Smartphone addiction, sleep quality, depression, anxiety, and stress among medical students

IntroductionStudies consistently link excessive smartphone use to poor sleep quality, depression, anxiety, and stress. This study specifically aimed to investigate these associations among medical students in Belgrade and Nis (Central Serbia).Materials and methodsThe cross-sectional study included a sample of 761 students, who were selected from both the Faculties of Medicine at the University of Belgrade and the University of Nis. Questionnaires, including the International Physical Activity Questionnaire – Short Form (IPAQ-SF), Smartphone Addiction Scale – Short Version (SAS-SV), the Pittsburgh Sleep Quality Index (PSQI), and the Depression, Anxiety, and Stress Scale – 21 items (DASS-21), were completed by the participants. Statistical analysis techniques, such as the Chi-square test, student’s t-test, and logistic regression, were employed to examine the relationship between smartphone addiction, physical activity, sleep quality, depression, anxiety, and stress.ResultsThe findings indicated a prevalence of smartphone addiction among medical students at 21.7%, with rates of 22.9% among males and 21.1% among females. Females exhibited significantly higher scores on the SAS-SV scale compared to males (p = 0.032). Univariate logistic regression analysis revealed significant associations between smartphone addiction and spending over 4 h daily on smartphones (OR = 2.39; p < 0.001), poor sleep quality (OR = 1.65; p = 0,005), as well as elevated levels of stress (OR = 1.75; p = 0.003), anxiety (OR = 2.04; p < 0.001), and depression (OR = 2.29; p < 0.001). Multivariate regression analysis identified spending more than 4 h daily on smartphones (OR = 2.39; p < 0.001) and increased levels of depression (OR = 2.51; p < 0.001) as independent significant factors associated with smartphone addiction.ConclusionThis study sheds light on the prevalence of smartphone addiction among medical students, with spending excessive time on smartphones and higher levels of depression standing out as significant factors. Future research should delve into the underlying mechanisms and causal relationships between smartphone addiction and these psychosocial factors. Understanding these connections will aid in developing effective interventions and strategies to tackle this growing public health concern

An Optimized Checkerboard Method for Phage-Antibiotic Synergy Detection

Phage-antibiotic synergy is a promising therapeutic strategy, but there is no reliable method for synergism estimation. Although the time-kill curve assay is a gold standard, the method is not appropriate for fast and extensive screening of the synergy. The aim is to optimize the checkerboard method to determine phage-chemical agent interactions, to check its applicability by the time-kill curve method, and to examine whether the synergy can be obtained with both simultaneous and successive applications of these agents. In addition, the aim is to determine interactions of the Pseudomonas phage JG024 with ciprofloxacin, gentamicin, or ceftriaxone, as well as the Staphylococcus phage MSA6 and SES43300 with ciprofloxacin, gentamicin, and oxacillin. The results show that the optimized checkerboard method is reliable and that results correspond to those obtained by the time-kill curve. The synergy is detected with the phage JG024 and ciprofloxacin or ceftriaxone against Pseudomonas aeruginosa, and the phage SES43300 with ciprofloxacin against MRSA. The synergy was obtained after simultaneous applications, and in the case of P. aeruginosa, after application of the second agent with delay of one hour, indicating that simultaneous application is the best mode of synergy exploitation for therapy. The checkerboard method can be used for thorough clinical studies on synergy and in the future for personalized therapy when infections are caused by multiple resistant bacteria