|Year : 2018 | Volume
| Issue : 1 | Page : 20-28
Health-related quality of life among female university students in Dammam district: Is Internet use related?
Samar S Barayan1, Badria K Al Dabal1, Moataza M Abdelwahab2, Marwa M Shafey3, Reem S Al Omar1
1 Department of Family and Community Medicine, Medical College, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
2 Department of Family and Community Medicine, Medical College, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; Department of Biostatistics, High Institute of Public Health, Alexandria University, Alexandria, Egypt
3 Department of Family and Community Medicine, Medical College, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; Department of Community Medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt
|Date of Web Publication||5-Jan-2018|
Dr. Samar S Barayan
Department of Family and Community Medicine, Medical College, Imam Abdulrahman Bin Faisal University, P.O. Box 40010, Al-Khobar 31952
Source of Support: None, Conflict of Interest: None
| Abstract|| |
BACKGROUND: Quality of life (QOL) is defined by the World Health Organization as the individual's perception of his/her position in life, within the context of culture and system of values in which the individual lives, and as relates to his/her objectives, expectations, standards, and concerns. Life in university is so stressful; it can affect health-related QOL (HRQOL). There are many factors that affect HRQOL of university students. The aim of this study was to assess the QOL of female university students in Dammam, Saudi Arabia, and identify factors related to it, with special emphasis on Internet use.
MATERIALS AND METHODS: This cross-sectional study surveyed 2516 female students at Imam Abdulrahman Bin Faisal University in Dammam, using a self-administered questionnaire with sections on sociodemographics, score for Internet use/addiction (IA), and an assessment of HRQOL. Two latent factors were extracted: physical component summaries (PCSs) and mental component summaries (MCSs). Bivariate analyses and MANOVA were then performed.
RESULTS: The overall PCS and MCS were 69% ± 19.6 and 62% ± 19.9, respectively. Almost two-thirds of the students were found to have IA or possible IA. Students whose parents had lower education reported less PCS. Students with high family income reported higher PCS and MCS than those with a lower income. MANOVA model has shown that the higher the IA score, the lower the score of both the PCS and MCS.
CONCLUSION: HRQOL in female students was found to be affected by parental educational level, family income, and problematic Internet use.
Keywords: Internet addiction, quality of life, university students
|How to cite this article:|
Barayan SS, Al Dabal BK, Abdelwahab MM, Shafey MM, Al Omar RS. Health-related quality of life among female university students in Dammam district: Is Internet use related?. J Fam Community Med 2018;25:20-8
|How to cite this URL:|
Barayan SS, Al Dabal BK, Abdelwahab MM, Shafey MM, Al Omar RS. Health-related quality of life among female university students in Dammam district: Is Internet use related?. J Fam Community Med [serial online] 2018 [cited 2018 Jan 21];25:20-8. Available from: http://www.jfcmonline.com/text.asp?2018/25/1/20/222259
| Introduction|| |
The term, quality of life (QOL), was first used in the US after the Second World War to demonstrate that having a good life is of more value than just being financially well off., QOL is defined by the World Health Organization (WHO) as the individual's perception of his/her position in life within the context of culture and system of values where the individual lives, and in relation to his objectives, expectations, standards, and concerns. QOL issues have become steadily more important so that the measurement of health should include not only an indication of changes in the frequency and severity of diseases, but also an estimation of well-being, which can be assessed by measuring the improvement in the QOL related to health. Health-related QOL (HRQOL) is a multidimensional concept that includes domains related to physical, mental, emotional, and social functioning. It goes beyond the direct measures of population health, life expectancy, and causes of death to focus on the impact of the status of health on the QOL. The most frequently used multi-item HRQOL instruments assess physical function, role limitations due to physical health problems, bodily pain, general health vitality, social functioning, role limitations due to emotional problems, and emotional well-being, and can be aggregated into two measures of physical component summaries (PCSs) and mental component summaries (MCSs).
The term QOL is broad and subjective rather than specific and objective. It is reasonable to state that QOL can be impacted by many factors, including stress. Life in university is a stressful period that can result in lowered levels of HRQOL, and the common stressors in university students include academic pressure, peer pressure, and being away from home.
There have been several studies on factors that affect the QOL of students such as sociodemographic factors, family income, parent's education level, and occupation.,,, Other factors described in the literature include the use of the Internet.
Of late, the Internet has become an essential part of daily life. Despite its usefulness in accessing a wide range of information, there is a great deal of concern about the improper use of the Internet by adolescents and young adults which has led to the phenomenon described as Internet addiction (IA). IA is defined as an addictive behavior with extreme or poorly controlled fixation, desires, or actions concerning computer use and Internet access that may lead to harm or anguish., It entails excessive use, which may be accompanied by an impaired sense of the passage of time and/or the neglect of basic drives such as hunger or the need for sleep; withdrawal which may be manifested in anger, tension, or depression; tolerance, which may be indicated by longer use or a perceived need for upgrades or new software; negative repercussions to behavior, which may include arguments, fatigue, problems at school or work, lying, lack of achievement, and social isolation.
The condition has attracted growing attention in the popular media and among researchers, and is aligned to the growth in computer and Internet access. IA occurs worldwide, but mainly in countries where computer access and technology are widespread, and prevalence studies on IA in adolescents have reported huge variations. Some studies in Saudi Arabia have reported a prevalence of 5.3% and 4% in students., In another study, it was found that IA was mild in 47.8% of medical students, while 5.8% had moderate IA. Higher prevalence rates of IA were reported in Iranian and Jordanian studies (22.2% and 40%, respectively).,
IA is a worldwide mental health problem in university students and has negative psychosocial and physical effects  and the overall QOL. Despite the widespread use of Internet in the Kingdom of Saudi Arabia (KSA), there is not enough data on the relationship between Internet use or addiction in adolescents and young adults and its effects on the QOL.
The objective of the present study was to assess the overall HRQOL of female university students in Dammam, Saudi Arabia, and identify factors related to HRQOL, such as sociodemographic elements, with a special emphasis on problematic Internet use.
| Materials and Methods|| |
This cross-sectional study surveyed 2516 female university students proportionately drawn from the departments of Art, Education and Sciences of Arrayan campus, Imam Abdulrahman Bin Faisal University (IAU). After consultation with the administration, the students were addressed in their classrooms. Students' support for the completion of the questionnaire was taken as consent. The overall missing answers did not exceed 21 (0.8%) for any of the questions. Participants completed a self-administered questionnaire with sections on sociodemographics, patterns, and effect of Internet use and an assessment of HRQOL.
Guided by an analysis of the content of Young's short version IA test, an IA tool that covered aspects of the loss of control of time management, craving for the Internet and social problems, was developed. The IA tool assessed IA of respondents by means of 10 yes”no questions. These questions were aggregated to produce a compound percentage score with a sum of all scores divided by ten, so that the higher the score, the higher the perceived addiction. This was developed according to the results obtained from a pilot study that tested the questionnaire to obtain more internal consistency and a better response rate. Internal consistency reliability of the compound score was confirmed by a calculated Kuder”Richardson 20 value of 0.72, which was considered satisfactory. The ceiling and flooring effects were found to be 4.7% and 2.3%, respectively. Then, the IA score was categorized as non-IA (IA score <40%), possible IA (40% - <70%), and Internet addict (70%+).
Guided by the 12-item short-form health survey (SF-12) that is used as a generic measure of HRQOL besides the results of the pilot study, an Arabic questionnaire was developed and modified to measure performance status by eight concepts: physical functioning, role limitations resulting from physical health problems, bodily pain, general health, vitality (energy/fatigue), social functioning, role limitations resulting from emotional problems, and mental health (psychological distress and well-being). Reverse coding was performed where necessary so that lower scores depicted a bad evaluation and higher scores a better evaluation. The percentage of the highest possible score was then computed for all 12 questions, so for example, for the 5-point Likert scale questions, the value was multiplied by 100 and divided by 5.
In order to understand the latent structure of these QOL questions (indicators), a principal component analysis (PCA) was used. This method comes up with a small number of principal factors that explain a large amount of variation within the indicators. The analysis was performed in Stata software version 12 (Stata Statistical Software: Release 12. College Station, TX: StataCorp LP, USA). The data were first checked using the Kaiser”Meyer”Olkin test, which yielded a result of 0.77 and the Bartlett's test, which returned significant. Both of these tests indicated that the data were suitable for a PCA. The first was used to assess whether the partial correlation coefficients were small, indicating that the indicators were highly correlated; and the second was to check whether the correlation matrix was an identity one., After the model was run, the number of retained factors depended on the Kaiser Rule and interpretability of these factors. The initial factors were then rotated to facilitate their interpretation through an oblique rotation which allowed the resulting factors to correlate.
The PCA initially resulted in three factors which accounted for 22.6%, 17.5%, and 13% of the variance. The internal consistency for each factor is shown in [Table 1]. Due to the inability to interpret factor 3, and its low internal consistency compared to factors 1 and 2 (0.53), it was discarded. The retained two-factor construct explained 40% of the variance with factor loadings >0.30 as acceptable (>0.5 in half of the items). Question 9 which concerned the perceived general well-being loaded on the third component was analyzed separately with IA. The resulting two factors were labeled as the physical and mental components. The highest ceiling and flooring effects were observed in questions 1, 2, and 9.
|Table 1: Factor loadings, item-total correlations, and Cronbach's alpha coefficients of the short-form quality of life instrument in University of Dammam female student population|
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Subsequently, Cronbach's alpha and item-to-domain correlational analysis were used to determine the internal consistency of the items within each factor. This further provided the rationale for the decision to retain the resulting factors. The ceiling and flooring effects were used to examine the score distributions of each of the 12 questions.
The 5-point score for perceived general well-being ( first item in the 12 questions) was presented in three categories, namely “Poor” combined the lower 2 scores, “Fair” for the middle score, and “Good” for the highest 2 scores.
Statistical analyses were performed using IBM SPSS version 21.0 and confirmed by STATA version 12; 2-tailed statistical significance was set at p < 0.05. Frequency distribution and summary statistics (range, median, mean, and standard deviation) were used as descriptive analysis. Differences between PSC and MCS for Saudis and non-Saudis were analyzed using independent samples t-test, and among all the other factors using ANOVA with a further application of Bonferroni correction for pairwise comparisons. Chi-square test was used to test association between categories of IA and those of perceived general well-being. MANOVA was performed with PCS and MCS as dependent variables and all factors studied in bivariate analyses as independent factors.
| Results|| |
The present study comprised 2516 female students of IAU-City of Dammam, aged from 17 to 25 years with an average age of 21; further distribution of the sample according to sociodemographic characteristics and scholastic achievement is displayed in [Table 2]. About 30% the students were considered as having IA, while 38.2% had a possible IA problem.
|Table 2: Distribution of Imam Abdulrahman Bin Faisal University female students according to sociodemographics, scholastic achievement, and level of Internet usage (2015-2016) (n=2516)|
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Concerning average HRQOL PCS among the students, overall PCS percentage was 69% ± 19.6 [Table 3]. Non-Saudi students had higher scores than Saudi students. Students whose fathers and mothers had lower education reported lower scores. Students with total family income >10,000 SR per month reported higher scores than those with lower incomes. Also, those who had had “A” grades the year before reported higher PCS (70% ± 19.8) than those who got “D” (66% ± 19.3).
|Table 3: Physical component summary and mental component summary of health-related quality of life according to sociodemographics of Imam Abdulrahman Bin Faisal University female students (2015-2016)|
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As regards average HRQOL “mental component score” (MCS) of the students, overall MCS percentage was 62% ± 19.9 [Table 3]. Students whose mothers were business women reported lower scores than those whose mothers worked as teachers, nurses, or clerks. Students with a total family income of >10,000 SR per month reported higher scores than those with incomes <5000 SR. Students who had higher grades, i.e., “A” or “B” grades in the previous year reported higher MCS (63.2% ± 19.3 and 63%±20, respectively) than those who got “D” (59.2% ± 18.6), yet this was not statistically significant.
Students who were considered not to have IA reported the highest PCS and MCS, those considered as possible IA had lower scores in both components, while students considered to be Internet addicts reported the lowest PCS and MCS; the differences among the three categories were statistically significant (p < 0.0001) [Figure 1]. Students suffering from any chronic diseases, pain, tremors, or disturbed sleep reported lower PCS and MCS.
|Figure 1: Physical component summary and mental component summary of Internet addiction categories|
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Perceived good general well-being was lower in percentage in students considered to be IA (71%) than those who were non-IA (83%) or possible IA. Perceived poor general well-being was higher in percentage in IA (8%) than possible IA and non-IA (3%). The differences were statistically significant (p < 0.0001) [Figure 2]. After adjusting for all studied factors in a bivariate analysis by entering them into MANOVA model, [Table 4] shows significant independent factors for PCS and MCS of HRQOL.
|Figure 2: Perceived general well-being among Imam Abdulrahman Bin Faisal University female students according to Internet addiction (2015–2016)|
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|Table 4: MANOVA results for independent factors associated with physical component summary and mental component summary, Imam Abdulrahman Bin Faisal University female students (2015-2016)|
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The higher the IA score, the lower both PCS and MCS. Saudi students had lower PCS than non-Saudis. Students whose fathers had higher education had higher physical scores. Compared to housewife mothers, students whose mothers were business women had lower MCS, while students whose mothers were teachers, nurses, or clerks had higher PCS and MCS. Compared to students with total family income of >10,000 SR, students in a family with an income of <5000 SR per month had lower PCS and MCS and those with 5000”10,000 SR had lower MCS. Students who reported that they had pain in the hand had lower PCS and those who reported hand tremors or disturbed sleep had lower MCS than those who did not. Students who had “D” grades the previous year had lower MCS than those who had higher grades.
| Discussion|| |
Since early nineties, there has been a significant increase in the number of students in universities in the KSA, and now the university student population constitutes a major part of young adult population. Women comprise 60% of Saudi Arabia's college students., The transition to higher education has been recognized as a critical period that may affect student QOL. University students, especially females, are a special population group with regard to health issues, concerns, burdens, and worries. They are subjected to a diversity of stresses, such as academic and social pressures and financial problems that ultimately affect their QOL.
QOL is one's subjective perception of one's own well-being within one's sociocultural context. HRQOL measures make it possible to demonstrate scientifically the impact of QOL (on health).
This is the first study to examine QOL in university students in the KSA using the Arabic version of the SF-12 derived from SF-36. The current study shows that overall PCS percentage was 69% ± 19.6 and overall MCS percentage was 62% ± 19.9. The results of the study indicate that the higher value was obtained for physical functioning and the lower for mental functioning, which is consistent with the results of other studies which adopted SF-36 to study QOL in university students. At King Khalid University in the KSA, female students scored 73.58 + 16.01 in physical functioning and 58.21 + 18.14 in emotional well-being. In a Jordanian university, females had a mean score of 83.58 + 18.60 in physical functioning and 53.58 + 22.30 in emotional well-being, whereas in Lebanon, they scored 88.8 + 10.6 and 54.0 + 20.7 in physical functioning and emotional well-being, respectively., Turkish female university students scored 50.09 ± 8.63 and 43.67 ± 9.50 in physical and mental functioning, respectively. In Croatian students, the summary scores in physical and mental components were 54.89 ± 7.03 and 42.80 ± 9.32, and in Serbia, female students had 78.4 ± 14.0 and 68.6 ± 19.1 in PCS and MCS, respectively.
In the current study, the lower MCS than PCS scores obtained agree with most of the studies in Arab and Western countries. University students are subjected to many stresses related to their studies and their future. These stressful life situations tend to impact on female students' self-evaluation of their well-being.
HRQOL is influenced by a number of factors. In the present study, non-Saudi female students had higher scores than Saudi students for both PCS and MCS, possibly due to the cultural conservatism in Saudi Arabia that proscribes physical activity, which consequently affects their perception of physical well-being. Our study shows that students whose parents had little education reported lower scores of PCS and MCS. Evidently, education enhances people's understanding and thinking and molds their perception of life which is subsequently reflected in their offspring.
There are few studies on the socioeconomic status (SES) of family and QOL. Economic support from the family is essential in a student's life. We related the scores of HRQOL of students with family incomes per month, as a direct measure of SES. Students with a total family income of >10,000 SR per month reported higher scores than those on incomes <5000 SR. This was in accord with the study of Belgrade University students in whom the total SF-36 score significantly correlated with the average monthly family income (P = 0.002).
Significant relationship between QOL and academic achievement was shown in both bi- and multi-variate analyses in which students who reported that they had had “A” grades the previous year had higher PCS than those who reported “D” grades. Students who had had higher grades, i.e., “A” or “B” grades the previous year reported higher MCS than those who got a “D”. Very few studies have examined the relationship between QOL and the academic achievement of university students, which make a comparison difficult Further research is, therefore, required. However, the Jordanian study found no significant relation between QOL and academic achievement. The significant results in QOL in terms of grade point average (GPA) in the current study could be due to the fact that students are elated when their GPA is high, thereby positively improving their QOL domains.
One of the important factors affecting the QOL is the IA. In the current study, IA was reported at 28.7% of the female students and 38.2% for those with possible IA. Al-Hantoshi and Al-Abdullateef reported a prevalence rate of 5.3% in secondary school students. A study of Taif University students showed an estimated 4% prevalence of IA and a possible addiction in 45.3%. Recently, a study to screen for IA in King Khalid University reported mild IA in 47.8% medical students, whereas 5.8% had moderate IA.
IA in Jordanian university students was reported as 40%, while it was 22.2% in Iranian university students., These differences in the prevalence of IA in various studies may be due to the diversity of the study designs, different assessment methods used, and the sampling from different subpopulation.
IA has been found to affect the overall QOL and cause detrimental physical and psychosocial effects. In our current study, the higher the IA score, the lower both the PCS and MCS. These findings are similar to a study in India using WHOQOL-BREF where the higher Internet use, the lower QOL. In Japan, a significant association had been shown between more Internet-addicted adolescents and more disturbed mental status compared to nonaddicted adolescents.
“Well-being is a positive and sustainable condition that allows individuals, groups, or nations to thrive and flourish.” As seen in the results, perceived good general well-being was lower percent wise in students considered IA (71%) than those who had possible IA or non-IA (83%). A cross-sectional study conducted in India revealed that adolescents who use the Internet excessively have higher scores in depression and anxiety. Al-Hantoshi and Al-Abdullateef also found that Internet addicts are at a higher risk of having poor sleep, and an increased level of depression. It was also observed in Turkish students that there were significant correlations between IA and psychological well-being. Findings from India indicated that the level of IA is high among university students and that it affects their subjective well-being.
| Conclusion|| |
HRQOL in female students was found to be affected by parental educational level, family income, and problematic Internet use.
The main limitation of the study is that the data reported here for QOL and IA are derived from self-report, which can have the problem of positivity bias.
From the study findings of HRQOL in female students, and its related factors, it is recommended that more studies are done to explore factors affecting the QOL of university students, especially as related to Internet use and its negative impact on health. IA is a growing problem that requires preventive strategies and interventions. Counseling and physical activity programs are highly recommended to help relieve students' stress and strains and improve their health.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Mazaheri M. Overall, and specific life satisfaction domains: Preliminary Iranian students norms. Iran J Public Health 2010;39:89-94.
Campbell A. The sense of well-being in America. Psychol Med 1981;12:436-7.
The World Health Organization quality of life assessment (WHOQOL): Position paper from the World Health Organization. Soc Sci Med 1995;41:1403-9.
Das P, Basu M, Dasgupta U, Roy B, Das PK, Mundle M. Health related quality of life among undergraduate medical students of Kolkata. Healthline 2013;4:56-63.
Farivar SS, Cunningham WE, Hays RD. Correlated physical and mental health summary scores for the SF-36 and SF-12 health survey, V.I. Health Qual Life Outcomes 2007;5:54.
Ribeiro JS. Rafael IP, Freire VI, Oliveira BG, Casotti AC, Boery EN. Stress and quality of life among university students: A systematic literature review. Health Professions Education 2017. http://dx.doi.org/10.1016/j.hpe.2017.03.002
Hamaideh SH. Stressors and reactions to stressors among university students. Int J Soc Psychiatry 2011;57:69-80.
Sabbah I, Sabbah H, Sabbah S, Khamis R, Droubi N. Health related quality of life of university students in Lebanon: Lifestyles behaviors and socio-demographic predictors. Health 2013;5:1-12.
Oztasan N, Ozyrek P, Kilic I. Factors associated with health-related quality of life among university students in Turkey. Mater Sociomed 2016;28:210-4.
Rakovac M, Pedisic Z, Pranic S, Greblo Z, Hodak D. Sociodemographic and lifestyle correlates of health related quality of life in Croatian university students. Appl Res Qual Life 2013;8:493-509.
Afroz N. Internet addiction and subjective well-being of university students. Indian J Health Wellbeing 2016;7:787-94.
Alzayyat A, Al-Gamal E, Ahmad MM. Psychosocial correlates of internet addiction among Jordanian university students. J Psychosoc Nurs Ment Health Serv 2015;53:43-51.
Block JJ. Issues for DSM-V: Internet addiction. Am J Psychiatry 2008;165:306-7.
Shaw M, Black DW. Internet addiction: Definition, assessment, epidemiology and clinical management. CNS Drugs 2008;22:353-65.
Al-Hantoshi M, Al-Abdullateef S. Internet addiction among secondary school students in Riyadh city, its prevalence, correlates and relation to depression: A questionnaire survey. Int J Med Sci Public Health 2014;3:10-5. doi: 10.5455/ijmsph.2013.130920131.
Alshehri A, Azahrani H, Alotaibi M. Internet addiction among Taif university students and its association with psychiatric co-morbidities. MR J 2015;3:536-44.
Alqahtani NA, Alqahtani AM, Alqahtani KA, Abdulfattah HS, Alessa EA, Algelban KS, et al
. Screening for internet addiction among medical students in a Saudi community. Int J Med Health Sci 2016;3:1. Abstract for 18th
International Conference on Addiction Treatment and Therapy. Miami, USA; 24-25 March, 2016.
Ahmadi K. Internet addiction among Iranian adolescents: A nationwide study. Acta Med Iran 2014;52:467-72.
Vaish PS, Dey B, Ami P. Internet use pattern coping styles and quality of life: Is there a relationship? Indian J Health Wellbeing 2014;5:1463-7.
Pawlikowski M, Altsotter-Gleich C, Brand M. Validation and psychometric properties of a short version of Young's Internet Addiction Test. Comput Hum Behav 2013; 29:1212-23.
Panayides P, Walker MJ. Evaluation of the psychometric properties of the Internet Addiction Test (IAT) in a sample of Cypriot high school students: The Rasch measurement perspective. Eur J Psychol 2012;8:327-51.
Ware J Jr., Kosinski M, Keller SD. A 12-item short-form health survey: Construction of scales and preliminary tests of reliability and validity. Med Care 1996;34:220-33.
Fabrigar LR, Wegener DT. Exploratory Factor Analysis. USA: Oxford University Press; 2012.
StataCorp. Stata: Release 12. Statistical Software. TX: College Station; 2011.
Kaiser HF, Rice J, Little J, Mark IV. Educational and Psychological Measurement 1974,34:111-7.
Bartlett MS. Tests of significance in factor analysis. Br J Psychol (Statistical Section) 1950;3:77-85.
Cronbach L. Coefficient alpha and the internal structure of tests. Psychomerika 1951;16:297-334.
Higher Education: The Path to Progress for Saudi Women World Policy Blog; 18th
The Road Not Travelled: “Education Reform in the Middle East and North Africa”. World Bank 2008 Education Flagship Report. The World Bank; 2008. p. 171.
Moriarty DG, Zack MM, Kobau R. The centers for disease control and prevention's healthy days measures ” Population tracking of perceived physical and mental health over time. Health Qual Life Outcomes 2003;1:37.
Megahed MM. Health-related quality of life among students at King Khalid University ” Mohail Asser. Int J Nurs Sci 2014;4:22-5.
Suleiman K, Alghabeesh S, Jassem H, Abu-Shahroor L, Ali R. Quality of Life (QOL) among university students in Jordan: A-descriptive study. J Educ Pract 2013;4:161.
Pekmezovic T, Popovic A, Tepavcevic DK, Gazibara T, Paunic M. Factors associated with health-related quality of life among Belgrade University Students. Qual Life Res 2011;20:391-7.
Kawabe K, Horiuchi F, Ochi M, Oka Y, Ueno S. Internet addiction: Prevalence and relation with mental states in adolescents. Psychiatry Clin Neurosci 2016;70:405-12.
Centers for Disease Control and Prevention (CDC). Health-Related Quality of Life (HRQOL). Well-Being Concepts. Atlanta, USA. Available from https://www.cdc.gov/hrqol/index.htm
. [Last accessed on 2016 May 27].
Çardak M. Psychological well-being and internet addiction among university students. Turk Online J Educ Technol 2013;12:134-41.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]