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.
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 (R2 = 0.24–0.44) than non-specified traits (R2 = 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.
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.
BackgroundDysregulation 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.MethodsThe 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-1β), and Tumor Necrosis Factor-beta (TNF-β) 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).ResultsOur analysis results showed that IL-1β 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-β (p = 0.008) levels were significantly higher in UHR-T group compared with UHR-NT group.ConclusionIn 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-1β and TNF-α are the representatives of the specific biomarkers for UHR and FES, respectively. IL-17 and TNF-β may be the potential selective predictive biomarkers for future transition in UHR individuals.
BackgroundIndividuals 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.MethodsThe 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.ResultsFifteen 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.ConclusionOur 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.
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