Aims: The purpose was to compare the frequency of needs of patients with schizophrenia in forensic services across five European countries as assessed by both the patients and their care staff. Methods: Patients with schizophrenia and a history of significant interpersonal violence were recruited from forensic psychiatric services in Austria, Germany, Italy, Poland and England. Participants’ needs were assessed using the Camberwell Assessment of Needs—Forensic Version (CANFOR). Multiple linear regression analyses were used to identify predictors of numbers of needs. Results: In this sample, (n = 221) the most commonly reported need according to patients (71.0%) and staff (82.8%) was the management of psychotic symptoms. A need for information was mentioned by about 45% of staff and patients. Staff members reported a significantly higher number of total needs than patients (mean 6.9 vs. 6.2). In contrast, staff members reported a significantly lower number of unmet needs than patients (mean 2.0 vs. 2.5). Numbers of total needs and met needs differed between countries. Unmet needs as reported by patients showed positive associations with the absence of comorbid personality disorder, with higher positive symptom scores and lifetime suicide or self-harm history. Significant predictors of unmet needs according to staff were absence of comorbid personality disorder and higher positive as well as negative symptom scores according to PANSS. Conclusions: Staff rated a significantly higher number of total needs than patients, while patients rated more unmet needs. This indicates that patients’ self-assessments of needs yield important information for providing sufficient help and support.

A constituting feature of item response models is that item and person parameters share a latent scale and are therefore comparable. The Person–Item Map is a useful graphical tool to visualize the alignment of the two parameter sets. However, the “classical” variant has some shortcomings, which are overcome by the new RMX package (Rasch models—eXtended). The package provides the RMX::plotPIccc() function, which creates an extended version of the classical PI Map, termed “PIccc”. It juxtaposes the person parameter distribution to various item-related functions, like category and item characteristic curves and category, item, and test information curves. The function supports many item response models and processes the return objects of five major R packages for IRT analysis. It returns the used parameters in a unified form, thus allowing for their further processing. The R package RMX is freely available at osf.io/n9c5r.

Response time (RT) data play an important role in psychology. The diffusion model (DM) allows to analyze RT-data in a two-alternative-force-choice paradigm using a particle drift diffusion modeling approach. It accounts for right-skewed distributions in a natural way. However, the model incorporates seven parameters, the roles of which are difficult to comprehend from the model equation. Therefore, the present article introduces the diffusion model visualizer (DMV) allowing for interactive manipulation of each parameter and plotting the resulting RT densities. Thus, the DMV serves as a valuable tool for understanding the specific role of each model parameter. It may come in handy for didactical purposes and in research context. It allows for tracking down parameter estimation problems by delivering the model-based ideal densities, which can be juxtaposed to the data-based densities. It will also serve a valuable purpose in detecting outliers. The article describes the basics of the DM along with technical details of the DMV and gives several hints for its usage.

Objectives: The Clinical Outcome in Routine Evaluation–Outcome Measure (CORE‐OM) is a freely accessible self‐assessment questionnaire with a total of 34 items measuring the progress of psychological or psychotherapeutic treatments according to four scales (well‐being, problems, functioning, and risk). The CORE‐OM originated in the United Kingdom and has been translated into 54 languages and dialects. The aim of this study is to systematically compare the translated versions.Method: A total of 21 translations were compared using methods of systematic review and meta‐analysis.Results: The results show a certain heterogeneity between the studies; however, the 21 translations can be declared as equivalent.Conclusion: The factorial structure could not be replicated in any of translations. Therefore, further analysis of the CORE‐OM domains is recommended. In addition, some supplementary restrictions on the translation process, data collection, and reporting of results are necessary to ensure comparability and quality of CORE‐OM translations.

The Ratcliff Diffusion Model has become an important and widely used tool for the evaluation of psychological experiments. Concurrently, numerous programs and routines have appeared to estimate the model's parameters. The present study aims at comparing some of the most widely used tools with special focus on freely available routines (i.e., open source). Our simulations show that (1) starting point and non-decision time were recovered better than drift rate, (2) the Bayesian approach outperformed all other approaches when the number of trials was low, (3) the Kolmogorov-Smirnov and χ² approaches revealed more bias than Bayesian or Maximum Likelihood based routines, and (4) EZ produced substantially biased estimates of threshold separation, non-decision time and drift rate when starting point z ≠ a/2. We discuss the implications for the choice of parameter estimation approaches for real data and suggest that if biased starting point cannot be excluded, EZ will produce deviant estimates and should be used with great care.