinical and clinical samples. Full scalar invariance was observed across clinical and non-clinical samples and across sex in the clinical sample; only partial scalar invariance was observed across sex in the non-clinical sample. Conclusions A four-factor structured TEPS can assess motivation-driving dimensions of anticipatory and consummatory pleasure, consistent with the recently advanced multidimensional structure of anhedonia. CFA and measurement invariance results support application of the TEPS for assessing motivation aspects of anhedonia.

It is unclear whether the altered decision-making (DM) observed in patients with major depressive disorder (MDD) is neurophysiological and whether it improves with remission of depressive symptoms. The aim of this study was to identify developmental patterns of DM behavior, related cognitive characteristics, and electrophysiological abnormalities in patients with MDD across clinical stages.A sample of 48 first-episode MDD patients (FD group), 41 remitted MDD patients (RD group), and 43 healthy controls (HCs) completed psychometric assessments and performed the balloon analogue risk task (BART) while event-related potentials (ERPs) were recorded.The RD group had lower depressiveness, self-blame, rumination, and catastrophizing tendencies, and higher mental resilience scores than the FD group, but retained significant differences from HCs. MDD patients showed a more conservative DM strategy than HCs, with no significant difference between the FD and RD groups. Compared to the FD group, the RD group had a smaller FRN for negative feedback and a trend toward a smaller P3 for positive feedback. Compared with HCs, the RD group had a smaller P3 during the positive feedback phase. FRN amplitude correlated positively with depression level and negatively with mental resilience.Because a comparative cross-section design was employed, longitudinal studies are needed to make causal inferences.MDD patients presented a stable risk-avoidance bias in actively depressed and remission periods, consistent with a state-independent impairment pattern. Significantly reduced FRN amplitudes during remission indicated a state-dependent impairment pattern, and FRN amplitudes correlated with depression level. An abnormal feedback P3 component may be a state-independent characteristic that may become more pronounced with MDD progression.

Background The Personality Inventory for DSM-5 Brief Form (PID-5-BF) is a 25-item measuring tool evaluating maladaptive personality traits for the diagnosis of personality disorders(PDs). As a promising scale, its impressive psychometric properties have been verified in some countries, however, there have been no studies about the utility of the PID-5-BF in Chinese settings. The current study aimed to explore the maladaptive personality factor model which was culturally adapted to China and to examine psychometric properties of the PID-5-BF among Chinese undergraduate students and clinical patients. Methods Seven thousand one hundred fifty-five undergraduate students and 451 clinical patients completed the Chinese version of the PID-5-BF. Two hundered twenty-eight students were chosen randomly for test-retest reliability at a 4-week interval. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to discover the most suitable factor structure in China, measurement invariance(MI), internal consistency, and external validity were also calculated. Results The theoretical five-factor model was acceptable, but the exploratory six-factor model was more applicable in both samples (Undergraduate sample: CFI = 0.905, TLI = 0.888, RMSEA = 0.044, SRMR = 0.039; Clinical sample: CFI = 0.904, TLI = 0.886, RMSEA = 0.047, SRMR = 0.060). In the Chinese six-factor model, the Negative Affect domain was divided into two factors and the new factor was named “Interpersonal Relationships”, which was in line with the Big-Six Personality model in Chinese. Measurement invariance across non-clinical and clinical sample was established (configural, weak, strong MI, and partial strict MI). Aside from acceptable internal consistency (Undergraduate sample: alpha = 0.84, MIC = 0.21; Clinical sample: alpha = 0.86, MIC = 0.19) and test-retest reliability(0.73), the correlation between the 25-item PID-5-BF and the 220-item PID-5 was significant(p Conclusions Both the theoretical five-factor model and the exploratory six-factor model of the PID-5-BF were acceptable to the Chinese population. The five-factor model could allow for comparison and integration with other work on the original theoretical model. However, the Chinese six-factor structure may be more culturally informed in East Asian settings. In sum, the PID-5-BF is a convenient and useful screening tool for personality disorders.

Objective We explored the neural mechanisms underlying disadvantageous risk decision making in un-medicated major depressive disorder patients who had recent suicide attempts. Methods 53 patients with major depressive disorder (MDD), including 23 with a history of suicide attempts (SA) and 30 without (NS), and 30 healthy controls (HCs) completed pertinent psychometric assessments, and the dynamic decision making balloon analogue risk task (BART) under fMRI. We also built a 4-parameter Bayesian computational modeling for decision making analyses. Results Several distinct findings emerged. First, SA patients had no depression intensity difference but higher pain avoidance in psychometrics, and more risk aversion in the BART when compared to the NS patients, with computational modeling confirming such reduced risk-taking propensity. Second, SA patients showed smaller left insular cortex activation than NS patients during the high risk, decisional phase of BART, and the modulation correlated with pain avoidance in both SA and NS groups. Third, during feedback phase of loss trials of the BART, SA patients had greater activation in the left dorsolateral prefrontal cortex (dlPFC) than NS patients. Conclusion Taken together, we present novel findings and propose interpretations that the differential insula activation likely relates to high uncertainty-aversion in SA patients, contrary to the typical view that they are impulsive and risk prone. The differential left dlPFC activation likely suggests hypersensitivity to loss, contributing to conservative decision-making at large, and extreme choices such as suicide when value estimations are compromised and emotionally overwhelmed. The interactive interpretation places a renewed focus on psychological pain avoidance as a robust motivator for suicidal behavior.

Background Anhedonia is a core clinical symptom of mental disorders. The Revised Physical Anhedonia Scale (RPAS) and the Revised Social Anhedonia Scale (RSAS) have been applied in clinical and non-clinical samples since 1980s. However, the construct of a unified RPAS&RSAS for comprehensive measurement of anhedonia has never been explored. Therefore, the purpose of our study was to examine the factor structure of the unified RPAS&RSAS among undergraduates and clinical patients. Methods A total of 3435 undergraduates from two universities and 294 clinical patients with mental disorders had completed the Chinese version of the RPAS and the RSAS. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were each conducted to reveal the constructs of the RPAS and the RSAS. CFA was used to evaluate first- and second-order models for the unified RPAS&RSAS in undergraduates and clinical patients. The internal consistency and test-retest reliability of the RPAS and the RSAS were also evaluated. Results EFA and CFA indicated 2-factor structures for RPAS and RSAS, with the factors being defined as anticipatory anhedonia and consummatory anhedonia. The second-order model of the unified RPAS&RSAS in the undergraduates and clinical patients both had satisfactory fit index values (Undergraduate sample: CFI = 0.901, TLI = 0.899, RMSEA = 0.055, SRMR = 0.086; Clinical sample: CFI = 0.922, TLI = 0.911, RMSEA = 0.052, SRMR = 0.078). The psychometric robustness of the RPAS&RSAS were confirmed by high internal consistency and test-retest reliability values. Conclusions The unified RPAS&RSAS with a second-order structure was confirmed in both undergraduates and clinical samples in Chinese. The construct of anhedonia was refreshed as covering physical and social domains, and each of them includes both anticipatory and consummatory components.

Background Anhedonia, a key symptom of depression and schizophrenia, has emerged as a potential endophenotype. The aim of this study was to evaluate the psychometric properties of a Chinese version of the Snaith-Hamilton Pleasure Scale(SHAPS), a self-report anhedonia scale, in a non-clinical sample and clinical sample inclusive of major depressive disorder (MDD), schizophrenia, or a personality disorder. Methods A total of 4,722 undergraduate students and 352 clinical patients participated in this study. Internal consistency was assessed by calculating Cronbach's α and mean inter-item correlation (MIC) values. Test-retest reliability and convergent validity were assessed with Pearson r coefficients. The best fitting of six potential factor-structure models was determined by confirmatory factor analysis (CFA). Measurement invariance across genders and samples was determined by multi-group CFA. Results Internal consistency of the Chinese version of the SHAPS was acceptable in non-clinical (Cronbach's α = 0.90) and clinical (Cronbach's α = 0.91) samples. Four-week interval test-retest reliability was 0.60. Moreover, the Spanish four-factor structure had the best fit indexes in both samples. Scalar invariance was established across genders as well as across non-clinical sample and clinical sample. SHAPS was significantly related with the Temporal Experience of Pleasure Scale (TEPS) and Beck Depression Inventory (BDI). Limitations There was a restricted scope of convergent validity and the size of clinical sample is relatively small, psychometric properties in elderly sample is also required. Conclusion The Chinese version of the SHAPS is a reliable, effective, simple and convenient tool for assessing and screening for anhedonia.