Exploring the psychometric properties of the English version of the Internet Addiction Test in the Pakistani population: a cross-sectional survey Ahmed Waqas, Faisal Farooq, Anum Bhatti, Saamia Javed, Mahrukh Elahi Ghumman, Mohsin Raza, Spogmai Khan, Waqas Ahmad

Introduction: Despite growing concerns over pathological use of the Internet, studies based on validated psychometric instruments are still lacking in Pakistan. The present study aimed to examine the psychometric properties of Young’s Internet Addiction Test (IAT) in a sample of the Pakistani population. We examined the validity, internal consistency, readability and floor and ceiling effects of IAT scores.Methods: This crosssectional study was conducted at CMH Lahore Medical College and Institute of Dentistry, Lahore, Pakistan from 1 March 2015 to 30 May 2015. A total of 522 medical and dental students completed the questionnaire, which consisted of three sections: (a) demographics and percentage grades in annual examinations, (b) a categorical question to record the estimated number of hours spent on the Internet per day, and (c) the English version of the IAT. All data were analyzed in SPSS v. 20. Principal axis factor analysis was used to validate the factor structure of the IAT in our study sample. An alpha coefficient > .7 was sought in the reliability analysis. Histograms and the values of skewness and kurtosis were analyzed for floor and ceiling effects. In addition, readability of the IAT was assessed as the Flesch Reading Ease score and Flesch-Kincaid Grade level function. Results: A total of 522 medical and dental students participated in the survey. Most respondents were female medical students enrolled in preclinical years of their degree program. Median age (minmax) of the respondents was 20 years (17-25 years). A single-factor model for IAT score explained 33.71% of the variance, with a high alpha coefficient of .893. In addition, the IAT had good face and convergent validity and no floor and ceiling effects, and was judged easy to read by participants. Conclusion: The English version of the IAT showed good psychometric properties in a sample of Pakistani university students. A single-factor model for assessing internet addiction showed good reliability and was found suitable with our study sample.

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Exploring the psychometric properties of the English version of the Internet Addiction Test

2

in the Pakistani population: a cross-sectional survey

3 4

Ahmed Waqas1, Faisal Farooq1, Anum Bhatti2, Saamia Tahir Javed1, Mahrukh Elahi Ghumman1,

5

Mohsin Raza1, Spogmai Khan1, Waqas Ahmad1

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Affiliations: 1Undergraduate students, CMH Lahore Medical College and Institute of Dentistry,

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Lahore Cantt, Pakistan

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2Undergraduate

student, Portland State University, Oregon, USA

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Running title: Psychometric properties of Internet Addiction Test in the Pakistani population

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Corresponding author:

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Ahmed Waqas

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Email: [email protected]

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Contact #: +92-03434936117

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Address: CMH Lahore Medical College and Institute of Dentistry, Lahore Cantt, Pakistan

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Abstract word count: 319

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Manuscript word count: 2569 (excluding tables and references)

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Funding: none

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Conflicts of interest: none

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Abstract

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Introduction:

26

Despite growing concerns over pathological use of the Internet, studies based on validated

27

psychometric instruments are still lacking in Pakistan. The present study aimed to examine the

28

psychometric properties of Young’s Internet Addiction Test (IAT) in a sample of the Pakistani

29

population. We examined the validity, internal consistency, readability and floor and ceiling

30

effects of IAT scores.

31

Methods:

32

This cross-sectional study was conducted at CMH Lahore Medical College and Institute of

33

Dentistry, Lahore, Pakistan from 1 March 2015 to 30 May 2015. A total of 522 medical and

34

dental students completed the questionnaire, which consisted of three sections: (a) demographics

35

and percentage grades in annual examinations, (b) a categorical question to record the estimated

36

number of hours spent on the Internet per day, and (c) the English version of the IAT. All data

37

were analyzed in SPSS v. 20. Principal axis factor analysis was used to validate the factor

38

structure of the IAT in our study sample. An alpha coefficient > .7 was sought in the reliability

39

analysis. Histograms and the values of skewness and kurtosis were analyzed for floor and ceiling

40

effects. In addition, readability of the IAT was assessed as the Flesch Reading Ease score and

41

Flesch-Kincaid Grade level function.

42

Results:

43

A total of 522 medical and dental students participated in the survey. Most respondents were

44

female medical students enrolled in preclinical years of their degree program. Median age (min-

45

max) of the respondents was 20 years (17-25 years). A single-factor model for IAT score

46

explained 33.71% of the variance, with a high alpha coefficient of .893. In addition, the IAT had

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good face and convergent validity and no floor and ceiling effects, and was judged easy to read

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by participants.

49

Conclusion:

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The English version of the IAT showed good psychometric properties in a sample of Pakistani

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university students. A single-factor model for assessing internet addiction showed good

52

reliability and was found suitable with our study sample.

53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69

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70 71 72

Introduction

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There has been tremendous growth in the number of Internet users in Pakistan, from 0.1% of the

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total population in 2000 to 10.9% (over 20 million) in 2013 1. This sudden rise in Internet usage

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has attracted much attention from mental health experts interested in exploring the potential

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harms associated with its excessive or pathological use.

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The problematic, uncontrollable and impulsive use of the Internet has been

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conceptualized as a behavioral addiction comparable to pathological gambling 2. The etiology of

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these behavioral addictions is rooted in biological processes such as conditioned learning and the

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brain’s reward system. Hence, certain behaviors elicit short-term rewards, promote continuous

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behavior and diminish control over behavior 3. Such behaviors are being recognized as a

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compulsive-impulsive spectrum disorder 2 entailing at least three domains: gaming, pornography

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and emailing/text messaging 4. According to Shapira et al., the diagnostic criteria for Internet

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addiction include (a) maladaptive and excessive use of the Internet for longer times than planned,

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(b) significant impairment in social, occupational and other domains of functioning, and (c)

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excessive use that cannot be accounted for by any axis I disorders 5.

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Previous studies have increasingly delineated the harmful effects of problematic use of

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the Internet in different populations. Such use has been associated with significant psychosocial

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impairment leading to low work performance, relationship problems, loneliness, self-destructive

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behaviors and several psychiatric disorders such as depression, anxiety, social phobias and

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Attention Deficit Hyperactivity Disorder5–11. Recently, a number of cross-sectional and

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longitudinal studies have explored the association of Internet use with axis II disorders. An

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interesting study by Floros and colleagues reported a high comorbidity of axis II disorders

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including personality disorders and use of impaired ego defenses in a clinical sample of people

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with Internet addiction disorder (IAD) 12. However, in several longitudinal studies, the evidence

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for the direction of a causal relationship between IAD and axis I and II disorders is not yet clear

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10–12,

and more evidence is required.

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Because of the potential harms of Internet addiction, internet gaming disorder has been

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incorporated into section III of the Diagnostic and Statistical Manual of Mental Disorders fifth

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edition (DSM-5) 13. A new diagnostic category of behavioral addictions including Internet

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addiction is also being introduced in the International Classification of Diseases (ICD-11) 14. At present, there are no estimates of the prevalence of IAD in the Pakistani population.

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However, according to Jadoon et al., 44% of Pakistani medical students are regular Internet users

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15.

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psychometric instruments are still lacking in Pakistan. Therefore, the paucity of validated tools to

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study IAD in the Pakistani population warranted the present study. This study aimed to examine,

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in a sample of the Pakistani population, the psychometric properties of the Internet Addiction

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Test (IAT) devised by Young 9. We studied the validity, internal consistency, readability and

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floor and ceiling effects of IAT scores.

Despite growing concerns over pathological use of the Internet, studies based on validated

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The IAT continues to be one of the most extensively used validation tools to study IAD

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in different populations, and in both clinical and nonclinical settings. This test was selected for

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analysis because it has shown excellent psychometric properties in many languages, cultures,

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ethnicities and countries including China 16, Germany 17, France 18, Sweden, Lebanon 19, Greece

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and Bangladesh 21. However, validations in different settings have led to heterogeneous factor

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structures of the IAT, ranging from a one-factor structure to as many as six factors 16–21,

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sometimes giving rise to different constructs.

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Methods

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Study design

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This cross-sectional study was conducted at CMH Lahore Medical College (CMH LMC) and

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Institute of Dentistry, Lahore, Pakistan from 1 March, 2015 to 30 May, 2015. Ethical approval

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was sought from and granted by the Ethical Review Committee of CMH LMC. A total of 550

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questionnaires were distributed among medical and dental students enrolled in all years of the

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medical or dental degree program. Respondents were selected with a random sampling approach

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using computer software. All respondents read and signed a consent form, and were ensured

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anonymity and that only group findings would be reported.

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The questionnaire consisted of three sections: (a) demographics of the respondents, (b) a

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categorical question to document the estimated number of hours spent on the Internet per day,

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and (c) the IAT developed by Young 2,22. This instrument has shown excellent psychometric

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properties 16–21 in a variety of settings. It consists of 20 items that investigate the respondent’s

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potentially problematic use of the Internet and disruption in psychosocial functioning 22.

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Responses are recorded on a 6-point Likert scale of frequencies, ranging from “does not apply”

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(0) to “always” (5). For purposes of analysis, a global score is obtained by adding the scores for

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the responses to each item.

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Pilot survey

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Before starting the survey, a pilot study was conducted at CMH LMC in a sample of 20 medical

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students selected by convenience sampling. We received positive comments from the

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participants that the English version of the IAT was easily comprehensible. Therefore, we did not

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feel the need to translate it into Urdu (the official language of Pakistan).

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Sample size calculation

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Sample size calculations are generally based on expected effect sizes and variability in the study

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sample. Both of these were unknown before we started the study; so we relied on “rules of

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thumb” to calculate the sample size for factor analysis. Comrey and Lee suggested samples of

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500 or more for factor analysis studies 23. According to their rating scale, a sample size of 100 is

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considered poor, 200 fair, 300 good, 500 very good, and 1000 or more as excellent. Therefore,

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we aimed for a sample size of at least 500 respondents as recommended by Comrey and Lee 23.

149 150

Data analysis

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All data were analyzed in SPSS v. 21 (IBM Chicago, IL, USA). Frequencies and were calculated

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for demographic variables, and descriptive statistics were obtained for total scores on the IAT.

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Assumptions of normality and floor and ceiling effects of IAT scores were verified by plotting

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histograms and Q-Q plots. The percentages of individuals with the lowest and highest possible

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IAT scores were recorded to examine floor and ceiling effects, and values >20% were considered

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significant.

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Exploratory factors with principal axis factoring and quartimax rotation were studied to

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analyze the factor structure of the IAT. The suitability of principal axis factoring for our

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purposes was determined with the following criteria: correlation coefficient >0.3 for all

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variables, Kaiser-Meyer-Olkin (KMO) value greater than 0.6, and a statistically significant

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Barlett test of sphericity (P < 0.05). The maximum number of components to be retained was

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determined with a Cattell’s scree plot, eigenvalues >1, an interpretability criterion, the amount of

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variance explained, and reliability analysis. Factor loading values > 0.3 were sought. Internal

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consistency of the IAT was evaluated with Cronbach’s alpha reliability analysis, and an alpha

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coefficient of > .70 was considered acceptable 24. Item total correlations were analyzed with

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Pearson’s product moment correlation coefficient, and values between 0.2 to 0.8 were sought 24.

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Convergent validity of the IAT was evaluated by analyzing the association between the number

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of hours spent on the Internet per day and the IAT score. Participants were asked, “How many

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hours do you estimate you spend on the Internet each day?”. Responses were recorded on the

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following scale; (a) 1 hour to 3 hours, (c) >3 to 6 hours or more. This

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association was analyzed with one-way analysis of variance (ANOVA). A similar study that

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analyzed the convergent validity of the IAT in a Greek population sample used the same method

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to determine convergent validity 20.

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Readability of the questionnaire was recorded as the Flesch Reading Ease score and

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Flesch-Kincaid Grade level function 25. Associations between gender, residence, year of study,

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degree program and respondents’ IAT scores were analyzed with independent sample t-tests.

177 178

Results

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Of the 550 questionnaires distributed, 522 (94.90%) were returned. Most of the respondents were

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female medical students enrolled in preclinical years of their degree program. Median age (min-

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max) of the respondents was 20 years (17-25 years). Most students were average users of the

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Internet (from >1 to 3 hours daily). Detailed results for demographic characteristics and Internet

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use are shown in Table 1.

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The independent sample t-test showed that male students scored significantly higher on

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the IAT than females. According to one-way ANOVA and post-hoc least significant difference

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(LSD) tests, IAT scores were positively associated with hours spent using the Internet. Detailed

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results are given in Tables 1 and 2.

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The IAT demonstrated easy readability, with a Flesch reading ease value of 71.1 (rated as

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fairly easy) and a Flesch-Kincaid level of 7.1. Respondents indicated that items 1, 2, 12, 14, 16

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and 17 were the easiest to understand, whereas items 3, 4, 19, 20 were the hardest.

191 192

Construct validity

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The overall KMO value for sample adequacy was 0.920, which is classified as meritorious which

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according to Kaiser’s criteria (1974). The Bartlett test of sphericity was significant (P < 0.001).

195

Therefore, the data in the present study were suitable for exploratory factor analysis. Inspection

196

of the correlation matrix showed that all variables had at least one correlation coefficient greater

197

than 0.3.

198

Initially, principal axis factor analysis with the quartimax method extracted three

199

components/factors with an eigenvalue >1 and a high degree of cross-loading of statements on

200

different factors. Most of the variance in IAT scores was explained by the first factor (33.71%),

201

while the second factor was associated with a modest variance of 7.68%, and the third with a

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variance of 5.79%. However, the lack of theoretical underpinning for this three-factor structure,

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visualization of the Cattell’s scree plot (Figure 1) together with the modest variance explained by

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second and third factors favored a unidimensional model of the IAT. Factor loadings of

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the rotated three-component solution for the 20-item IAT based on eigenvalues greater than 1 are

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presented in Table 3. Factor loadings for the unrotated one-factor structure of the test are given

207

in Table 4.

208 209

Normality and floor and ceiling effects

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Mean IAT score was 43.8. Inspection of skewness (−0.030, std. error = 0.107), kurtosis (−0.486,

211

std. error = 0.213) and the histogram (Figure 2) revealed that IAT scores did not deviate

212

significantly from normality, and no floor or ceiling effects were found in IAT scores for the

213

present sample.

214 215

Reliability analysis

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The IAT consists of 20 items. Cronbach’s alpha value for the one-factor structure of the IAT was

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.893, which indicates excellent reliability of this tool in the present study sample. Item total

218

statistics for the IAT are detailed in Table 5. All items had corrected item correlations greater

219

than 0.3, thus exhibiting the same construct. To further analyze internal consistency, item total

220

correlations adjusted for overlap were calculated for each item; these values ranged from 0.32 to

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0.60, which reflect substantial and moderate correlation.

222 223

Discussion

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The English version of the IAT was judged easy to read, and had good face, content and

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convergent validity and high internal reliability in our sample of Pakistani medical and dental

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students. In addition, our analysis detected no floor or ceiling effects in IAT scores.

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Initial exploratory factor analysis revealed a three-factor structure based on Kaiser’s

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criterion of eigenvalues >1. However, the factor structure of the IAT was not very clear cut, with

229

a few items cross-loading on different factors. The three-factor structure for the IAT lacks any

230

theoretical underpinning, therefore the Cattell’s scree plot together with the modest variance

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explained by the second and third factors favor a unidimensional factor structure for the IAT.

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These results are in consonance with the factor structures of the Arabic 19, French 26 and

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Portuguese 27 versions of this test. However, studies of the psychometric properties of the IAT in

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Germany 17, Korea 28, USA 29, Bangladesh 21, Malaysia 30, Italy 31, Greece 20 and China 16 have

235

reported heterogeneous factor structures for the IAT. Factor models ranging from two to six

236

components have been proposed in different studies with different factor loadings and constructs,

237

albeit with very high internal consistency for this instrument. These discrepancies may be due to

238

the use of different factor analysis techniques, and/or to variations in demographics, culture and

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age groups of the respondents. As noted, sample sizes ranged from as low as 151 postgraduate

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and undergraduate medical students in Greece 20 to as high as 1882 respondents in a validation

241

study of the IAT in Germany 17. The respondents in most studies were college and university

242

students; however, sampling strategies differed in some studies such as the German study 17, in

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which respondents completed an online questionnaire as well as an offline sample, a study of

244

students in the USA who were contacted through Facebook29, and research in China16 and

245

Lebanon19, which involved adolescent male and female students. As noted in the literature, most

246

studies used principal components analysis, although others used exploratory factor analysis and

247

confirmatory factor analysis to validate the factor structure of the IAT in their respective

248

population samples. Regardless of the number of factors that have been extracted to date, all

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studies reported high internal consistency with alpha values ranging from 0.89 21 to 0.93 26. Table

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6 summarizes the factor models that have been proposed in different studies, highlighting the

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population characteristics, methods and results of the different factor analysis techniques.

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Our sample included medical and dental students from Pakistan, which is a

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predominantly Muslim country. Therefore, we expected findings similar to those reported in

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other Muslim populations. For example, as reported in an Arab population, our analysis revealed

255

that item 4 had a low inter-item correlation – a finding that highlights the cultural restrictions

256

regarding premarital relationships in Muslim cultures 19. Similarly, item 1 had the lowest inter-

257

item correlation (0.323), indicating that the number of hours spent online is not a strong

258

determinant of the IAT score, and other factors such as impairment in psychosocial life might

259

play a greater role than has been recognized thus far. A validation study of the IAT in a Bengali

260

population identified four sub-scales, i.e. ‘Neglect of duty’, ‘Online dependence’, ‘Virtual

261

fantasies’, and ‘Privacy and self- defense’21.

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Male students scored higher on the IAT than their female counterparts, probably because

263

males are more likely to engage in cyber-sexual behavior, online gaming and gambling –

264

behaviors that are likely to affect their psychosocial health 32. Similar trends in the scores for

265

male and female respondents were observed in the Bengali population 21.

266 267

Limitations

268

This study evaluated the psychometric properties of the English version of the IAT in a sample

269

of Pakistani medical and dental students. The test demonstrated fairly easy readability and

270

comprehensibility in our study sample. But because most of the general population is not

271

proficient in the English language, further studies are advised to test the psychometric properties

272

of the translated Urdu version of the IAT. Our sample comprised randomly selected respondents

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from a single medical school; therefore, future studies should include a more diverse study

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sample. Moreover, comparator instruments were not included in the present study to establish the

275

criterion validity of the IAT; therefore further efforts to address this issue are needed.

276 277

Conclusion

278

The English version of the Internet Addiction Test demonstrated good psychometric properties in

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a sample of the Pakistani population. However, future studies are encouraged to assess the

280

psychometric properties of the Urdu version of this instrument in the general Pakistani

281

population.

282 283

Acknowledgment

284

The authors thank K. Shashok (AuthorAID in the Eastern Mediterranean) for improving the use

285

of English in the manuscript.

286 287

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365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383

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Table 1(on next page) Demographic characteristics of respondents and mean Internet Addiction Test scores (n = 522)

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Table 1. Demographic characteristics of respondents and mean Internet Addiction Test scores (n

2

= 522)

Variable

Gender

Male

Frequency

Median (min-

Mean IAT

Statistical

(n)

max)

score (SD)

value

194 (37.2%)

-

48.96 (15.9)

t value = 5.41

Female

328 (62.8%)

Median age (min-max) Study year

Degree

Residence*

Hours spent surfing

-

40.77 (17.2)

20 (17-25)

43.82 (4-95)

t value =.8

Preclinical

296 (56.7%)

-

43.28 (16.7)

Clinical

226 (43.3%)

-

44.52 (17.8)

MBBS

414 (79.3%)

-

45.02 (17.4)

BDS

108 (20.7%)

-

39.19 (15.35)

Off-campus

267 (51.1%)

-

44.27 (16.6)

On-campus

253 (48.5%)

-

43.46 (17.5)

1 hour – 3 hours

220 (42.1%)

-

43.40 (15.4)

>3 – 6 or more

157 (30.1%)

-

50.67 (16.9)

Average user

320 (61.3%)

20-49

Frequent problems

193 (37%)

50-79

Significant

6 (1.1%)

80-100

hours Level of addiction

Χ2 = 2881

problems

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*Missing values 2 or more, 1 denotes P < 0.001

4

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Table 2(on next page) Post-hoc least significant difference test for hours spent surfing the Internet. (Dependent variable: Internet Addiction Test scores)

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Table 2. Post-hoc least significant difference test for hours spent surfing the Internet. (Dependent

2

variable: Internet Addiction Test scores)

(I) hours spent

(J) hours spent

Mean

Std. error

Sig.

difference (I-J)

95% Confidence interval Lower bound Upper bound

-6.32803*

1.76834

0.000

-9.8021

-2.8540

-13.59694*

1.90243

0.000

-17.3344

-9.8595

6.32803*

1.76834

0.000

2.8540

9.8021

>3 – 6 hours or more

-7.26891*

1.71624

0.000

-10.6406

-3.8972

1 – 3 hours 3 – 6 hours or more 1 – 3 hours

>3 – 6 hours or more >1 –3 hours *Mean difference significant at the 0.05 level. 3 4

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Table 3(on next page) Factor matrix for Internet Addiction Test scores in a sample of Pakistani medical and dental school students (n = 522)

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Table 3. Factor matrix for Internet Addiction Test scores in a sample of Pakistani medical and dental school students (n = 522) Factor 1

2

3

Item 1: How often do you find that you stay on-line longer than you 0.349

0.461

0.498

0.348

intended? Item 2: How often do you neglect household chores to spend more time on-line? Item 3: How often do you prefer the excitement of the Internet to 0.437 intimacy with your partner? Item 4: How often do you form new relationships with fellow on-line 0.416 −0.366 users? Item 5: How often do others in your life complain to you about the 0.549 amount of time you spend on-line? Item 6: How often do your grades or school work suffers because of the 0.609 amount of time you spend on-line? Item 7: How often do you check your email before something else that 0.418 you need to do? Item 8: How often does your job performance or productivity suffer 0.542

0.393

because of the Internet? Item 9: How often do you become defensive or secretive when anyone 0.574 asks you what you do on-line?

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Item 10 : How often do you block out disturbing thoughts about your life with soothing thoughts of the Internet?

0.583

Item 11 : How often do you find yourself anticipating when you will go on-line again?

0.563

Item 12: How often do you fear that life without the Internet would be boring, empty, and joyless?

0.483

Item 13: How often do you snap, yell, or act annoyed if someone bothers you while you are on-line? Item 14: How often do you lose sleep due to late-night log-ins?

0.641

0.605

Item 15: How often do you feel preoccupied with the Internet when offline, or fantasize about being on-line?

0.637

Item 16: How often do you find yourself saying “just a few more minutes” when on-line?

0.602

Item 17: How often do you try to cut down the amount of time you spend on-line and fail? Item 18: How often do you try to hide how long you’ve been on-line?

0.565

0.628

Item 19: How often do you choose to spend more time on-line over going out with others?

0.611

Item 20: How often do you feel depressed, moody or nervous when you are off-line, which goes away once you are back on-line?

0.640

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Table 4(on next page) Unrotated factor solution for Internet Addiction Test scores (n = 522)

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Table 4. Unrotated factor solution for Internet Addiction Test scores (n = 522) Factor Item 1

0.338

Item 2

0.487

Item 3

0.431

Item 4

0.405

Item 5

0.549

Item 6

0.601

Item 7

0.418

Item 8

0.530

Item 9

0.576

Item 10

0.586

Item11

0.565

Item 12

0.484

Item 13

0.641

Item 14

0.605

Item 15

0.634

Item 16

0.596

Item 17

0.565

Item 18

0.629

Item 19

0.606

Item 20

0.637

Extraction method: Principal axis factor analysis

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Table 5(on next page) Item total statistics for statements in the Internet Addiction Test (n = 522)

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Table 5. Item total statistics for statements in the Internet Addiction Test (n = 522)

Item

Scale mean if item Scale variance if Corrected item

Squared multiple

Cronbach’s alpha if

deleted

item deleted

total correlation

correlation

item deleted

Item 1

39.41

270.579

0.323

0.272

.894

Item 2

39.77

266.092

0.471

0.344

.889

Item 3

41.08

266.434

0.406

0.286

.891

Item 4

41.06

270.416

0.375

0.291

.892

Item 5

40.33

262.256

0.522

0.311

.888

Item 6

40.39

262.554

0.573

0.425

.886

Item 7

40.36

268.442

0.401

0.215

.891

Item 8

40.54

264.702

0.501

0.386

.888

Item 9

40.57

262.794

0.547

0.370

.887

Item 10

40.20

259.364

0.556

0.371

.887

Item 11

40.46

262.782

0.531

0.346

.887

Item 12

39.66

263.897

0.457

0.278

.890

Item 13

40.46

260.269

0.598

0.426

.885

Item 14

40.08

257.881

0.575

0.398

.886

Item 15

40.63

261.108

0.589

0.418

.886

Item 16

39.62

259.275

0.562

0.399

.886

Item 17

40.12

262.735

0.531

0.353

.887

Item 18

40.45

259.193

0.586

0.418

.886

Item 19

40.67

261.338

0.564

0.425

.886

Item 20

40.68

259.375

0.593

0.468

.885

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Table 6(on next page) Comparison of psychometric properties of different versions of the Internet Addiction Test

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Table 6. Comparison of psychometric properties of different versions of the Internet Addiction

2

Test

Version

Characteristics of

Factor analysis method

study sample

Criteria for

Names of factors, % variance

number of

and reliability

factors Arabic19

817 intermediate

PCA with oblimin

Two

and secondary

rotation

components

school students,

Parallel analysis and

with eigenvalue

mean age 15 (2.12) Velicer’s minimum

>1 but only one

years

average partial (MAP)

of these

test

retained

One factor, 40.64%, α= .921

Confirmatory factor analysis Malay30

162 undergraduate

Principal component

Five factors

Lack of control, Neglect of duty,

medical students,

analysis with varimax

with eigenvalue

Social relationship disruption,

>1

Problematic use, email primacy,

mean age 19 (0.19) rotation method years

63.84%, Factor-wise alpha values: .55 – .89, For all items: .91

Banglades 177 internet users,

Principal component

Four based on

Neglect of duty, Online

h21

mean age 22.33

(PC) with varimax

Cartell scree

dependence, Virtual fantasies,

(2.01) years

rotation

plot

and Privacy and

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self-defense 55.68%, Cronbach’s alpha = .89 for the IAT, and .60 – .84 for the factors Italian31

485 college

Principal axis factoring

Parallel

Emotional and cognitive

students, mean age

with oblique rotation

analysis, scree

preoccupation with the Internet

24.05 (SD 7.3)

(promax criterion)

plot, eigenvalue

and

>1

Loss of control and interference

years

with daily life, One factor model = 36.18% Two factor model = 42.15%, Alpha values for one-factor solution (Cronbach’s alpha = .91), and the two-factor solution (Cronbach’s alpha = .88 and Cronbach’s alpha = .79) Chinese16

844 Hong Kong

Confirmatory factor

Chinese

analysis results

and social problems, time

adolescents

indicated 18-item

management and performance,

(37.7% boys),

second-order

and reality substitute. A total of

mean age 15.9

three-factor model

80.5%, 94.7% and 95.9% of the

(standard deviation

-

Withdrawal

total variances

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3.5) years

of the second-order factor were accounted for. Cronbach’s alpha = .93).

Factor wise = .87, .86 and .70 Korean28

279 college

Principal components

students at a

analysis with varimax

Withdrawal, and Avoidance of

national university

rotation

reality, 58.91%, α= .91

Portugese

593 Portuguese

Confirmatory factor

27

students, average

analysis, with robust

age 19.9 (SD =

maximum-likelihood

2.7) years

estimates (MLR)

151 postgraduate

Greek20

Eigenvalue >1

Excessive use, Dependence,

-

One factor, α = .90

Exploratory factor

Visual

‘Psychological/Emotional

and undergraduate

analysis with varimax

examination of

conflict, Time management and

medical students

rotation

a scree plot and

Neglect work, 55.3%, α= .91

eigenvalues >1 USA29

German17

215 Undergraduate Exploratory factor

Scree plot and

Dependent use and Excessive

students selected

analysis with varimax

eigenvalues >1

use, 91%, α= .90 – .93

through Facebook

rotation

Online (ON)

EFA with varimax

Horn’s parallel

Emotional and cognitive

sample (n= 1041,

rotation

analysis

preoccupation with the Internet

age 24.2 – 7.2

and Loss of control and

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years) and Offline

interference with daily life,

[OF] sample, n =

46.7% (ON) and 42.0% (OF), α

841, age: 23.5 –3.0

= .91 (ON) and α = .89 (OF)

years French26

246 adults, age:

Exploratory factor

Velicer’s

mean 24.11,

analysis, confirmatory

minimum

standard deviation

factor analysis

average partial

9, range 18–54

One factor, 45%, α = .93

(MAP) test

years) 3

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1 Cattell's scree plot for Internet Addiction Test scores in a sample of Pakistani medical and dental students

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2 Histogram of the distribution of Internet Addiction Test scores in a sample of Pakistani medical and dental students

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