The Effect of Social Media / Smartphone Addiction and Sleep Quality on Academic Success: A Retrospective Study in Pre-Clinic Medical Faculty Students

Objective: The aim of this study was to evaluate the effects of smartphone / social media use and sleep related variables on academic achievement in pre-clinical medical students.

Material and Methods: 226 students receiving pre-clinical medical education at the same institution were included in the study. All participants completed the Pittsburg Sleep Quality Index (PSQI), Social Media Addiction Scale - Adult Form (SMAS-AF), Smartphone Addiction Scale (SAS) and Personal Information Form prepared for the study. All participants were questioned Average Academic Marks (AAM).  The participants were categorized as low / medium / high risk according to the scores of smartphone addiction scale.

Results: According to the risk of smartphone addiction, the mean score of AAM of the group with low dependency risk was 71.8 ± 8, the mean score of AAM of the group with the middle risk dependency risk was 68.4 ± 8.77, and the mean score of AAM of the group with the high dependency risk was 67.4 ± 9.75. The mean scores of AAM of the low-risk group in terms of smartphone addiction were significantly higher than the high-risk group (p = 0.035). Similarly, when the total scores of the participants' social media addiction are examined; the average of the low-risk group was 40.4 ± 11.17, the average of the medium-risk group was 51.7 ± 9.2, and the average of the high-risk group was 50.8 ± 12.9. Social media addiction total scores of the high risk group in terms of smartphone addiction were significantly higher than the medium and low risk group (p <0.001). There was no significant difference between sleep times and PDQI total scores between groups. When the factors associated with AAM were analyzed by Pearson correlation analysis, a positive statistically significant relationship was detected with sleep efficiency (r = 0.19, p <0.001), while a significant negative correlation was observed with total SAS score and hours spent in bed (r = -23, p <0.001; r = -27, p <0.05, respectively). A multivariate hierarchical regression analysis model suggested that gender, sleep efficiency, SAS and SMASAF scores affected AAM.

Conclusion: Use of social media / smartphone by medical students can affect sleep habits and academic success during the period of pre-clinical education. Inclusion of training on conscious use of social media and smartphone and emphasizing the importance of sleep habits in medical education have the potential to contribute to the development of better-equipped physicians.