Introduction: Medical students who take intellectually challenging coursework have elevated stress levels, which may have a detrimental effect on both their study performance and general well-being. This study aims to investigate the interpreted stress levels among clinical undergraduates and the therapeutic potential of physical activity in stress reduction and mental well-being by using physical activity as a predictor of mental health. Design and methods: Several medical colleges in Pakistan participated in a cross-sectional study. The Brief Symptom Inventory-18 scale, the Perceived Stress Scale, and the International Physical Activity Questionnaire were employed to gather information from medical undergraduates in order to assess their mental health profile, perceived stress level, and physical activity status. Results: The online survey was completed by 291 students. The mean score for physical activity was 0.247 (0.432). Three mental health profiles were found: 4.46% were extremely distressed ( n = 13), 3.09% were moderately distressed ( n = 9), and 92.4% were relaxed ( n = 269). Similarly, four stress level profiles – low stress (6.87%, n = 20), fairly stressed (40.5%, n = 118), moderately stressed (48.45%, n = 141), and extremely stressed (4.12%, n = 12) – were examined. Undergraduate females had higher levels of stress (mean score = 1.51) than male co-workers (mean score = 0.146). Out of 291 respondents, 24.7% were moderately active ( n = 72) and 75.2% were physically inactive ( n = 219). They all declined to be physically active. Gender and physical activity were found to be positively correlated. Physical activity was negatively associated with stress and mental health. Conclusion: The data indicate that medical undergraduates have a high perceived stress level and involve themselves in scant physical activity routinely. In order to control their stress levels, physical activity must be incorporated into their daily schedule. For the well-being of medical undergraduates, it is also strongly advised that they receive therapy, educational support, and a less workload.

BackgroundArtificial Intelligence (AI) in clinical decision support systems (CDSS) has become an essential tool in improving patient outcomes, enhancing diagnostic accuracy, and assisting in treatment planning. However, healthcare professionals’ perceptions and accessibility to AI-powered CDSS vary across different roles, impacting their effectiveness. Understanding how clinicians, physicians, and nurses interact with AI can provide valuable insights for improving AI integration in hospitals. ObjectiveTo evaluate the perception, accessibility, and practical use of AI-powered CDSS among clinicians, physicians, and nurses in a hospital setting, focusing on how these factors influence the overall adoption and effectiveness of AI. MethodsA cross-sectional survey was conducted in a hospital setting in Sheikhupura, Pakistan, over three months (Feb 2024 to Apr 2024). A total of 54 participants were divided into three groups: clinicians (n=18), physicians (n=18), and nurses (n=18). Data was collected using a structured questionnaire assessing perception (positive/negative), accessibility (easy/complex), and beneficiaries of AI (yes/no). Descriptive statistics, chi-square tests, and ANOVA were used for data analysis, performed using SPSS version 25. ResultsClinicians showed the highest positive perception of AI at 83.3% (15/18), compared to 77.8% (14/18) for physicians and 55.6% (10/18) for nurses. AI accessibility was reported as easy by 66.7% (12/18) of clinicians, 55.6% (10/18) of physicians, and 44.4% (8/18) of nurses. Beneficiaries of AI were 72.2% (13/18) of clinicians, 66.7% (12/18) of physicians, and 50% (9/18) of nurses. Statistically significant differences were observed among the groups (p < 0.05). ConclusionThe study demonstrated that while clinicians and physicians generally have a positive perception and easier access to AI, nurses experience more challenges in both areas. Targeted interventions, including training and support, are essential to improving AI accessibility and perception across all healthcare professional groups for optimal clinical decision-making.

Objectives To estimate Global, Regional, and National prevalence of Malnutrition, specifically Coexisting forms of malnutrition (CFM) and its various types: Coexistence of underweight with stunting (CUS), Coexistence of underweight with wasting (CUW), Coexistence of underweight with wasting & stunting (CUWS), Coexistence of stunting with overweight/obesity (CSO) among children under five years in low- and middle-income countries (LMICs). Methods This cross-sectional observational study utilized latest nationally representative Demographic and Health Surveys (DHS) datasets of 62 LMICs corresponding to six global regions from 2006 to 2024. Data of 541,707 children aged 0 to 59 months with complete anthropometry were analysed descriptively (prevalence estimates) and inferentially (multivariate logistic regression). Results The global malnutrition prevalence among children was 43.9%, of which CFM was observed among 20.9% children. Among various CFM types, CUS was highly prevalent (11.8%), followed by CUW (4.2%), CUWS (3.2%), and CSO (2.1%). South & Southeast Asian had highest CFM prevalence of 29.6%, while Central Asia and Latin America & Caribbean reported the lowest CFM prevalence of 8.1% and 6.2%, respectively. Among all the LMIC included, Timor-Leste exhibited the highest CFM at 41.8%. In general, children aged between 12 to 35 months had 2-3 times higher odds of various forms of CFM. However, female sex, maternal education, improvement in socioeconomic status, medium to large family size showed significantly lower odds with various forms of CFM. Conclusions This study advances the understanding of CFM’s prevalence, determinants, and regional variations, filling a critical gap in global nutrition research. The findings serve as a reminder to reinvest in efforts to protect children from malnutrition during their early years of life. Governments and other global health sector must invest in a well-established system of nutrition surveillance for addressing CFM, informing targeted interventions to improve child health outcomes in LMICs.

1. For over a century, the Bacillus Calmette – Guérin (BCG) vaccine, derived from an attenuated strain of Mycobacterium bovis, has been the primary prophylactic intervention against Tuberculosis gl...