Medical students experience extensive pressure during their undergraduate courses. Given the complex associations between psychological factors in association with academic pressure. We investigated the study with objectives: To examine psychological factors related to academic pressure by analysing interactions between ‘study motivation’, ‘study environment’, ‘study conditions’, ‘teacher quality’, ‘training programme’, ‘management system’, ‘evaluation’, and ‘extracurricular activities’ using a network analysis approach. A total of 878 medical students majoring in general medicine from the first, third, and fifth years of a six-year course at the largest medical university in central and highland regions of Vietnam were involved in this cross-sectional study. The approach used was convenient cluster sampling with a self-administered questionnaire by the participants. Network analysis for pairwise correlations between psychological factors was estimated . Important factors in the network analysis were calculated using centrality indices including node strength (S), closeness (C), and betweenness (B). The higher score of S, C, and B indicate the more importance of the node. The results obtained from the network analysis of eight psychological factors showed that ‘teaching quality’ was mostly connected with other factors overall, while the ‘training programme’ was seen in both genders and freshman students. ‘Study conditions’ and ‘training programme’ were mostly connected with other factors in junior and senior students, respectively. The strong pairwise correlation was confirmed: management system and evaluation activity, followed by study environment and study conditions, and teaching quality and training programme. Additionally, nodes with high centrality were shown to be ‘management system’ (S = 0.97, C = 0.019, B = 1), and ‘training programme’ (S = 0.96, C = 0.021, B = 4). Our study findings indicate that satisfaction with the training programme amongst eight psychological factors is the most important factor affecting academic pressure among medical students. The training programme is linked with teaching quality, whereas the management system is correlated with evaluation activity.
Purpose: The current study aimed to use network analysis to investigate medical and health students’ readiness for online learning during the coronavirus disease 2019 (COVID-19) pandemic at the University of Medicine and Pharmacy, Hue University.Methods: A questionnaire survey on the students’ readiness for online learning was performed using a Google Form from May 13 to June 22, 2021. In total, 1,377 completed responses were eligible for analysis out of 1,411 participants. The network structure was estimated for readiness scales with 6 factors: computer skills, internet skills, online communication, motivation, self-control, and self-learning. Data were fitted using a Gaussian graphical model with the extended Bayesian information criterion.Results: In 1,377 students, a network structure was identified with 6 nodes and no isolated nodes. The top 3 partial correlations were similar in networks for the overall sample and subgroups of gender and grade levels. The self-control node was the strongest for the connection to others, with the highest nodal strength. The change of nodal strength was greatest in online communication for both gender and grade levels. The correlation stability coefficient for nodal strength was achieved for all networks.Conclusion: These findings indicated that self-control was the most important factor in students’ readiness network structures for online learning. Therefore, self-control needs to be encouraged during online learning to improve the effectiveness of achieving online learning outcomes for students.
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