The present study aimed to investigate the factor structure of a set of neurocognitive tests theoretically assessing executive functions (EF), verbal abilities (VA), and processing speed (PS). This study extended previous research by analyzing if each test is better explained by the specific factor to which it theoretically belongs or by a more general neurocognitive factor; and also by analyzing the relations between the neurocognitive factors. Using confirmatory factor analysis (CFA) we examined the factor structure of nine neurocognitive tests (EF: Working Memory, Tower, Divided Attention, Stroop, and Verbal Fluency tests; VA: Word List and Confrontation Naming tests; PS: Coding and Telephone Search tests) in a nonclinical sample (N = 90; 18-33 years old, 76 women). We tested five factor models of neurocognitive functioning: a one-factor model; two models with two-correlated factors; and two models with three-correlated factors. A three-correlated-factor model, with EF, VA, and PS factors, was the most suitable for our neuropsychological data. The Verbal Fluency test was better explained by the VA factor rather than by the EF factor. The EF factor was correlated with the PS factor, but not with the VA factor. Most of the neurocognitive measures used in the present study loaded in the expected factors (with the exception of the Verbal Fluency that was apparently more related to VA). EF and PS represent related but separable functions. Our results highlight the need for a careful interpretation of test scores since performance on one test usually requires multiple functions.

This study adapted and validated the European Portuguese version of the Fear of Missing Out scale (FoMOs-P) and determined an “optimal” cutoff score for higher education students with high social media engagement. Five hundred Portuguese students (M = 22.37, SD = 5.68) completed FoMOs-P and measures of sleep quality, rumination, and social media. Following previous conflicting results, Confirmatory Factor Analysis (CFA) was conducted to compare two competing factor structures. Model invariance regarding sex was tested using multi-group CFA. FoMOs-P’ internal consistency, convergent and discriminant validity were analyzed, and an “optimal” cutoff point was explored through Receiver Operating Characteristic (ROC) analysis. When comparing CFA models, the two-related-factor model fit best (Δχ² (1) = 495.01, p < .001), demonstrating a good fit (χ²/df = 2.96; CFI = .98; TLI = .97; RMSEA [90 CI] = .063 [.049;.077]). This model showed metric invariance but not scalar invariance across sex. There was adequate reliability for both factors and total scale (ω > .7). Convergent and discriminant validity were supported. ROC analysis revealed an AUC = .742 (p < .001) and an “optimal” cutoff point of 20 (70.1% sensitivity, 68.4% specificity) to detect probable disruptive social media engagement. FoMOs-P was shown to be a reliable and valid instrument, supporting its use among higher education students. FoMOs-P appears to be composed of two factors [(i.e., internalizing and externalizing Fear of Missing Out (FoMO)] and has moderate accuracy to screen students with high social media usage.

The present study primarily aimed to investigate the interactive effect of chronotype and time of day on adolescent’s emotional states. Chronotype influences behaviour throughout the day, with variables such as mood exhibiting circadian rhythmicity. We also considered the influence of potential covariates, such as sleep variables and psychopathological symptoms. A total of 190 8^th-grade students (53.7% males; mean age 13.47 ±.70) completed a two-part protocol: part one probing sleep (BaSIQS), chronotype (CSM), and psychopathological symptoms (SDQ); part two targeting emotional states (FS; STAIC-S; EAPNC), while manipulating the time of day (first and last hours of the school day). The hypothesized interaction failed to reach significance, despite correlational analyses and visual inspection of mean values suggesting some interactive effects. Time of day independently impacted positive emotional states, rising from morning to afternoon, and anxiety-state, which dropped. Chronotype independently influenced momentary mood (non-significant when sleep and psychopathological symptoms were controlled for), positive affect (non-significant when controlling for psychopathological symptoms), and anxiety (non-significant when sleep quality and psychopathological symptoms were controlled for). There were consistent effects of time of day, but its interaction with chronotype did not reach significance. Some associations between chronotype and emotional states seemed to be influenced by sleep and/or psychopathological symptoms.

The Pre-Sleep Arousal Scale (PSAS) is a self-report tool for assessing cognitive and somatic arousal before sleep. While the English version is well-validated, research on translations is limited. This meta-analysis examines PSAS translations' internal consistency and reliability. We conducted a comprehensive literature search using multiple databases to identify studies that reported the reliability of the PSAS. We used a random-effects meta-analysis model to pool estimates of internal consistency and test-retest reliability and explored potential moderators using subgroup analyses and meta-regression. To ensure transparency, we registered the study protocol, utilized the PRISMA checklist, and made all study code and data available on the Open Science Framework. Systematic review yielded a total 27 studies (reported in 25 publications) with 9354 participants employing eleven language versions of the PSAS. Meta-analysis showed good internal consistency for the total PSAS (0.88, 95%CI 0.86-0.90) as well as the cognitive (α = 0.89, 95%CI 0.88-0.90) and somatic (α = 0.80, 95%CI 0.77-0.83) subscales. The PSAS also displayed excellent test-retest reliability for the total scale (r = 0.87, 95%CI 0.84-0.90), cognitive subscale (α = 0.80, 95%CI 0.77-0.84) and somatic subscale (α = 0.70, 95%CI 0.67-0.74). Participant characteristics (age and sex) did not significantly affect results. This meta-analysis shows that the PSAS is a reliable tool for detecting pre-sleep arousal based on its high internal consistency and test-retest reliability. The PSAS is useful across languages but quality translation appears to be crucial. Recommendations are offered for future adaptations and clinical use.