Cell Phone and Internet Addiction among Students in

�Isfahan University of Medical Sciences (Iran)

 

Maryam Amidi Mazaheri1, Fatemeh Rahmati Najarkolaei*,2

 

1 Health Services Department, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran.

2 Health Research Centre, Baqiyatallah University of Medical Sciences, Tehran, Iran

 

Received: 2014/5/29 �������������� Accepted: 2014/8/5

 

Abstract

Objective: In recent years, there has been a rapid expansion in use of Internet and cell phone. The purpose of this survey was to identify the extent of cell phone and Internet addiction and relationship between these two forms of behavioral addiction in students at Isfahan University of Medical Sciences in Iran.

Methods: This descriptive cross-sectional study was performed in Isfahan University of Medical Sciences in 2012. Sampling method was convenience and sample size of 1180 persons was considered. Participants completed demographic questionnaire, Internet Addiction Test, Mobile Phone Addiction Index. Data were analyzed by SPSS version 18.0, T‑test and one way ANOVA were used to identify the possible relations between demographic variables and cell phone and Internet addiction.

Results: Overall prevalence of internet addiction was 20% and moderate and severe internet addictions were19.1% and .9%, respectively. The prevalence of cell phone use addiction was 56.2%% for female students and 64.5%% for male students.

Conclusion: Internet and cell phone addiction were related to male gender, age less than 25 year, higher educated father, and high socioeconomic status of family.

Educational institutions such as schools and universities should try to develop new teaching concepts to educate the students to use internet and cell phone meaningfully and correctly.

 

Key Words: Behavior Addictive, Internet, Mobile Applications


Introduction

Throughout past decades, there has been a rapid expansion in use of the Internet and Cell phone. Numerous studies have demonstrated young people are more likely than any other demographic group to use cell phone (1).Also, there has been a rapid growth of investigation focusing on use of technology (2) especially cell phone and internet (3).Beside the discussion about possible physical risks of communication technology, more recent research has focused on problematic behaviors or behavioral addiction such as addiction to cell phones that may threaten health or well-being (4).Defining behavioral addictions is not easy because of the variety of symptoms associated with it (5) although there is an increasing movement to recognize and categories it (6).Conceptual and methodical disagreements about Internet addiction are less than cell phone addiction (1).

�The concept of Internet addiction was introduced by Young in 1996 as an �impulse disorder� not involving the ingestion of an intoxicant, making it a �behavioral addiction� similar to gambling addiction and unlike alcoholism (7) and several diagnostic criteria have been developed for Internet addiction (8).

Carbonell study (2009) mentions Internet addiction is studied more frequently than addiction to cell phones, cell phone addiction is a new field and the number of publications in this area is growing, but it is difficult to conduct precise searches due to a lack of clear terminology (9).

Furthermore, in case of cell phone addiction there are conceptual controversies for instance how this behavior could be defined was not concluded? Some studies measured problematic cell phone usage (10), else research preferred to use the term maladaptive cell phone usage (11) another research categorizes the over-usage of cell phones as a pathological behavior (12), other research focused to excessive cell phone use (13).

Although there is fragmentary evidence that extensive cell phone use can have adverse effects on well-being and life quality especially in youth (4). Little research has been done in developing countries (9). According to the IT News in 2011; the number of cell phone users in Iran was 73 million people (www.mobna.net).Studies have demonstrated cell phone have become highly prevalent with youth, in Iran. Also has been reported that by 2009, some 98% of Iranian adults between the age of 20 and 30 years had used the Internet (14) and the incidence of Internet addiction has been estimated to vary from 3.8% to 30% among the Iranian youth. For Instance, Kheirkhah (2010) investigated the prevalence of Internet addiction among north Iranian Internet users. The results revealed that 22.8% of Internet users were dependent users and there was a significant difference between gender and Internet addiction (15).Studies also indicate that prevalence of Internet addiction among Iranian college students has increased markedly (16-17).

To our knowledge, Iranian previous Studies In the case of cell phone are very few. Baqhyany Moghadam (2011) explored the pattern of cell phone usage among Yazd University of Medical Sciences(Iran), 97% of students have cell phone and 14 % of girls and 24 % of boys experienced sleep disorders after buying� cell phone most of them stated that their daily use of cell phone is moderate (18).

Naderi (2009) investigated relationship between impulsivity and loneliness with usage of the cell phone among university students (19).

The purpose of this survey was to identify the extent of cell phone and Internet addiction and relationship between these two forms of behavioral addiction in university students.

 

Methods�

2.1 Participants

This descriptive cross-sectional study was performed in Isfahan University of Medical Sciences in 2012. By convenience sampling method1180 persons was considered. In lunch time, on all days of two weeks, interviewers were stationed in central restaurants, and the questionnaires were distributed among students. Inclusion criteria were having a cell phone and internet access and a willingness to participate in the study.Exclusion criteria were lack of opportunity to participate in the study. Central restaurant was chosen because in this location, confounding variables of samples such as sex, marital status, etc randomly selected. A total of 1500 questionnaires were distributed, 1295 were responded. There were 1180 useable questionnaires.

2.2 Measurements

Internet Addiction test: Persian version of Young Internet Addiction test (IAT) was applied which had a good reliability with a Cronbach�s alpha of 0.89 and test�retest of 0.68 after 2 weeks (17).

Cell phone addiction index (MPAI): The 17- items Mobile phone Addiction Index (MPAI) developed by Leung, (2008) was applied (20). In Leung study; the reliability of the scale as indicated by Cronbach�s alpha was remarkably high at .90.

This tool translated into Persian in Iran in 2009 by Naderi and Hagh Shenas and acceptable reliability and validity have been reported (19). A five-point likert scale was used on the 17-item MPAI scale with 1 = not at all, 2 = rarely, 3 = occasionally, 4 = often, and 5 = always.

2.3 Statistical analyses

Data were analyzed by SPSS 18.0. T-test were used to check for possible gender differences and one way ANOVA were used to identify the possible relations between demographic variables and cell phone and internet addiction. Pearson correlations were additionally used to determine the extent of associations between the cell phone and internet addiction.

According to the manual; participants were divided into three levels based on their score, i.e., score less than 50 as normal, score 50 to 79 as light addicts, and score higher than 79 as severe addicts to Internet.

Young�s classic definition of Internet addiction was adopted; in which a total of 8 items from 17 that are most conceptually equivalent to Young�s (1996) screening instrument on internet addiction were employed (long). A chance probability level of less than .05 was set to reject the null hypotheses.

 

Result

Among the 1180 university students, 65.5% were female, 88% were single, 56.7% lived in dormitory and 80.1% were unemployment, mean and standard deviation of age were 20.96� 2.32years, ages ranged from 18 to 39 years.The mean age in the beginning of the use of cell phone in female and male students were 16.2 and 17.5 respectively.

Nearly ten percent of female and 15.6% of male had more than one SIM card. Twenty-five point seven percent of female and 41.4% of the male had changed their phone more than twice (P ≤ .001).

According to the IAT, the prevalence of ��light Internet addiction�� was 13.5% for female students and 29.6% for male students, and the prevalence of ��severe Internet addiction�� was 0.8% for female students and 1.1% for male students (P<0.05),

According to the MPAI, The prevalence of cell phone addiction was 56.2%% for female students and 64.5%% for male students (p=.005).

There were significantly positive correlations between the score of MPAI and score of IAT, r=0.453, p<0.001.

The relations between mean of cell phone addiction and demographic variables were shown in Table 1 and relations between mean of Internet addiction and demographic variables were shown in Table 2.

 

Discussion

Despite the growing number of Iranian cell phone users, few studies have been done about it. This study can be considered as primary step to better understand and estimate cell phone addiction among university students in Iran.

Age of first use of cell phone is one of the variables affecting the amount and how to use the cell phone. Similar to Inyang et al in Australian adolescents (21) males were significantly younger at age of first use of cell phone. Also19% of females and 33% of males had purchased cell phone under the age of 15 years. Cell phone addiction scores in students who had purchased cell phone under the age of 15 years were significantly higher than the others similar to Zokaee (22). Nearly 10% of female and 15.6% of male had more than one SIM card. The first and most obvious reasons that come to mind about having more than one SIM card are improper use of cell phone and hide contact and information or data of others. Cell phone addiction scores in students who had more than one SIM card were significantly higher than the others.

Male significantly more than female change their phone. This finding was consistent with Baqhyany moghadam (18). Cell phone addiction scores in students who had changed their cell phone more than 2 times were significantly higher than the others.


 

 

Table 1. Relations between demographic variables and mobile phone addition in the students

Variables

N

Mean

SD

F

Age

≤20

20 thru 25

≥25

 

505

477

57

 

32.19

32.80

29.38

 

9.91

9.96

10.01

 

3.08*

Gender

Female

male

 

686

361

 

31.41

33.82

 

9.90

9.90

 

14.19**

Marital Status

Single

married

 

917

125

 

32.24

32.16

 

9.88

10.68

 

.008

Accommodation

Home

Dormitory

 

452

589

 

31.44

32.94

 

9.74

10.19

 

5.79*

Father Education

Less than high school

Diploma
Bachelor
Higher education

 

189

306

353

141

 

30.60

31.67

33.19

34.45

 

8.79

9.62

10.31

10.80

 

 

5.37**

Socioeconomic Status

Wealthy
Relatively wealthy
Middle income
Low-income

 

93

313

588

49

 

34.39

33.68

31.17

32.56

 

10.75

10.56

9.47

9.10

 

 

5.96**

Educational levels

Bachelor

General Medicine

Higher Education

 

618

355

54

 

32.10

32.47

32.38

 

9.68

10.47

10.51

 

 

.464

Times of phone change

0

1

2

≥3

 

149

252

267

328

 

28.91

31.26

32.92

34.22

 

8.94

9.12

8.87

10.85

 

 

11.20**

�

Table 2. Relations between demographic variables and Internet addiction in the students

Variables

N

Mean

SD

F

Age

≤20

20 thru 25

≥25

 

538

480

60

 

35.75

36.29

33.05

 

15.50

14.89

14.39

 

1.24

Gender

Female

male

 

709

372

 

33.21

4.062

 

14.00

16.09

 

61.43**

Marital Status

Single

married

 

947

129

 

36.48

30.49

 

15.31

13.02

 

17.93**

Accommodation

Home

Dormitory

 

458

616

 

36.08

35.54

 

15.03

15.27

 

.335

Father Education

Less than high school

Diploma
Bachelor
Higher education

 

200

316

359

144

 

30.21

34.57

36.77

44.22

 

12.54

13.83

15.60

16.74

 

 

26.7**

Socioeconomic Status

Wealthy
Relatively wealthy
Middle income
Low-income

 

99

320

608

46

 

41.71

37.81

33.79

35.15

 

18.11

15.48

14.07

15.19

 

 

10.77**

Educational levels

Bachelor

General Medicine

Higher Education

 

650

358

53

 

34.16

37.11

38.91

 

14.63

15.54

15.77

 

 

11.58**

Times of phone change

0

1

2

≥3

 

149

252

267

328

 

��������������� 32.75

32.81

36.22

39.68

 

13.60

13.37

15.23

16.41

 

 

13.26**

�


 

Also the mean of cell phone addiction and Internet addiction scores in younger students were significantly higher than the older students. This finding was consist with previous studies (10, 4, 23). It can be said that the younger age is a related factor for internet and cell phone addiction.

Beranuy expressed that the use of cell phone and Internet is more problematic during adolescence and normalizes with age toward a more professional and less playful use, and with fewer negative consequences (11).Although both males and females have squeezed cell phone technology equally; comparing the use of it in both sexes seems interesting.� Different rate of cell phone and Internet addiction was seen in two genders.This finding has confirmed previous result (10, 16).

Cell phone and internet addiction scores in students who had wealthy family were significantly higher than the other students that were consistent whitprevious findings (24, 25).

wealthy families may not only have the economic resources for cell and Internet expenditures, but also create a particular cultural environment for their use.Also cell phone and Internet addiction scores in students who had higher educated fathers were significantly higher than the other students.These fathers are more likely to socialize their children into the world of modern information technology.

Cell phone addiction scores in students who lived in dormitory were significantly higher than other students. This could be due to be away from family and homesickness and loneliness. Prior study among university students revealed that there is a significant relationship between loneliness and cell phone addiction (19).

The overall prevalence of internet addiction was 20% and moderate and severe internet addictions were19.1% and .9%, respectively.

In Alavi (2010) study 15% of the students were suffering from internet addiction (17).

It can be said Internet addiction in students has been increasing after two years.

In June et al.'s study among Korean students, prevalence of internet addiction was 20%, which was similar to our results (26). In Ghamari et al.'s study in medical students of Arak University (Iran)(2009) the prevalence of light Internet addiction was 8.1% (23)and in Lam et al.'s study (2009), was10.2% (27) and in Johansson et al.'s study among Norwegian young people, was 10.66% which were less than that of our study (28). In Lu et al.'s study the prevalence of ��light Internet addiction�� among Japanese adults was 33.7% for men and 24.6% for women, and the prevalence of ��severe Internet addiction�� was 6.1% for men and 1.8% for women (3) which was more than that of our study.

The prevalence of cell addiction was 56.2%% for female students and 64.5%% for male students.Interpretation of this finding and comparison with other studies is difficult since in comparison with Internet addiction, only few studies have dealt with cell phone addiction so far.� According to Carbonell et al. (2009) searched phones only 2.1% of the published studies dealt with cell phones (9). In addition previous studies have used various tools which make it difficult to compare results.

In Leung study the prevalence of cell phone addiction was 27.4% (20).A Spanish survey with 13�20-year-old adolescents identified prevalence for cell phone dependence of 20% (29). Ahmed et al study indicated that university students in Pakistan used their cell phone under reasonable limits (30).

In Billieux et al(2006) study the general level of perceived dependence to cell phone was high (31).This dissimilitude may be because of cultural, social and, economical differences in different societies.

Also significantly positive correlations between cell phone addiction and internet addiction, which was consist with previous studies (32, 33).

There are several limitations involved in this study initially, the more concern is about the validity and accuracy of self reported data regarding cell phone and Internet addiction; however, Tokola et al. (2008) obtained a correlation coefficient of 0.71 between self reported cell phone use and network operators� information (34).

Further limitation is about generalization of the results, although a relatively suitable sample size of 1180 was studied, it was confined to a limited region. Therefore, generalization of the results must be interpreted with caution and continued research should include larger sample sizes to draw more accurate conclusions.However the enormous existence of cell phones in our daily lives further underlines the importance of research in this area.

Limitation

Due to the high prevalence of cell phone and Internet addiction in students, future longitudinal studies should focus on the long-term effects of cell phone and Internet addiction and discover the causal relationship between addiction and depression or other psychological symptoms.

 

Conclusion

Internet and cell phone addiction were related to male gender, age less than 25, higher educated father, and high socioeconomic status of family.

Educational institutions such as schools and universities should try to develop new teaching concepts to educate the students to use internet and cell phone meaningfully and correctly.

 

References

1. Yen CF, Tang TC, Yen JY, Lin HC, Huang CF, Liu SC, et al. Symptoms of problematic cellular phone use, functional impairment and its association with depression among adolescents in Southern Taiwan. J adolesc. 2009;32(4):863-73.

2.Buckner JE, Castille CM, Sheets TL. The Five Factor Model of personality and employees� excessive use of technology. Computers Human Behav .2012;28(5):1947-1953.

3 .Lu X, Watanabe J, Liu Q, Uji M, Shono M, Kitamura T. Internet and mobile phone text-messaging dependency: Factor structure and correlation with dysphoric mood among Japanese adults.Computers� Human Behav. 2011;27(5);1702-1709.

4 .Augner C, Hacker GW. Are people living next to mobile phone base stations more strained? Relationship of health concerns, self-estimated distance to base station, and psychological parameters. Indian J Occup Environ Med .2009;13(3):141.

5 -Walsh SP, White KM, Young RM. Over-connected? A qualitative exploration of the relationship between Australian youth and their mobile phones. J Adolesce. 2008;31(1):77-92.

6 .Block J. Issues for DSM-V: Internet addiction. Am J Psychiatry. 2008;165(3):306-7.

7 .Young KS. Internet Addiction: A New Clinical Phenomenon and Its Consequences. Am� Behav� sci. 2004;48(4):402-415.

8 . Ko CH, Yen JY, Chen SH, Yang MJ, Lin HC, Yen CF. Proposed diagnostic criteria and the screening and diagnosing tool of Internet addiction in college students. Comprehensive psychiatry. 2009;50(4):378-84.

9. Carbonell X, Guardiola E, Beranuy M, Bell�s A. A bibliometric analysis of the scientific literature on Internet, video games, and cell phone addiction. J Med Library Assoc: JMLA. 2009;97(2):102.

10 . Bianchi A, Phillips JG. Psychological predictors of problem mobile phone use. CyberPsychology & Behav. 2005;8(1):39-51.

11. Beranuy M, Oberst U, Carbonell X, Chamarro A. Problematic Internet and mobile phone use and clinical symptoms in college students: The role of emotional intelligence. Computers� Human Behav. 2009;25(5):1182-7.

12.Jenaro C, Flores N, G�mez-Vela M, Gonz�lez-Gil F, Caballo C. Problematic internet and cell-phone use: Psychological, behavioral, and health correlates. Addict Res theory. 2007;15(3):309-20.

13. Khan MM. Adverse effects of excessive mobile phone use. Int j occup med environ health. 2008;21(4):289-93.

14.Alavi SS. The Psychometric Properties of GPIUS, CIUS in Students Internet Users of Isfahan Universities. The final report of the research project. Vice Chancellery for research, Isfahan University of Medical Sciences; 2009 .

15.Kheirkhah F, Ghabeli Juibary A, Gouran A. Internet addiction, prevalence and epidemiological features in Mazandaran Province, Northern Iran. Iran Red Crescent Med J. 2010;12(2):133-7.

16. Ghassemzadeh L, Shahraray M, Moradi A. Prevalence of internet addiction and comparision of internet addicts and non-addicts in Iranian high Schools. Cyberpsychol Behav .2008;11(6):731-3.

17.Alavi SS, Alaghemandan H, Maracy MR, Jannatifard F, Eslami M, Ferdosi M. Impact of Addiction to Internet on a Number of Psychiatric Symptoms in Students of Isfahan Universities, Iran, 2010. Inte J Prev Med. 2012;3(2):122.

18 .Baghiyani MoghadamMH, Shahbazi H, An Explanatory Analysis of Mobile Phone Usage Pattern among Medical Students of Yazd Shahid Sadoghi University of Medical Sciences, 2010, Global Media J, 2011;6(1): 1-13.

19 . Naderi F,Haghshenas F. Relationships between impulsivity and loneliness, with the use of mobile students, new findings psychol, 2009; 4(12)� :111-121.

20. Leung L. Linking psychological attributes to addiction and improper use of the cellular phone among adolescents in Hong Kong. J Child� Media. 2008;2(2):93-113.

21 .Inyang I, Benke G, Dimitriadis C, Simpson P, McKenzie R, Abramson M. Predictors of mobile telephone use and exposure analysis in Australian adolescents. J Paediatr� Child Health. 2010;46(5):226-33.

22. Zokaee MS, Valizade V, Youth culture and mobile phones. Iran Cultural Res.2009; 2 (7) :119-152.

23.Ghamari F, Mohammadbeigi A, Mohammadsalehi N, Hashiani AA. Internet addiction and modeling its risk factors in medical students, iran. Indian j psychol� med. 2011;33(2):158-62.

24.Zulkefly SN, Baharudin R. Mobile phone use amongst students in a university in Malaysia: its correlates and relationship to psychological health. Eur J Sci� Res. 2009;27(2):206-18.

25.Koivusilta LK, Lintonen TP, Rimpela� AH. Orientation in adolescent use of information and communication technology: a digital divide by sociodemographic background, educational career, and health. Scand J Public Health.2007; 35(1):95�103.

26.June KJ, Sohn SY, So AY, Yi GM, Park SH. A study of factors that influence Internet addiction, smoking, and drinking in high school students. Taehan Kanho Hakhoe Chi. 2007;37(6):872�82.

27 .Lam LT, Peng ZW, Mai JC, Jing J. Factors Associated with Internet Addiction among Adolescents. Cyberpsychol Behav. 2009;12(5):551�5.

28.Johansson A, G�testam KG. Internet addiction: Characteristics of a questionnaire and prevalence in Norwegian youth (12-18 years) Scand J Psychol. 2004;45(3):223�9.

29- S�nchez-Mart�nez M, Otero A. Factors associated with cell phone use in adolescents in the community of Madrid (Spain). Cyberpsychol Behav. 2009;12(2):131-7.

30.Ahmed I, Qazi TF, Perji K. Mobile phone to youngsters: Necessity or addiction. Afr J Business Manag. 2011;5(32):12512-9.

31.Billieux J, Van der Linden M, d'Acremont M, Ceschi G, Zermatten A. Does impulsivity relate to perceived dependence on and actual use of the mobile phone? Appl Cognitive Psychol. 2006;21(4):527-37.

32 .Hong FY, Chiu SI, Huang DH. A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students. Comput Human Behav. 2012;28(6):2152-2159.

33 .Pawlowska B, Potembska E. P-78-Involvement in the internet and addiction to the mobile phone in polish adolescents. Eur� Psychiatry. 2012;27(1):1.

34.Tokola K, Kurttio P, Salminen T, Auvinen A. Reducing overestimation in reported mobile phone use associated with epidemiological studies. Bioelectromagnetics. 2008;29(7):559-63.


 

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

Creative Commons License
Journal of Health Policy and Sustainable Health is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.