Journal of Psychosocial Nursing and Mental Health Services

CNE Article 

Psychosocial Correlates of Internet Addiction Among Jordanian University Students

Abdulkarim Alzayyat, RN, MSC; Ekhlas Al-Gamal, PhD, RN, MSC; Muayyad M. Ahmad, PhD, RN

Abstract

Internet addiction is a significant international mental health problem among university students. The purpose of the current study was to investigate the correlation of Internet addiction with university students’ characteristics in Jordan using a descriptive, correlational, cross-sectional design. The Internet Addiction Test, Beck Depression Inventory, and Multidimensional Scale of Perceived Social Support were administered to a random sample of 587 undergraduate university students. The findings demonstrated that university year level, student age, depression, and family support were significant correlates of Internet addiction. The current study should raise awareness in nurses and other health care providers that Internet addiction is a potential mental health problem for this student population. The findings from the current study will help develop appropriate interventions for these students and inform future research. [Journal of Psychosocial Nursing and Mental Health Services, 53(4), 43–51.]

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Abstract

Internet addiction is a significant international mental health problem among university students. The purpose of the current study was to investigate the correlation of Internet addiction with university students’ characteristics in Jordan using a descriptive, correlational, cross-sectional design. The Internet Addiction Test, Beck Depression Inventory, and Multidimensional Scale of Perceived Social Support were administered to a random sample of 587 undergraduate university students. The findings demonstrated that university year level, student age, depression, and family support were significant correlates of Internet addiction. The current study should raise awareness in nurses and other health care providers that Internet addiction is a potential mental health problem for this student population. The findings from the current study will help develop appropriate interventions for these students and inform future research. [Journal of Psychosocial Nursing and Mental Health Services, 53(4), 43–51.]

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Despite the benefits of Internet use for university students, there has been increased attention in the professional literature about the negative consequences of too much or improper use of the Internet (AL-Qudah, 2012; Shaw & Black, 2008). This phenomenon has been described as Internet addiction (Ghamari, Mohammadbeigi, Mohammadsalehi, & Hashiani, 2011). Internet addiction is usually conceptualized as an impulse control disorder that causes a harmful effect on psychosocial and physical well-being (Lee et al., 2012; Shaw & Black, 2008). Sim, Gentile, Bricolo, Serpelloni, and Gulamoydeen (2012) suggested that the most reliable and valid criteria of conceptualizing Internet addiction was using adapted Diagnostic and Statistical Manual of Mental Disorders (4th ed., DSM-IV; American Psychiatric Association [APA], 1994) criteria for pathological gambling. Similarities exist between the criteria for pathological gambling in the DSM-IV as well as the recently published DSM-5 (APA, 2013). The main signs and symptoms of Internet addiction based on the criteria for pathological gambling used in the DSM-IV (APA, 1994) include restlessness when attempting to minimize or stop surfing the Internet, unsuccessful attempts and efforts to control excessive use, cravings, feelings of distress, anxiety, and continuous online surfing regardless of the negative effects on social and psychological well-being (Young, 1998). Internet addiction has been noted in the appendix of the DSM-5 (APA, 2013) as being worthy of further empirical research studies. Recent studies reveal that Internet addiction presents among a broad range of age groups, from teenagers using the computer at home (Gunuc & Dogan, 2013) to university students on campus (Chen & Peng, 2008; Özcan & Buzlu, 2007; Yang, Sato, Yamawaki, & Miyata, 2013).

In Jordan, there are 29 universities (Ministry of Higher Education and Scientific Research, 2014). In 2012, approximately 250,000 students were enrolled in universities in Jordan (Department of Statistics, 2012). The purpose of the current study was to investigate the correlates that are associated with Internet addiction among undergraduate university students in Jordan. The current study offers information that can be used by nurses and other health care providers, including physicians, psychologists, and counselors, to increase their awareness of Internet addiction and its correlates to plan appropriate interventions.

Background

Overview

Researchers have reported that university students are considered the most vulnerable group in society to develop Internet addiction (Chen & Peng, 2008; Özcan & Buzlu, 2007). According to university rules and disciplines, most addictive behaviors, such as drug abuse, alcoholism, gambling, and smoking, are forbidden (Hong, 2011). However, Internet use is available, necessary, and even encouraged in universities, as many of the educational activities must be performed online (Ko, Yen, Chen, Chen, & Yen, 2008). Furthermore, the Internet is considered a good source for socialization with others through the formation of close and strong relationships, especially for students who have social anxiety or are shy in face-to-face situations (Schoenfeld, 2011). Other researchers reported that Internet addiction is a maladaptive coping mechanism to relieve anxiety, depression, and stress associated with the transition from high school to college (Hicks & Heastie, 2008).

Several studies investigated Internet addiction among university students, with most addressing students’ patterns of Internet use, such as the number of years using the Internet (Ghamari et al., 2011), time spent online (Ceyhan, 2008; Huang et al., 2009; Ni, Yan, Chen, & Liu, 2009), and the purpose of Internet use (Ceyhan, 2008; Ghamari et al., 2011; Huang et al., 2009). Moreover, many of these studies examined the relationship between Internet addiction and potential correlates, such as individual characteristics, including gender (Ceyhan, 2008; Christakis, Moreno, Jelenchick, Myaing, & Zhou, 2011), age (Christakis et al., 2011; Ghamari et al., 2011; Ni et al., 2009), university year level (Lee, 2009), grade point average (GPA; Schoenfeld, 2011), and length of time using the Internet (Ghamari et al., 2011; Ni et al., 2009); buffered factors, including social support (Yang et al., 2013); and psychopathology (e.g., depression) (Christakis et al., 2011; Huang et al., 2009; Ni et al., 2009).

Association Between Depression and Internet Addiction

Several studies have documented associations between Internet addiction and psychiatric symptoms among university students, such as depression, somatization, obsessive-compulsive disorder, adult attention deficit/hyperactivity disorder, and anxiety (Alavi, Maracy, Jannatifard, & Eslami, 2011; Christakis et al., 2011; Ko et al., 2008). Among these psychiatric symptoms, the association between depression and Internet addiction is the most prominent (Alavi et al., 2011; Goel, Subramanyam, & Kamath, 2013). In a Chinese study, Huang et al. (2009) found that Internet addiction is more prevalent among university students with depression. Their results showed that approximately 26% of Chinese students with depression developed Internet addiction compared with 9% of Internet addiction cases among those students without depression (Huang et al., 2009). In a similar study, the level of Internet addiction was higher in Turkish university students with depression (Sahin, Ozdemir, & Unsal, 2013). The association between Internet addiction and depression has been investigated by several researchers in different countries (e.g., China, Japan, Turkey) (Huang et al., 2009; Sahin et al., 2013; Yang et al., 2013). However, no known study in Jordan has investigated the association between depression and Internet addiction among university students. The current study helps fill this gap in knowledge from the Jordanian perspective.

Buffering Role of Social Support

Social support is correlated with perception of psychological well-being and has served as a buffer against chief mental health problems among university students (Al-Zayyat & Al-Gamal, 2014; Merianos, Nabors, Vidourek, & King, 2013). Family, friends, and significant others are considered the major sources of social support for university students because they offer necessary emotional, informational, or instrumental assistance (Hefner & Eisenberg, 2009). This assistance is acknowledged as a coping resource that favorably affects students’ personal resources (e.g., self-efficacy, self-esteem) and provides a buffer from potential negative impacts of university life stressors (Alzayyat & Al-Gamal, 2014; Hefner & Eisenberg, 2009). An extensive literature review demonstrated a strong association between social support and Internet addiction (Esen & Siyze, 2011; Gunuc & Dogan, 2013; Yang et al., 2013). However, most studies examined school-age populations, and few studies investigated the relationship between social support and Internet addiction among university students (Yang et al., 2013). Thus, the current study was performed to broaden the current literature by supporting mental health professionals with evidence-based data that can assist in the development of appropriate prevention plans against Internet addiction among university students.

Internet Addiction Among Jordanian University Students

The Jordanian literature has limited studies that focus on Internet addiction among university students in Jordan. To the authors’ best knowledge, only two published Jordanian studies have investigated Internet addiction among university students (AL-Qudah, 2012; Eyadat, Alzghoul, & Sharqawi, 2012). AL-Qudah (2012) demonstrated that only 0.9% of university students are severely addicted to the Internet. Data were collected from participants via the Internet Addiction Test, and a score of 80 was used as the cut-off for severe Internet addiction (AL-Qudah, 2012). Eyadat et al. (2012) reported that Jordanian students had moderate levels of Internet addiction, with no significant differences noted between male and female participants regarding level of Internet addiction. The level of Internet addiction among participants was measured using the Chinese Internet Addiction Inventory (Huang, Wang, Qian, Zhong, & Tao, 2007). Therefore, the current study is considered one of the first Jordanian studies that examines possible correlates of Internet addiction among undergraduate university students in Jordan.

Research Questions

The specific research questions that guided the current study were:

  1. What are the patterns of Internet use among university students in Jordan?

  2. Which variables (i.e., gender, age, GPA, university year level, number of years using the Internet, depression, family support, friend support, and others’ support) have a relationship with Internet addiction among students?

Method

Design

A descriptive correlational cross-sectional design was used. Data were collected from students during the first semester of the 2013–2014 academic year.

Setting

The current study was conducted at six Jordanian universities (three public and three private) located in the central region of Jordan. The researchers conducted the study at these universities for the following reasons: (a) the universities were located in large cities (Amman, Salt, and Zarqa), (b) they contained different majors, and (c) students from these universities represent diverse economical, ethnic, and geographical backgrounds. Data were collected during the students’ classes (Polit & Beck, 2012).

Sampling

Sample Size. A power analysis was conducted to determine the appropriate sample for this study using G*Power 3.1 (Faul, Erdfelder, Buchner, & Lang, 2009). A sample size of 322 participants was needed. However, to overcome the problems of attrition and incomplete questionnaires, the final sample was 587 students.

Sampling Method. The target population of the current study was all undergraduate university students in Jordan. The accessible population was all undergraduate university students who study at one of the previously selected universities and registered for the first semester of the 2013–2014 academic year. Eligibility criteria included (a) undergraduate student status, (b) ability to speak and read Arabic (Arabic is the primary language in Jordan), (c) Internet use of at least 2 hours per week, and (d) agreement to participate in the study (by consent form). A systematic random sampling method was used to select eligible students.

Instrumentation

Demographic Questionnaire. For the purpose of the current study, the researchers developed a questionnaire to collect information regarding student demographics and characteristics, including gender, age, GPA, current university year level, marital status, and patterns of Internet use (i.e., number of years using the Internet, frequency of Internet use per week, number of Internet surfing hours per day, purpose of Internet use, and method of Internet access).

Young’s Internet Addiction Test. Young (1998) established the Internet Addiction Test (IAT) and presented it in her book, Caught in the Net. The IAT evaluates Internet use in terms of the degree of preoccupation, inability to control use, extent of hiding or lying about online use, and continued online use regardless of negative outcomes of behavior (Young, 2007). The IAT consists of 20 items; each item is scored using a 5-point Likert scale. The score of the total scale ranges from 20 to 100. Scores ≥50 indicate Internet addiction (Ni et al., 2009). The IAT has excellent internal consistency reliability (Cronbach’s alpha = 0.93) (Goel et al., 2013) and face and construct validity (Widyanto & McMurran, 2004). Moreover, the IAT has demonstrated adequate concurrent validity (Chang & Law, 2008). In the current study, the IAT had excellent internal consistency reliability (Cronbach’s alpha = 0.91).

Arabic Version of the Beck Depression Inventory. The Beck Depression Inventory (BDI; Beck & Steer, 1978) comprises 21 items that assess depression symptoms and attitudes, including pessimism, sense of failure, self-dissatisfaction, guilt, self-dislike, suicidal ideas, social withdrawal, indecisiveness, body image change, insomnia, fatigability, weight loss, somatic preoccupation, and loss of libido in the week preceding administration. Items are rated on a 4-point Likert scale, ranging from 0 to 3. The total scale ranges from 0 to 63, and scores are interpreted as follows: 0 to 9 (not depressed), 10 to 18 (mild depression), 19 to 29 (moderate depression), and 30 to 63 (severe depression). The cut-off point between having depression and not having depression is a score of 10 (Beck & Steer, 1978). The Arabic version of the BDI was examined among Jordanian university students and was found to have good internal consistency reliability (Cronbach’s alpha = 0.87) and good test–retest reliability (Cronbach’s alpha = 0.88) (Hamdan-Mansour, Puskar, & Bandak, 2009). In the current study, the Cronbach’s alpha coefficient for the Arabic version of the BDI was 0.87, indicating adequate internal consistency reliability.

Multidimensional Scale of Perceived Social Support. The Multidimensional Scale of Perceived Social Support (MSPSS; Zimet, Dahlem, Zimet, & Farley, 1988) assesses perceptions of social support adequacy from three sources: (a) family, (b) friends, and (c) significant others. The total score ranges from 7 to 84, with higher scores indicating higher perceived social support. Reported Cronbach’s alpha coefficient for the MSPSS is 0.88, and construct validity was confirmed by factor analysis (Zimet et al., 1988). In the current study, the MSPSS had reasonable internal consistency reliability (Cronbach’s alpha = 0.88).

Translation and Piloting. To eliminate any language barrier and achieve reliable student responses, the IAT and MSPSS were translated from English to Arabic according to Brislin’s model (1986). Brislin’s model includes three steps: (a) translation, (b) back translation, and (c) comparison between the back translated and original versions. Later (after translation), a pilot study was conducted on 30 undergraduate university students to verify the suitability and quality of the translated Arabic versions for the Jordanian university students. The pilot results indicated a Cronbach’s alpha of 0.89 for the IAT and a Cronbach’s alpha of 0.85 for the MSPSS, demonstrating that the Arabic versions were suitable for use in the current study.

Ethical Considerations

Ethical approval was obtained from The University of Jordan, Faculty of Nursing and all selected universities before data collection. Study participants were informed (through a student information sheet) about the study goals and data collection procedures. All students signed informed consent reflecting their voluntarily nature of participation. Students’ responses were strictly anonymous, and Jordanian data protection process laws were respected. Due to the nature of the study, students were informed to stop completing the questionnaire if they became emotionally expressive (e.g., scowling, crying); a psychological counselor was available to provide necessary care.

Data Collection Method

Two classes at each of the participating universities were chosen randomly. The researchers contacted the teachers of the selected classes, provided details about the study, and determined a plan for data collection throughout their class sessions. Approximately 100 students were selected from each university using the systematic random technique. Data collection was conducted during the first semester of the 2013–2014 academic year.

Data Analyses

Data analyses were performed using SPSS version 21.0. Descriptive statistics, including frequency, mean, standard deviation, and range, were used to describe participant demographics and to answer the first research question. Inferential statistics, including correlation measures (Pearson and point biserial), were used to answer the second research question. The normality and linearity underlying assumptions of correlation were verified (Garson, 2012).

Results

Sample Characteristics

Participant characteristics are presented in Table 1. Female participants comprised 57% of the sample. Mean student age was 21.15 (SD = 1.42 years, range = 17 to 49 years). The majority (95%) of participants were single, and only three participants were divorced or widowed. Of all students, 235 (40%) met the criteria for Internet addiction. Moreover, 383 (65%) students had depression problems, with depression scores >10; 213 (55.6%) were mildly depressed, 111 (29%) were moderately depressed, and 59 (15.4%) were severely depressed. The mean score on the MSPSS was 57.1 (SD = 11.75), indicating moderate perceived support. The results showed that the significant other (mean = 21.3, SD = 5.24) and family support subscales (mean = 20.8, SD = 5.18) were ranked the highest among all perceived social support subscale scores. The friend support subscale was ranked the lowest (mean = 19.9, SD = 5.29).

Characteristics of the Study Sample (N = 587)

Table 1:

Characteristics of the Study Sample (N = 587)

Patterns of Internet Use

The majority of students (85%) surf the Internet more than four times per week. Chatting was rated the highest (34%) reason for Internet use. Of interest, Internet use for academic purposes was ranked lowest (8%). Regarding the method of Internet access, most participants (38%) used the Internet through their mobile phones, with only a small percentage of participants (16%) accessing the Internet via university computer laboratories (labs) (Table 2).

Patterns of Internet Use Among Jordanian University Students (N = 587)

Table 2:

Patterns of Internet Use Among Jordanian University Students (N = 587)

Correlations With Internet Addiction

The correlations between Internet use and student characteristics are presented in Table 3. Level of depression, student age, university year, and having family support were significantly correlated with Internet addiction. Pearson correlation results showed a statistically significant positive relationship between depression and Internet addiction scores (r = 0.28; p < 0.001). Statistically significant negative relationships were noted between Internet addiction scores and the following student characteristics: university year (r = −0.14; p = 0.001), student age (r = −0.13; p = 0.001), and family support (r = −0.12; p = 0.004).

Correlations Between Student Characteristics and Internet Addiction (N = 587)

Table 3:

Correlations Between Student Characteristics and Internet Addiction (N = 587)

Discussion

Patterns of Internet Use

In relation to Jordanian students’ online lifestyle, the current study revealed that students use the Internet mainly for chatting, which is consistent with previous research findings (Chen & Peng, 2008; Huang et al., 2009; Lee, 2010; Özcan & Buzlu, 2007), indicating that university students use the Internet mainly to communicate with other individuals. These results demonstrate that Internet technology promotes university students’ social lives because it allows them to communicate in a convenient manner (Lee, 2010). On the other hand, the results of the current study demonstrated that using the Internet for academic purposes occupies little of students’ time. Consequently, it seems that university students use the Internet for aims not associated with their status as students, and thus do not compose part of a particular group of Internet users (Castells, Tubella, & Sancho, 2007).

Regarding the method of Internet use, the results of the current study revealed that Jordanian university students prefer to access the Internet via their mobile phones. In contrast, the results showed that few participants use the university computer labs to access the Internet. These results can be explained in several ways. First, Internet services on university grounds are limited in scope by restricted time periods and different filter programs. As a result, students may not have adequate freedom to choose their Internet activities at university computer labs. Conversely, using mobile phones (that offer access to the Internet from mobile phone companies and outside universities’ domains) for Internet access may enable students to surf different websites without filtration or time restrictions. Second, compared with desktop or laptop computers, mobile phones offer an interesting feature for university students. Mobile phones are constantly available; students can use their smartphones while riding in a car, walking to class, or waiting for the elevator.

Psychosocial Correlates of Internet Addiction

The results of the current study demonstrated a positive relationship between depression and Internet addiction, implying that university students who have depressive symptoms are at higher risk for developing Internet addiction than students who did not display such symptoms. These results are consistent with previous literature, which indicated that degree of Internet addiction was higher in university students with depression (Huang et al., 2009; Özcan & Buzlu, 2007; Sahin et al., 2013; Yang et al., 2013). A possible justification for this result is that university students who have depression are more vulnerable to participate in addictive activities as a method to self-relieve (Ko et al., 2008; Özcan & Buzlu, 2007). The most important matter lies in not dealing with the cause of the depression (Ceyhan, 2008). Thus, university students may achieve instantaneous, yet short-term, relief by misusing the Internet (Yang et al., 2013). This behavior generates an intensive harmful cycle, which continues the addictive behavior. These findings indicate that university prevention programs should focus on psychoeducational support to alleviate depression and the provision of early screening for high-risk groups with depression symptoms to decrease the risk of Internet addiction (Ni et al., 2009). Early psychological support by nurses and other health care professionals is of vital importance.

The results of the current study revealed that university students at lower-year levels (e.g., first or second year) are more vulnerable to Internet addiction than those at higher-year levels (i.e., third and fourth year). This study finding is supported by Lee (2009) who found that first-year university students are more vulnerable to Internet addiction than graduate students. Student development theory has indicated that university students encounter various development tasks throughout each consecutive year in their studies (Evans, Forney, Guido, Patton, & Renn, 2009). It was assumed that these developmental tasks may influence how students use the Internet during different university year levels (DiNicola, 2008). Moreover, it was hypothesized from a developmental standpoint that lower-year students may possess extra leisure time and may be more likely to participate in risk-taking behaviors, such as binge drinking (Carlson, Johnson, & Jacobs, 2010; Correia, Murphy, & Barnett, 2012) and hazardous sexual conduct (Fielder & Carey, 2010). All of these factors may contribute to the development of Internet compulsive behaviors and, ultimately, Internet addiction among university students in lower-year levels. These findings emphasize the importance of interventions to take preventive measures and early diagnosis of Internet addiction among first-year students. Therefore, university teachers should guide students to use the Internet appropriately.

The current study revealed a negative relationship between student age and Internet addiction. It is important to mention that although age and university year variables seem similar, they are different. In Jordan, students typically enroll in undergraduate courses after passing the high school examination. However, some students receive low grades on this examination, and as result, enroll at community college before going to a university. Moreover, some students have financial difficulties that hinder them from enrolling in undergraduate courses immediately after high school. Therefore, students may be in the same university year but have different ages. The results revealed that younger students are at higher risk for Internet addiction than older students. The negative correlation between student age and emergence of Internet addiction is well-documented in the literature (Ghamari et al., 2011; Lee, 2009; Shaw & Black, 2008). The current study results can be justified in several ways. In Jordan, the Internet recently became one of the luxury manifestations of contemporary life and an important device for teaching younger generations of individuals (Abu-Shanab, Al-Rub, & Nor, 2010; Khasawneh, 2009). Therefore, younger students’ have been exposed to an environment that supports Internet use, and in that case, Internet use became a central activity in their lives (Shaw & Black, 2008). It is recommended that higher education institutions collaborate with mental health organizations to make planned efforts directed toward these younger students and their parents about prevention of improper Internet use.

The correlational findings of the current study are consistent with previous research regarding Internet addiction and social support (Gunuc & Dogan, 2013; Yang et al., 2013). A significant negative relationship was noted between family social support and Internet addiction, which implied that students with inadequate family social support were more likely to be addicted to the Internet. On the other hand, no significant relationship was noted between Internet addiction and social support from significant others or friends. These study findings are significant because they demonstrate that family remains to be the primary source of support; as a result, the quality of the relations formed within the family is anticipated to have beneficial effects on the psychosocial well-being of university students (Gunuc & Dogan, 2013). In this context, parents should be sensitive to the needs of their children and express love and understanding when managing problematic behaviors, such as misuse of the Internet (Yang et al., 2013).

Limitations

Several limitations are recognized in the current study. First, the cross-sectional design was considered a limitation. The use of longitudinal designs in future studies is recommended. Second, data were collected from students who attended class; therefore, students who did not attend class, possibly due to excessive Internet use, were unable to participate. Accordingly, the study findings may not reflect the actual responses of those active online users. Including other data collection methods (e.g., use of a social network site) may overcome this issue.

Conclusion

The current study contributes to the available literature that investigated the correlates of Internet addiction among Jordanian university students. Considering the study findings, higher education administrators and mental health professionals, including nurses, should establish campus prevention programs to focus on addressing depressive symptoms among high-risk university students. Furthermore, counseling programs are recommended to increase the awareness of families regarding Internet addiction and their responsibilities in providing psychological support for their children. Future interventional studies are needed. These studies could evaluate the effect of depression management strategies on the degree of Internet addiction among affected students. Additional research is also needed to address other risk factors for Internet addiction, such as negative self-concept and sensation seeking.

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Characteristics of the Study Sample (N = 587)

Characteristic n (%) Mean (SD), Range
Gender
  Female 336 (57.2)
  Male 251 (42.8)
Marital status
  Single 556 (94.7)
  Married 28 (4.8)
  Other 3 (0.5)
Student year
  First 115 (19.6)
  Second 178 (30.3)
  Third 152 (25.9)
  Fourth 142 (24.2)
Internet use 44.3 (18.5), 4 to 95
  Normal 352 (60)
  Addiction 235 (40)
Depressiona 17.7 (9.9), 0 to 46
  Present 383 (65)
  Not present 204 (35)
Perceived Social 57.12 (11.75), 16 to 77
Supportb
  Family support 20.8 (5.18)
  Friends support 19.9 (5.29)
  Others support 21.3 (5.24)
Age (years) 21.15 (1.42), 17 to 49
GPA 2.94 (0.52), 1.75 to 4.0

Patterns of Internet Use Among Jordanian University Students (N = 587)

Variable Mean (SD)
Number of years using the Internet 6.68 (2.9)
Internet use hours per day 4.3 (3.5)
n (%)
Internet use per week
  >4 times 500 (85.2)
  3 to 4 times 46 (7.8)
  1 to 2 times 41 (7)
Main purpose of Internet use
  Chatting 197 (34)
  Social networking 160 (27)
  E-mail 71 (12)
  Entertainment 60 (10)
  Surfing websites 52 (9)
  Academic activities 47 (8)
Primary method of Internet use
  Mobile phone 220 (38)
  Personal computer 147 (25)
  Internet café 125 (21)
  University computer labs 95 (16)

Correlations Between Student Characteristics and Internet Addiction (N = 587)

Characteristic Pearson Correlation p Value
Gender 0.024a 0.557
Age −0.133 0.001***
Number of years using the Internet 0.010 0.811
GPA −0.021 0.605
University year −0.138 0.001***
Depression 0.277 <0.001***
Family support −0.118 0.004**
Friends support 0.063 0.127
Others support −0.020 0.634

Keypoints

Alzayyat, A., Al-Gamal, E. & Ahmad, M.M. (2015). Psychosocial Correlates of Internet Addiction Among Jordanian University Students. Journal of Psychosocial Nursing and Mental Health Services, 53(4), 43–51.

  1. The risk factors of Internet addiction were examined among Jordanian university students.

  2. University year level, age, and depression were identified as risk factors.

  3. Family support played a significant role against Internet addiction.

  4. Chatting was ranked the highest purpose of Internet use among Jordanian students.

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Authors

Mr. Alzayyat is Lecturer, Nursing Department, Al-Ghad International Colleges for Applied Medical Sciences, Abha - Kingdom of Saudi Arabia; and Dr. Al-Gamal is Associate Professor, Psychiatric and Mental Health Nursing, Department of Community Health Nursing, and Dr. Ahmad is Professor, Clinical Nursing Department, Faculty of Nursing, The University of Jordan, Amman, Jordan.

The authors have disclosed no potential conflicts of interest, financial or otherwise. The study was funded by The University of Jordan Deanship of Academic Research (grant 2014-2015/20). The authors thank the Deanship of Scientific Research/The University of Jordan for funding this project, and all students who participated in this study.

Address correspondence to Abdulkarim Alzayyat, RN, MSC, Lecturer, Nursing Department, Al-Ghad International Colleges for Applied Medical Sciences, Abha - Kingdom of Saudi Arabia, P.O. Box 183499 Amman, 11118 Jordan; e-mail: A.alzayyat@gmail.com.

Received: November 21, 2014
Accepted: February 23, 2015

10.3928/02793695-20150309-02

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