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1. INTRODUCTION
The internet and smartphones are two of the most popular and strongly developing electronic technology industries in Vietnam and globally. According to Internet World Stars News statistics for 2021, there were more than 5 billion internet users, accounting for 65.6% of the world’s population [1]. In addition, a smartphone is a mobile device capable of accessing the internet in any environment and at any time. According to Statista’s 2021 data, about 6.4 billion people were using smartphones, and it is estimated that by 2026, this number could reach 7.5 billion people [2]. With the strong development of smartphones and the internet, it is inevitable that people will have a high demand for these technologies. However, overuse of the internet or smartphones can lead to internet or smartphone addiction, which adversely affects user’s health [3,4], including mental disorders, depression, or the overall well-being, especially in relation to sleep [4,5].
Nowadays, the use of the internet and smartphones has become commonplace among teenagers and young adults [6,7]. According to some figures in Turkey, 96.7% of people aged 16–24 used smartphones, and 95.7% reported using the internet [8]. Many studies have also shown the relationship between internet addiction and/or smartphone addiction and their effects on sleep as well as the quality of sleep in teenagers [9–11].
In Vietnam, there have not been many studies investigating how the link between smartphone addiction and internet addiction affects sleep quality; only a few studies have shown a separate link between smartphone addiction or internet addiction and quality of sleep [12,13]. While sleep is one of the basic human activities that can affect the quality of life, its importance is often overlooked.
Students in the Faculty of Public Health at the University of Medicine and Pharmacy at Ho Chi Minh City regularly use the internet to search for documents and stay updated on current news. In addition to mobile devices, smartphones are an indispensable tool for students engaged in learning and clinical practice. Therefore, these students may be particularly susceptable to the negative of effects of internet and smartphone addiction on sleep quality.
For these reasons, the team carried out the topic “Effects of internet addiction and smartphone addiction on the sleep quality of students of the Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City in 2023” with the goal of determining internet addiction, smartphone addiction, and poor sleep quality in students of the Faculty of Public Health and the associations between internet addiction, smartphone addiction, and sleep quality in students. The results from the study will provide information to have a basis for developing solutions to help students use the internet or smartphone more appropriately, improve the quality of sleep for students, and improve student health.
2. METHODS
A cross-sectional study was conducted between March 2023 and June 2023 among a sample of full-time students enrolled in the first to sixth years at the Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City.
The study used a self-administered questionnaire that included individual characteristics and three main components of characteristics and scales for surveying Smartphone Addiction Scale-Short Version (SAS-SV) with 10 questions, Internet Addiction Test (IAT) with 20 questions, and Pittsburgh Sleep Quality Index (PSQI) with 19 questions for data collection.
The sample size estimation in this study was conducted using a formula that estimates a proportion of the population:
To ensure a 95% confidence interval (α=0.05) in the estimation of the percentage (p) of students with poor sleep quality [14] at 47.9% with a margin of error (d) of 5%, a minimum sample size (n) of 384 students was determined.
The study used a whole sample selection technique to select students enrolled in the Faculty of Public Health who were at least 18 years old. Students who used smartphones and the internet and agreed to participate in the study were selected for the research sample; in addition, students who did not complete the SAS-SV, IAT, or PSQI scales were excluded from the study.
Students were selected according to the entry and exit criteria to limit selection bias. All students who met the selection criteria for the study completed a survey using a pre-prepared self-administered questionnaire.
Variables investigated in the study include background variables: age, gender (male or female), major (Preventive Medicine, Nutrition, or Public Health), year of study (from the first year to the sixth year), academic ability (from weak to excellent), current residence (family, motel, or dormitory), and smartphone usage characteristics, and internet usage characteristics. Independent variables were smartphone addiction, internet addiction. While the outcome variable was students’ sleep quality.
The study used the SAS-SV scale of Min Kwon (2013) to consider whether or not to be addicted to smartphones [15]. The total scale score ranged from 10 to 60 points, with a cut point of 31 points for men and 33 points for women. Smartphone addiction was identified as follows:
Smartphone addiction: total SAS-SV score≥31 in men and ≥33 in women.
No smartphone addiction: total SAS-SV score<31 in men and <33 in women.
The scale has been translated into Vietnamese by the author group.
Internet addiction has been assessed on an IAT scale of 20 questions [16]. The score of each statement ranged from 1 to 5, corresponding to the following frequency categories: never, rarely, occasionally, often, always. Internet addiction has been identified as follows:
Level of internet addiction:
The quality of sleep has been assessed by the PSQI scale. The Vietnamese version of the PSQI scale was translated by author To Minh Ngoc and assessed as having a high level of reliability, with no issues or disagreements reported when used on patients in Vietnam [17]. The scale consisted of 19 questions organized into seven components. Each component had levels of 0–3 points. The general sleep quality score of seven components, raging from 0 to 21 points. The quality of sleep was assessed as follows:
The PSQI scale has been translated by Suzhou et al. and found to be reliable and valid.
The questionnaire was built with a clear, well-informed structure that was targeted, easy to understand, and easy to answer. The collected information was retested and cleaned to limit information bias.
The IAT scale is used to assess internet addiction; however, the scale only generally determines whether students are addicted to the internet, without distinguishing between different types of internet addiction.
The IAT and SAS-SV scales are translated from English to Vietnamese, so there may be some misunderstandings in the questions. However, when conducting the survey, the research team clearly explained to the participants.
Categorical variables are presented using frequency and percentage (%). The Wilson score interval method was used to calculate the 95% confidence interval (CI) for the variables “Smartphone addiction” and “Internet addition”. Continuous variables are presented as mean±SD. The Chi-square test or Fisher’s exact test was used to determine the relationship between background variables, independent variables, and outcome variables. Fisher’s exact test serves as an alternative when the expected frequency in more than 20% of cells is less than 5, or when any cell has an expected frequency of less than 1.
The study used the prevalence ratio (PR) with a 95% CI to evaluate the association between background variables, independent variables, and outcome variables. Regarding the analysis of the PSQI score, a Poisson multivariate regression model was used to control for confounding factors in the study due to its suitability for modeling count data, especially when the data are non-negative integers and the variance is approximately equal to the mean. Potential confounding factors considered in the model are grouped as follows: Background variables: age, gender (male or female), major (Preventive Medicine, Nutrition, or Public Health), year of study (from first to sixth year), academic performance (from weak to excellent), current residence (family, rental, or dormitory), characteristics of smartphone usage, and characteristics of internet usage. Independent variables: smartphone addiction, internet addiction. Outcome variable: students’ sleep quality.
The research was conducted entirely with the voluntary participation of students. All personal information and data collected were encrypted, kept confidential, and used solely for scientific research purposes. Students participating in the research were provided with comprehensive information about the content, purpose, benefits, and risks of the study. Before participating, students were given full contact information for the researcher to address any questions or complaints during their participation. The study did not record full names, contact details, or identifying information unless the student provided explicit consent. Students had the option to refuse to answer any questions or to withdraw from the study at any time during the questionnaire. Completing the questionnaire took approximately 10–15 minutes.
The study protocol was approved in terms of medical ethics by the ethics committee in biomedical research, University of Medicine and Pharmacy at Ho Chi Minh City, No. 309/HDDD-DHYD, signed on March 14, 2022.
This study adhered to the CROSS (Checklist for Reporting of Survey Studies) checklist in order to ensure the development of a comprehensive manuscript that facilitates a thorough understanding and critical evaluation by readers [18].
3. RESULTS
In 2023, the total enrollment of the Faculty of Public Health was 1,116 students. At the time of data collection, 844 students were present, of whom 94 declined to participate in the study, leaving 750 who agreed to participate in the survey. After collecting 750 survey responses, 32 students were excluded from the research due to incomplete responses to the SAS-SV, IAT, and PSQI scales. Ultimately, 718 students remained in the study sample for analysis. The response rate was approximately 88.9%.
The average age of students participating in the study was 21.3±2.0 years old, of which 32.9% were male and 67.1% were female. Preventive Medicine has the highest percentage of students participating in research, while Public Health made up the lowest. In addition, there was no significant difference in the academic year of the students participating in the study; however, the 5th and 6th years were only in Preventive Medicine, which accounted for the lowest rate in the study. Students with good academic standing had the highest rate of 52.8%. Additionally, 47.5% of students lived with their families, and students living in hostels accounted for 42.1% (Table 1).
The students participating in the study had an average smartphone use time of 7.4±2.6 years. Most students used smartphones to access social networks for learning purposes, exercise, and entertainment. Students with an average smartphone use time of 5 hours or more per day accounted for 78.3%. Most students used smartphones after waking up, of whom 89.6% had 30 minutes of use or less. In addition, 94.6% of students who used smartphones before sleeping for a duration of more than 30 minutes accounted for the highest percentage (Table 2).
| Variables | Frequency | Ratio (%) | CI 95% |
|---|---|---|---|
| Smartphone addiction | |||
| No | 378 | 52.6 | |
| Yes | 340 | 47.4 | 44–51 |
According to the SAS-SV scale, the research results showed that out of 718 students participating in the survey, there were 340 students were identified as having smartphone addiction, accounting for 47.4% with a 95% CI of 0.44–0.51 (Table 2).
Research results showed that students spent an average of 6.8±3.5 hours per day using the internet, mainly for studying, accessing social networks, and serving entertainment needs. The majority of students used mobile phones (97.2%) and personal computers (74.6%) to access the internet (Table 3).
| Variables | Frequency | Percentage (%) | CI 95% |
|---|---|---|---|
| Internet addiction | |||
| No | 324 | 45.1 | 51–59 |
| Yes | 394 | 54.9 | |
| Internet addiction level | |||
| Light-Medium | 377 | 95.7 | |
| Heavy | 17 | 4.3 |
Out of a total of 718 students participating in the study, 54.9% of students had internet addiction according to the IAT scale, with a 95% CI of 0.51–0.59, of which students with mild–moderate addiction accounted for the highest percentage (95.7%) and 4.3% had severe internet addiction (Table 3).
The average score of students’ sleep quality according to the PSQI scale was 5.2±2.9 points; the percentage of students with poor sleep quality was still relatively high (39.7% with a 95% CI: 0.36–0.43; Table 4).
| Variables | Frequency | Percentage (%) | CI 95% |
|---|---|---|---|
| Sleep quality | |||
| Sleep quality score | 5.2±2.91) | ||
| Poor sleep quality | 433 | 60.3 | 0.36–0.43 |
| Good sleep quality | 285 | 39.7 | |
Using a Poisson multivariable regression model to control for personal characteristics, smartphone addiction, and internet addiction, the results showed that there was a significant association between internet addiction and poor sleep quality. Accordingly, students with internet addiction were 1.72-times more likely to have poor sleep quality compared to students without internet addiction (p<0.001, 95% CI: 1.36–2.17). In addition, the results also recorded that the 2nd year students were 43% less likely to have poor sleep quality compared to the 1st year students (p=0.002, 95% CI: 0.40–0.81). Smartphone addiction was not associated with the poor sleep quality of students (p>0.05) (Table 5).
When considering the interaction and confounding of smartphone addiction and internet addiction on sleep quality, the results showed that smartphone addiction was not interactive and was not a confounding factor in the relationship between internet addiction and sleep quality of students (p=0.125, crude PR value=1.84, PR M-H value=1.72, difference between crude PR and adjusted PR=6.4% (<10%)) (Table 6).
However, internet addiction was noted in the study as a confounding factor in the association between smartphone addiction (crude PR value=1.44, PR M-H value=1.08, crude PR and adjusted PR=33.3% (>10%)) and students’s sleep quality, but there was no interaction with smartphone addiction (p=0.126) (Table 7).
4. DISCUSSION
The study was conducted on Public Health students at the University of Medicine and Pharmacy at Ho Chi Minh City, and the results indicated that the average age of the students in the study (21.3 years old) was consistent with the average age of students at the University of Medicine and Pharmacy at Ho Chi Minh City. The proportion of female students in the study was 67.1%, which is similar to the ratio of male and female Public Health students at the University of Medicine and Pharmacy at Ho Chi Minh City. Moreover, most students participating in the study were Preventive Medicine students, accounting for 60.6%; in addition, there was not much difference in the rate of student participation in the study in academic years (Table 1). The study found that students with good academics accounted for a high percentage, indicating that their academic performance was quite good. Most students were not dependent on their families; this is suitable for the lifestyle of students in various provinces who lived in dormitories or boarding rooms.
The average time that a student used a smartphone was high, at 7.4 years. With the development of technology, the time students have spent using phones is quite reasonable. They mainly used smartphones to access social networks, for learning, and for entertainment. The features integrated into smartphones are convenient for them anywhere, anytime, so students prefer to choose smartphones to fulfill these needs.
On average, students using smartphones daily for 5 hours or more accounted for a high percentage (78.3%), which is higher than the study of Matar [19] in Lebanon at 49.0%. In addition, the majority of students using the phone after waking up and having a use time of 30 minutes or less made up a sigificant percentage, which was higher than the research of Thao [20], with 37.6% of students using their phones between 5 to 30 minutes after waking up. Furthermore, the study also found that the percentage of students using smartphones before sleeping for more than 30 minutes was noticeable, which was quite similar to the research results of Thao [20], with the rate of using smartphones over 30 minutes accounting for 46.3%.
The average time that students used the internet daily was about 6.8 hours, which was lower than the time students used smartphones in each day. Additionally, this result was higher than the previous result in the research of Thao [21] in 2016 at the University of Medicine and Pharmacy at Ho Chi Minh City, with the main purpose of learning, entertainment, and accessing social networking sites. The means of access were mainly mobile phones and personal computers. This result was similar to the study of Kolaib [22] in 2019, showing that 95.8% of students used mobile phones to access the internet, as well as the results of the authors Hieu [23] and Kha [24] in Phu Yen, Vietnam, which also reported similar findings.
The research results showed that the percentage of students with smartphone addiction was relatively high (47.4%). This rate was quite similar to the study on smartphone addiction in India [25], which was 44.7% and higher than the percentage of students addicted to mobile phones in the study in Turkey [3] (34.6%) and of the author Thanh’s study [13](33.3%). This difference may be due to the advancement of science and technology, the introduction of new phone lines, and improved features, leading to an increased usage rate, which could contribute to a rise in the prevalence of smartphone addiction. Therefore, students need to have reasonable smartphone usage time and manage their time effectively to limit smartphone addiction and improve their health.
A remarkable record was that the rate of internet addiction among students is quite high compared to previous studies conducted on the same subject, such as the study by author Ngoc [26] at Hai Phong Medical University, where the rate of internet addiction was 38.5%; at the University of Medicine and Pharmacy at Ho Chi Minh City in 2015, by author Thanh [27], the rate was 13.9%; and in the study by Thao [21] in 2016 was 17.2%. The high rate of internet addiction can be attributed to the increasing development of the internet, the rising demand for information, and the updating of news by users. In addition, the research results showed that most students had a mild to moderate addiction to the internet, so it is necessary to implement interventions such as managing and regulating internet access time to limit excessive use, which can leadi to addiction and adversly affecting students’ health.
According to the PSQI scale, the average score of students’ sleep quality was 5.2 points; this score is lower than the study of author Thao [20] (5.58 points). Additionally, students with poor sleep quality accounted for a low percentage (39.7%), which indicates that students’ sleep quality is improving. However, there were still some problems that prevented students’ sleep, and this rate is lower than the poor sleep rate of Thao [20] (44.79%); this difference may be due to the different survey times of the studies. Furthermore, this rate is also lower than studies in India [28] (63.39%) by author Ozcan [29] (52.4%). This finding shows that the sleep quality of the students in the study was quite good, but there were still problems that were not resolved, so students need to have a reasonable evening routine to improve their sleep.
The study also recorded an interesting result: internet addiction is a confounding factor in the association between smartphone addiction and students’ sleep quality.
After controlling for potential confounding factors, the study found that internet addiction was indeed associated with students’ sleep quality, while smartphone addiction was not, indicating that students with internet addiction had worse sleep quality than students without internet addiction. This is also consistent with reports that the mechanism through which internet addiction cause sleep disturbance is long-term exposure to light emitted by electronic devices, leading to inhibition of melatonin hormone secretion, a hormone that plays an important role in sleep, thereby disrupting the human circadian clock [30]. In addition, the brain is overexcited by using the internet for a long time, which can lead to a series of sleep problems such as difficulty falling asleep, waking up easily, and poor sleep quality [31]. Moreover, the results also showed that second-year students were associated with poor sleep quality. This result is quite similar to the results of a study by author Acikgoz [32] conducted in Turkey that found that internet addiction and smartphone addiction are related to students’ sleep quality. However, the difference in the association between smartphone addiction and sleep quality in the two studies may be caused by the different sample sizes and population characteristics in each country. Another reason could be the difference in smartphones usage habits, as well as the time and purpose of using a smartphone.
Besides the results obtained, the study also has some limitations. First, the data collected were from self-completed questionnaires completed by students, which can lead to information errors due to recall. Second, the SAS-SV and IAT scale questionnaires were self-translated by the authors, so there might be some questions that students may misunderstand. Third, the IAT scale only generally assesses whether a person is addicted to the internet or not; it cannot differentiate between addiction to a smartphone and that to a desktop or other tools.
5. CONCLUSION
In summary, the study recorded that the prevalence of smartphone addiction and internet addiction among students of the Faculty of Public Health at the University of Medicine and Pharmacy at Ho Chi Minh City was quite high. In addition, the study found an association between internet addiction and the sleep quality of students but did not find an association between smartphone addiction and the sleep quality of students. With this result, the research team hopes that the school and students will gain a more comprehensive view of student’s smartphone addiction as well as internet addiction so that measures can be taken to avoid affecting the mental and physical health of students.
