| Objective: The present study aimed to predict internet addiction based on general self-efficacy,
difficulty in emotion regulation, and resilience in medical students.
Methods: This was a cross-sectional study. The statistical population included all medical
students of Shahid Beheshti University of Medical Sciences. The research sample consisted of 96
medical students selected by random sampling method in 2018. Data collection was performed by
Sherer General Self-Efficacy Scale, Gramat’s and Roemer’s Difficulties in Emotion Regulation
Scale, Connor–Davidson Resilience Scale, and Young’s Internet Addiction test.
Results: To analyze the obtained data, Pearson’s correlation coefficient and the stepwise
regression model were used. The obtained results suggested a significant relationship between
internet addiction and general self-efficacy, difficulty in emotion regulation, and resiliency
(P<0.05). Additionally, general self-efficacy, difficulty in emotion regulation, and resilience are
able to predict 27% of internet addiction variance in medical students.
Conclusion: To prevent and reduce the harm of internet addiction in students in stressful events,
they should be trained to improve their resilience, self-efficacy, and emotion regulation skills. |