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Features and Predictors of Problematic Internet Use in Chinese College Students

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Title: Features and Predictors of Problematic Internet Use in Chinese College Students
Language: English
Authors: Huang, R. L., Lu, Z., Liu, J. J., You, Y. M., Pan, Z. Q., Wei, Z., He, Q., Wang, Z. Z.
Source: Behaviour & Information Technology. Sep 2009 28(5):485-490.
Availability: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 6
Publication Date: 2009
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Descriptors: College Students, Internet, Depression (Psychology), Foreign Countries, Incidence, Computer Uses in Education, Student Surveys, Questionnaires, Addictive Behavior, Low Achievement, Family Relationship, Family Influence, Gender Differences, At Risk Students, Interpersonal Relationship, Academic Achievement
Geographic Terms: China
Assessment and Survey Identifiers: Zung Self Rating Depression Scale
DOI: 10.1080/01449290701485801
ISSN: 0144-929X
Abstract: This study was set to investigate the prevalence of problematic internet use (PIU) among college students and the possible factors related to this disorder. About 4400 college students, ranging from freshmen to juniors, from eight different universities in Wuhan, China were surveyed. Young's Diagnostic Questionnaire for Internet Addiction (YDQ) and the Zung Self-rating Depression Scale were used to define PIU and depression accordingly. Data was analysed with "chi-squared" testing and logistic regression. Out of the 3496 participants, 9.58% (male 13.54%, female 4.88%) met the criteria of PIU. Factors such as heavy internet use habits, poor academic achievement, lack of love from the family, etc. were found to be significantly associated with PIU. About 48.51% (1696) of the students were light internet users, who use the internet less than 5 h/week, while 16.36% (572) were heavy users who use it more than 15 h/week, though heavy users were more likely to develop PIU. Also, 25.53% of the students with depression developed PIU, in comparison with 8.91% of PIU among those without depression (p less than 0.001). Being male, frequent internet use, poor academic achievement, poor family atmosphere and lack of love from parents were predictors of PIU among college students. The habit and purpose of using the internet is diverse, which influences the susceptibility of PIU as well. There was a correlation between depression and the development of PIU as well. (Contains 4 tables.)
Abstractor: As Provided
Number of References: 24
Entry Date: 2009
Accession Number: EJ865991
Database: ERIC
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  Value: <anid>AN0043607485;b6q01sep.09;2019Mar27.13:54;v2.2.500</anid> <title id="AN0043607485-1">Features and predictors of problematic internet use in Chinese college students. </title> <p>This study was set to investigate the prevalence of problematic internet use (PIU) among college students and the possible factors related to this disorder. About 4400 college students, ranging from freshmen to juniors, from eight different universities in Wuhan, China were surveyed. Young's Diagnostic Questionnaire for Internet Addiction (YDQ) and the Zung Self-rating Depression Scale were used to define PIU and depression accordingly. Data was analysed with chi-squared testing and logistic regression. Out of the 3496 participants, 9.58% (male 13.54%, female 4.88%) met the criteria of PIU. Factors such as heavy internet use habits, poor academic achievement, lack of love from the family, etc. were found to be significantly associated with PIU. About 48.51% (1696) of the students were light internet users, who use the internet <5 h/week, while 16.36% (<reflink idref="bib572" id="ref1">572</reflink>) were heavy users who use it more than 15 h/week, though heavy users were more likely to develop PIU. Also, 25.53% of the students with depression developed PIU, in comparison with 8.91% of PIU among those without depression (p < 0.001). Being male, frequent internet use, poor academic achievement, poor family atmosphere and lack of love from parents were predictors of PIU among college students. The habit and purpose of using the internet is diverse, which influences the susceptibility of PIU as well. There was a correlation between depression and the development of PIU as well.</p> <p>Keywords: college students; risk factor; depression; problematic internet use</p> <hd id="AN0043607485-2">1. Introduction</hd> <p>The growth of internet users has been exponential. Since 1989, the online population worldwide has grown from 500,000 to over 700,000,000 worldwide (ET Forecasts [<reflink idref="bib9" id="ref2">9</reflink>], Click [<reflink idref="bib6" id="ref3">6</reflink>], Morahan-Martin [<reflink idref="bib17" id="ref4">17</reflink>]). The CNNIC (China Internet Network Information Centre) recently reported that there are a total of 103 million internet users in China (95%CI 96.78 million, 109.22 million). Among them, 46.284 million are aged from 18 to 30. The biggest proportion of internet users is between the ages of 18 and 24, reaching 37.7%. About 54.5% are college students, and the majority of them are students living on campus (CNNIC [<reflink idref="bib7" id="ref5">7</reflink>]).</p> <p>In spite of the widely perceived merits of the internet, policy makers, psychologists, and educators have been aware of the negative impacts of its use, especially excessive use, and the related physical and psychological problems (Young [<reflink idref="bib23" id="ref6">23</reflink>] and [<reflink idref="bib24" id="ref7">24</reflink>], Griffiths [<reflink idref="bib10" id="ref8">10</reflink>]). These include symptoms of internet dependence, such as negative feelings (e.g. depression) when not on the internet, spending excessive time and money when participating in online activities, having a growing tolerance to any effects that may do harm to him/her while online, and developing a strong sense of denial about having any sort of problem (Scherer and Bost [<reflink idref="bib20" id="ref9">20</reflink>], Orzack and Orzack [<reflink idref="bib19" id="ref10">19</reflink>]). These pathological effects of internet use were first proposed by Dr Ivan Goldberg, using the term 'internet addiction'. Further studies utilised other methods to identify this disorder, which was also termed 'internet dependency', 'problematic internet use' or 'pathological internet use' (Davis [<reflink idref="bib8" id="ref11">8</reflink>]).</p> <p>However, up until now, there has been no accepted set of criteria for internet addiction in <emph>Diagnostic and Statistical Manual – Fourth Edition</emph> (DSM-IV, APA, 1994) (Louis [<reflink idref="bib15" id="ref12">15</reflink>]), making its proper detection and diagnosis difficult. Using pathological gambling as a model, Young ([<reflink idref="bib23" id="ref13">23</reflink>]) proposed the diagnostic criteria for 'internet addictive disorder (IAD)' and 'problematic internet use (PIU)', which were used as a starting point for subsequent research. One of the widely used diagnostic criteria is the 'Diagnostic Questionnaire for Internet Addiction' (YDQ; Young [<reflink idref="bib24" id="ref14">24</reflink>]), which was adapted from DSM-IV criteria for pathological gambling (APA, 1994), based on the similarities of PIU to gambling addiction and compulsive shopping, since these disorders do not feature chemical dependence.</p> <p>According to the studies mentioned, students appear to be more vulnerable to developing internet dependence than any other group in society, especially college students as stated by Kandell ([<reflink idref="bib11" id="ref15">11</reflink>]). Nathalie's anecdotal and empirical findings lend support to Kandell's vulnerability model; they further addressed that the ones with shyness and who spent long hours online were even easier to develop internet dependence (Nathalie and Michael [<reflink idref="bib18" id="ref16">18</reflink>]). The prevalence varied in different places. In a survey examining internet addiction among 387 university students, Scherer and Bost ([<reflink idref="bib20" id="ref17">20</reflink>]) found that 13% met the criteria for internet addiction. Chou and Hsiao ([<reflink idref="bib4" id="ref18">4</reflink>]) identified 5.9% as internet addicted in 910 Taiwanese college students, compared with 9.6% in mainland China (Xuanhui and Gonggu [<reflink idref="bib22" id="ref19">22</reflink>]). Chou and Hsiao also found a communication pleasure score to be highly predictive of internet dependence. Liu <emph>et al</emph>. ([<reflink idref="bib14" id="ref20">14</reflink>]) reported that internet dependence was correlated with the grade of the students. Agenta and Gunnar ([<reflink idref="bib1" id="ref21">1</reflink>]) showed that different place for internet access, internet use habits, but not for demographic variables were correlated with the development of PIU. According to the research of Morahan-Martin and Schumacher in 2000, the loneliness students were more likely to develop internet addiction, and some activities such as online gambling and net sex are more common among those who develop internet-related problems than those who do not (Morahan-Martin and Schumacher [<reflink idref="bib16" id="ref22">16</reflink>]).</p> <p>As addictive use of the internet may be associated with significant social, psychological and occupational impairment (Louis [<reflink idref="bib15" id="ref23">15</reflink>]), this study was aimed at investigating the prevalence of PIU and the possible predictors of PIU in college students on a larger scale with more samples, as well as the feature of problematic internet users' behaviour online. We also wanted to find out whether there was a correlation between PIU and negative psychological state.</p> <hd id="AN0043607485-3">2 Subjects and methods</hd> <p></p> <hd id="AN0043607485-4">2.1 Subjects and sampling</hd> <p>A total of 4400 college students, ranging from freshmen to juniors, from eight different universities in Wuhan, a large city in central China, were surveyed. Wuhan is the third largest 'college city' in China, with 343,951 undergraduate students from 24 colleges or universities in the year the survey conducted, among which eight universities with 185,371 college students are 'nationally administrated' (or 'federal administrated', Group 1) and the remaining 16 with 158,580 students are 'provincial administrated' (Group 2).</p> <p>In Group 1, three out of eight universities were selected randomly, then two to three majors were selected randomly from each university. Among the schools/majors selected, for each grade, one class was randomly chosen and students willing to accept the research were surveyed. Before distributing the questionnaires, the purpose of the study and the content were explained to the students and teachers with identified instruction; anonymity was emphasised. The questionnaires were answered and collected immediately. No reward was given. On the basis of the proportion and the number of students in each university, altogether 2376 questionnaires were randomly distributed to students from the three selected universities; while in Group 2, 2024 questionnaires were proportionately distributed to students from five selected colleges in the same way. Finally, the unsatisfactory questionnaires were removed and effective ones were numbered by the investigators.</p> <p>This sample (4400 students) employed the proportional random cluster sampling method, which represented 1.28% college students in Wuhan city.</p> <hd id="AN0043607485-5">2.2 Ways to reduce bias</hd> <p>All ways possible were taken to ensure the reliability of our investigation. First, before the investigation, the objective was fixed beforehand to control selection bias. By choosing students from different fields of study, different grades, confound bias was controlled. Since the questionnaire used in the investigation was a self-rating one, which was read and answered by the subject himself or herself (for instance, a yes or no question about whether you feel loved by your parents). When designing the questionnaire, we asked experts for advice and used as few professional terms as possible to avoid misunderstanding. A pilot survey was also carried out to refine the questionnaire. Second, all the investigators had received unified training to understand the content of the research and explain the items to the students so as to increase the response rate. They were also asked to answer questions during the investigation, verified the information, and supplemented and modified it immediately when any omission was found.</p> <hd id="AN0043607485-6">2.3 Tools used</hd> <p>The tools used in the study were as follows:</p> <p></p> <ulist> <item> 1. <emph>Young's Diagnostic Questionnaire for Internet Addiction</emph> (YDQ). Young adapted seven of the ten DSM-IV criteria for pathological gambling (APA, 1994), and added another item. The questionnaire thus consisted of eight yes/no questions. Respondents who answered 'yes' to five or more of the eight criteria were classified as addicted internet users. Johansson and Götestam also suggested that the fulfilment of three to four criteria during the past 12 months to denote at-risk internet use is more helpful (Agenta and Gunnar [<reflink idref="bib1" id="ref24">1</reflink>]). To detect persons with internet addiction and those who are at very high risk of developing this, so as to facilitate a more effective way to prevent its occurrence, we define those who met four or more questions as indication that these persons were 'problematic internet users'. The consistency tested with Cronbach's alpha was 0.713. Spearman's correlations, calculated between the eight items, show highly significant correlations (<emph>p</emph> < 0.01).</item> <p></p> <item> 2. <emph>Zung Self-rating Depression Scale</emph>. This is a 20-item self-report inventory measure on a four-point scale. Each question is followed by four answers ranging from 'a little of the time' to 'most of the time'. A score was given according to a key consult, correlating with the response to each statement. Add up the numbers for a total score. Students who scored 53 or more were classified as 'depressed'. The highest possible score was 80. The internal consistency of it tested with Cronbach's alpha was 0.81. About validity, Spearman's coefficient showed <emph>ρ</emph> = 0.87, <emph>p</emph> < 0.001 (Kitamura <emph>et al</emph>. [<reflink idref="bib13" id="ref25">13</reflink>]).</item> <p></p> <item> 3. <emph>Other potential predictors of PIU</emph>. Other questions in the questionnaire include demographic variables (gender, age, grade), further demographic variables (state of health, interpersonal relationship, school grade and intimacy with parents), internet usage (frequency, number of hours per week), activities online (surfing, playing games, downloading music, BBS, e-mailing or chatting) and the impact of the internet on their real life (reading news, asking for help, broadening one's horizons, whether the internet had damaged their normal life, etc.).</item> </ulist> <hd id="AN0043607485-7">2.4 Statistical analysis</hd> <p>Professional software (Database 3.0) was used to record the data and checked the data logically. <emph>Chi-square</emph> test was used to test the correlation between PIU and all possible predictors, then all the factors that showed statistical significance in <emph>chi-square</emph> test were analysed by multiple logistic regressions. Using multiple logistic regressions, the impact of each factor on PIU was weighed and the possible prevalence of PIU was estimated. Statistical software was SPSS 12.0.</p> <hd id="AN0043607485-8">3 Results</hd> <p>The response rate was 79.45%, which resulted in 3496 (1898 male and 1598 female) study subjects for the final analysis.</p> <hd id="AN0043607485-9">3.1 Demographic information and PIU rates</hd> <p>Among the 3496 respondents, 54.29% (1898 respondents) were male compared with 45.71% (1598 respondents) female. The age of the respondents ranged from 16 to 30 (20.19 ± 1.26). In general, 9.58% (335 students) of the subjects met the criteria of PIU. Male college students seemed to be more vulnerable to internet addiction. Out of 1898 male college students, 13.54% developed PIU compared with 4.88% PIU out of 1598 female students.</p> <hd id="AN0043607485-10">3.2 Risk factors of PIU</hd> <p>Table 1 shows predictors of PIU and the statistical method used. Being male, frequent internet use, poor academic achievements and poor interpersonal relationships were shown to be the predictors of PIU among college students. Attention was given to the relationship between the college students and their family members, especially their parents, which was often neglected. The result shows that students with a poor relationship with their parents were still, as expected, more vulnerable to PIU. However, the state of health of the subjects along with exercise habits had a negative correlation with the incidence of PIU (data not shown).</p> <p>Table 1. Comparison of PIU and non-PIU over associated factors.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Non-PIU No. (<italic>n</italic> = 3161)</td><td>PIU No. (<italic>n</italic> = 335)</td><td><italic>p</italic></td></tr></thead><tbody valign="top"><tr><td>Gender (<italic>n</italic>, 100%)</td><td /><td /><td>0.000, χ<sup>2</sup> = 74.09</td></tr><tr><td>Male (1898)</td><td char=".">1641</td><td char="(">257 (13.54%)</td><td /></tr><tr><td>Female (1598)</td><td char=".">1520</td><td char="(">78 (4.88%)</td><td /></tr><tr><td>Number of hours online (<italic>n</italic>, 100%)</td><td /><td /><td char=".">0.000</td></tr><tr><td>  <5 h/week (1696)</td><td char=".">1635</td><td char="(">61 (3.6%)</td><td /></tr><tr><td>  5 – 10 h/week (891)</td><td char=".">815</td><td char="(">76 (8.53%)</td><td /></tr><tr><td>  11 – 15 h/week (337)</td><td char=".">286</td><td char="(">51 (15.13%)</td><td /></tr><tr><td>  >15 h/week (572)</td><td char=".">425</td><td char="(">147 (25.70%)</td><td /></tr><tr><td>Maximal days online per week (<italic>n</italic>, 100%)</td><td /><td /><td char=".">0.011</td></tr><tr><td>  1 – 2 days (1997)</td><td char=".">1902</td><td char="(">95 (4.76%)</td><td /></tr><tr><td>  3 – 4 days (710)</td><td char=".">628</td><td char="(">82 (11.55%)</td><td /></tr><tr><td>  >4 days (789)</td><td char=".">631</td><td char="(">158 (20.03%)</td><td /></tr><tr><td>Interpersonal relationship (<italic>n</italic>, 100%)</td><td /><td /><td char=".">0.000</td></tr><tr><td>  Excellent (673)</td><td char=".">618</td><td char="(">55 (8.17%)</td><td /></tr><tr><td>  Good (2201)</td><td char=".">2009</td><td char="(">192 (8.72%)</td><td /></tr><tr><td>  General (566)</td><td char=".">493</td><td char="(">73 (12.90%)</td><td /></tr><tr><td>  Poor (56)</td><td char=".">41</td><td char="(">15 (26.78%)</td><td /></tr><tr><td>Familial atmosphere (<italic>n</italic>, 100%)</td><td /><td /><td char=".">0.000</td></tr><tr><td>  Good (2021)</td><td char=".">1849</td><td char="(">172 (8.51%)</td><td /></tr><tr><td>  General (1398)</td><td char=".">1253</td><td char="(">145 (10.3%)</td><td /></tr><tr><td>  Bad (76)</td><td char=".">59</td><td char="(">17 (22.37%)</td><td /></tr><tr><td>Feel love from parents (<italic>n</italic>, 100%)</td><td /><td /><td char=".">0.001</td></tr><tr><td>  Yes (3139)</td><td char=".">2871</td><td char="(">268 (8.54%)</td><td /></tr><tr><td>  No (357)</td><td char=".">290</td><td char="(">67 (18.77%)</td><td /></tr><tr><td>Willingness to pour out one's heart (<italic>n</italic>, 100%)</td><td /><td /><td char=".">0.001</td></tr><tr><td>  Yes (2112)</td><td char=".">1953</td><td char="(">159 (7.53%)</td><td /></tr><tr><td>  No (1384)</td><td char=".">1208</td><td char="(">176 (12.72%)</td><td /></tr><tr><td>Academic achievement</td></tr><tr><td>  Outstanding (286)</td><td char=".">271</td><td char="(">15 (5.24%)</td><td /></tr><tr><td>  Good (1965)</td><td char=".">1837</td><td char="(">128 (6.51%)</td><td /></tr><tr><td>  General (1097)</td><td char=".">948</td><td char="(">149 (13.58%)</td><td /></tr><tr><td>  Poor (148)</td><td char=".">105</td><td char="(">43 (29.05%)</td><td /></tr><tr><td>Table 1 showed the general information that correlated with PIU. The number of students with different conditions was listed in two main groups, PIU and non-PIU. The figure in the bracket was the number of total students who chose the item and the proportion of PIU number to the corresponding item. For instance, there were 1898 male respondents, with 257 developed PIU, which took the proportion of 13.54%. While within 1598 respondents, only 78 had PIU, which were 4.88% of all female students. Chi-square was done to test the statistical relation between each factor and PIU. The results are shown in the last column.</td></tr></tbody></table> </ephtml> </p> <p>Multiple logistic regressions analysis showed that the model was statistically significant. All factors tested as predictors of PIU are listed in Table 2. Depression, to which we had paid special attention, weighs most heavily in the risk factors of PIU (OR 2.309), which means depressed feeling greatly increase susceptibility to developing PIU. Followed by lack of love from family (OR 2.147), frequent internet use (heavy users OR 1.563), poor academic achievement (OR 1.544), shyness (OR 1.411), maximal time online (OR 1.322) and being male. No statistical significant was found for other general demographic variables (age, social background, school, financial state of the family, etc.; data not shown).</p> <p>Table 2. Multiple logistic regressions of correlated factors for PIU (n = 3496, χ2 = 319.81, p = 0.000).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>OR</td><td>95% Wald confidence limits</td><td><italic>p</italic></td></tr></thead><tbody valign="top"><tr><td>Depression</td><td char=".">2.309</td><td char="–">1.466 – 3.635</td><td char=".">0.000</td></tr><tr><td>Love from parents</td><td char=".">2.147</td><td char="–">1.316 – 3.504</td><td char=".">0.002</td></tr><tr><td>Number of hours online</td><td char=".">1.563</td><td char="–">1.349 – 1.811</td><td char=".">0.000</td></tr><tr><td>Academic achievement</td><td char=".">1.544</td><td char="–">1.299 – 1.836</td><td char=".">0.000</td></tr><tr><td>Willingness to pour out one's heart</td><td char=".">1.411</td><td char="–">1.098 – 1.812</td><td char=".">0.0069</td></tr><tr><td>Maximal days online per week</td><td char=".">1.332</td><td char="–">1.089 – 1.631</td><td char=".">0.0071</td></tr><tr><td>Gender (female)</td><td char=".">0.626</td><td char="–">0.469 – 0.836</td><td char=".">0.004</td></tr><tr><td>Table 2 showed the result of multiple logistic regressions. Depression weighs more heavily in all risk factors of PIU, which means depressed feeling greatly increases the susceptibility to developing PIU, followed by lack of love from parents, long time online, poor academic achievement, unwillingness to pour out one's heart and being male according to the OR. Multiple logistic regressions were applied. (χ<sup>2</sup> = 319.81, <italic>p</italic> = 0.000).</td></tr></tbody></table> </ephtml> </p> <hd id="AN0043607485-11">3.3 Pattern of internet use and PIU</hd> <p>In general, light users formed the largest group among all respondents. Out of 3496 correspondents, 1696 students (48.51% of all respondents) were light users, which was the sum of students who used the internet <5 h/week, followed by 1228 moderate users (35.13%), who used the internet for 5 – 15 h/week and 572 heavy users (16.36%) for >15 h/week, respectively (see Table 1). However, as expected, the result shows that heavy users were more likely to develop internet addiction. Among 572 heavy users, 147 develop PIU, which constitutes 25.70% of heavy users, compared with only 61 among 1696 light users, which was 3.60% of total light users.</p> <p>All the subjects had accessed the internet at least once. Most of the college students, both male and female, use the internet for surfing, chatting and watching movies. Online-game players tend to be more likely to develop PIU. Interestingly, more students without PIU chose 'search for information' as one of their main activities online. Other online activities were not statistically correlated with PIU (see Table 3).</p> <p>Table 3. Relationship between PIU and different online activities (n = 3496, male = 1898, female = 1598).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Main online activities</td><td>PIU (<italic>n</italic> = 335, 100%)</td><td>Non-PIU (<italic>n</italic> = 3161, 100%)</td><td>Total (<italic>n</italic> = 3496, 100%)</td><td><italic>p</italic></td></tr><tr><td>No. (%)</td><td>No. (%)</td><td>No. (%)</td></tr></thead><tbody valign="top"><tr><td>Play games online</td><td char="(">177 (52.83)</td><td char="(">1072 (33.91)</td><td char="(">1249 (35.73)</td><td char=".">0.000</td></tr><tr><td>Search information</td><td char="(">164 (48.96)</td><td char="(">2153 (68.1)</td><td char="(">2317 (66.28)</td><td char=".">0.000</td></tr><tr><td>Surf internet (www.</td><td char="(">203 (60.60)</td><td char="(">2051 (64.89)</td><td char="(">2254 (64.47)</td><td char=".">0.262</td></tr><tr><td>Chat/make friend</td><td char="(">222 (66.27)</td><td char="(">2048 (64.79)</td><td char="(">2270 (64.93)</td><td char=".">0.705</td></tr><tr><td>Watch movies</td><td char="(">164 (48.96)</td><td char="(">1568 (49.6)</td><td char="(">1732 (49.54)</td><td char=".">0.893</td></tr><tr><td>Other</td><td char="(">46 (13.73)</td><td char="(">294 (9.3)</td><td char="(">340 (9.73)</td><td char=".">0.019</td></tr><tr><td>This table demonstrated the main activities of students online. The result was grouped by PIU and non-PIU. The figure in the bracket was the proportion of each number to the total number of the corresponding group. For instance, within 335 PIU sufferers, 52.83% (177 respondents) usually use the internet for playing games online, 48.96% (164 respondents) often use it for information-searching. While in all, 35.73% of all students (1249) chose playing online games as their main activity. The statistical relationship between PIU and every single activity were shown in the last column, using chi-square test.</td></tr></tbody></table> </ephtml> </p> <hd id="AN0043607485-12">3.4 Depression and PIU</hd> <p>We also analysed the correlation between depression and PIU. The data in Table 4 shows an obvious statistically significant association between depression and PIU. Of the 141 students suffering from depression, 36 developed PIU, a rate of 25.53%, while among 3355 non-depressed students, only 299 developed PIU, a rate of 8.92% (<emph>χ</emph><sups>2</sups> = 125.06, <emph>p</emph> < 0.001).</p> <p>Table 4. Correlation of PIU and depression (n = 3496).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>PIU No. (%)</td><td>Non-PIU No. (%)</td><td>Total No. (%)</td></tr></thead><tbody valign="top"><tr><td>Depression</td><td char="(">36 (25.53*)</td><td char="(">105 (74.47*)</td><td char="(">141 (4.03)</td></tr><tr><td>No depression</td><td char="(">299 (8.91<sup>#</sup>)</td><td char="(">3056 (91.08<sup>#</sup>)</td><td char="(">3355 (95.96)</td></tr><tr><td>Total</td><td>335</td><td>3161</td><td>3496</td></tr><tr><td>The relation of PIU and depression is shown.</td></tr><tr><td>*The proportion of different group of students with depression to total depressed number.</td></tr><tr><td><sup>#</sup>The proportion of students without depression to the total non-depressed number in each group.</td></tr><tr><td>For instance, of the 141 students that suffered from depression, 36 developed PIU, rates 25.53%, while among 3355 non-depression students, only 299 developed PIU, rates 8.92% (<italic>χ</italic><sup>2</sup> = 125.06, <italic>p</italic> < 0.001). Others in the bracket were the proportion of the total number. Chi-square was done to test the significance. <italic>χ</italic><sup>2</sup> = 125.06, <italic>p</italic> = 0.000.</td></tr></tbody></table> </ephtml> </p> <hd id="AN0043607485-13">4 Discussions</hd> <p>The main findings from this large-scale investigation suggested that 9.58% of the college students met the criteria of YDQ for PIU, which was slightly lower than the previous report (Xuanhui and Gonggu [<reflink idref="bib22" id="ref26">22</reflink>], Agenta and Gunnar 2004, Clark <emph>et al</emph>. [<reflink idref="bib5" id="ref27">5</reflink>], Liu <emph>et al</emph>. [<reflink idref="bib14" id="ref28">14</reflink>]). This may be due to the variety of diagnostic criteria and the relatively small sample populations of other surveys. The significant difference shown between different genders (male 13.54%, female 4.88%) was in accordance with most of the previous studies (Clark <emph>et al</emph>. [<reflink idref="bib5" id="ref29">5</reflink>]). The results implicate the extent and characteristics of PIU in college students in Wuhan, which may play an important role in the search for acquisition factors in the design of prevention and intervention of PIU in the future.</p> <p>The data in our study also showed that college students with poor academic achievements, bad family atmosphere or lack of love from parents were more vulnerable to developing PIU, which is not hard to understand considering the 'nature' of the internet. The internet provides a safe haven where feelings of social discomfort are alleviated. Internet users eliminate, when online, the negative and undesirable feelings that accompany face-to-face communication. Internet dependents may feel more confident when interacting online rather than in face-to-face situations. However, they do nothing to improve real-world social relationships.</p> <p>It is also of great interest that the students using the internet more for game-playing were more vulnerable to PIU, while the ones who use the internet for information were the opposite. In fact students could easily be attracted by opportunities offered by surfing the internet, engaging in chat room gossip and online games (Kanwal and Archanapreet [<reflink idref="bib12" id="ref30">12</reflink>]). Probably the information seekers had better self-restraint than those attracted by online games. This is in accordance with the common notion that the worse one's self-restraint was, the easier addiction developed, though further verification is needed.</p> <p>In this investigation, we tried further to study the correlation between depression and PIU. As indicated by our study, PIU was proved to have negative psychiatric consequences. Likewise, depression had an obvious correlation with PIU as well. It is understandable considering the studies about the co-occurrence of internet addiction and other addictive behaviours, such as gambling addiction, because of their similarities (Orzack and Orzack [<reflink idref="bib19" id="ref31">19</reflink>]). But whether the strong correlation between PIU and certain psychiatric disorders was coincidental needs further verification. Up until now, research has rarely focused on this area, so it is worthwhile to pay more attention to it, in order to get clear information and enable the prevention of potential increases of such problems.</p> <p>Despite the negative effects of the internet, there are also beneficial aspects which should not be neglected. As addressed by college students in Taiwan (Chien [<reflink idref="bib3" id="ref32">3</reflink>]), the internet significantly enhanced their sense of identity, closer relationship with friends and bonding with the world. Indeed, as the internet's continuously expanding bandwidth continues to deliver multimedia resources in increasing amounts, with higher quality at a lower cost, the popularity of the internet will definitely gain ascendancy among college students as well as students of other levels. Hence, as suggested by Chou and Hsiao ([<reflink idref="bib4" id="ref33">4</reflink>]), for those excessive or addicted internet users, the goal of intervention should not be to stop using the internet altogether, but rather use it in a productive, healthy, and controlled way. Some researchers (Orzack and Orzack [<reflink idref="bib19" id="ref34">19</reflink>], Keith and Beard [<reflink idref="bib2" id="ref35">2</reflink>], Shao-Kong <emph>et al</emph>. [<reflink idref="bib21" id="ref36">21</reflink>]) suggested the treatment of internet addiction could not be abstinence: it should be treated like an eating disorder, with a goal to normalise network usage to survive. Therefore, how to make students aware of the importance of appropriate and productive use of the internet has become a great task for educators.</p> <hd id="AN0043607485-14">Acknowledgements</hd> <p>Professor Lianke Weng, Huazhong University of Science and Technology, provided us with invaluable advice and helped during data collection. Ms Li Qiu gave strong support in data statistics and the manuscript preparation. Mr Jimin Zhang, Rutgers University/UMDNJ (University of Medicine and Dentistry of New Jersey), and Nick M., Huazhong University of Science and Technology, kindly helped with the modification of the manuscript.</p> <ref id="AN0043607485-15"> <title> References </title> <blist> <bibl id="bib1" idref="ref21" type="bt">1</bibl> <bibtext> Agenta, J. and Gunnar, K.G.2004. Internet addiction: characteristics of a questionnaire and prevalence in Norwegian youth (12–18 years). Scandinavian Journal of Psychology, 45: 223–229.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref35" type="bt">2</bibl> <bibtext> Beard, K.W.2005. Internet addiction: a review of current assessment techniques and potential assessment questions. CyberPsychology & Behavior, 8: 7–14.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref32" type="bt">3</bibl> <bibtext> Chien, C.2001. Internet heavy use and addiction among Taiwanese college students: an online interview study. CyberPsychology & Behavior, 4: 573–585.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref18" type="bt">4</bibl> <bibtext> Chou, C. and Hsiao, M.C.2000. Internet addiction, usage, gratification, and pleasure experience: the Taiwanese college students' case. Computers & Education, 35: 65–80.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref27" type="bt">5</bibl> <bibtext> Clark, D.J., Frith, K.H. and Demi, A.S.2004. The physical, behavioral, and psychosocial consequences of internet use in college students. Lippincott Williams & Wilkins, 22: 153–161.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref3" type="bt">6</bibl> <bibtext> Click, Z.S.2004. Population explosion!. Retrieved March 12, 2004, from <ulink href="http://www.clickz.com/stats/big%5fpicture/geographics/article.php/5911%5f151151">http://www.clickz.com/stats/big%5fpicture/geographics/article.php/5911%5f151151</ulink></bibtext> </blist> <blist> <bibl id="bib7" idref="ref5" type="bt">7</bibl> <bibtext> CNNIC. 2005. The statistic report of the development of China internet network, No.16th, from <ulink href="http://www.cnnic.net.cn/uploadfiles/pdf/2005/7/20/210342.pdf">http://www.cnnic.net.cn/uploadfiles/pdf/2005/7/20/210342.pdf</ulink></bibtext> </blist> <blist> <bibl id="bib8" idref="ref11" type="bt">8</bibl> <bibtext> Davis, R.A.2001. A cognitive-behavioral model of pathological internet use. Computers in Human Behavior, 17: 187–195.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref2" type="bt">9</bibl> <bibtext> ET Forecasts. 2003. Internet user forecast by country: executive summary. Retrieved September 29, 2003, from <ulink href="http://www.etforecasts.com/products/ES%5fintusers">http://www.etforecasts.com/products/ES%5fintusers</ulink>. htm</bibtext> </blist> <blist> <bibtext> Griffiths, M.2000. Does internet and computer addiction exist? Some case study evidence. CyberPsychology & Behavior, 3: 211–218.</bibtext> </blist> <blist> <bibtext> Kandell, J.J.1998. Internet addiction on campus: the vulnerability of college students. CyberPsychology & Behavior, 1: 11–17.</bibtext> </blist> <blist> <bibtext> Kanwal, N. and Archanapreet, A.2003. Internet addiction in students: a cause of concern. CyberPsychology & Behavior, 6: 653–656.</bibtext> </blist> <blist> <bibtext> Kitamura, T., Sugawara, M.Shima, S.1999. Temporal variation of validity of self-rating questionnaires: improved validity of repeated use of Zung's self-rating depression scale among women during the perinatal period. Journal of Psychosomatic Obstetrics & Gynaecology, 20: 112–117.</bibtext> </blist> <blist> <bibtext> Liu, L., Xie, S., Wan, X., Li, D.J., Zhang, C.F. and Hou, L.J.2005. Incidence of addiction to the network of the students in Dalian University. Chinese Journal of Health Education, 21: 122–124.</bibtext> </blist> <blist> <bibtext> Louis, L.2004. Net-generation attributes and seductive properties of the internet as predictors of online activities and internet addiction. CyberPsychology & Behavior, 7: 333–348.</bibtext> </blist> <blist> <bibtext> Morahan-Martin, J. and Schumacher, P.2000. Incidence and correlates of pathological internet use among college students. Computers in Human Behavior, 16: 13–29.</bibtext> </blist> <blist> <bibtext> Morahan-Martin, J.2005. Internet abuse: addiction? disorder? symptom? alternative explanations?. Social Science Computer Review, 23: 39–48.</bibtext> </blist> <blist> <bibtext> Nathalie, C.Y. and Michael, J.L.2004. Internet dependence in the collegiate population: the role of shyness. CyberPsychology & Behavior, 7: 379–383.</bibtext> </blist> <blist> <bibtext> Orzack, M.H. and Orzack, D.S.1999. Treatment of computer addicts with complex co-morbid psychiatric disorders. CyberPsychology & Behavior, 2: 465–473.</bibtext> </blist> <blist> <bibtext> Scherer, K. and Bost, J.Internet use patterns: is there internet dependency on campus?. Paper presented at the 105th Annual Convention of the American Psychological Association. Chicago, IL, IL.</bibtext> </blist> <blist> <bibtext> Shao-Kong, L., Chin-Chin, W. and Wengchang, F.2005. Physical interpersonal relationships and social anxiety among online game players. CyberPsychology & Behavior, 8: 15–20.</bibtext> </blist> <blist> <bibtext> Xuanhui, L. and Gonggu, Y.2001. Internet addiction disorder, online behavior and personality. Chinese Mental Health Journal, 15: 281–283.</bibtext> </blist> <blist> <bibtext> Young, K.S.1996. Addictive use of the internet: a case study that breaks the stereotype. Psychological Reports, 79: 899–902.</bibtext> </blist> <blist> <bibtext> Young, K.S.1998. Internet addiction: the emergence of a new clinical disorder. CyberPsychology & Behavior, 1: 237–244.</bibtext> </blist> </ref> <aug> <p>By R.L. Huang; Z. Lu; J.J. Liu; Y.M. You; Z.Q. Pan; Z. Wei; Q. He and Z.Z. Wang</p> <p>Reported by Author; Author; Author; Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib572" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib17" firstref="ref4"></nolink> <nolink nlid="nl3" bibid="bib23" firstref="ref6"></nolink> <nolink nlid="nl4" bibid="bib24" firstref="ref7"></nolink> <nolink nlid="nl5" bibid="bib10" firstref="ref8"></nolink> <nolink nlid="nl6" bibid="bib20" firstref="ref9"></nolink> <nolink nlid="nl7" bibid="bib19" firstref="ref10"></nolink> <nolink nlid="nl8" bibid="bib15" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib11" firstref="ref15"></nolink> <nolink nlid="nl10" bibid="bib18" firstref="ref16"></nolink> <nolink nlid="nl11" bibid="bib22" firstref="ref19"></nolink> <nolink nlid="nl12" bibid="bib14" firstref="ref20"></nolink> <nolink nlid="nl13" bibid="bib16" firstref="ref22"></nolink> <nolink nlid="nl14" bibid="bib13" firstref="ref25"></nolink> <nolink nlid="nl15" bibid="bib12" firstref="ref30"></nolink> <nolink nlid="nl16" bibid="bib21" firstref="ref36"></nolink>
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  Data: Features and Predictors of Problematic Internet Use in Chinese College Students
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  Data: <searchLink fieldCode="AR" term="%22Huang%2C+R%2E+L%2E%22">Huang, R. L.</searchLink><br /><searchLink fieldCode="AR" term="%22Lu%2C+Z%2E%22">Lu, Z.</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+J%2E+J%2E%22">Liu, J. J.</searchLink><br /><searchLink fieldCode="AR" term="%22You%2C+Y%2E+M%2E%22">You, Y. M.</searchLink><br /><searchLink fieldCode="AR" term="%22Pan%2C+Z%2E+Q%2E%22">Pan, Z. Q.</searchLink><br /><searchLink fieldCode="AR" term="%22Wei%2C+Z%2E%22">Wei, Z.</searchLink><br /><searchLink fieldCode="AR" term="%22He%2C+Q%2E%22">He, Q.</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Z%2E+Z%2E%22">Wang, Z. Z.</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Behaviour+%26+Information+Technology%22"><i>Behaviour & Information Technology</i></searchLink>. Sep 2009 28(5):485-490.
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  Data: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
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  Data: <searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Internet%22">Internet</searchLink><br /><searchLink fieldCode="DE" term="%22Depression+%28Psychology%29%22">Depression (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Incidence%22">Incidence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Uses+in+Education%22">Computer Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Surveys%22">Student Surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22Addictive+Behavior%22">Addictive Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Low+Achievement%22">Low Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Family+Relationship%22">Family Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Family+Influence%22">Family Influence</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22At+Risk+Students%22">At Risk Students</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+Relationship%22">Interpersonal Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink>
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  Data: <searchLink fieldCode="SU" term="%22Zung+Self+Rating+Depression+Scale%22">Zung Self Rating Depression Scale</searchLink>
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  Data: 10.1080/01449290701485801
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  Data: 0144-929X
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  Data: This study was set to investigate the prevalence of problematic internet use (PIU) among college students and the possible factors related to this disorder. About 4400 college students, ranging from freshmen to juniors, from eight different universities in Wuhan, China were surveyed. Young's Diagnostic Questionnaire for Internet Addiction (YDQ) and the Zung Self-rating Depression Scale were used to define PIU and depression accordingly. Data was analysed with "chi-squared" testing and logistic regression. Out of the 3496 participants, 9.58% (male 13.54%, female 4.88%) met the criteria of PIU. Factors such as heavy internet use habits, poor academic achievement, lack of love from the family, etc. were found to be significantly associated with PIU. About 48.51% (1696) of the students were light internet users, who use the internet less than 5 h/week, while 16.36% (572) were heavy users who use it more than 15 h/week, though heavy users were more likely to develop PIU. Also, 25.53% of the students with depression developed PIU, in comparison with 8.91% of PIU among those without depression (p less than 0.001). Being male, frequent internet use, poor academic achievement, poor family atmosphere and lack of love from parents were predictors of PIU among college students. The habit and purpose of using the internet is diverse, which influences the susceptibility of PIU as well. There was a correlation between depression and the development of PIU as well. (Contains 4 tables.)
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