Pasquale Anselmi

Rating scales are widely used to measure attitudes, personality traits, and other psychological constructs, yet their response categories may not function as intended. This paper introduces a probability-based framework for interpreting threshold ordering and threshold advancement in the polytomous Rasch model. Specifically, the framework clarifies why threshold ordering and threshold advancement by a useful amount matter for measurement and what is at stake when either requirement is violated. Within this framework, the paper proposes a probability-ratio criterion that links threshold distance to the relative probabilities of adjacent and nonadjacent response categories. The criterion provides researchers and practitioners with a simple, readily interpretable, and context-sensitive basis for determining the minimum threshold distance required to distinguish response categories with a desired probability contrast. The framework is illustrated theoretically and evaluated empirically using the rating scale model and the partial credit model, two parameterisations of the polytomous Rasch model, across a large set of instruments that employ common 4- and 5-point agreement and frequency scales. The empirical findings show that the same rating scale may function differently across instruments, even when administered to the same respondents, and that the central neutral response category in agreement scales warrants particular attention because it frequently exhibits problematic threshold functioning. Taken together, these methodological and empirical contributions advance the analysis of rating-scale functioning using the polytomous Rasch model.

Hikikomori, or prolonged social withdrawal, is an issue of global relevance. The HRI-15 is a brief tool for its assessment. This study enhances its utility by adding clinical thresholds to identify risk and person-centered clinical profiles, and by developing a machine-learning(ML)–based computerized adaptive test (CAT) to enable rapid screening. Data from a national survey of Italian adolescents ( N = 8,755) were used to conduct ROC analysis and latent profile analysis (LPA). The findings indicated that a score of ≥ 42 achieved optimal classification performance, and four profiles with distinct meanings and systematic differences in anxiety, depression, impulsivity, and risk behaviors were identified. A multivariate conditional inference tree was estimated to develop an ML-based adaptive version of the instrument. The CAT reduced administered items by 53% (7.03/15), accurately reproducing full-length scores ( r = .77–.997) and the corresponding classification; alignment was assessed with latent transition analysis (entropy = .96). The procedure was integrated into an application supporting administration, scoring, and reporting (score, risk, profiles, graphs). Combining a cross-validated cutoff and clinically useful profiles with CAT and its automated administration and reporting application strengthens triage and personalization, enabling large-scale, multidomain screening and earlier intervention for hikikomori risk.

Conventional evaluations of matrix reasoning have focused predominantly on total accuracy scores, thus overlooking qualitative error patterns that may reflect distinct cognitive mechanisms in psychiatric populations. This study examined performance on MatriKS, a digital matrix reasoning task, in a sample of 28 individuals diagnosed with Schizophrenia, 31 individuals diagnosed with Bipolar disorder, and 371 healthy controls. The present study analysed four conceptual error types: repetition (R), wrong principle (WP), distractor (D), and incomplete correlate (IC). The results showed that both clinical groups exhibited a lower level of accuracy and a higher total number of errors when compared to the control group. However, these differences were not statistically significant. The qualitative error analysis revealed informative dissociations: D errors, which reflect the selection of visually salient but relationally irrelevant options, were found to be more prevalent in both clinical groups, with a tendency observed in individuals with Schizophrenia. Multinomial logistic regression with bootstrap resampling identified selective visual attention, measured by the Attentive Matrices Test, as the only significant cognitive predictor of reasoning errors. It was also found that higher visuospatial attentional capacity significantly reduced WP errors and showed a marginal protective effect against IC errors. Furthermore, the study revealed that there were no significant interactions between cognitive measures and diagnostic group. Symptom severity, as measured by the Brief Psychiatric Rating Scale, did not demonstrated correlations with total errors. The overall findings of this study underscore the clinical value of qualitative error profiling as a complement to total score metrics, and highlight selective visual attention as a key cognitive mechanism in matrix reasoning.

The increasing prevalence of social media addiction (SMA) among adolescents poses significant challenges for mental health, highlighting the need for effective prevention and intervention strategies. This study investigates how two well‐known emotion regulation strategies—cognitive reappraisal and expressive suppression—relate to SMA, with depressive symptoms and social anxiety as mediators, focusing on gender differences in an Italian adolescent sample. Using multiple‐group path analysis, results showed that both expressive suppression and cognitive reappraisal directly predict SMA similarly across genders, while indirect effects via depressive symptoms and social anxiety differ by gender. Expressive suppression was positively associated with depressive symptoms and social anxiety, with stronger expressive suppression–depressive symptom links in males and stronger expressive suppression–social anxiety links in females. Cognitive reappraisal was protective, particularly against social anxiety in females. Depressive symptoms mediated the impact of emotion regulation strategies on SMA more strongly in females, whereas social anxiety mediated these effects mainly in males, with social anxiety directly linked to SMA only in males. These gender‐specific pathways highlight distinct emotional vulnerabilities contributing to SMA. The study also provides a primary validation of the Italian Social Media Use Disorder Scale for Adolescents, reinforcing its utility as a reliable tool for assessing SMA. Overall, these findings offer valuable insights for developing gender‐sensitive, targeted prevention and treatment programs aimed at improving adolescent emotional well‐being and reducing SMA risk.

Tower tasks are popular tools used to measure planning skills. The sequences of moves undertaken by the respondents in solving tower tasks might provide important and useful information to shed light on their planning skills. The article focuses on the distinction between a situation where planning occurs before action (pre-planning) from one where planning and action are interlaced all along the execution of the task (interim-planning). While the model for pre-planning was already developed by Stefanutti et al. (2021), an alternative model for the interim-planning is proposed. The two models are compared with one another in an empirical study. In accordance with the literature on the development of planning skills, the pre-planning model better fits data collected on individuals aged 14 on, while the interim-planning model displays a better fit with data collected on individuals aged 4–8. This result is further corroborated by the analysis of the time performance.