The prevalence of major depressive disorder (MDD) is growing worldwide, and experiencing violent victimization, especially during childhood, worsens its symptoms and raises the likelihood of being...Show moreThe prevalence of major depressive disorder (MDD) is growing worldwide, and experiencing violent victimization, especially during childhood, worsens its symptoms and raises the likelihood of being victimized again. This study assessed the impact of different forms of child abuse (physical, emotional, sexual) on depressive symptoms in patients with MDD and a recent history of victimization, and whether gender moderates this relationship. Additionally, it investigates whether Internet Emotion Regulation Training (iERT) as an addition to Treatment as Usual (TAU) can reduce emotion regulation difficulties and depressive symptoms in the same population. 153 patients filled in questionnaires and the hypotheses were tested by a hierarchical regression analysis and two repeated measure ANOVAs. Regarding the first research question, a significant association was found between depression and physical- and emotional child abuse, but not sexual abuse. This effect was not moderated by gender. Regarding the second research question, no significant effect was found of adding iERT to TAU on either emotion regulation difficulties or depressive symptoms.Show less
Since the emergence of Generative AI-powered (GenAI) chatbots, their potential impact on education has been widely discussed in academic and educational fields. This study explores students’...Show moreSince the emergence of Generative AI-powered (GenAI) chatbots, their potential impact on education has been widely discussed in academic and educational fields. This study explores students’ acceptance and use of GenAI chatbots, by examining the relationship between their perceptions and usage. Additionally, the study investigates potential gender differences in these perceptions and usage patterns. A correlational study was conducted using online questionnaires distributed among higher education students in the Netherlands. Only students with experience using GenAI chatbots for educational purposes were included. The sample consisted of 134 students, with an average age of 22.64 years (SD = 5.145). Among them, 35 were men, 97 were women, and two identified as ‘other’. Most students were enrolled in behavioral and social sciences, as well as education and upbringing programs. Multiple regression analysis revealed that perceptions (performance expectancy, effort expectancy, perceived risk, and anxiety) and gender predicted 21 percent of the variance in behavioral intention. These perceptions, along with gender and type of education, accounted for 16.8 percent of the variance in actual usage frequency. Performance expectancy for study in general (PEa) was the strongest predictor in both models, showing a positive effect on both behavioral intention and usage frequency, while other predictors did not significantly enhance the prediction. The study also found gender differences. Men used the chatbot more frequently than women and reported less difficulty interacting with GenAI chatbots, while women expressed more concerns about potential consequences. Based on the results, several recommendations for educational institutions are suggested. Institutions should clearly inform students about how GenAI chatbots work, provide training on how to use them effectively, and promote the importance of academic integrity. These measures can help reduce gender disparities and alleviate concerns, allowing all students to benefit from this emerging technology.Show less
Background: Coffin-Siris Syndrome (CSS) is a rare genetic disorder caused by de novo mutations in the BAF-complex, resulting in severe developmental delays. Despite insights from case studies, the...Show moreBackground: Coffin-Siris Syndrome (CSS) is a rare genetic disorder caused by de novo mutations in the BAF-complex, resulting in severe developmental delays. Despite insights from case studies, the relationship between developmental characteristics of CSS-affected children and parental caregiving burden remains underexplored. Method: This study mainly aimed to investigate to what extent language proficiency and adaptive functioning predict the parental caregiving burden for CSS-affected children, whilst accounting for the chronological age of the children. Data were collected using standardized questionnaires to assess language proficiency (PPVT, CELF-4-NL, CELF-Preschool-2-NL), adaptive functioning (ABAS-3-NL) and parental caregiving burden (OBVL). The sample included 26 CSS-affected children aged 4-18 years (M = 10.30 years, SD = 4.23 years), recruited from the LUMC expert clinic and patient associations in the Netherlands and Belgium. Results: Language comprehension did not correlate significantly with parental caregiving burden. The correlation remained non-significant after controlling for chronological age. Similar patterns were observed between language comprehension and adaptive functioning and between adaptive functioning and caregiving burden. Chronological age significantly correlated positively with language comprehension (r = 0.43, p = 0.04), and a trend was observed for a negative correlation between age and adaptive functioning (r = -0.39, p = 0.08). Hierarchical regression analyses indicated that neither language comprehension nor adaptive functioning significantly predicted parental caregiving burden (R² = 0.13; F(2,15) = 1.130; p = .349). even after controlling for chronological age (R² = 0.148; F(3,15) = 1.199, p = .315). Conclusion: Despite exploring language proficiency, adaptive functioning, and chronological age in CSS-affected children, no significant predictors were identified for parental caregiving burden. Further research is needed to deepen our understanding of the developmental trajectories and caregiving dynamics within CSS-affected families.Show less