Predictive modeling of antidepressant efficacy based on cognitive neuropsychological theory.

BACKGROUND: We aimed to develop a clinical predictive model based on the cognitive neuropsychological (CNP) theory and machine-learning to examine SSRI efficacy in the treatment of MDD. METHODS: Baseline assessments including clinical symptoms (HAMD, HAMA, BDI, and TEPS scores), negative biases (NEO-PI-R-N and NCPBQ scores), sociodemographic characteristics (social support and SES), and a 5-min eye-opening resting-state EEG were completed by 69 participants with first-episode major depressive disorder (MDD) and 36 healthy controls. The clinical symptoms and negative bias were again assessed after an 8-week treatment of depression with selective serotonin reuptake inhibitors (SSRIs). A multi-modality machine-learning model was developed to predict the effectiveness of SSRI antidepressants. RESULTS: At baseline, we observed significant differences between MDD patients and healthy controls in terms of social support, clinical symptoms, and negative bias characteristics (p < 0.001). A negative association was found (p < 0.05) between neuroticism and alpha asymmetry in both the central and central-parietal areas, as well as between negative cognitive processing bias and alpha asymmetry in the parietal region. Compared to responders, non-responders exhibited less negative cognitive processing bias and greater alpha asymmetry in both central and central-parietal regions. Importantly, we developed a multi-modality machine-learning model with 83 % specificity using the above salient features. CONCLUSIONS: Research results support the CNP theory of depression treatment. To some extent, the multimodal clinical model constructed based on the CNP theory effectively predicted the efficacy of this treatment in this population. LIMITATIONS: Small sample and only focus on the mechanisms of delayed-onset SSRI treatment.

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

BACKGROUND: Understanding the neural mechanism underlying the transition from suicidal ideation to action is crucial but remains unclear. To explore this mechanism, we combined resting-state functional connectivity (rsFC) and computational modeling to investigate differences between those who attempted suicide(SA) and those who hold only high levels of suicidal ideation(HSI). METHODS: A total of 120 MDD patients were categorized into SA group (n=47) and HSI group (n=73). All participants completed a resting-state functional MRI scan, with three subregions of the insula and the dorsal anterior cingulate cortex (dACC) being chosen as the region of interest (ROI) in seed-to-voxel analyses. Additionally, 86 participants completed the balloon analogue risk task (BART), and a five-parameter Bayesian modeling of BART was estimated. RESULTS: In the SA group, the FC between the ventral anterior insula (vAI) and the superior/middle frontal gyrus (vAI-SFG, vAI-MFG), as well as the FC between posterior insula (pI) and MFG (pI-MFG), were lower than those in HSI group. The correlation analysis showed a negative correlation between the FC of vAI-SFG and psychological pain avoidance in SA group, whereas a positive correlation in HSI group. Furthermore, the FC of vAI-MFG displayed a negative correlation with loss aversion in SA group, while a positive correlation was found with psychological pain avoidance in HSI group. CONCLUSION: In current study, two distinct neural mechanisms were identified in the insula which involving in the progression from suicidal ideation to action. Dysfunction in vAI FCs may gradually stabilize as individuals experience heightened psychological pain, and a shift from positive to negative correlation patterns of vAI-MFC may indicate a transition from state to trait impairment. Additionally, the dysfunction in PI FC may lead to a lowered threshold for suicide by blunting the perception of physical harm.

Understanding guilt-related interpersonal dysfunction in obsessive-compulsive personality disorder through computational modeling of two social interaction tasks.

BACKGROUND: Obsessive-compulsive personality disorder (OCPD) is a high-prevalence personality disorder characterized by subtle but stable interpersonal dysfunction. There have been only limited studies addressing the behavioral patterns and cognitive features of OCPD in interpersonal contexts. The purpose of this study was to investigate how behaviors differ between OCPD individuals and healthy controls (HCs) in the context of guilt-related interpersonal responses. METHOD: A total of 113 participants were recruited, including 46 who were identified as having OCPD and 67 HCs. Guilt-related interpersonal responses were manipulated and measured with two social interactive tasks: the Guilt Aversion Task, to assess how anticipatory guilt motivates cooperation; and the Guilt Compensation Task, to assess how experienced guilt induces compensation behaviors. The guilt aversion model and Fehr-Schmidt inequity aversion model were adopted to analyze decision-making in the Guilt Aversion Task and the Guilt Compensation Task, respectively. RESULTS: Computational model-based results demonstrated that, compared with HCs, the OCPD group exhibited less guilt aversion when making cooperative decisions as well as less guilt-induced compensation after harming others. CONCLUSION: Our findings indicate that individuals with OCPD tend to be less affected by guilt than HCs. These impairments in guilt-related responses may prevent adjustments in behaviors toward compliance with social norms and thus result in interpersonal dysfunctions.

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

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

State-independent and -dependent behavioral and neuroelectrophysiological characteristics during dynamic decision-making in patients with current and remitted depression.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. LIMITATIONS: Because a comparative cross-section design was employed, longitudinal studies are needed to make causal inferences. CONCLUSION: 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.

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.

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.

Hypersensitivity to negative feedback during dynamic risky-decision making in major depressive disorder: An event-related potential study.

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.

Factor structure and sex invariance of the temporal experience of pleasure scale (TEPS) in Chinese university students and clinical population.

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.

Psychometric Properties of the Chinese Version of the 10-Item Ruminative Response Scale Among Undergraduates and Depressive Patients.

Objective: Rumination is considered as a key process in the mechanism of depression. Assessing rumination is important for both research and clinical practice. The Ruminative Response Scale (RRS) is a widely-used instrument to measure rumination. This study aimed to examine the psychometric properties of the Chinese 10-item Ruminative Response Scale (RRS-10) in a large sample of Chinese undergraduates and depressive patients. Methods: A total of 1,773 university students and 286 clinical patients with major depressive disorder finished the Chinese version of the RRS10, State Trait Anxiety Inventory (STAI), and Beck Depression Inventory (BDI). A confirmatory factor analysis (CFA) was performed to examine the two-factor structure (reflection and brooding) of the RRS-10. The correlations among RRS-10, STAI, and BDI were explored in two samples. In addition, the measurement invariance of the RRS-10 across gender, time, and groups with and without depressive symptoms were further investigated. The internal consistency and test-retest reliability were also evaluated. Results: Confirmatory Factor Analysis revealed that the two-factor structure of RRS-10 fitted reasonably both in undergraduates (CFI = 0.933, TLI = 0.905, RMSEA = 0.071, SRMR = 0.035) and depressive patients (CFI = 0.941, TLI = 0.910, RMSEA = 0.077, SRMR = 0.057). The results of the multi-group confirmatory factor analysis supported the full strict invariance across genders and across groups (undergraduates and depressive patients). The full strong invariance over time was also supported by MGCFA. Besides, the RRS-10 showed acceptable internal consistency and good stability. Conclusions: The RRS-10 has good reliability and validity in different samples and over time, which demonstrated that RRS-10 is a valid measurement instrument to assess rumination.

From motivation, decision-making to action: An fMRI study on suicidal behavior in patients with major depressive disorder.

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.

Personality Inventory for DSM-5 in China: Evaluation of DSM-5 and ICD-11 Trait Structure and Continuity With Personality Disorder Types.

The Personality Inventory for the DSM-5 (PID-5) is an established tool for assessing personality disorder (PD) traits that was developed based on section III of the DSM-5. It is composed of 220 items, organized into 25 facets, which are distributed among five domains. The psychometric properties of the Chinese version of the PID-5 remain to be demonstrated. Two samples were embodied in this study that included 3,550 undergraduates and 406 clinical patients. To probe the structure of the PID-5, parallel analyses were conducted to explore the unidimensionality of its 25 facets and a series of confirmatory factor analyses (CFAs) were carried out to confirm the 25 lower-order facets and their distribution among five higher-order domains. Then, the PID-5 was employed to measure the DSM-5 and ICD-11 trait models and to explore the relationship of DSM-IV categorical PDs with DSM-5 and ICD-11 personality traits. Correlation and regression analyses were conducted to probe how well DSM-IV categorical PDs correspond with maladaptive personality traits specified in the DSM-5 and five ICD-11 domains. The respective average internal reliability coefficients of the 25 facets obtained for undergraduate and clinical patient samples were 0.76 and 0.81, those obtained for the five DSM-5 domains were 0.89 and 0.91, and those obtained for the five ICD-11 domains were 0.87 and 0.89. Serial CFAs confirmed the rationality of the PID-5's lower-order 25-facet structure and higher-order five-domain structure in both samples. Correlation and regression analyses showed that DSM-5 specified traits explain the variance in PD presentation with a manifold stronger correlation (R 2 = 0.24-0.44) than non-specified traits (R 2 = 0.04-0.12). Overall, the PID-5 was shown to be a reliable, stable, and structurally valid assessment tool that captures pathological personality traits related to DSM-5 and ICD-11 PDs.

Personality inventory for DSM-5 brief form(PID-5-BF) in Chinese students and patients: evaluating the five-factor model and a culturally informed six-factor model.

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 < 0.01). The six PDs measured by Personality diagnostic questionnaire-4+ (PDQ-4+) were associated with and predicted by expected domains of PID-5-BF. 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.

Factor Structure and Measurement Invariance of the Chinese version of the Snaith-Hamilton Pleasure Scale (SHAPS) in Non-clinical and Clinical populations.

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.

A novel construct of anhedonia revealed in a Chinese sample via the Revised Physical and Social Anhedonia Scales.

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.