Symptom Checklist SCL-90

The SCL-90 [19] is an instrument for the measurement of psychological distress and certain aspects of psychopathology. It comprises 90 statements that describe physical and psychic symptoms. Subjects were asked to indicate the amount they were bothered by each of the symptoms over the past week on a 5-point Likert scale ranging from “not at all” (0) to “extremely” (4). Applying factor analysis, Derogatis [19] had derived nine subscales or dimensions from the instrument which he labeled somatisation (SOM), obsessive-compulsive (O-C), interpersonal sensitivity (INT), depression (DEP), anxiety (ANX), hostility (HOS), phobic anxiety (PHOB), paranoid ideation (PAR), psychoticism (PSY), and additional items (ADD). A high score in a given dimension indicates high expression of the corresponding distress. The Chinese version of SCL-90, as it was adapted and tested by Wang [20] and were widely used in researches and clinical measures in China [21].

Young's Online Internet Addiction Test

Young's online Internet addiction test has 20 items associated with online Internet use, including psychological dependence, compulsive use, and withdrawal, as well as the related problems of school or work, sleep, family, and time management. For each item, a graded response is selected from 1 =  “Rarely” to 5 =  “Always”, or “Does not Apply”. People scored more than 50 were thought experiencing occasional or frequent problems because of the Internet. People scored more than 80 was thought causing significant problems in their life [22]. In present study, participants scored more than 80 were viewed as Internet addicts.

Participant Selection

In September 2008, 2132 freshman students were tested using the SCL-90. The data were obtained from 1024 (48%) female and 1108 (52%) male student. In Sept. 2009, all of them were tested by Young's online Internet addiction test. To control participants' exposure time to the Internet, students majoring in software, computer information, and related fields were excluded from survey. By Young's definition [9], a total of 66 students (12 female) were judged to be Internet addicts in this study. In order to know if these 66 students were addicted to Internet when they just entered the university (Sept. 2008), a retrospective diagnosis was assessed on these Internet addicts. Seven addicted male students were excluded because their classmates or tutors reported that they were familiar with the Internet when they entered the university. This is to guarantee that all changes were taken placed in their first year in the subjects. The other 59 students were unfamiliar with the Internet as freshmen; however, one year later, they were diagnosed as addicted to the Internet. Also, the mental states of these 59 IADs were measured using SCL-90 (Sept. 2009). The first test of SCL-90 was arranged by the university (It is the university's policy to know all students' mental fitness when they entered the university). So, no informed consent forms were signed. In the second time, each subject signed an informed consent form for the study. The research procedure was in accordance with the ethical principle of the 1964 Declaration of Helsinki (World Medical Organization). The institute review board of Zhejiang Normal University approved the research procedure.

Mental States before Addiction

Based on the comparison, we find that the scores of the 59 students were lower than the norm for most of the SCL-90 dimensions before their addiction. Only the score of O-C (obsessive-compulsive) dimension among IADs was significantly higher than Norm. The result suggests that people showed more O-C behaviors before they became addicted to the Internet. In fact, addiction is usually defined as a brain disease that manifests as a compulsive behavior, or the compulsive and continued use of a substance or behavior even if the user considers it harmful [23]. This result is consistent with Shapria's study that IADs usually manifest compulsive behaviors [7]. Studies on individuals suffering from substance [24] and tobacco [25] addictions also showed evident in O-C behaviors. Therefore, the relation between O-C and IAD was easily confirmed.

When People Become Addicted to the Internet

The current mental states of IADs can be explored by comparing IAD09 and the norm. Results show that the scores of O-C, DEP, ANX, and HOS in IADs were significantly higher than norm, suggesting that students suffering from IAD likewise currently suffer from the above-mentioned pathological problems. For SOM, INT, PHOB, PAR, PSY, and ADD, findings suggest that IAD is not related with these dimensions. Meanwhile, depression and anxiety were proven types pathological problems associated with IAD in previous studies [14], [16]. The present study therefore supports related findings on DEP and ANX. Previous studies have likewise found that hostility is associated with Internet addiction among males [26]. Hostility has been reported to predict escape-avoidance coping styles, as well as substance use triggered by known cues (e.g., negative emotional states and tension) [27]. For adolescents, higher hostility usually leads to interpersonal conflict and rejection. Since substances are made less available to them, the Internet could provide a virtual world to escape from stress from the real world [28].

Highlights on the SCL-90 Results from 2008 and 2009

The comparative results between the data collected in 2008 and 2009 provide the mental states in these 59 Internet addicts that changed during the year. The scores for INT, DEP, ANX, HOS, and PSY changed significantly during this year. However, scores for SOM, O-C, PHOB, and PAR did not change significantly, suggesting that these dimensions are not related to IAD. Previous studies have in fact shown the harm induced by IAD, such as mood disorders, attentional disorders, and substance dependencies were cited as comorbidities [29], [30]. As such, when comorbid disorders are addressed alongside IAD, patient outcomes can be greatly improved [31].

Precursor or Sequela

The features of SCL-90 dimensions in present study can be divided into four types. First, SOM, PAR, and PHOB did not change greatly before and after their addiction, which means that these dimensions were neither precursors nor Sequela of IAD. Simply put, they showed no relationship with IAD. Second, the O-C score was much higher than the norm before IAD, and thus, could be considered a predictor for IAD. However, The O-C score did not change significantly in 2009, which may somehow affect the reliability of this finding. In one hand, results suggest that the O-C can be a predictor of IAD since it showed a higher score before Internet addiction. Yet, since O-C score did not change significantly in 2009, the O-C dimension may not be related to IAD. As such, we can not absolutely conclude the certainty of O-C being a predictor of IAD.

Third, before their addicted to Internet, the scores of DEP, ANX, and HOS for students with IAD were lower than the norm, which means that nothing erroneous was found in these dimensions. Essentially, these dimensions can not be categorized as predictors of IAD. After their addiction, the dimensions scored high and even increased significantly, suggesting that DEP, ANX, and HOS were outcomes of IAD, and not precursors for IAD. This finding may help us better understand the causality between pathological disorders and IAD [15], [17]. The fourth type, which focuses on INT and PSY, showed that these dimensions were normal before Internet addiction. Although their scores were not significant in relation to the norm compared to the SCL-90 data collected in 2009, it was observed that they changed significantly in 2009, as evidenced by the comparison between the SCL-90 data collected in 2008 and 2009. As such, we can conclude that the increased score for INT and PSY dimensions were outcomes of IAD.

A large number studies have explored the predictors of Internet addiction. Communication pleasure [5], impulsivity [32], and competition and cooperation [33] were proven predictors of Internet addiction. Most of these studies have emphasized on experiences in using the Internet and personality traits as related to Internet addiction. However, only few studies clearly explored its causality with pathological disorders. The results of present study may further our understanding about the relationship between pathological disorders and Internet addiction. Thus, the causal relationship between pathological disorders and Internet addiction should be further evaluated by prospective studies.

Limitations and Shortcomings

Results from present study revealed several important findings to deepen our understanding about the pathological disorders of Internet addiction, however, several limitations should be considered. First, this research lasted for one year. During this year, many things happened that might change a person's mental states. So, it is hard to make conclusions with 100 percent certainty that these changes were related with IAD. Second, the SCL-90 is a useful tool in measuring the mental states in the recent past week, however, it can not trace the changing process during a longer period. This research only showed the static mental states of the students before and after their addicting to Internet. Third, the number of IADs is limited (59), more participants should be found if possible in future studies. Fourth, we used the norm but not the data from control group as comparison level. This is because it is very hard to do another extensive investigator as the first measure in present study. Using the norm as comparative level is useful and easy.

Although there are so many limitations in this study, we still believe it is valuable. First, it is harder to control extra variables in longitudinal studies than in experimental studies, especially studies with patients. Second, the present study showed that it is hard to find a solid predictor for IAD, which is different from previous study results. It broadened our knowledge about IAD.

Conclusions

In summary, we can find that there are no solid pathological predictors for IAD. While O-C may be considered as one dimension, it remains that this finding cannot be absolutely concluded. On the contrary, Internet addiction disorder may bring some pathological problems to the people who suffering from it, although, the conclusion still need more support because of the limitation of the research design in present study.