Background: Mobile phones with internet access have become a necessity in today’s world. An increasing number of students have been buying and using smartphones across developed and developing nations. With the growing popularity and affordability of these gadgets, there is a rising concern over the problematic usage of mobile phones, an entity which is catching up in today’s technology-driven society. Excessive dependence on digital media has started to reveal its burgeoning side effects on the psychophysiological milieu of the students.
Aims and Objectives: The objectives of the study were (1) to assess the perception levels of medical students about problematic internet usage, (2) to study the effect of problematic internet usage on depression, stress, and anxiety quotients, and (3). to study the effect of problematic internet usage on heart rate and blood pressure (BP) during digital time out.
Materials and Methods: A cross sectional study design was used to conduct the study among the students of a medical college. Semi-structured, pre-tested questionnaires were developed and administered to the study population after obtaining informed consent. The questionnaire consisted of socio-demographic details of the medical students, questions based on pattern of internet usage and perception of problematic usage. Chen’s Internet Addiction Scale (CIAS) and depression, anxiety, and stress scale 21 Scale were used to assess internet addiction (IA) and depression, anxiety, and stress levels, respectively. Physiological parameters such as heart rate and BP components were recorded with the fully automated digital BP monitors certified by European Hypertension Society. Data were tabulated using Microsoft Excel 2010 and SPSS software (Version 24). P â‰¤ 0.05 was considered statistically significant.
Results: The total prevalence rate of IA was 44%, out of which female students had higher scores (52%) compared to males (31%). About 85% were aware of the entity “problematic internet usage.” There was a significant correlation r (199) = 0.538 between IA and stress with P = 0.0001. A marginally significant correlation r (199) = 0.472 was found between IA and depression with P = 0.11. A positive trend was seen between IA and anxiety, r (199) = 0.443 but it was not significant (P = 0.73). There was no significant correlation between IA score and basal physiological variables such as heart rate and BP. However, during digital time out, there was a net 3.7% increase in heart rate which was statistically significant . 3.2% increase in systolic BP and 0.5% decrease in diastolic BP during digital time out, which were not statistically significant.
Conclusion: Mobile phones with internet, influence medical students’ lives in numerous ways. The difference in prevalence rates of IA is largely due to the different scales used for assessment. Significant psychological and physiological changes are associated with problematic internet usage. The medical curriculum should include “problematic internet usage” during the introductory year of the course so as to expose the students to this entity and improves their perception level regarding the problem. This study proposes early recognition and implementation of rehabilitation measures to prevent medical students from getting severely addicted to internet.
Digital Time Out; Internet; Psychophysiological Parameters; Medical Students
Predicting Residence Time of GPCR Ligands with Machine Learning.
Potterton A, Heifetz A, Townsend-Nicholson A
Methods in molecular biology (Clifton, N.J.). 2022; 2390(): 191-205
Geographic distribution and time trend of human exposure of Di(2-ethylhexyl) phthalate among different age groups based on global biomonitoring data.
Qu J, Xia W, Qian X, Wu Y, Li J, Wen S, Xu S
Chemosphere. 2022; 287(Pt 2): 132115
First, do no harm: impact of the transition to an integrated curriculum on medical knowledge acquisition of the transitional cohort.
Nackers K, Tatar R, Cowan E, Zakowski L, Stewart K, Ahrens S, Jacques L, Chheda S
Medical education online. 2022; 27(1): 2007561
Physical and chemical properties of edamame during bean development and application of spectroscopy-based machine learning methods to predict optimal harvest time.
Yu D, Lord N, Polk J, Dhakal K, Li S, Yin Y, Duncan SE, Wang H, Zhang B, Huang H
Food chemistry. 2022; 368(): 130799
Implementing a graduate medical education anti-racism workshop at an academic university in the Southern USA.
Simpson T, Evans J, Goepfert A, Elopre L
Medical education online. 2022; 27(1): 1981803