Association between childhood trauma and Internet gaming disorder: a moderated mediation analysis with depression as a mediator and psychological resilience as a moderator.

BACKGROUND: The effect of childhood trauma on Internet gaming disorder remains unclear. In this study, we examined this association in Chinese students and explored the possible associated roles of psychological resilience and depression. METHODS: In total, 8,579 students from Hunan Province, China, provided information regarding their sociodemographic factors, history of childhood trauma, any symptoms of depression, psychological resilience, and characteristics of Internet gaming disorder for this cross-sectional study. The impact of childhood trauma on Internet gaming disorder, as well as the extent to which it was mediated by depression and moderated by psychological resilience was evaluated. RESULTS: The influence of childhood trauma on Internet gaming disorder was partially mediated by depression (B = 0.07, 95% CI [0.04, 0.05], p < 0.001), with psychological resilience acting as a mitigating factor (B = -0.002, 95% CI [13.74, 21.72], p < 0.001). Psychological resilience also moderated the association between childhood trauma and depression (B = - 0.003, 95% CI [22.17, 28.10], p < 0.001). Our moderated mediation model elucidated psychosocial mechanisms, revealing the underlying link between childhood trauma and Internet gaming disorder. It also demonstrated the partial mediating role of depression and modulating role of psychological resilience among Chinese students. CONCLUSIONS: Education and interventions, along with effective social support, should be provided to enhance students' psychological resilience and prevent childhood trauma and depression.

Compensatory thickening of cortical thickness in early stage of schizophrenia.

Brain structural abnormality has been observed in the prodromal and early stages of schizophrenia, but the mechanism behind it is not clear. In this study, to explore the association between cortical abnormalities, metabolite levels, inflammation levels and clinical symptoms of schizophrenia, 51 drug-naive first-episode schizophrenia (FES) patients, 51 ultra-high risk for psychosis (UHR), and 51 healthy controls (HC) were recruited. We estimated gray matter volume (GMV), cortical thickness (CT), concentrations of different metabolites, and inflammatory marks among four groups (UHR converted to psychosis [UHR-C], UHR unconverted to psychosis [UHR-NC], FES, HC). UHR-C group had more CT in the right lateral occipital cortex and the right medial orbito-frontal cortex (rMOF), while a significant reduction in CT of the right fusiform cortex was observed in FES group. UHR-C group had significantly higher concentration of IL-6, while IL-17 could significantly predict CT of the right fusiform and IL-4 and IL-17 were significant predictors of CT in the rMOF. To conclude, it is reasonable to speculate that the increased CT in UHR-C group is related to the inflammatory response, and may participate in some compensatory mechanism, but might become exhaustive with the progress of the disease due to potential neurotoxic effects.

Impairment of olfactory identification ability in ultra-high risk for psychosis and drug-naïve first episode psychosis.

OBJECTIVE: Patients with psychotic diseases have been reported to exhibit abnormalities in their olfactory discrimination. These alterations have also been identified in people at high genetic or clinical risk for psychosis, suggesting olfactory discrimination dysfunction may be a potential risk factor for developing psychosis. Thus, the purpose of our study is to explore the difference in olfactory discrimination ability in the prosal stage and early stage of psychosis and to explore the potential risk factor of developed psychosis. METHODS: We compared olfactory identification and cognitive function in 89 ultra-high-risk (UHR) individuals, 103 individuals with Drug-naïve first-episode schizophrenia (FES), 81 genetic high-risk (GHR) individuals, and 97 healthy controls (HC). Additionally, we compared olfactory identification and cognitive function between two groups; UHR individuals who later transitioned to psychosis (UHR-T; n = 33) and those who did not transition (UHR-NT; n = 42)). Furthermore, we analyzed the correlations between olfactory discrimination ability and cognitive function and symptoms and compared the olfactory function between men and women. RESULTS: Patients with first-episode schizophrenia (FES) and those at ultra-high risk (UHR) for psychosis exhibited more significant deficits in olfactory identification than healthy controls (HC), while no differences in olfactory identification dysfunction were observed between the genetic high risk (GHR) and HC groups. Notably, individuals in the UHR group who later developed psyhchosis displayed a steeper marked decline in their baseline olfactory identification ability than that of those in the UHR group who did not develop psychosis. Cognitive dysfunction is widely observed in both the FES and UHR groups, with a distinct correlation identified between olfactory discrimination function and cognitive performance. Finally, overall, women exhibit significantly superior olfactory function than men. CONCLUSION: In conclusion, these findings suggest that impairment of olfactory identification exists in the early stage of psychosis. Olfactory identification dysfunction may therefore be a potential marker of predicting the transition to schizophrenia.

Glutamatergic basis of antipsychotic response in first-episode psychosis: a dual voxel study of the anterior cingulate cortex.

A subgroup of patients with schizophrenia is believed to have aberrant excess of glutamate in the frontal cortex; this subgroup is thought to show poor response to first-line antipsychotic treatments that focus on dopamine blockade. If we can identify this subgroup early in the course of illness, we can reduce the repeated use of first-line antipsychotics and potentially stratify first-episode patients to intervene early with second-line treatments such as clozapine. The use of proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate and Glx (glutamate plus glutamine) may provide a means for such a stratification. We must first establish if there is robust evidence linking elevations in anterior cingulate cortex (ACC) glutamate metabolites to poor response, and determine if the use of antipsychotics worsens the glutamatergic excess in eventual nonresponders. In this study, we estimated glutamate levels at baseline in 42 drug-naive patients with schizophrenia. We then treated them all with risperidone at a standard dose range of 2-6 mg/day and followed them up for 3 months to categorize their response status. We expected to see baseline "hyperglutamatergia" in nonresponders, and expected this to worsen over time at the follow-up. In line with our predictions, nonresponders had higher glutamate than responders, but patients as a group did not differ in glutamate and Glx from the healthy control (HC) group before treatment-onset (F1,79 = 3.20, p = 0.046, partial η2 = 0.075). Glutamatergic metabolites did not change significantly over time in both nonresponders and responders over the 3 months of antipsychotic exposure (F1,31 = 1.26, p = 0.270, partial η2 = 0.039). We conclude that the use of antipsychotics without prior knowledge of later response delays symptom relief in a subgroup of first-episode patients, but does not worsen the glutamatergic excess seen at the baseline. Given the current practice of nonstratified use of antipsychotics, longer-time follow-up MRS studies are required to see if improvement in symptoms accompanies a dynamic shift in glutamate profile.

The month of walking alone and BDNF level differ between drug-naive first-episode schizophrenia patients and healthy controls.

Introduction: Schizophrenia is a neurodevelopmental disorder, characterized by impairment in reasoning, affectivity, and social relationships. Previous studies have shown delayed motor development and Brain-Derived Neurotrophic Factor (BDNF) level change in individuals with schizophrenia. We researched the month of walking alone (MWA) and BDNF level between drug-naive first-episode schizophrenia patients (FEP) and healthy control (HC), as well as how they behave in neurocognitive function and severity of symptoms. Predictors of schizophrenia were further explored too. Methods: We researched the MWA and BDNF levels between FEP and HCs in the Second Xiangya Hospital of Central South University from August 2017 to January 2020, as well as how they behave in neurocognitive function and the severity of symptoms. A binary logistic regression analysis was used to examine the risk factors affecting the onset and treatment outcome of schizophrenia. Results: We find that FEP showed a walking delay and lower BDNF levels compared to HCs, which were associated with cognitive impairment and severity of symptoms. According to the difference and correlation analysis results, and combined with the appropriate application conditions for binary logistic regression, Wechsler Intelligence Scale Picture completion, Hopkins Verbal Learning Test-Revised, and Trail Making Test: part A were added to the binary logistic regression analysis to distinguish FEP and HCs. Conclusion: Our study has shown delayed motor development and changes in BDNF levels in schizophrenia, extending insight into the early identification of patients with schizophrenia versus healthy populations.

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.

Short-chain fatty acids in patients with schizophrenia and ultra-high risk population.

Background: Individuals who experience the prodromal phase of schizophrenia (SCZ), a common and complex psychiatric disorder, are referred to as ultra-high-risk (UHR) individuals. Short-chain fatty acid (SCFA) is imperative in the microbiota-gut-brain axis and brain function. Accumulating amount of evidence shows the connections between psychiatric disorders and SCFAs. This study aims to explore the underlying roles SCFAs play in SCZ by investigating the association of alterations in SCFAs concentrations with common cognitive functions in both the SCZ and UHR populations. Methods: The study recruited 59 SCZ patients (including 15 participants converted from the UHR group), 51 UHR participants, and 40 healthy controls (HC) within a complete follow-up of 2 years. Results of cognitive functions, which were assessed by utilizing HVLT-R and TMT, and serum concentrations of SCFAs were obtained for all participants and for UHR individuals at the time of their conversion to SCZ. Results: Fifteen UHR participants converted to SCZ within a 2-year follow-up. Valeric acid concentration levels were lower in both the baseline of UHR individuals whom later converted to SCZ (p = 0.046) and SCZ patients (p = 0.036) than the HC group. Additionally, there were lower concentrations of caproic acid in the baseline of UHR individuals whom later transitioned to SCZ (p = 0.019) and the UHR group (p = 0.016) than the HC group. Furthermore, the caproic acid levels in the UHR group are significantly positively correlated with immediate memory (r = 0.355, p = 0.011) and negatively correlated with TMT-B (r = -0.366, p = 0.009). Significant differences in levels of acetic acid, butyric acid and isovaleric acid were absent among the three groups and in UHR individuals before and after transition to SCZ. Conclusion: Our study suggests that alterations in concentrations of SCFAs may be associated with the pathogenesis and the cognitive impairment of schizophrenia. Further researches are warranted to explore this association. The clinical implications of our findings were discussed.

Alteration of a brain network with stable and strong functional connections in subjects with schizophrenia.

It is widely accepted that there are some common network patterns in the human brain. However, the existence of stable and strong functional connections in the human brain and whether they change in schizophrenia is still a question. By setting 1% connections with the smallest coefficient of variation, we found a widespread brain functional network (frame network) in healthy people(n = 380, two datasets from public databases). We then explored the alterations in a medicated group (60 subjects with schizophrenia vs 71 matched controls) and a drug-naive first-episode group (68 subjects with schizophrenia vs 45 matched controls). A linear support vector classifier (SVC) was constructed to distinguish patients and controls using the medicated patients' frame network. We found most frame connections of healthy people had high strength, which were symmetrical and connected the left and right hemispheres. Conversely, significant differences in frame connections were observed in both patient groups, which were positively correlated with negative symptoms (mainly language dysfunction). Additionally, patients' frame network were more left-lateralized, concentrating on the left frontal lobe, and was quite accurate at distinguishing medicated patients from controls (classifier accuracy was 78.63%, sensitivity was 86.67%, specificity was 76.06%, and the area under the curve (AUC) was 0.83). Furthermore, the results were repeated in the drug-naive set (accuracy was 84.96%, sensitivity was 85.29%, specificity was 88.89%, and AUC was 0.93). These findings indicate that the abnormal pattern of frame network in subjects with schizophrenia might provide new insights into the dysconnectivity in schizophrenia.

Abnormal Brain Network Interaction Associated With Positive Symptoms in Drug-Naive Patients With First-Episode Schizophrenia.

Positive symptoms are marked features of schizophrenia, and emerging evidence has suggested that abnormalities of the brain network underlying these symptoms may play a crucial role in the pathophysiology of the disease. We constructed two brain functional networks based on the positive and negative correlations between positive symptom scores and brain connectivity in drug-naive patients with first-episode schizophrenia (FES, n = 45) by using a machine-learning approach (connectome-based predictive modeling, CPM). The accuracy of the model was r = 0.47 (p = 0.002). The positively and negatively associated network strengths were then compared among FES subjects, individuals at genetic high risk (GHR, n = 41) for schizophrenia, and healthy controls (HCs, n = 48). The results indicated that the positively associated network contained more cross-subnetwork connections (96.02% of 176 edges), with a focus on the default-mode network (DMN)-salience network (SN) and the DMN-frontoparietal task control (FPT) network. The negatively associated network had fewer cross-subnetwork connections (71.79% of 117 edges) and focused on the sensory/somatomotor hand (SMH)-Cingulo opercular task control (COTC) network, the DMN, and the visual network with significantly decreased connectivity in the COTC-SMH network in FES (FES < GHR, p = 0.01; FES < HC, p = 0.01). Additionally, the connectivity strengths of the right supplementary motor area (SMA) (p < 0.001) and the right precentral gyrus (p < 0.0001) were reduced in FES. To the best of our knowledge, this is the first study to generate two brain networks associated with positive symptoms by utilizing CPM in FES. Abnormal segregation, interactions of brain subnetworks, and impaired SMA might lead to salience attribution abnormalities and, thus, as a result, induce positive symptoms in schizophrenia.

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.

IL-17 and TNF-ß: Predictive biomarkers for transition to psychosis in ultra-high risk individuals.

Background: Dysregulation of immunity, such as levels of inflammatory factors, has been regarded as a sign of schizophrenia. Changes in cytokine levels are not only described in the early onset of disease, but also observed in ultra-high risk (UHR) individuals. This study aimed to investigate the potential of cytokines as biomarkers for psychotic disorders and in individuals at UHR of developing a psychotic disorder in the future. Methods: The Luminex liquid chip technology was used to detect the concentrations of Interferon-gamma (INF-γ), Interleukin (IL)-2, Interleukin (IL)-4, Interleukin (IL)-6, Interleukin (IL)-17, Interleukin-1beta (IL-1ß), and Tumor Necrosis Factor-beta (TNF-ß) in the plasma of all subjects. Meanwhile, the plasma level of Tumor Necrosis Factor-Alpha (TNF-α) was measured with the enzyme-linked immunosorbent assay (ELISA) kits. Then, the levels of these cytokines were compared among patients with Drug-naïve first-episode schizophrenia (FES; n = 40), UHR population (UHR; n = 49), and healthy controls (HCs; n = 30). Baseline cytokine levels were compared among UHR individuals who later transitioned (UHR-T; n = 14), those who did not transition (UHR-NT; n = 35), and HCs (n = 30). Results: Our analysis results showed that IL-1ß levels were significantly higher in UHR group than HC group (p = 0.015). Meanwhile, TNF-α concentration was significantly increased in FES group compared with HC group (p = 0.027). IL-17 (p = 0.04) and TNF-ß (p = 0.008) levels were significantly higher in UHR-T group compared with UHR-NT group. Conclusion: In conclusion, our findings suggest that the immuno-inflammatory activation level is increased in the early stage of psychosis before psychotic conversion and the Drug-naïve FES. IL-1ß and TNF-α are the representatives of the specific biomarkers for UHR and FES, respectively. IL-17 and TNF-ß may be the potential selective predictive biomarkers for future transition in UHR individuals.

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.

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.