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Pressures and responsibilities of medical school put a strain on medical student's personal wellbeing, leading among all to high rates of anxiety, emotional discomfort and stress. In this work we evaluated the effectiveness of a comprehensive Mindfulness-Based Intervention (MBI) in reducing this load. The intervention comprised 10 twice-a-week Integral Meditation classes, dietary advice, and brief yoga sessions. We performed a randomized trial on two cohort of medical students from Italian universities: 239 in cohort 1 (106 treated and 133 controls), and 123 in cohort 2 (68 treated and 55 control) for a total sample of 362 students. Nine questionnaires for evaluating the effectiveness of our intervention on stress (PSS), state anxiety (STAIX-1), well-being (WEMWBS), mind-wandering (MW-S), overall distress (PANAS), emotion regulation (DERS), resilience (RS-14), and attentional control (ACS-C and ACS-D) were collected both pre and post intervention. Linear mixed effect models were run on the whole sample showing that, after multiple testing correction, our intervention was effective in reducing perceived stress (β = − 2.57 [− 4.02; − 1.12], p = 0.004), improving mental well-being (β = 2.82 [1.02; 4.63], p = 0.008) and emotional regulation (β = − 8.24 [− 12.98; − 3.51], p = 0.004), resilience (β = 3.79 [1.32; 6.26], p = 0.008), reducing the tendency to wander with the mind (β = − 0.70 [− 0.99; − 0.39], p = 0.0001), ameliorating the ability to maintain attention (AC-S (β = − 0.23 [− 0.44; − 0.02], p = 0.04) and AC-D (β = − 0.19 [− 0.36; − 0.01], p = 0.04)), and the overall distress (β = 1.84 [0.45; 3.23], p = 0.02).

Background Mental health issues are common among university students, but the latter are unlikely to seek professional help even when mental health services are available. Coping strategies, stigma and psychological distress are often considered as factors that can affect help-seeking intentions in university students. Methods This study aimed to determine the role of coping strategies, stigma and psychological distress on the intentions to seek professional help for psychological problems. All students (N = 13,886) from an Italian medium-sized university were asked to participate in a multidimensional online survey and 3754 (27.1%) agreed to participate. A Structural Equation Modelling approach was applied to explore the simultaneous direct and indirect effects of distress, stigma and coping strategies on professional help-seeking intentions. Results Results showed that students were not very likely to seek professional help and, through the Structural Equation Model, psychological distress was found to be positively correlated with coping strategies, which in turn was negatively associated with the stigma of seeking help. The latter was negatively associated with professional help-seeking intentions. These effects suggest that students with significant psychological distress use coping strategies to face the stigma of seeking help: the lower the stigma of seeking help, the higher the chance of developing intentions to seek professional help. Conclusions This study suggests the importance of implementing programs to encourage college students to seek help, including measures that foster a stigma-free environment, reduce psychological distress and promote the use of adaptive coping strategies. Interventions should be focused firstly on self-stigma and secondly on perceived stigma, taking into consideration the level of psychological distress and social stereotypes associated with mental disorders and help seeking behaviours. Programs about coping are also essential and should focus on promoting emotion-focused strategies and problem-focused strategies.

Background Suicide is one of the leading causes of death among young people and university students. Research has identified numerous socio-demographic, relational, and clinical factors as potential predictors of suicide risk, and machine learning techniques have emerged as promising ways to improve risk assessment. Objective This cross-sectional observational study aimed at identifying predictors and college student profiles associated with suicide risk through a machine learning approach. Methods A total of 3102 students were surveyed regarding potential suicide risk, socio-demographic characteristics, academic career, and physical/mental health and well-being. The classification tree technique and the multiple correspondence analysis were applied to define students’ profiles in terms of suicide risk and to detect the main predictors of such a risk. Results Among the participating students, 7% showed high potential suicide risk and 3.8% had a history of suicide attempts. Psychological distress and use of alcohol/substance were prominent predictors of suicide risk contributing to define the profile of high risk of suicide: students with significant psychological distress, and with medium/high-risk use of alcohol and psychoactive substances. Conversely, low psychological distress and low-risk use of alcohol and substances, together with religious practice, represented the profile of students with low risk of suicide. Conclusions Machine learning techniques could hold promise for assessing suicide risk in college students, potentially leading to the development of more effective prevention programs. These programs should address both risk and protective factors and be tailored to students’ needs and to the different categories of risk.

University years represent a period of major transition during which health-related behaviors, such as sleep and physical activity, may influence students’ academic functioning. This cross-sectional, single-center study, conducted at an Italian university, examined the associations between sleep, physical activity, and academic well-being. Students completed an online survey assessing sleep, physical activity, and several indicators of academic functioning (i.e., academic stress, self-efficacy, dropout intention, and motivation). Nonparametric tests (Kruskal–Wallis, Jonckheere–Terpstra) were used to explore differences in these indicators across sleep quality and physical activity categories, while linear regressions tested associations between sleep duration and Metabolic Equivalent of Task–minutes/week with the same academic outcomes. A total of 2192 students (15.55%) accessed the survey, and 1246 (8.84%) completed all questionnaires. Most participants were female (62.7%) and Italian (94.5%). Both sleep and physical activity showed significant but small associations with academic stress, dropout intention, and self-efficacy, whereas associations with academic motivation were weaker. These findings suggest that maintaining regular physical activity and healthy sleep habits may contribute to students’ academic adjustment, although the cross-sectional design limits causal interpretation and underscores the need for integrative models to better understand the underlying psychological mechanisms.

Background: The rapid diffusion of generative Artificial Intelligence (AI) in higher education is reshaping students’ learning practices and raising concerns about unequal access and educational equity. In the Italian university context, where institutional guidelines on AI use are still developing, examining how students adopt and perceive tools such as ChatGPT is particularly relevant. Methods: This quantitative study investigated patterns of ChatGPT use and perceptions among Italian university students, with specific attention to its perceived support for learning and the development of transversal skills. Data were collected through an online survey. Differences across socio-demographic and academic characteristics were analysed using Mann–Whitney and Kruskal–Wallis tests, while associations between ChatGPT use, students’ perceptions, and study-related outcomes were examined using Spearman’s rho coefficients. Results: Students perceived ChatGPT as a useful tool, particularly in supporting the development of analytical, writing, and digital skills. Significant differences emerged across student groups. Higher levels of use and more positive perceptions were reported by freshmen, students studying in urban areas, and those with stronger economic resources. Conclusions: ChatGPT adoption and subjectively perceived institutional support and benefits vary by academic experience and socio-economic background. As the findings are based on self-reported perceptions, they reflect perceived rather than measured learning outcomes, highlighting the need for further research using objective indicators.

Dropout is a critical concern in higher education, with a considerable number of students leaving within the first two years of university. Dropout affects students’ well-being and their academic and career prospects, and institutions’ retention and graduation rates. The aim of this study was to explore the mediating role of motivation and cognitive strategies for learning in the relationship among self-efficacy, connectedness, and university dropout intention. A total of 790 Italian college freshmen were involved in this study. The sample was recruited through a web survey consisting of the Academic Motivation Scale, Perceived School Self-Efficacy Scale, University Connectedness Scale, and Self-Regulated Knowledge Scale-University. The freshmen’s intentions to drop out were assessed with five questions. The average age of the freshmen was 20.9 years, most of them were female, and were attending a degree program in the medical area. The results show that self-efficacy is the most important predictor of dropout intentions, followed by university connectedness. Self-regulated knowledge has an important role in predicting dropout intention by acting as a mediator between self-efficacy and motivation.This study underlines the importance of investing in training and orientation interventions in order to develop the skills to face the university path, increasing self-efficacy, motivation, and consequently students’ well-being.

To validate the Italian Perceived Maternal Parenting Self-Efficacy (PMP S-E), the first questionnaire specifically developed for mothers of preterm neonates hospitalized in the Neonatal Intensive Care Unit. Two hundred mothers filled the PMP S-E, the General Self-Efficacy Scale (GSES), the Edinburgh Postnatal Depression Scale (EPDS), the Parental Distress Index (PSI-SF/Pd). The Explanatory Factor Analysis outlined four factors: care-taking procedures, evoking behaviours, reading and managing bodily cues, reading and managing emotional cues. This factor-solution demonstrated adequate goodness of fit when the Confirmatory Factor Analysis was carried out. Internal consistency was high for the overall scale ( α  = 0.932), and the all the factors (all α  > 0.80). There was a moderate correlation with GSES ( r  = .438; p  < .001), while the associations with EPDS ( r  = .295; p  < .001) and PSI-SF/Pd ( r  = .193; p  = .006) were low. Good test–retest reliability was found over 2 weeks ( r  = .73; p  < .001). These findings support the validity and reliability of the Italian PMP S-E.

Background: Alcohol and substance use among young people is a well-documented public health concern, and is particularly prevalent in college populations. Problematic internet use is also an emerging issue, with potential negative effects on academic achievement. University dropout remains a critical challenge, especially among freshmen, with research highlighting the role of academic engagement factors such as motivation, self-efficacy, and university connectedness in students’ academic trajectories. Methods: This study explored the relationships among risky substance use, problematic internet use, academic engagement factors, and academic outcomes, identifying potential mediators. Freshmen from an Italian university were invited to complete an online survey assessing these variables. The study defined two academic outcomes: (i) academic performance (Grade Point Average, GPA) and (ii) dropout intentions. Spearman’s rho coefficients and multiple linear regression models examined the associations among risky substance/internet use, academic engagement factors, and academic outcomes. Mediation analyses assessed whether academic engagement variables mediated the relationship between risky substance/internet use and academic outcomes. Results: The results showed that only problematic internet use was significantly associated with GPA, with self-efficacy and lack of motivation fully mediating this relationship. Regarding dropout intentions, problematic internet use and the risky use of alcohol, cannabis, and sedatives were directly and positively associated with dropout intentions. Several motivation subscales, self-efficacy, and university connectedness mediated these relationships. Conclusions: These findings highlight the role of academic engagement factors in mitigating the impact of risky behaviors on students’ academic trajectories, emphasizing the need for targeted prevention and intervention strategies.

It is estimated that one in three students drop out of university by the end of the first year of study. Dropping out of university has significant consequences, not only for the student but also for the university and for society as a whole. A total of 1.154 Italian freshmen were involved in this study and were divided based on their intention to dropout from university. The intention to dropout was assessed using five questions, and motivation was assessed through the Academic Motivation Scale. Differences in socio-demographic factors, extra-curriculum activities, academic characteristics, and academic motivation between freshmen with low and high dropout risks were assessed for highlighting potential intervention for limiting dropout rates. The majority of the freshmen were female, from low-income families, had attended high school, and lived out of town; the most represented field of study was health professions. The results indicate that the variables increasing the likelihood of belonging to the high dropout risk group are as follows: unsatisfactory relationships with lecturers/professors and fellow students, low income, amotivation, and extrinsic motivation. This study underlines the importance of adopting new teaching approaches that include spaces and time dedicated to fostering relationships, supporting academic success, and promoting the psychosocial well-being of students.

ObjectivesTo investigate the early information needs of women with a recent diagnosis of breast cancer (BC) according to their employment status.DesignCross-sectional.SettingSecondary-care patients attending three outpatient oncology clinics in northern Italy.Participants377 women with a recent diagnosis of early-stage, non-metastatic BC aged 18–75 were recruited. Of them, 164 were employed, 103 non-employed and 110 retired.Outcome measuresThe first consultation visit with an oncologist was audio-recorded and analysed for the number and type of questions asked. Linear regression models considering consultations’ and patients’ characteristics as confounding variables were applied.ResultsEmployed patients asked significantly more questions than non-employed and retired patients (17 vs 13 and 14; F=6.04; p<0.01). When age and education were included in the statistical model, the significance of employment status was rearranged among all the variables and was no more significant (b=1.2, p=0.44). Employed women asked more questions concerning disease prognosis (0.7 vs 0.4 and 0.6; F=3.5; p=0.03), prevention (1.4 vs 0.6 and 0.7; F=10.7; p<0.01), illness management (7.2 vs 6 and 5.4; F=3.8; p=0.02) and social functioning (37% vs 18% and 20%; χ2=14.3; p<0.01) compared with the other two groups. Finally, they attended more frequently the consultation alone (37% vs 18% and 25%; χ2=10.90, p<0.01), were younger (50 vs 58 and 67 years; F=63.8; p<0.01) and with a higher level of education (77% vs 27% and 45%; χ2=68.2; p<0.01).ConclusionsEmployment status is related to the type of questions asked during the first consultation. Also, it interrelates with other patients' characteristics like age and education in determining the number of questions asked. Patients' characteristics including employment status could be considered in tailoring work and social-related information provided during the first oncological consultation. Future studies could explore potential differences in information needs according to the different kinds of work.