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Introduction: While personality traits and early maladaptive schemas (EMSs) can affect an individual’s behavior and well-being, the links between these constructs are under-researched, especially in non-clinical samples. Aims: Two studies were conducted to address these links, intending to explore their specifics, as previous research evidenced various associations’ models. Methods: In Study 1, the sample consisted of 120 respondents (65.0% females) living in the UK and the USA. In Study 2, the sample consisted of 244 respondents (68.0% females) living in Lithuania. In both studies, most of the respondents were aged 18-25. The survey was administered online. Studies 1 and 2 applied the Big Five Inventory and Young Schema Questionnaire. Results: In Study 1, neuroticism was significantly positively associated with 17 EMSs. Extraversion stood significantly negatively related to 12 EMSs, conscientiousness was significantly negatively related to 15 EMSs, openmindedness stood significantly negatively related to 2 EMSs, but significantly positively related to admiration, and agreeableness appeared significantly negatively related to 9 EMSs. In Study 2, neuroticism was significantly positively associated with 16 EMSs. Extraversion stood significantly negatively related to 9 EMSs, conscientiousness was significantly negatively related to 12 EMSs, open-mindedness and agreeableness were significantly negatively related to 10 EMSs. Conclusions: Study 2 partly failed to replicate the results of Study 1, which implies that the model of links between EMSs and personality traits could be impacted by cultural factors, and needs further investigation.

Previous studies reported that acquiring computer programming skills is challenging and might result in high dropout rates. A quasi-experimental design was used to examine the role of different factors in dropping out of an e-based computer programming course. This study applied a knowledge in programming assessment test (20 multiple-choice questions covering the following topics: variables, loops, conditionals, functions, and general knowledge of Python), The Learning Motivating Factors Questionnaire, The Big Five-2, and The Basic Psychological Need Satisfaction & Frustration Scale. Ninety-four participants (38 males and 56 females) completed the course, while 305 participants started it. The mean age of e-learners was 29.96 years (SD 8.27), age range = 18 to 54. The results showed that e-learners who completed the course had higher initial knowledge assessment scores than those who dropped out after the first assessment. Reward and recognition as a motivator were significantly higher in males who completed the course than those who dropped out after the second knowledge assessment. Extraversion was significantly lower in females who completed the course than those who dropped after the first or second knowledge assessment test. Relatedness frustration was significantly higher in those who dropped out after the first knowledge assessment. Due to significant limitations of the sample size, cultural context, measures applied, and research design, the findings would preferably be regarded with caution.

In recent years, many governments around the world have placed a stronger emphasis on people’s wellbeing with the aim of making societies more inclusive and cohesive. As part of this approach, the public sector has introduced a number of initiatives to measure and support students’ psychological flourishing. Previous research reported that students’ flourishing could be linked to certain positive/negative cognitions, but the specifics of these links were under-researched. This study aimed to reveal links between students’ automatic thoughts and flourishing in a sample of public sector university students (n = 226), where 75.7% of participants (n = 171) were 18 to 24 years old and 24.3% (n = 55) were aged 25+. The participants represented four fields of study: Life Sciences (n = 35), Humanities (n = 71), Social Sciences (n = 85), and Technology Sciences (n = 31). The Flourishing Scale (FS) was used to assess students’ flourishing, and the Automatic Thoughts Questionnaire-Revised (ATQ-R) was applied to measure participants’ positive and negative automatic thoughts. The findings revealed that students’ negative self-concepts and negative expectations negatively predicted flourishing, while positive automatic thoughts and positive self-statements positively predicted flourishing. The findings also revealed that positive automatic thoughts and self-statements mediate the link between negative self-concept, negative expectations, and flourishing. Moreover, the results show that strengthening students’ positive cognitions can contribute to students’ increased flourishing, despite coexisting negative cognitions. Based on these findings, fostering a positive and supportive educational environment that promotes mental wellbeing is recommended. This can be achieved by implementing policies prioritizing students’ mental health and providing resources such as counseling services and support systems. Creating an environment where students feel valued, supported, and encouraged can help counteract their negative cognitions, leading to improved flourishing.