Background: University students are known to have higher sleep disorders prevalence than the general population. Among them, nursing students are even more susceptible to sleep disorders. This study evaluates sleep disorders’ risk factors among nursing students and their potential association with symptoms and assesses whether night shifts affect sleep quality by increasing the prevalence of sleep disorders. Methods: A total of 202 nursing students were included; a self-administered questionnaire was used to collect data on sociodemographic and academic characteristics (i.e., gender, age, height, weight, and year of nursing program) and risk factors for sleep disorders (e.g., smoking, lack of physical activity, and coffee intake late in the evening). The survey included the General Health Questionnaire to assess perceived stress, the Sleep and Daytime Habits Questionnaire, and the Epworth Sleepiness Scale to assess sleep disorders symptoms. Results: A high level of perceived stress is associated with sleep disorders symptoms and with poor sleep quality. Daytime symptoms are also associated with smoking. Students who drink coffee late in the evening report fewer nighttime symptoms. Night shifts and their increasing number are not associated with sleep disorders symptoms. The perception of an unsatisfying academic performance is associated with daytime symptoms and poor sleep quality. Conclusions: Although night shifts seem to not affect sleep quality among nursing students, sleep disorders represent a critical issue in this population since sleep disorders symptoms may result in errors, accidents, or low academic performance.

Background: The General Health Questionnaire-12 (GHQ-12) is a widely used screening tool for mental health assessment however its traditional scoring methods and cutoffs may not adequately capture the mental health complexities of younger populations. Methods: This study explores GHQ-12 responses from a sample of university students. Possible differences in means scores considering gender, age, academic field and degree course were assessed through t-test or one-way ANOVA as appropriate. To deeper understanding different levels of severity and individual item impact on general distress measurement, we applied Item-Response-Theory (IRT) techniques (two-parameters logistic model). We compared students’ population with a population of workers who underwent a similar psychological evaluation. Results: A total of 3834 university students participated in the study. Results showed that a significant proportion (79%) of students reported psychological distress. Females and younger students obtained significantly higher average scores compared to others. IRT analysis found item-specific variations in mental distress levels, with more indicative items for short-term fluctuations and potential severe mental health concerns. Latent class analysis identified three distinct subgroups among students (including 20%, 37%, 43% of the participants respectively) with different levels of psychological distress severity. Comparison with a population of adults showed that students reported significantly higher scores with differences in the scale behavior. Conclusion: Our results highlighted the unique mental health challenges faced by students, suggesting a reevaluation of GHQ-12 applicability and cutoff scores for younger populations, emphasizing the need for accurate instruments in mental health evaluation.

Healthcare students (HCSs) represent a target category for seasonal flu vaccination. This study aimed to examine adherence to flu vaccination campaigns from 2016 to 2019 among HCSs and to investigate knowledge and perception of and attitude toward influenza and flu vaccination. This cross-sectional study was conducted among the HCSs of a northern Italian university. Data on adherence, knowledge, perception, and attitude were investigated through an anonymous online self-administered questionnaire. The questionnaire was filled out by 352 out of 392 third-year HCSs (response rate = 90%). The main reason for refusal was the perception of influenza as non-threatening (24.4%), while self-protection was the main reason for adherence (87.5%). A univariate logistic regression analysis revealed some statistically significant associations with the adherence to the 2018–2019 campaign: being a nursing/midwifery student (OR: 4.14; 95% CI: 1.77–9.71) and agreeing with (OR: 19.28; 95% CI: 2.47–146.85) or being undecided (OR: 10.81; 95% CI: 1.33–88.27) about the obligation of vaccination in health facilities. The associations were also evaluated with a multiple logistic regression model. Despite the low vaccine uptake, good knowledge of the risks for HCSs and patients related to flu has emerged. Improving promotion strategies will be necessary to increase the adhesion of future healthcare workers.

Background: Over the past few years, studies have increasingly focused on the development of mobile apps as complementary tools to existing traditional pharmacovigilance surveillance systems for improving and facilitating adverse drug reaction (ADR) reporting. Objective: In this research, we evaluated the potentiality of a new mobile app (vaxEffect@UniMiB) to perform longitudinal studies, while preserving the anonymity of the respondents. We applied the app to monitor the ADRs during the COVID-19 vaccination campaign in a sample of the Italian population. Methods: We administered vaxEffect@UniMiB to a convenience sample of academic subjects vaccinated at the Milano-Bicocca University hub for COVID-19 during the Italian national vaccination campaign. vaxEffect@UniMiB was developed for both Android and iOS devices. The mobile app asks users to send their medical history and, upon every vaccine administration, their vaccination data and the ADRs that occurred within 7 days postvaccination, making it possible to follow the ADR dynamics for each respondent. The app sends data over the web to an application server. The server, along with receiving all user data, saves the data in a SQL database server and reminds patients to submit vaccine and ADR data by push notifications sent to the mobile app through Firebase Cloud Messaging (FCM). On initial startup of the app, a unique user identifier (UUID) was generated for each respondent, so its anonymity was completely ensured, while enabling longitudinal studies. Results: A total of 3712 people were vaccinated during the first vaccination wave. A total of 2733 (73.6%) respondents between the ages of 19 and 80 years, coming from the University of Milano-Bicocca (UniMiB) and the Politecnico of Milan (PoliMi), participated in the survey. Overall, we collected information about vaccination and ADRs to the first vaccine dose for 2226 subjects (60.0% of the first dose vaccinated), to the second dose for 1610 subjects (43.4% of the second dose vaccinated), and, in a nonsponsored fashion, to the third dose for 169 individuals (4.6%). Conclusions: vaxEffect@UniMiB was revealed to be the first attempt in performing longitudinal studies to monitor the same subject over time in terms of the reported ADRs after each vaccine administration, while guaranteeing complete anonymity of the subject. A series of aspects contributed to the positive involvement from people in using this app to report their ADRs to vaccination: ease of use, availability from multiple platforms, anonymity of all survey participants and protection of the submitted data, and the health care workers’ support.

Background/Objectives: Inappropriate posture, overweight, and physical inactivity are common causes of pathologies on muscles, ligaments, joints, and bone structures, which could negatively impact the quality of present and future life. The challenge of this work was to develop a diagnostic approach to identify the causes of musculoskeletal disorders in an adolescent population in order to implement preventive procedures. Methods: A total of 147 subjects aged between 14 and 18 years who were affected by musculoskeletal disorders and who accessed the Clinical Posturology unit of the IRCCS San Gerardo hospital, Monza, Italy, from 2015 to 2023, were enrolled. The clinical evaluation of each subject included a posturology visit, a physical examination, instrumental devices, such as stabilometric platform, gait analysis, MuscleLab, and imaging tests, such as Radiographic and Magnetic resonance, and a final diagnosis. Results: Ninety-eight (66.6%) subjects reported pain at the lumbar spine (33.3%), followed by knee/lower limb (22.4%), cervical spine (13%), and dorsal spine (12.3%). Imaging diagnostics underlined alterations in the musculoskeletal components, bone dimorphism, and asymmetry of the skeleton in 68% of cases. Thirty-one (21%) subjects received a diagnosis of postural dysfunction, seventy-two (49%) received a diagnosis of somatic dysfunction, and ten (7%) received a diagnosis of both postural and somatic dysfunctions. Conclusions: Our work highlighted that the three instrumental devices used allowed us to detect somatic and postural functional changes that cause musculoskeletal pathologies in adolescents.