The aim of the present study was to evaluate the construct validity, internal consistency and psychometric indicators of the reduced version of the Cognitive Emotion Regulation Questionnaire (CERQ-short). The CERQ-short was adapted and translated to Portuguese prior to its administration to 254 adults, mainly from the state of Paraíba, Brazil. The Difficulties in Emotion Regulation Scale (DERS), the Compulsive Buying Scale (CBS) and a sociodemographic questionnaire were also applied. The original CERQ-short nine-factor structure was preserved. The convergent and discriminant validity, the reliability and the psychometric adequacy concerning item difficulty and item discrimination were also confirmed. The results support the use of this scale for rapid screening and research.

The present study examined haptic and visual memory capacity for familiar objects through the application of an intentional free-recall task with three-time intervals in a sample of 78 healthy older adults without cognitive impairment. A wooden box and a turntable were used for the presentation of haptic and visual stimuli, respectively. The procedure consisted of two phases, a study phase that consisted of the presentation of stimuli, and a test phase (free-recall task) performed after one hour, one day or one week. The analysis of covariance (ANCOVA) indicated that there was a main effect only for the time intervals (F (2,71) = 12.511, p = .001, η² = 0.261), with a lower recall index for the interval of one week compared to the other intervals. We concluded that the memory capacity between the systems (haptic and visual) is similar for long retrieval intervals (hours to days).

The objective of this study is to integrate and classify electroencephalogram (EEG), electrocardiogram (ECG), and galvanic skin response (GSR) signals from a participant exposed to emotional stimuli—happiness, anger, fear, and sadness. We used the LazyPredict library to identify the most effective classification model, leveraging its simplified implementation and wide range of models and performance metrics. The signals were processed in Python following a detailed workflow: (1) normalization, (2) band-pass filtering, (3) epoch extraction and selection, and (4) relative energy extraction using Discrete Wavelet Transform (DWT). After preprocessing, the data were input into LazyPredict, where the Extra Trees model consistently demonstrated the best performance for binary emotion classification. Our experience with LazyPredict proved to be practical and efficient, facilitating the exploration of high-performing models for emotion classification.

The COVID-19 pandemic significantly impacted the mental health of young individuals globally, leading to increased emotional dysregulation due to various cumulative stressors. This study assesses a therapeutic approach that combines group-based cognitive-behavioral therapy (CBT) with executive function (EF) training in 36 children (55% female, M = 11.2 ± 1.8 years; 45% male, M = 10.4 ± 1.6 years) experiencing emotional distress in the post-pandemic context of returning to in-person classes. We evaluate executive functions, including working memory, inhibition, and cognitive flexibility, as well as emotional responses (self-reported) and psychophysiological changes measured by heart rate variability (HRV). Post-intervention, children exhibit improvements in working memory, inhibition, cognitive flexibility, emotional regulation (cognitive reappraisal), and parasympathetic activity. Executive functioning domains, such as working memory and flexibility, significantly predict enhancements in emotional responses. The findings indicate that integrating CBT and EF training can effectively improve cognitive and emotional regulation in children experiencing post-pandemic distress. This suggests the feasibility and preliminary potential of integrating executive function training with CBT to enhance and foster emotional regulation. However, further research is needed to confirm its effectiveness in larger samples.