The ADHD general factor explained most of the common variance. Given the low reliable variance ratios, the specific factors were difficult to interpret. However, in clinical samples, inattention acquired sufficient specificity and stability for interpretation beyond the general factor. Implications for research and clinical practice are discussed.

We tested first-order factor and bifactor models of attention-deficit/hyperactivity disorder (ADHD) using confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) to adequately summarize the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, (DSM-IV-TR) symptoms observed in a Spanish sample of preschoolers and kindergarteners. Six ESEM and CFA models were estimated based on teacher evaluations of the behavior of 638 children 4 to 6 years of age. An ESEM bifactor model with a central dimension plus 3 specific factors (inattention, hyperactivity, and impulsivity) showed the best fit and interpretability. Strict invariance between the sexes was observed. The bifactor model provided a solution to previously encountered inconsistencies in the factorial models of ADHD in young children. However, the low reliability of the specific factors casts doubt on the utility of the subscales for ADHD measurement. More research is necessary to clarify the nature of G and S factors of ADHD.

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Suicidal ideation is differentially connected to specific psychotic experiences. Auditory PE, persecutory ideation, and social anxiety symptoms could play a central role in the interconnectedness of the two constructs.

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Several studies have reported the factor structure of posttraumatic stress disorder (PTSD) using confirmatory factor analysis (CFA). The results show models with different number of factors, high correlations between factors, and symptoms that belong to different factors in different models without affecting the fit index. These elements could suppose the existence of considerable item cross-loading, the overlap of different factors or even the presence of a general factor that explains the items common source of variance. The aim is to provide new evidence regarding the factor structure of PTSD using CFA and exploratory structural equation modeling (ESEM). In a sample of 1,372 undergraduate students, we tested six different models using CFA and two models using ESEM and ESEM bifactor analysis. Trauma event and past-month PTSD symptoms were assessed with Life Events Checklist for DSM-5 (LEC–5) and PTSD Checklist for DSM-5 (PCL–5). All six tested CFA models showed good fit indexes (RMSEA = .051–.056, CFI = .969–.977, TLI = .965–.970), with high correlations between factors (M = .77, SD = .09 to M = .80, SD = .09). The ESEM models showed good fit indexes (RMSEA = .027–.036, CFI = .991–.996, TLI = .985–.992). These models confirmed the presence of cross-loadings on several items as well as loads on a general factor that explained 76.3% of the common variance. The results showed that most of the items do not meet the assumption of dimensional exclusivity, showing the need to expand the analysis strategies to study the symptomatic organization of PTSD.

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The usage of rigorous analyses based on contemporary methods to enhance psychometric properties of screening questionnaires aimed to address psychotic-like experiences (PLE) is currently being encouraged. The Brief Self-Report Questionnaire for Screening Putative Pre-psychotic States (BQSPS) is a recently created tool addressing PLE beyond attenuated positive symptoms (APS). Its psychometric properties as a screening tool for first step assessment seems to be adequate, but further research is needed to evaluate certain validity aspects, particularly its dimensionality, internal structure, and psychometric properties in different populations. We assessed the reliability, construct validity, and criterion validity of BQSPS in two samples: 727 adolescents aged 13–18 years, and 245 young adults aged 18–33 years. We used exploratory structural equation modeling (ESEM), confirmatory factor analysis (CFA), and Structural Equation Modeling (SEM). The original four-factor structure was not replicated. The best fit in adolescents was obtained by a structure of three-correlated factors: social anxiety (SA), negative symptoms (NS), and positive symptoms (PS). This structure was confirmed in young adult subjects. The three-factor model reached a predictive capability with suicidality as external criterion. PLE are represented by a three-factor structure, which is highly stable between adolescent and young-adult samples. Although the BQSPS seems to be a valid tool for screening PLE, its psychometric properties should be improved to obtain a more accurate measurement.