|Year : 2016 | Volume
| Issue : 2 | Page : 80-87
The impact of social media volume and addiction on medical student sleep quality and academic performance: A cross-sectional observational study
Saad Mohammed Al Suwayri
Department of Internal Medicine, College of Medicine, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia
|Date of Submission||20-Dec-2016|
|Date of Acceptance||10-Jun-2017|
|Date of Web Publication||21-Aug-2017|
Saad Mohammed Al Suwayri
Department of Internal Medicine, College of Medicine, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), P.O. Box 7544, Riyadh
Kingdom of Saudi Arabia
Source of Support: None, Conflict of Interest: None
Problem Statement: Social media use may be detrimental to sleep quality, self-esteem, and mental health and may affect academic performance in medical students. However, the effects of problematic social media use on sleep quality and academic performance in medical students are unknown.
Approach: A total of 170 medical students in a Saudi Arabian medical school were studied. The relationships between social media use volume (duration of use per day) and addiction (measured using the Bergen Facebook Addiction Scale) of seven platforms and (i) quality of sleep measured using the Pittsburgh Sleep Quality Index and (ii) academic performance according to the grade point average were examined. Caffeine intake was considered as a potential confounder, and data were analyzed using uni- and multi-variable logistic regression.
Results: Poor quality sleep (72.9% and 63.5% during the week or at the weekend, respectively) and social media addiction (27.1% addicted to three or more platforms) were common. Individuals with high-volume WhatsApp (odds ratio [OR] 1.59 [1.20–2.10], P = 0.001) and Snapchat (OR 1.41 [1.10–1.81], P = 0.007) use were more likely to have very poor sleep quality at the weekend, the latter persisting in multivariable analysis. Students who were addicted to Snapchat (OR 2.53 [1.03–6.22], P = 0.044) or who were addicted to three or more social media platforms (OR 2.93 [1.19–7.23], P = 0.019) had an even greater risk of very poor weekend sleep quality. Social media addiction was not associated with academic performance.
Conclusions/Recommendations: Educational programs on sleep and social media hygiene and changes to class start times to prevent weekend sleep debt should be considered.
Keywords: Bergen Facebook addiction scale, caffeine, facebook, grade point average, Pittsburgh sleep quality index, snapchat, social media, YouTube, WhatsApp
|How to cite this article:|
Al Suwayri SM. The impact of social media volume and addiction on medical student sleep quality and academic performance: A cross-sectional observational study. Imam J Appl Sci 2016;1:80-7
|How to cite this URL:|
Al Suwayri SM. The impact of social media volume and addiction on medical student sleep quality and academic performance: A cross-sectional observational study. Imam J Appl Sci [serial online] 2016 [cited 2020 Oct 30];1:80-7. Available from: https://www.e-ijas.org/text.asp?2016/1/2/80/213393
| Background|| |
The sleep-wakefulness cycle is known to be in part regulated by endogenous neurochemistry and the output of circadian rhythms. However, the timing and quality of sleep and its cycling are also highly dependent on exogenous environmental (e.g., caffeine, alcohol, and sleep medication) and medical (e.g., sleep apnea and depression) factors. High-quality sleep is essential for maintaining mental and physical health, with poor sleep quality and sleep disorders associated with chronic diseases such as type II diabetes and cardiovascular disease and cognitive performance. This is particularly true for medical students, who are known to be at particular risk for different types of sleep-related problems including sleep deprivation, poor quality sleep,,,,, and excessive daytime sleepiness.,, Since poor sleep quality and daytime sleepiness have been associated with poor academic performance in some studies,,,, understanding the factors that contribute to poor sleep quality is important so that students can make proactive and informed lifestyle choices that have a positive impact on their medical training and quality of life.
Social media has been defined as “a collection of software that enables individuals and communities to gather, communicate, share, and in some cases collaborate or play.” Social media use has grown rapidly over recent years, facilitated by the widespread availability of low-cost smartphones. Saudi Arabia is one of the largest social media markets in the world, accounting for nearly half of the 5.8 million Twitter users in the Arab world (March 2014) and the highest per-capita YouTube usage globally. Although some data suggest that smartphone use by college students may increase depression and anxiety and reduce sleep quality  and that general internet addiction and insomnia may contribute to depression, much less is known about the association between social media use and sleep quantity and quality and there have be no studies on social media use and sleep quality in medical students. In young adults and adolescents, social media use is associated with nearly twice the risk of sleep disturbance in the heaviest users compared with the lightest users  and with poorer sleep quality, lower self-esteem, and higher levels of anxiety and depression.
Given this knowledge gap, we investigated the relationship between social media use in terms of both volume (duration of use per day) and addiction (measured using the validated short Bergen Facebook Addiction Scale) of seven social media platforms and (i) quality of sleep measured using the Pittsburgh Sleep Quality Index (PSQI) and (ii) academic performance according to grade point average (GPA) in medical students in a Saudi Arabian medical school. Since caffeine is known to have a negative effect on sleep and circadian rhythm in both epidemiological and experimental studies, caffeine consumption was also assessed as a potential confounder. We establish that poor quality sleep and social media addiction are common in medical students and that prolonged daily use and addiction to particular social media platforms increase the risk of very poor sleep quality at the weekend.
| Methods|| |
This cross-sectional observational study was conducted between January and March 2016 at the College of Medicine, Al Imam Mohammed Ibn Saud University, Saudi Arabia. All medical students were invited to participate. The authors explained the study objectives and protocol to the medical students. All 645 students in the College of Medicine were asked to complete a self-administered online questionnaire. Participation was voluntary, anonymous, and unpaid. The College of Medicine Institutional Review Board approved the study protocol. Classes usually start at 07:30–08:00.
The questionnaire [Supplemental Material] [Additional file 2] was designed based on the study objectives and previously published survey instruments to assess: (i) study population demographics; (ii) social media usage; (iii) caffeine usage; (iv) sleep quality; and (v) academic performance. Basic demographics included participant age, height, weight, sex, and year of study.
Social media use
Two social media use variables were assessed with multiple items to measure (i) volume and (ii) addiction for seven networking sites: Facebook (Facebook Inc., Menlo Park, California, USA), YouTube (Google Inc., San Bruno, CA, USA), Twitter (Twitter Inc., San Francisco, CA, USA), WhatsApp (WhatsApp Inc., Mountain View, CA, USA), Instagram (Facebook Inc.,), Snapchat (Snapchat Inc., Venice, CA, USA) and Telegram Messenger (Berlin, Germany).
Volume was assessed according to the total number of minutes of social media network use per day: Never, <15 min/day, 15–30 min/day, 31–60 min/day, 61–120 min/day, 121–180 min/day, or over 180 min/day. In addition, participants were asked whether their social media use was predominantly in the daytime, in both the daytime and at nighttime, or mostly in the evenings/at bedtime.
Addiction was assessed using the well-validated modified six-item Bergen Facebook addiction scale as proposed by Andreassen et al., a self-reported instrument measuring six core items of addiction in the preceding year: salience, tolerance, mood modification, relapse, withdrawal, and conflict. All items were scored on the following scale: (1) very rarely; (2) rarely; (3) sometimes; (4) often; (5) very often. Addiction rates were calculated according to Lemmens et al., where a score of 3 or more on at least four items was regarded as addicted. Since medical students are known to use different types of social media for educational purposes, participants who reported using social media for >50% of total activity for educational purposes were not considered as addicted and were excluded from the addicted group.
Sleep quality was assessed using the well-validated PSQI.,, The PSQI consists of 19 items measuring seven sleep pattern domains: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction. The PSQI seeks to determine sleep quality on the majority of days over the preceding month, but since weekday and weekend sleep patterns of medical students are markedly different due to different routines and class start times during the week, participants were asked to report weekday and weekend sleep times separately. A PSQI score >5 was considered as poor quality sleep as in the original publication and a PSQI score of >10 was considered as very poor quality sleep.
Caffeine intake was measured as approximate number of caffeinated drinks (coffee, tea, cola, caffeine (“energy”) drink (e.g., “Redbull”) per day scored as (0) none, (1) one cup/drink; or (2) two or more cups/drinks. Scores were summed for each participant and a score of 0 was considered as no caffeine intake, 1–3 as mild-moderate caffeine intake, and ≥4 as high intake.
Academic performance was assessed according to the self-reported GPA (APD) out of 5, a common measure of academic performance. Academic performance was stratified as “excellent” (GPA ≥4.5), “above average” (GPA <3.75–4.49), “average” (GPA <2.75–3.74), or “below average” (GPA <2.74/5).
Four outcomes were investigated and assessed: (i) poor quality sleep at the weekend; (ii) very poor quality sleep at the weekend; (iii) poor quality sleep during the week; (iv) very poor quality sleep during the week; and (v) GPA.
Participant demographics were analyzed using descriptive statistics with means (±standard deviation) or medians (± interquartile ranges for continuous variable depending on the data distribution and counts (with percentages) for categorical variables. Differences between weekend and weekday PSQI scores were assessed using the Mann–Whitney U-test. To design the most appropriate multivariable model for each outcome variable, univariable logistic regression analysis was first carried out for each explanatory variable. Variables with a P < 0.05 were then used in a multiple logistic regression model. Odds ratios (ORs) were calculated with 95% confidence intervals. The value of P < 0.05 was considered statistically significant. All analyses were performed using IMS SPSS Statistics version 23 (IBM, Chicago, IL, USA).
| Results|| |
The demographics of the study participants are shown in [Table 1]. Out of 645 students, 170 students completed the survey (response rate 26.3%). All participants completed all questions. Participants were more commonly male (65.3%), nonsmokers (84.1%), and although not evenly distributed, there were participants from all academic years.
|Table 1: Participant demographics, caffeine consumption, sleep quality, and academic performance|
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Social media volume and addiction
Details of social media use are shown in [Table 2]. Only one participant did not use social media at all (0.6%), with all other participants using three or more different social media platforms. WhatsApp and Snapchat were the most commonly used instant messaging platforms (99.4% and 87.1%, respectively), and the YouTube video sharing site was also used by 93.5% of all students each day. However, Facebook (26.5%), Telegram (41.8%), and Instagram (70.6%) were less popular. In terms of the amount of use per day (volume), <10% of participants used each social media site for >180 min/day with the exception of WhatsApp, which was used for >180 min/day by 20.0% of students.
The majority of students (82.4%) used social media during both the daytime and in the evening/at night, with only 1.8% using it solely during the day and 15.9% exclusively in the evenings/at night. In terms of addiction, participants were most commonly addicted to Snapchat (41.2%) and WhatsApp (31.2%), although addiction to Twitter (30.6%) and Instagram (28.2%) were also common. Thirty percent of participants reported no addiction to social media and the majority of students reported only one addiction (24.7%). However, over a quarter (27.1%) of students reported three or more addictions to different social media platforms.
Although approximately one-half of students drank at least one cup of coffee (53.5%, daytime), tea (49.4%, evening), or cola (40.0%) at some point during day, caffeinated (“energy”) drink use was very uncommon (<5% of participants) at any time of the day [Table 1]. 7.1% of participants had high caffeine intake during the day, 10.6% had high caffeine intake during the evening/at night, and 17.1% of participants had high overall caffeine intake.
The median PSQI at the weekend was significantly lower than during the week (6.5 [5–9] vs. 7.0 [5–10]; P < 0.001); therefore, sleep quality during the week and at the weekend were considered separately [Table 1]. During the week, 72.9% of participants experienced poor quality sleep, and 22.9% of participants experienced very poor quality sleep. At the weekend, fewer students experienced poor quality (63.5%) or very poor quality (13.5%) sleep.
Of the 170 students, 17.6% had excellent, 44.1% above average, 28.8% average, and 9.4% below average academic performances. Academic performance was not associated with sleep quality either at the weekend (P = 0.405) or during the week (P = 0.889).
Impact of social media use on sleep quality and academic performance
There were few associations between demographic, social media, or caffeine intake variables and poor sleep quality either during the week or at the weekend or very poor sleep quality during the week in the univariable analysis [[ Table 3] and Table S1 in Supplemental Material] [Additional file 1]. However, female (OR 0.28 [0.11–0.70], P = 0.007), younger (OR 0.75 [0.58–0.96], P = 0.024), shorter (OR 0.93 [0.88–0.98], P = 0.006), and lighter (OR 0.96 [0.95–0.99], P = 0.010) participants were more likely to have very poor sleep quality at the weekend. Individuals who used WhatsApp (OR 1.59 [1.20–2.10], P = 0.001) and Snapchat (OR 1.41 [1.10–1.81], P = 0.007) were more likely to have very poor sleep quality, as were those addicted to Snapchat (OR 2.53 [1.03–6.22], P = 0.044) or who had more than three addictions (OR 2.93 [1.19–7.23], P = 0.019). Drinking cola during the day was weakly negatively associated with very poor sleep quality at the weekend (OR 0.31 [0.10–0.99], P = 0.050). In multivariable analysis, the time spent using Snapchat each day was associated with increased odds of very poor sleep quality at the weekend (OR 1.68 [1.13–2.48], P = 0.010).
In univariable analysis, females (OR 0.42 [0.21–0.83], P = 0.013) who were younger (OR 0.81 [0.70–0.94], P = 0.006), lighter (OR 0.98 [0.97–0.99], P = 0.005) or nonsmokers (OR 0.43 [0.19–0.99], 0.047) were more likely to have better academic performance. Furthermore, lower daytime tea (OR 0.51 [0.29–0.87], P = 0.014), evening tea (OR 0.61 [0.38–0.97], P = 0.037), evening cola (OR 0.60 [0.38–0.94], P = 0.028), and total daytime caffeine (OR 0.77 [0.60–0.98], P = 0.036) consumption were associated with better academic performance. However, none of these variables were significant in multivariable analysis and social media use was not associated with academic performance.
| Discussion|| |
Here, we report the associations between problematic social media use, sleep disturbance, and academic performance in a cross section of medical students. We show that individuals who used WhatsApp or Snapchat for a greater proportion of the day were approximately 1.5-times more likely to have very poor sleep quality at the weekend, the latter persisting in multivariable analysis. Students who were addicted to Snapchat or who were addicted to three or more social media platforms had an even greater risk of very poor weekend sleep quality (2.3-and 3-times, respectively). Although social media use and addiction were not associated with academic performance, we confirm the results of previous studies of a positive association between being female and academic performance, including in Saudi Arabia.
This is the most comprehensive study of social media usage in medical students. In a 2014 study of social media addiction in health sciences students, YouTube was most commonly used (100%) followed by Facebook (91.4%) and Twitter (70.4%). We also established that YouTube and Twitter (but not Facebook) were commonly used by medical students (93.5% and 83.5%); however, WhatsApp and Snapchat, which were not studied by Masters, were the most common social media platforms used in our study, reflecting the rapid evolution in different platforms and their variable uptake in different socioeconomic and geographic populations. Despite the difference in social media platforms studied, addiction rates were similar (4.1%–41.2%). Furthermore, over a quarter of all students reported addiction to three or more platforms, a relatively high proportion of students. Given that social media addiction has also been reported to be associated with low self-esteem and psychiatric symptoms,, our results may indicate that a relatively high proportion of medical students may be at risk from new types of harm related to modern technologies in addition to their existing predisposition to psychological distress, emotional exhaustion, and burnout.
Our findings that the volume of WhatApp or Snapchat use was associated with about a 1.5-times increased odds of very poor sleep quality at the weekend is consistent with recent findings that heavy social media use (defined as >121 min/day) was associated with a nearly 2-times risk of sleep disturbance in young adults aged 19–32. Two other studies on the effect of social media use on sleep have revealed a negative effect on sleep parameters including time taken to fall asleep, delayed bedtime, and reduced total sleep time,, and a very recent study of adolescents showed that social media use–especially at night– was associated with poorer sleep. Although there are few studies with respect to social media addiction, a study of over 400 Peruvian students revealed an association between Facebook dependence and poor sleep quality (also assessed via the PSQI).
We found that some platforms were associated with very poor sleep, suggesting that different types of social media platform or the way in which they are used may have different effects on sleep. Social media may disturb sleep in one of three ways: (i) by directly reducing the number of hours of sleep, for instance by direct messaging friends with Snapchat late into the night; (ii) by promoting neurological, emotional, or physiological arousal, such as by viewing disturbing videos on YouTube just before sleep; or (iii) from disturbed circadian rhythms caused by the light emitted by the device. Indeed, it has been shown that the proximity of digital media use to bedtime is associated with negative effects on sleep, particularly in the preceding two hours, and that night-time specific social media use is more strongly related to poor sleep than overall social media use. Here, we found that WhatsApp and Snapchat, which are predominantly direct messaging platforms used to communicate between individuals or small groups, were most associated with very poor weekend sleep. Given the active nature of the communication (between individuals known to each other) rather than passive consumption of videos (via YouTube), it is likely that these platforms, when consumed on mobile devices, are likely to impact on all three sleep disturbance mechanisms.
The overall very high levels of poor sleep quality (72.9% during the week and 63.5% at the weekend) in medical students are consistent with previous studies reporting poor sleep quality in up to 77% of students.,, The difference between weekday and weekend sleep quality was not unexpected since the weekday routine of medical students is dictated by university schedules (such as first classes at 07:30). This is known to result in a need to make up for “sleep debt” at the weekend, and it has been reported that students attending later classes are more likely to attain adequate sleep levels during the week and not require compensatory sleep at the weekend. Given the prevalence of poor sleep quality, especially during the week, it is therefore unsurprising that the effects of different variables on sleep quality were only apparent at the weekend; this has been observed in similar studies, justifying the analysis of these endpoints in the current study. Although not significant in multivariate analysis, similar associations between being female and poor sleep quality have previously been reported.
There were no significant associations between sleep quality and academic performance measured using the GPA, consistent with the ambiguous results reported elsewhere. For instance, a study of Malaysian biomedical science students failed to find an association between total hours of sleep and GPA, and PSQI and academic performance were not associated in a study of Saudi Arabian medical students. However, others have shown that hours slept is the most significant predictor of GPA, and Cates et al. reported that poorer sleep quality measured using the PSQI was more common in pharmacy students with a lower GPA. These discrepancies are consistent with our negative findings between sleep quality and academic performance. Similarly, although caffeine is often consumed by medical students to enhance cognitive performance, we found that lower caffeine use was generally associated with better GPA scores in univariate analysis. However, this is likely to have been due to the overall lower caffeine consumption in females versus males in this cohort (χ2 test P = 0.04).
This study was strengthened by the use of two validated questionnaires. All participants completed the online questionnaire thoroughly. However, this study also has a number of limitations. This was a self-selecting population of only 170 students with a relatively low response rate of 26.3%; there is, therefore, a high probability of selection bias. The study design was cross-sectional, and hence the information on social media use, sleep, and academic performance were collected at the same time, limiting the interpretation of causality. Since the participants were asked to recall information, some of which was subjective, over the previous month and year, the data may be influenced by recall bias. Our collection of demographic details was relatively limited, so there may well have been other factors that ultimately influenced the endpoints of interest.
| Conclusions|| |
We can report that poor quality sleep and social media addiction is very common in medical students and that prolonged daily use and addiction to certain social media platforms– particular those that involve direct messaging-increase the risk of very poor sleep quality at the weekend. Since poor sleep is associated with ill health and there is emerging evidence that social media use itself may be associated with psychiatric morbidity, there may be room to introduce educational programs on sleep and social media hygiene and change class start times to prevent the build-up of sleep debt at the weekend.
The author would like to thank all the students that participated in this study by responding to the questionnaire. The author received no financial support for this research and authorship of this article and there are no conflicts of interest.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]