Background: Simulation is a crucial component in the training of healthcare professionals, offering a safe environment for practical learning without posing risks to patients. Aim: This study aims to evaluate the effect of simulation with a standardized patient on the acquisition and retention of knowledge, as well as on the self-efficacy of nursing students. Methods: A quasi-experimental study with a pre-test and post-test design was conducted with 120 nursing students, who were randomly assigned to two groups. The experimental group (60) received training through simulation with a standardized patient, supplemented by a lecture-based course. The control group (60) received only the same lecture-based course. A pre-test was conducted to assess students’ baseline knowledge and self-efficacy before any intervention. Student performance was then assessed with a post-test immediately after the training to measure knowledge acquisition and self-efficacy and a post-test three months after the intervention to measure long-term knowledge retention. Results: The results showed a statistically significant difference in mean scores between the intervention and control groups in terms of knowledge acquisition (14.92 vs. 13.32; p < 0.001; d = 0.99), self-efficacy (33.02 vs. 31.05; p < 0.001; d = 1.03) and knowledge retention three months after training (12.4 vs. 10.6; p < 0.001; d = 0.94). Conclusions: The results of this study confirmed the effectiveness of simulation in knowledge acquisition and retention, as well as in the self-efficacy of nursing students. These findings support the integration of this method into training programs to strengthen the skills of future healthcare professionals.

Background: Smartphone addiction and poor sleep quality are prevalent health concerns that negatively impact students’ physical and mental well-being, which could affect their academic performance. However, research on this subject in Morocco remains limited. Objective: This study aimed to examine the impact of smartphone addiction on sleep quality and identify risk factors that moderate this relationship among nursing students. Methods: This cross-sectional study was conducted from March to July 2023, involving 451 nursing students aged 17 to 23 at the Higher Institute of Nursing Professions and Health Techniques in Meknes, Morocco. Participants completed the Mobile Phone-Related Sleep Risk Factors Questionnaire (MRSRF), the Smartphone Addiction Scale–Short Version (SAS-SV), and the Pittsburgh Sleep Quality Index (PSQI). Binary logistic regression (BLR), Receiver Operating Characteristic (ROC) curves, and Area Under Curve (AUC) analyses were used to assess the impact of smartphone addiction on sleep quality and to identify moderating risk factors. Results: The study found that 81.23% of nursing students experienced smartphone addiction, and 86.47% reported poor sleep quality. Sleep quality was significantly correlated with smartphone addiction (β = 0.174; p <0.001), use before bedtime (β = 1.018; p = 0.030), and duration of use after lights-off (β = 0.768; p = 0.047). Logistic regression analysis indicated that smartphone addiction (AUC = 0.872; p <0.001) and duration of use after lights-off (AUC = 0.668; p <0.001) were significant predictors of sleep quality. Conclusion: This study found a significant correlation between smartphone addiction and poor sleep quality, as well as a negative impact of using smartphones in bed for more than 30 minutes after lights off. Nursing students with higher smartphone addiction levels, who use their devices for extended periods without blue light filters, are more likely to experience poor sleep quality. Addressing these challenges requires an integrated, multidisciplinary approach involving healthcare professionals, educators, and community stakeholders. Health promotion programs integrated into student curricula could help reduce smartphone addiction and encourage healthier sleep hygiene practices.

Iziki H, et al. Infect Chemother. 2024 Sep;56:e41. https://doi.org/10.3947/ic.2024.0056

Introduction: This study aims to investigate the clinical characteristics, therapeutic approaches, and factors influencing length of hospital stay of pneumothorax (PNO) cases. Materials & methods: This study employed a retrospective approach. Data were collected from January 2019 to April 2023, encompassing sociodemographic information, toxic habits, medical history, clinical signs, PNO characteristics, treatment modalities, evolution, and complications. Results: The study encompassed 158 PNO cases, predominantly males (89.2%) with a median age of 51 years [33-62]. Primary spontaneous pneumothorax accounted for 62.0% of cases, while secondary spontaneous pneumothorax (PSS) constituted 33.5% with chronic obstructive pulmonary disease as the leading cause (34.0%), followed by tuberculosis (20.8%). Drainage was the primary treatment (91.8%), with favorable outcomes in 84.2% of cases. PSS cases were associated with unfavorable evolution and longer hospital stays. Factors associated with prolonged hospitalization included female gender, PSS, total PNO, and surgical treatment. Conclusions: This study provides valuable insights into factors influencing prolonged hospitalization of PNO cases in Souss Massa Region. Understanding these factors can aid healthcare professionals in optimizing patient management and improving outcomes.

Objective: To examine the factors associated with the intention to use ChatGPT and its reported use among nursing students in Morocco.,Background: Generative artificial intelligence, including ChatGPT, is making its way into nursing education, bringing both potential benefits and risks.,Design: Cross-sectional study using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model extended to include trust.,Methods: An online questionnaire was administered from February to July 2026 . Data were analyzed using partial least squares structural equation modeling.,Results: The model explained 71.2% of the variance in intention and 35.3% of the variance in reported use. Intention was positively associated with hedonic motivation (β = 0.313), performance expectancy (β = 0.276), habit (β = 0.189), trust (β = 0.178), and social influence (β = 0.135) (all p < 0.001), but not with effort expectancy or facilitating conditions. Reported use was associated with intention (β = 0.292), habit (β = 0.244), and facilitating conditions (β = 0.154; p = 0.017).,Conclusions: In this convenience sample, intention to use ChatGPT was associated with hedonic motivation, performance expectancy, habit, trust and social influence, with small effect sizes; the cross-sectional design does not establish causality. Multicenter and longitudinal studies are warranted.