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The recent surge of affordable computers on the market has established that personal computers are both easily obtained and an essential learning tool at many educational levels. Specifically, the Internet has become indispensable to teachers and students, as it provides a plethora of information as well as various programs for entertainment and easy interpersonal communication. Unfortunately, for many of the same reasons that the Internet has expanded and enriched the lives of school-aged children, some unwanted effects have begun to appear in the form of overreliance or extended Internet use. Although there is no official diagnostic classification for a pathological preoccupation with the Internet, some professionals have proposed that this phenomenon be considered an Internet addiction (1–3). The condition is characterized as an impulse-control disorder that primarily involves psychological dependence on the Internet (3). Internet addiction is considered a behavioural addiction akin to pathological gambling, but further in-depth studies are needed to clarify whether it is a new diagnostic entity. In addition, there remains some hesitation about the use of the term “addiction,” despite the apparent descriptive fit between what constitutes an addictive disorder and what has been observed behaviourally in individuals with extensive and pathological Internet use. For this study, we use the term “excessive Internet use” to describe an overindulgence or abuse of the Internet to the extent that such use results in psychological dependence and a significant decline in sociopsychiatric functioning (4). The literature on excessive Internet use has begun to report on the various clinical problems associated with this behaviour. One study has suggested that the Internet is used to counteract other deficiencies in the person’s life, such as poor social relationships, lack of friends, dissatisfaction with physical appearance, disability, and poor coping (1). The range of clinical and environmental problems that have been associated with excessive Internet use include functional impairment and an increased likelihood of Axis I psychiatric disorders (5), increased social isolation (6), and a decreased sense of well-being (7). In regard to premorbid conditions, another study has suggested that preoccupation with the Internet may be related to various clinical problems that predate Internet use, including depression, anxiety, and low self-esteem (3). There also exists a small body of literature examining the personality traits of addiction-prone individuals, which include increased shyness, introversion, and social withdrawal (8,9–11). The results of the literature thus far suggest not only that excessive Internet use can have potential negative effects on a person’s functioning but also that certain symptom clusters may predispose some individuals to preoccupation with the Internet. The frequency and intensity of Internet use seems to vary widely among adolescents. Although this age group tends to be quite impressionable and may use the Internet extensively, not all overindulge or abuse it. Even fewer adolescents seem to experience detrimental side effects as a result of their Internet use; however, cases have begun to appear in academic and mental health settings. The research to date indicates that significant impairments in personality and psychiatric symptomatology are associated with excessive Internet use. Accordingly, our objective in this study was to further contribute to the literature by examining the psychiatric symptoms and personality profiles of excessive Internet users in an adolescent population. More specifically, this study attempts to describe the clinical profile of adolescents to help identify both the consequences of excessive Internet use and the personality traits that may make some adolescents more vulnerable to Internet abuse. Materials and MethodsSubjects Busan City, Korea, has 15 districts that can be divided into 3 groups: upper, middle, and lower economic status. One district was selected randomly from the upper, 2 from the middle, and 1 from the lower group. We than used a 2-stage sampling method to select 4 senior high schools from each of the 4 districts. From the selected schools, 337 first- to third-year students were approached with the opportunity to participate in the current research study. Of the original pool of participants, we used data from 328 volunteers (9 students did not complete the questionnaire). The mean age was 16.2 years, SD 0.95 (range 15 to 19 years). The subjects were evenly distributed in their grades and sex (Table 1).
Methods The questionnaire package comprised 4 measures: a brief personal profile including Internet use patterns during the previous month, the IAT, the SCL-90-R, and the 16PF. The questionnaires were administered in the middle of May 2002 because Korean students are not expected to take any kind of regular school examination for approximately 1 month before and after this point. We hypothesized that the Internet use patterns of students at this point might represent students’ usual patterns of Internet use. We obtained written informed consent from the participating students and from homeroom teachers and principals, since they represent the students’ parents at school in Korea. The ethical committee of our university medical centre approved the study protocol, and all data were collected simultaneously. Internet Addiction Test We used the IAT (3) to measure levels of Internet use during the previous month. The IAT has 20 items associated with Internet use, including psychological dependence, compulsive use, and withdrawal, as well as related problems of school, sleep, family, and time management. For each item, a graded response is selected (1 = “not at all” to 5 = “always”), and total scores can range between 20 and 100. The internal consistency (Cronbach’s alpha) of the IAT was 0.92, and its test–retest reliability, performed biweekly, was also satisfactory (r = 0.85, n = 60, P < 0.001). In a previous study (4), cut-off scores for the IAT were developed to divide Internet users into minimal (scores 20 to 39), moderate (scores 40 to 59), and excessive (scores 60 to 100) users on the basis of the severity of their Internet addictive behaviour (that is, total IAT scores) and the scores of a questionnaire probing Internet-induced behavioural alterations that are most likely associated with problems in the 5 areas of daily life. These same cut-off scores were used in the current study. Symptom Checklist-90-Revision The SCL-90-R is one of the most widely used and well- validated self-report symptom inventories designed to reflect the psychological symptoms seen in psychiatric and medical patients (12). Respondents rate 90 items using a 5-point scale (1 = “no problem” to 5 = “very serious”) to measure the extent to which they have experienced the listed symptoms in the last 7 days. The items are divided into 9 subscales: Somatization, Obsessive–Compulsive, Interpersonal Sensitivity, Depression, Anxiety, Hostility, Phobic Anxiety, Paranoid Ideation, and Psychoticism. Higher scores on the SCL-90-R indicate greater psychological distress. The SCL-90-R also has 3 global indexes: the Global Severity Index (GSI) measures the extent or depth of the individual’s psychiatric disturbance; the Positive Symptom Total (PST) counts the total number of questions rated above 1 point; and the Positive Symptom Distress Index (PSDI) represents the intensity of symptoms. Sixteen Personality Factor Questionnaire The 16PF, developed from the theories of Cattell and others, measures an individual’s underlying “normal” personality traits (13). Cattell and others’ measure is based on 16 primary factors or source traits that were believed to identify an individual’s total personality. Items for each factor are scored on a bipolar scale, and the primary factors are then combined to form global secondary factors. Data Analyses We performed all statistical analyses using SAS for Windows (14). In addition, we performed the chi-square test to find out whether statistical differences existed among the groups. We used 1-way ANOVA to find out whether differences existed among the groups on the SCL-90-R and 16PF. We made multiple comparisons and used the Bonferroni test when there was a significant difference among the groups. Linear and quadratic trend analysis were also examined to test the trends among the groups. A score of 70 is 2 SDs above the mean of each SCL-90-R scale and is considered clinically significant. We calculated the percentage of students with a score above 70 on the SCL-90-R and tested differences among the groups for significance, using the Cochran–Mantel–Haenszel test. ResultsStatus of Internet Use Of the 328 students, 269 (82.0%) reported use of the Internet during the previous month, and 59 students (18.0%) denied any use. Of the students who reported Internet use, 146 were male (89.0%) and 123 were female (75.0%), a significant difference (c2 = 17.2, P = 0.001). There were no differences in Internet use among the 3 grades. Length of Internet Use Average daily length of Internet use during weekdays was 0.8 hours, SD 1.1, for minimal users; 1.5 hours, SD 1.5, for moderate users; and 2.3 hours, SD 1.7, for excessive users. Results indicated significant differences among the 3 user groups (F = 14.5, P = 0.001). The average daily length of Internet use during weekends was 1.6 hours, SD 1.3, for minimal users, 2.4 hours, SD 1.6, for moderate users, and 3.5 hours, SD 3.6, for excessive users, which also revealed significant differences among the 3 groups (F = 13.7, P < 0.001). The multiple comparisons revealed a significant difference in the daily length of Internet use during weekdays and weekends among the 3 groups, with significantly longer use by excessive users, followed by moderate and minimal users. Ongoing Main Internet Activities According to the students’ self-report, the Internet was used mainly for virtual games (72.1%), chat room activity (12.3%), school-related activities (7.1%), file downloads (5.2%), news groups (1.9%), and other (1.4%). There was no significant difference among the 3 user groups in the principal Internet activities. The most frequent Internet activities reported by excessive users were virtual games (87.5%) and the use of chat rooms (12.5%). Principal activities differed between the sexes, with male students preferring games and female students preferring chatting (c2 = 171.9, P < 0.001). Internet Addiction Test According to the IAT cut-off score, 59 students (18.0%) were nonusers, 155 students (47.3%) were minimal users, 98 students (29.9%) were moderate users, and 16 students (4.9%) were excessive users. The 59 nonusers comprised 18 male students (30.5%) and 41 (69.5%) female students; the 155 minimal users comprised 74 (47.7%) male students and 81 (52.3%) female students; the 98 moderate users comprised 62 (63.3%) male students and 36 (36.7%) female students; and the 16 excessive users comprised 10 (62.5%) male students and 6 (37.5%) female students. A comparison of sex representation showed that male students significantly outnumbered female students in both the moderate and excessive user groups (c2 = 17.2, P = 0.001). Comparison of Average SCL-90-R Scores by Groups Table 2 represents the means, SDs, and ANOVAs with post hoc comparisons for each group. Some significant between-group differences were found on 8 subscales and 2 global indexes (the GSI and PSDI). Overall, excessive users had significantly higher scores than minimal users on all subscales except Paranoid Ideation, as well as on 2 of the global indexes (GSI and PSDI), which suggests higher levels of pathology among students who report excessive Internet use. We found no statistically significant differences among the subscales and global indexes for the nonuser, minimal, and moderate user groups. However, when we examined the trend analysis, the subscales Obsessive–Compulsive (F = 5.72, P = 0.017), Interpersonal Sensitivity (F = 6.54, P = 0.011), and Anxiety (F = 9.46, P = 0.002), as well as the PST (F = 3.93, P = 0.048), showed a U function. Conversely, the subscales Depression (F = 5.89, P = 0.016), Hostility (F = 6.02, P = 0.015), and Phobic Anxiety (F = 4.07, P = 0.045), as well as the GSI (F = 0.90, P = 0.028) showed an offset U function. The PSDI (F = 8.79, P = 0.003) showed a linear increase.
Table 3 shows the results of analyses that used the Cochran–Mantel–Haenszel test to compare the 4 groups with scores over 70 on the SCL-90-R subscales. Means are reported in terms of the percentage of students in each group with scores 2 SDs above the mean. We found significant differences among the groups for 2 subscales (Obsessive– Compulsive and Hostility) and 2 indexes (GSI and PST). In all cases where differences were found, the excessive users group had a significantly higher percentage of students with scores above 70 than did the other 3 groups. Among excessive users, the percentage of students scoring above 70 was shown to be highest for Obsessive–Compulsive symptoms (25.0%); followed by Hostility, Paranoid Ideation, and GSI (all 18.8%); and Somatization, Interpersonal Sensitivity, Depression, Anxiety, and Psychoticism (all 12.5%). An interesting pattern among the nonusers emerged, wherein students in this group reported greater levels of pathology on 7 of 9 SCL-90-R subscales and had significantly higher GSI and PST scores than did the minimal users group. This finding suggests a certain degree of symptomatology in students who do not have at least some exposure to the Internet.
Comparison of Average 16PF Scores by Groups Table 4 represents the mean, SD, and ANOVA, with post hoc comparison, for each of the 4 study groups. The mean score for every factor is 5.5, with scores of 8 and above and 3 and below considered significant. Because the 16PF measures normal personality, the individual factor scores are used to indicate the direction of traits. The mean scores of all the groups fell within the middle range (between 4.2 and 7.5). The 16PF profiles of excessive users differed significantly from those of the nonusers and minimal users on factors C, M, and Q2 among the primary factors and factor CRE among the secondary factors. When we examined the trend analysis, all factors that showed significant differences in mean values among the groups—M (F = 7.03, P = 0.008), Q2 (F = 18.72, P < 0.0001), and CRE (F = 7.92, P = 0.005)—showed a linear increase, whereas factor C (F = 8.93, P = 0.003) showed a linear decrease. In addition to these findings, factors that did not show significant differences in mean values among the groups—E (F = 3.96, P = 0.048), Q1 (F = 4.43, P = 0.036), and IND (F = 4.98, P = 0.026)—did show a linear increase. Factor Q4 showed a linear increase tendency, even though it failed to reach significance (F = 3.75, P = 0.054). Table 4 shows that excessive users revealed that they were easily affected by feelings, emotionally less stable, imaginative, absorbed in thought, self-sufficient, experimenting, and preferred their own decisions, compared with the remaining groups.
DiscussionThis study primarily focused on exploring the psychiatric symptomatology and personality characteristics of Korean senior high school students who report excessive Internet use. Our results indicate that some students use the Internet excessively and that their main ongoing Internet activities are virtual gaming and chatting. Moreover, these excessive Internet users reveal significantly more psychiatric symptoms and have some highly characteristic personality profiles, compared with Korean high school students who report less frequent Internet use. The SCL-90-R is a subjective measure of the degree of psychiatric symptoms. With the SCL-90-R, it is possible to differentiate the students into 2 groups in terms of the frequency of subjective psychiatric complaints (that is, neurotic and psychotic symptoms) and severity of use (that is, excessive vs moderate, minimal, and no use). In this study, the average score on the symptom dimensions reported by students who used the Internet excessively was not high enough to indicate a clinically significant abnormality. However, the results themselves are important because the excessive users revealed more psychiatric symptoms than did the remaining groups. Compared with other groups, a significantly higher percentage of students reporting excessive use had scores above 70 on the Obsessive–Compulsive and Hostility subscales and the GSI, as well as on the PST. These results indicate that students in this study who report excessive Internet use are characterized by complaints of indecisiveness, preoccupation with details, nervousness, irritability, aggressiveness, and impulsivity. The high percentage of excessive users with significant scores on the GSI suggests that the extent or depth of the present psychiatric disturbance is severe in this group. It was interesting to find that 3 of the 9 clinical scales and 1 scale of 3 global indexes in the SCL-90-R showed a U function, and 3 of the 9 clinical scales and 1 scale of 3 global indexes in the SCL-90-R showed an offset U function. These findings show that 1) the nonusers had higher scores than the minimal users, 2) the moderate users reported greater symptomatology than the minimal users, and 3) the excessive users showed the highest level of psychiatric symptoms. Internet use is common and widespread among adolescents. Therefore, not using the Internet may represent a trend deviating from the usual pattern of teenagers’ behaviour, and it might be expected that there will be some difference in psychiatric symptoms between students reporting no Internet use and students reporting at least some Internet use. These trend analysis results suggest a need for further studies to examine psychiatric symptoms of students who do not use the Internet. The Internet addictive process is not fully understood. However, there is a suggestion that personality traits may predispose certain individuals to overuse the Internet (15). In our study, the 4 personality factors most associated with excessive Internet use were factors C, M, Q2, and CRE. Individuals with low scores on factor C tend to have low tolerance for unsatisfactory conditions, to be changeable, to evade the necessary demands of reality, to be irritable, and to show some classic neurotic symptoms (for example, phobias, sleep disturbance, and psychosomatic complaints) (13). The Internet may be used as an escape from reality and, further, may be a tonic for people with inner conflicts. Students with such traits may use the Internet to counteract psychological distress rooted in their personality. Individuals with high scores on factor M can be described as imaginative, absent-minded, absorbed in thought, and impractical. They tend to be unconventional, unconcerned with everyday matters, self-motivated, imaginatively creative, concerned with essentials, often absorbed in thought, and oblivious of particular people and physical realities. The self-guided interests of high-M individuals may lead to unrealistic situations accompanied by expressive outbursts. Their individuality can lead to their rejection from group activities (13). This cluster of traits reflects a personality profile that may predispose an individual to derive a great deal of satisfaction from Internet activities rather than from more conventional social activities or friendships. The main ongoing Internet activity in the present study was game playing. Students who play virtual games excessively may have a more schizoid personality than other students; because of their inward-looking nature, the virtual games themselves are essentially solitary activities. High scores on factor Q2 suggest an individual who is self-sufficient, resourceful, and independent. Potential negative consequence of these traits are that these individuals can become accustomed to taking action on their own and can have some difficulties compromising with others. Although people with high factor Q2 scores do not dislike others, they simply do not feel the need to obtain their agreement or support (13). This trait is consistent with the results from previous studies that have identified both pride and frequent intellectualization as personality characteristics commonly associated with problematic Internet use (8,16). On the Internet, people have the freedom to explore cyberspace on their own, irrespective of social norms. Thus cyberspace may become an attractive place for a student who has the traits of egocentricity, familiarity with having his or her own way, and intellectual curiosity. High CRE scorers are imaginative and willing to explore new ideas. The characteristics of high CRE scorers are closely related to those associated with the high M and Q2 factors described earlier. According to Cattell and others (13), high CRE indicates people who are usually self-sufficient, who are often serious in their demeanour, and who generally prefer solitary activities. Sometimes high CRE scorers are overly imaginative, and their expectations or beliefs can become fantastical. These individuals may fail to see the practical limitations to their ideas. This cluster follows a personality pattern similar to that of the shy, scientific, less empathic, and introverted intellectual who is drawn to the Internet (8,9). A noticeable finding was that factors E, Q1, Q4, and IND showed a linear increase trend even though there were no significant differences in mean values among the groups. According to Cattell and others (13), individuals who score high on factor E tend to be dominant, assertive, self-assured, and independent-minded. Individuals who score high on factor Q1 tend to be experimenting, liberal, critical, open to change, and seeking intellectual stimulation. High scores on factor Q4 are an indication that one tends to be tense, fretful, impatient, and intensely motivated, while high scores on the IND factor suggest increased levels of aggressiveness. Although the small sample size likely contributed to the findings’ lack of statistical significance, the trend analysis helps to further describe characteristics of those who report excessive Internet use. It seems that all these personality traits appear contextually appropriate in the kind of environment provided by the Internet. Our study results suggest that personality profiles should be considered in accounts of the etiology of excessive Internet use among high school students. Future studies should continue to examine how personality traits influence problematic Internet use and should investigate whether a similar personality profile may be an etiologic factor in the development of any addictive syndrome, whether it be to alcohol, gambling, or the Internet. This study has several limitations. First, we used a questionnaire method rather than a direct, in-depth interview. Second, the sample size of excessive Internet users is too small to represent the overall characteristics of the population of excessive users. Third, our results do not clearly indicate whether the symptoms identified in this study preceded the development of Internet-dependent behaviour or were a consequence of Internet use. There is also a need for more studies of adolescents who visit psychiatric clinics and seek professional help for problematic Internet use. Despite this study’s limitations, the picture has begun to emerge that adolescents who overuse the Internet not only have an increased likelihood of psychiatric symptoms but also tend to be socially isolated from their peers. This isolation may not be strictly a result of spending more time on the Internet; it could in fact be an expression of preexisting personality traits. While definitive conclusions should be reserved until future research can produce similar results, an interesting profile has emerged from the results of this study, suggesting that certain personality traits may predispose some adolescents to become “addicted” to the Internet. ConclusionThe present study suggests that Korean senior high school students who use the Internet to excess report more psychiatric symptoms and differ in personality profiles from nonusers, minimal, and moderate users. The 4 personality factors identified appear to explain the profile of an individual who is drawn to the environment of the Internet. The study also provides some characteristic psychiatric symptomatology and personality profiles that may more broadly describe other students who use the Internet to excess. References1. Eppright T, Allwood M, Stern B, Theiss T. Internet addiction: a new type of addiction? Mo Med 1999;96:133–6. 2. Tsai CC, Lin SS. Internet addiction of adolescents in Taiwan: an interview study. Cyberpsychol Behav 2003;6:649–52. 3. Young KS. Caught in the net. New York: John Wiley & Sons; 1998. p 12–120. 4. Yang CK. Sociopsychiatric characteristics of adolescents who use computers to excess. Acta Psychiatr Scand 2001;103:1–6. 5. Shapira NA, Goldsmith TD, Keck Jr. PE, Khosla UM, McElroy SL. Psychiatric features of individuals with problematic Internet use. J Affect Disord 2000;57:267–72. 6. Kraut R, Patterson M, Lundmark V, Kiesler S, Mukopadhyay T, Scherlis W. Internet paradox: a social technology that reduces social involvement and psychological well-being? Am Psychol 1998;53:1017–31. 7. Moody EJ. Internet use and its relationship to loneliness. CyberPsychol Behav 2001;4:30:393–401. 8. Shotton MA. The costs and benefits of ‘the Internet addiction.’ Behav Inform Technol 1991;10:219–30. 9. Douse NA, McManus IC. The personality of fantasy game players. Br J Psychol 1993;84:505–9. 10. Pratarelli ME, Browne BL, Johnson K. The bits and bytes of computer/Internet addiction: a factor analytic approach. Behav Res Methods Instrum Comput 1999;31:305–14. 11. Young KS. Psychology of computer use: XL. Addictive use of the Internet: a case that breaks the stereotype. Psychol Rep 1996;79:899–902. 12. Kim KI, Kim JH, Won HT. Korean manual of Symptom Checkilist-90-Revision. Seoul: Jung Ang Juk Sung Publisher; 1984. p 8–10. 13. IPAT Staff. Administrator’s manual for the 16 PF. Champaign (IL): Institute for Personality & Ability Testing; 1986. 14. SAS Institute Inc. SAS/STAT for Windows. SAS Proprietary Software Release 8.2. Cary (NC): SAS Institute; 2000. 15. Griffiths MD, Dancaster I. The effect of type A personality on physiological arousal while playing computer games. Addict Behav 1995;20:543–8. 16. Pocius KE. Personality factors in human–computers interaction: a review of the literature. The Internets in Human Behavior 1991;7:103–35. Author(s)Manuscript received October 2004, revised, and accepted January 2005. 1. Professor, Department of Psychiatry, Dong-A University College of Medicine, Busan, Korea. 2. Staff Psychologist, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. 3. Associate Professor, Division of Management Information Science, Dong-A University, Busan, Korea. 4. Clinical Psychologist, Department of Psychology, Yang-San Neuropsychiatric Hospital, Yang-San, Korea. Address for correspondence: Dr CK Yang, Department of Psychiatry, Donga-A University College of Medicine, 3 Ga-1, Dongdaesin-dong, Seo-gu, Busan, 602-715 Korea e-mail: ckyang@daunet.donga.ac.kr
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