The Relationship between Impulsivity and Internet Addiction in Chinese College Students: A Moderated Mediation Analysis of Meaning in Life and Self-Esteem (2015)

PLoS One. 2015 Jul 14;10(7):e0131597. doi: 10.1371/journal.pone.0131597.

Zhang Y1, Mei S2, Li L2, Chai J2, Li J2, Du H3.

Abstract

Internet addiction (IA) has increasingly been recognized as a serious psychological malady among college students. Impulsivity has been shown to be associated to addictive behaviors, also to IA, and that the purpose of the study is to investigate whether or not there are variables modulating the relation between impulsivity and IA. “Meaning in life” is regarded as a desirable attribute, with positive mental health outcomes. “Self-esteem” is often regarded as an important component of psychological health which has relation to IA. Therefore, we examined meaning in life and self-esteem’s possible effects in this relationship. A total of 1068 Chinese college students ranging in age from 18 to 25 years were recruited for this cross-sectional survey study. Correlations and multivariate regressions were used to calculate the possible mediation and moderation relationship among the variables of meaning in life, self-esteem, impulsivity, and IA. In the analyses that we conducted, IA was shown to be prevalent among Chinese university students. The relationship between impulsivity and IA was partially mediated by meaning in life, and the relationship between meaning in life and IA was moderated by self-esteem. Our findings demonstrate that meaning in life and self-esteem can be useful buffers to IA for highly impulsive individuals. Further randomized trials to confirm these results are needed.

Introduction

Recently there has been explosive growth in the popularity of the internet at different stages of life. College students, who are at a critical developmental stage, warrant examination in this respect, because each has a laptop which initially facilitates academic activities, but later is available for recreational activities. Addiction to the internet is becoming a serious mental health issue and strongly impacts academic performance in college samples [1, 2]. Internet addiction (IA), appears to be a relatively common behavioral addiction, has certain symptoms and will undergo the same consequences brought about by addiction to alcohol and drugs as well as other obsessive behaviors [3]. Understanding how college students resist or fail to resist this temptation might shed light on internet addiction. Much research has been conducted in the account for what result in or follows from internet addiction, such as decision making, shyness, social anxiety, depression, conflictual family relations [47], and prefrontal control, dysfunctional inhibitory control, impulsivity [8, 9].

Impulsive individuals have problems in managing their behavior. Some core indicators of behavioral addiction are identical to those of chemical or substance addiction [10]. Behavioral addiction, such as IA criteria are presented firstly is recurrent failure to resist impulses to engage in a specified behavior [11], and a feeling of lack of control while engaging in the behavior. A large body of the literature in this area concerns impulsiveness impacting the addictive tendencies [1214]. Both behavioral and substance addictions are marked by an inability to stop. One of the most valid methods of intervening those addictions is by identifying and reducing the negative catalysts and strengthening the positive aspects. This pertains much to high impulsivity in addicts, also to internet addiction [15]. As impulsivity might not be greatly decreased by psychotherapeutic intervention [16, 17], other psychological variables may instead be more effective in reducing it. Perhaps impulsive individuals might also possess protective qualities that control them from becoming preoccupied with the internet. We sought to investigate whether or not there are variables modulating the relation between impulsivity and IA, and furthermore, to address the psychological strengths that predict one’s ability to resist the constant allure of the internet. To this end, we examined two complementary mental strengths in resisting IA: meaning in life, and self-esteem.

What kinds of psychological features do people have when they are overly involved in use of the internet? Meaning in life is found to have a stronger positive association with psychological well-being [18, 19]. Meaning in life as an association between psychosocial well-being and internet addiction has received much more attention and consistent empirical support [20, 21]. Meaning in life is typically referred to as a sense of purpose in one’s life and an accompanying sense of fulfillment [22, 23]. It is a desirable attribute in the realm of attitude evaluation. When they confront temptation, they have control over the outcomes, affecting them in important ways. Finding meaning in life means that people feel positive and efficacious, as a psychological strength [22, 24].

An decreased level of meaning in life has been correlated with several substantial addictive behaviors among individuals [25]. Meaning in life plays important role in treating people with alcoholism use [26]. Meaninglessness in life sometimes brings about a mediating effect on adolescents’ life events and substance used among it [27]. Having a weaker sense of meaning and purpose in life results in an increased proneness to boredom and empty life [28, 29]. Meaningfulness is a cognitive model of empowerment as the basis for worker empowerment [30]. Boredom was common trigger of intensive internet use [31]. This in turn, might increase the probability of internet addiction, especially for students at universities where surfing the internet is relatively easy and socially accepted. Consequently, it is important to determine whether meaning in life provides a buffer against addictive behavior in college students.

The essence of human motivation is the “will to meaning” [32], and a sense of meaning as a cognitive factor has been identified as a potential protective component for individuals [33]. Thus, while purpose or meaning in life confers benefits for enjoyment of work and positive life attitudes, what happens when people are confronted with the constant allure of the internet? Perhaps meaning in life only provides resiliency when individuals also possess characteristics that allow them to resist hedonism. Self-esteem may be such a characteristic. It may complement meaning in life to confer resistance to IA.

Self-esteem is a psychological strength reflecting one’s overall evaluation of oneself. High self-esteem is often regarded as an important component of psychological health [34, 35]. There is some debate over whether self-esteem is more trait-like or state-like [36]. For the purposes of our study, we considered self-esteem as a stable trait factor because we used an adult sample [37]. Given self-esteem’s broad implications, it seems a distinct possibility that high self-esteem impacts the pursuit of long-term goals with well-anchored, positive attitudes about the self and happiness [38]. A close relationship has been documented between low self-esteem and problems such as alcoholism, drug abuse, eating disorders, school dropouts, poor academic performance, pregnancy in adolescence [3942].

There are several studies on the relevance of self-esteem to internet addiction [43, 44]. One study found that emotional support from both parents would increase their child’s self-esteem, which in turn would reduce the child’s risk of being addicted to the internet [45]. Additionally, research has shown that self-esteem is one of the main antecedents of IA [46]. Individuals with lower self-esteem are more likely to be addicted to the internet [47, 48].

Further, there are several reasons why high self-esteem may be a source of resiliency. First, compatible with theories of self-esteem’s evaluation function and emotional experience [49], “high self-esteem” individuals are more likely to evaluate themselves as having positive self-esteem and self-competence. Individuals with positive self-value could generate and strengthen their degree of meaning in life. Though these people are lured by the internet as much as others, they may be more likely to maintain or promote their efforts toward attaining meaningful goals instead of aborting them. Second, some studies support the buffer hypothesis, that high self-esteem enhances initiative and pleasant feelings [50, 51]. “High self-esteem” confers personal ability and value, so it may serve as a positive factor against addiction which allows individuals to create and realize life goals and purpose in life. One of self-esteem psychological structure just is meaning in life [52]. In combination, the variables of meaning in life and self-esteem might confer optimal protection from internet addiction. The meaningful pursuits of “high self-esteem” individuals allow them to bridge the gap between their real and ideal selves.

Purpose of the Present Study

In this study, we examined the influences of meaning in life and self-esteem on internet addiction. We argue that meaning in life and self-esteem, each account for impulsivity individual addictive behavior to some degree. To date, the hypothesis that self-esteem moderates the relationship between meaning in life and internet addiction has not been tested. This is the first study to test a synergistic effect between a life attitude (meaning in life) and a self attitude (self-esteem) for a more sophisticated model of resiliency. As mentioned previously, we hypothesized that (H1) meaning in life mediated the relationship between impulsivity and internet addiction. Based on theoretical models of why people indulge in the internet [45, 50], we hypothesized that (H2) the relationship between meaning in life and internet addiction is moderated by self-esteem. This allowed a test of construct specificity to IA under more constricted methodological factors.

Methods

Ethics Statement

This study was a cross-sectional survey, and data collection occurred within the context of a larger lecture on mental health. The research was approved by the Institutional Review Board (IRB), School of Public Health, Jilin University, China. All participants gave written informed consent, and were ensured complete anonymity. Participation was voluntary, and students were given information about campus mental health resources upon completing the study.

Participants

We tested our hypotheses on a large random sample of college students (N = 1537). All participants were students of medical disciplines at three colleges in North China. They completed self-report measures in the classroom after a formal lecture. A total of 1068 eligible participants (61.1% female; mean age = 22.76, SD = 2.54, range 18–25) responded to the present study. The participation response rate was 69.5%. This rate is similar to those of previous studies [53, 54]. There were no significant interactions with gender and socioeconomic status (p > .05), so these factors were not included in further analyses.

Questionnaires

Participants completed paper-and-pencil self-report questionnaire packets and measures of demographic information, impulsivity (BIS-11), meaning in life (PIL), self-esteem (RSE), and internet addiction (YDQ).

IA was computed from responses on a widely-used eight-item Internet Addiction Diagnostic Questionnaire (YDQ). The YDQ pertains to all types of online activity and has no time limit. Respondents who answered yes to five or more of the eight criteria were classified as addicted internet users [55]. We considered lower general scores as an indicator of higher IA. The YDQ has been deemed valid and reliable in previous research reports [56].

Impulsivity was measured using the Barratt Impulsiveness Scale 11 (BIS-11). The BIS-11 is a questionnaire on which participants rate their frequency of several common impulsive or nonimpulsive behaviors/traits on a scale from 1 (rarely/never) to 4 (almost always/always). The questionnaire consists of thirty items, the minimum score is 30, and the maximum is 120; with higher scores indicating greater impulsivity. Its reliability and validity have been shown to be acceptable [57].

Meaning in life was measured with the widely used Purpose in Life Test (PIL) [58], an attitude scale which includes twenty ratings made on a 7-point scale, where a “1” indicates low purpose and a “7” indicates high purpose, the minimum score is 20, and the maximum is 140. The PIL provides participants with unique anchors for each item. Some of these anchors are bipolar, some are unipolar, and some utilize a continuum. For example, one item provides a continuum on which one end is “If I could choose, I would prefer never to have been born.” On the other end of the continuum is “If I could choose I would live nine more lives just like this one.” The scale has generally demonstrated good internal consistency [18].

The Rosenberg Self-Esteem scale (RSE) was used to measure overall feelings of self value and self acceptance [59]. Participants rated their level of agreement with ten statements on a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Sample items include, “I feel that I have a number of good qualities,” and “All in all, I am inclined to feel that I’m a failure.” The minimum score is 10, and the maximum is 40. Scores were computed by averaging the items, with higher scores indicating higher self-esteem. This instrument is a well-validated and reliable measure of global self-esteem [60].

Statistical Analysis

Preliminary analyses

Analysis of the data from this study was performed using SPSS 21.0 statistical software (SPSS, IBM, Lmd, Beijing, China). Missing values in the data were computed along with the sample means. Internet addicts in the general population have a relatively low base-rate occurrence and we found evidence of negative skewness in our sample (skewed = -1.461, SE = .075). Due to a large sample size (N = 1068), all variables were sufficiently normally distributed [61]. Bivariate scatter plots showed linear relationships between all variables, and we used stepwise linear regression analyses. Significance values were set at p < .05. Correlations were calculated between the variables of self-esteem, meaning in life, impulsivity, and internet addiction. Values for Cronbach’s alpha are reported in Table 1.

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Table 1. Means, standard deviations, intercorrelations, and internal consistency between study variables.

doi:10.1371/journal.pone.0131597.t001

Mediation and moderation analyses

As outlined in the Introduction, we conducted a specific mediation and a specific moderation hypothesis. As shown in Fig 1, we tested the extent to which the relationship between impulsivity and internet addiction is mediated by meaning in life, as well as the extent to which the relationship between meaning in life and internet addiction is moderated by self-esteem. To this end, we tested mediation by finding four regression coefficients: the total effect of impulsivity on internet addiction (c), the direct effect of impulsivity on internet addiction (c’), the effect of impulsivity on meaning in life (a), and the effect of meaning in life on internet addiction (b). When a, b, and c effects are significant, but the c’ effect is not significant, a total mediation effect is shown. When a, b, c and c’ effects are all significant, a partial mediation effect exists.

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Fig 1. The conceptual framework.

doi:10.1371/journal.pone.0131597.g001

Next, we tested moderation effects by implementing the hierarchical regression technique. In the first regression, internet addiction was regressed on impulsivity and self-esteem. The coefficient for impulsivity was significant. In the second regression, meaning in life was regressed on impulsivity and self-esteem. The coefficient for impulsivity was significant here too. In the third regression, internet addiction was regressed on all predictor variables (impulsivity, self-esteem, and meaning in life), and the coefficient for meaning in life was significant. In the final step, internet addiction was regressed on impulsivity, self-esteem, and meaning in life, and the interaction between meaning in life and self-esteem. If the coefficient for the interaction between meaning in life and self-esteem is significant, moderated mediation has occurred [6266].

Last, an interaction term was created by centering meaning in life and self-esteem around their grand means, and then multiplying them to avoid issues of collinearity with the interaction term. The main effects of meaning in life and self-esteem that is reported are the centered variables. The means and standard deviations reported are from the uncentered variables [67, 68]. Next, multiple regressions were conducted. Meaning in life (main effect) and self-esteem (main effect), were entered in Block 1 of the regression analysis while the interaction term (meaning in life × self-esteem) was entered in Block 2 when predicting internet addiction. If the interaction term significantly predicts internet addiction, a moderation effect has been found. To interpret the moderation effect, the data were entered into the regression equation based on high (1 SD above) and low (1 SD below) values of the moderator and mediator variables. In addition, a post-hoc probing of the interaction was conducted using two new conditional interaction terms (high and low) [69]. This was done to determine if the slopes of the regression equations for high and low values of the interaction differed from zero.

Results

Descriptive statistics

Table 1 displays the means, standard deviations, and correlations between study variables. All variables were significantly and positively correlated in the expected direction. The results indicate excellent reliability for the YDQ, BIS-11, PIL, and RSE questionnaires. Approximately 7.6% of the sample manifested clinically relevant levels of internet addiction. These rates are comparable to, and even above what might be expected. A recent cohort study of college students indicated that 74.5% were moderate users, 24.8% were possible addicts, and 0.7% were addicts [70]. Variance inflation factors of all predictor variables included in the regression analysis varied between 1.0 and 2.2, indicating that multi-collinearity between predictor variables did not bias our results.

Mediation of meaning in life between impulsivity and internet addiction

Table 2 shows the results of the three separate regression analyses testing the mediation hypothesis. In step 1, a significant effect of impulsivity on internet addiction resulted (b = -.139, p < .001). In step 2, the effect of impulsivity on meaning in life was also significant (b = -1.403, p < .001). In step 3, after including the mediator variable meaning in life as a predictor in the regression model, the effect of both meaning in life and impulsivity on internet addiction was highly significant. Meaning in life was thus a significant part mediator (△R2 = .606, p < .001)of the association between impulsivity and the outcome variables. This significant mediation effect is depicted in Fig 2.

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Table 2. Summary of hierarchical regression analysis for meaning in life in mediating the relationship between impulsivity and internet addiction.

doi:10.1371/journal.pone.0131597.t002

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Fig 2. Standardized regression coefficients for paths within the mediation model

 

. Explained variance: β, standardized regression coefficient.

doi:10.1371/journal.pone.0131597.g002

Moderation of self-esteem and meaning in life on internet addiction

Table 3 shows self-esteem as a moderator of the path from meaning in life to internet addiction, which was tested by the regression analyses just discussed. We controlled for age and gender here, and paths are labeled with coefficients from the regression equations used to estimate the predictor variables. First, internet addiction was predicted by the moderated variable and independent variable (β = -.55, p < .001). Subsequently, meaning in life was predicted by impulsivity and self-esteem (β = -.56, p < .001). Then, internet addiction was predicted by impulsivity, self-esteem and meaning in life (β = -.46, p < .001). Last, internet addiction was predicted by the moderated variable, meaning in life, self-esteem and meaning in life*self-esteem (β = -.25, p < .001). The R-square value changed due to the introduction of the interaction term in the analysis (△R2 ≤ .05). The significant interaction effect supported our hypothesis of moderated mediation.

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Table 3. The buffering effect of self-esteem on the relationship between meaning in life and internet addiction.

doi:10.1371/journal.pone.0131597.t003

Meaning in life and self-esteem as synergistic factors

Given that there was an interaction between meaning in life and self-esteem on one’s likelihood of internet addiction, post-hoc analyses were conducted and plotted [68, 71]. Fig 3 shows the results of these analyses. As meaning in life increased, internet addiction decreased. It is clear from the beta values for the prime condition that meaning in life positively predicted internet addiction scores for participants in both the low self-esteem and high self-esteem conditions. However, the relationship between meaning in life and internet addiction was stronger for those with low self-esteem than for those with high self-esteem. When meaning in life is low, low self-esteem has a substantial effect on internet addiction. Results from the post-hoc probing indicate that the slopes for high and low values of the moderator were significantly different from zero, further supporting moderation.

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Fig 3. Regression lines for relations between meaning in life and Internet addict as moderated by self-esteem.

 

(a 2-way interaction). b = unstandardized regression coefficient (i.e., simple slope); SD = standard deviation.

doi:10.1371/journal.pone.0131597.g003

Discussion

The results of the present study reveal the relationship between several variables. One such relationship is the significant direct effect of impulsivity on internet addiction. Our finding is in line with numerous studies that demonstrate that individuals with higher trait impulsivity are more likely to engage in impulsive internet use [15, 72].

The present research also supported that the effect of impulsivity on internet addiction is partially mediated by meaning in life. Partial mediation such as that found here is common and accepted in the behavioral sciences, as complete mediation is quite rare in this domain. There is theoretical support for depression, anxiety, lower for self-directedness and cooperativeness variables pathways to impulsive addictive behaviors. The nature of the relationship between impulsivity, meaning in life, and internet addiction is complicated. Meaning is recognized as a central human motivation [73], and living a meaningful life is associated with positive functioning [74]. For instance, purpose in life predicts better emotional recovery from negative stimuli [75]. However, meaning in life may be more distal as a protective factor.

College students are in a key life stage centered around the search for meaning and establishing self-identity [76]. Finding meaning in life is a critical dilemma for these students undergoing great mental and behavioral development. Students who were retaking the college entrance examination experienced a positive life change and found greater meaning in university life [77]. However, those with less impulse control and meaning in life may be more susceptible to problematic behavior.

Among the vast array of psychological variables, we chose self-esteem and meaning in life as our focus for important reasons. First, meaning in life is an attitude pertaining much to the external environment, while self-esteem is an internally-oriented evaluation of oneself. Self-esteem is a critical component of any self-improvement or rehabilitation program. Furthermore, high self-esteem individuals have an internal characteristic that to an extent, helps them resist addictive behaviors. An individual with both of these complementary strengths may be the most safeguarded from internet addiction. Second, self-esteem not only affects our values, but our feelings and actions in a variety of circumstances [78]. While meaning must be based on one’s daily experiences, we infer that high self-esteem can moderate a sense of purpose and meaning in life.

However, it is also necessary to understand other factors from which improper behaviors arise during this dynamic period of development. The self-esteem pathway has received much more attention and consistent empirical support. Prior work suggests that low self-esteem individuals are more likely to be identified as internet addicts [79]. Individuals at greatest risk for internet addiction possess a combination of boredom with leisure activities and other psychological traits such as self-exclusion, and identity problems. Self-esteem fits in well to the cumulative continuity principle of personality development because the consistency of self-esteem increases with age [37].

With the growth of positive psychology, the variables of meaning in life and self-esteem have received great attention [51, 80]. They may confer synergistic benefits in combating internet addiction. Studying co-occurring protective factors offer a broader understanding of how one factor changes the effect of another on a given behavior. Risk and protective factors are related, but are not interchangeable [81]. We suggest that people can circumvent internet addiction with resiliency factors. Since meaning in life and self-esteem could both be enhanced in positive psychotherapy [82, 83], we present this study as a model to describe possible moderators and mediators that may work in combination to restrain overindulgence in the internet. Our findings also suggest that individuals with high baseline levels of both strengths showed significantly decreased internet addiction relative to their counterparts without these strengths combined.

Taken together, the results reported here imply that meaning in life and self-esteem offer substantial protection against internet addiction. Our findings extend previous research by exploring additional psychological buffers against internet addiction, such as perceived social competence [84]. To our knowledge, this study is the first to examine meaning in life as it applies to internet addiction. Despite evidence for an inverse association between self-esteem and internet addiction, meaning in life predicted internet addiction only in combination with high levels of self-esteem. As described in detail previously [81], these findings highlight the importance of attending to psychological strengths in combination, instead of relying on a single predictor.

Our study has several strengths. The findings reported here provide evidence for increased meaning in life as a protective factor in internet addiction. Our findings also provide initial support for two specific psychological strengths working in tandem. The four research variables have been linked to many of the other personality constructs in the extant literature. As impulsivity might not largely decreased by psychological treatment, meaning and life, and self-esteem of psychological variables may instead be more effective in reducing addictive behaviors. This study contributes to diverse literatures, expanding the study of cognition, personality, clinical psychology, and psychiatry.

This study also has limitations. Due to the fact that the design is cross-sectional and correlational, it is limited in its usefulness in determining causality. In addition, our self-reported data may not be reliable, as it is subject to response bias. Because our examination did not control for relevant background predictors, we cannot be certain how well our results generalize to other groups. Future research investigating the same questions using an experimental design and truly random samples would address the limitations just discussed. Last, our results pertain only to meaning in life and self-esteem as protective factors against a general construction of internet addiction. Future research exploring additional personality traits as protective factors would yield more comprehensive insights into countering any specific dependent variables of behavior or substance addictions.

Conclusions

In conclusion, the results of this study support a moderated mediation model of how the discussed constructs influence internet addiction. Empirical examination revealed a stronger indirect influence of impulsivity on internet addiction. Meaning in life and self-esteem can be a useful buffer against internet addiction for at-risk individuals who are highly impulsive. This research supports the utility of inspecting the individual difference mechanisms that might drive the relationship between impulsivity and internet addiction.

Supporting Information

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Author Contributions

Conceived and designed the experiments: SLM YZ. Performed the experiments: YZ HYD. Analyzed the data: JML JXC. Wrote the paper: YZ SLM LL. Collected questionnaires: YZ.

References

  1. 1. Derbyshire KL, Lust KA, Schreiber L, Odlaug BL, Christenson GA, Golden DJ, et al. Problematic Internet use and associated risks in a college sample. Comprehensive psychiatry. 2013;54(5):415–22. doi: 10.1016/j.comppsych.2012.11.003. pmid:23312879
  2. 2. Wu AM, Cheung VI, Ku L, Hung EP. Psychological risk factors of addiction to social networking sites among Chinese smartphone users. Journal of behavioral addictions. 2013;2(3):160–6. doi: 10.1556/JBA.2.2013.006. pmid:25215198
  3. View Article
  4. PubMed/NCBI
  5. Google Scholar
  6. View Article
  7. PubMed/NCBI
  8. Google Scholar
  9. View Article
  10. PubMed/NCBI
  11. Google Scholar
  12. View Article
  13. PubMed/NCBI
  14. Google Scholar
  15. View Article
  16. PubMed/NCBI
  17. Google Scholar
  18. View Article
  19. PubMed/NCBI
  20. Google Scholar
  21. View Article
  22. PubMed/NCBI
  23. Google Scholar
  24. View Article
  25. PubMed/NCBI
  26. Google Scholar
  27. View Article
  28. PubMed/NCBI
  29. Google Scholar
  30. View Article
  31. PubMed/NCBI
  32. Google Scholar
  33. View Article
  34. PubMed/NCBI
  35. Google Scholar
  36. View Article
  37. PubMed/NCBI
  38. Google Scholar
  39. View Article
  40. PubMed/NCBI
  41. Google Scholar
  42. View Article
  43. PubMed/NCBI
  44. Google Scholar
  45. View Article
  46. PubMed/NCBI
  47. Google Scholar
  48. View Article
  49. PubMed/NCBI
  50. Google Scholar
  51. View Article
  52. PubMed/NCBI
  53. Google Scholar
  54. View Article
  55. PubMed/NCBI
  56. Google Scholar
  57. View Article
  58. PubMed/NCBI
  59. Google Scholar
  60. View Article
  61. PubMed/NCBI
  62. Google Scholar
  63. 3. Alavi SS, Ferdosi M, Jannatifard F, Eslami M, Alaghemandan H, Setare M. Behavioral addiction versus substance addiction: Correspondence of psychiatric and psychological views. International journal of preventive medicine. 2012;3(4):290–4. pmid:22624087
  64. 4. De Leo JA, Wulfert E. Problematic Internet use and other risky behaviors in college students: An application of problem-behavior theory. Psychology of addictive behaviors. 2013;27(1):133–41. doi: 10.1037/a0030823. pmid:23276311
  65. View Article
  66. PubMed/NCBI
  67. Google Scholar
  68. View Article
  69. PubMed/NCBI
  70. Google Scholar
  71. View Article
  72. PubMed/NCBI
  73. Google Scholar
  74. View Article
  75. PubMed/NCBI
  76. Google Scholar
  77. View Article
  78. PubMed/NCBI
  79. Google Scholar
  80. View Article
  81. PubMed/NCBI
  82. Google Scholar
  83. View Article
  84. PubMed/NCBI
  85. Google Scholar
  86. View Article
  87. PubMed/NCBI
  88. Google Scholar
  89. 5. Ko CH, Hsiao S, Liu GC, Yen JY, Yang MJ, Yen CF. The characteristics of decision making, potential to take risks, and personality of college students with Internet addiction. Psychiatry research. 2010;175(1):121–5. doi: 10.1016/j.psychres.2008.10.004
  90. View Article
  91. PubMed/NCBI
  92. Google Scholar
  93. 6. Saunders PL, Chester A. Shyness and the internet: Social problem or panacea? Computers in Human Behavior. 2008;24(6):2649–58. doi: 10.1016/j.chb.2008.03.005
  94. View Article
  95. PubMed/NCBI
  96. Google Scholar
  97. 7. Lee DH, Choi YM, Cho SC, Lee JH, Shin MS, Lee DW, et al. Relationship between adolescent internet addiction and depression, impulsivity, and obsessive-compulsivity. Journal of the Korean Academy of Child and Adolescent Psychiatry. 2006;17(1):10–8.
  98. View Article
  99. PubMed/NCBI
  100. Google Scholar
  101. View Article
  102. PubMed/NCBI
  103. Google Scholar
  104. View Article
  105. PubMed/NCBI
  106. Google Scholar
  107. View Article
  108. PubMed/NCBI
  109. Google Scholar
  110. View Article
  111. PubMed/NCBI
  112. Google Scholar
  113. View Article
  114. PubMed/NCBI
  115. Google Scholar
  116. View Article
  117. PubMed/NCBI
  118. Google Scholar
  119. View Article
  120. PubMed/NCBI
  121. Google Scholar
  122. View Article
  123. PubMed/NCBI
  124. Google Scholar
  125. View Article
  126. PubMed/NCBI
  127. Google Scholar
  128. View Article
  129. PubMed/NCBI
  130. Google Scholar
  131. View Article
  132. PubMed/NCBI
  133. Google Scholar
  134. View Article
  135. PubMed/NCBI
  136. Google Scholar
  137. View Article
  138. PubMed/NCBI
  139. Google Scholar
  140. 8. Choi JS, Park SM, Roh MS, Lee JY, Park CB, Hwang JY, et al. Dysfunctional inhibitory control and impulsivity in Internet addiction. Psychiatry research. 2014;215(2):424–8. doi: 10.1016/j.psychres.2013.12.001. pmid:24370334
  141. 9. Brand M, Young KS, Laier C. Prefrontal control and Internet addiction: a theoretical model and review of neuropsychological and neuroimaging findings. Frontiers in human neuroscience. 2014;8(375):1–13. doi: 10.3389/fnhum.2014.00375
  142. View Article
  143. PubMed/NCBI
  144. Google Scholar
  145. View Article
  146. PubMed/NCBI
  147. Google Scholar
  148. View Article
  149. PubMed/NCBI
  150. Google Scholar
  151. View Article
  152. PubMed/NCBI
  153. Google Scholar
  154. View Article
  155. PubMed/NCBI
  156. Google Scholar
  157. View Article
  158. PubMed/NCBI
  159. Google Scholar
  160. 10. Lesieur HR, Blume SB. Pathological gambling, eating disorders, and the psychoactive substance use disorders. Journal of Addictive diseases. 1993;12(3):89–102. pmid:8251548 doi: 10.1300/j069v12n03_08
  161. View Article
  162. PubMed/NCBI
  163. Google Scholar
  164. View Article
  165. PubMed/NCBI
  166. Google Scholar
  167. View Article
  168. PubMed/NCBI
  169. Google Scholar
  170. View Article
  171. PubMed/NCBI
  172. Google Scholar
  173. View Article
  174. PubMed/NCBI
  175. Google Scholar
  176. View Article
  177. PubMed/NCBI
  178. Google Scholar
  179. View Article
  180. PubMed/NCBI
  181. Google Scholar
  182. 11. Goodman A. Addiction: definition and implications. British journal of addiction. 1990;85(11):1403–8. pmid:2285834 doi: 10.1111/j.1360-0443.1990.tb01620.x
  183. View Article
  184. PubMed/NCBI
  185. Google Scholar
  186. View Article
  187. PubMed/NCBI
  188. Google Scholar
  189. View Article
  190. PubMed/NCBI
  191. Google Scholar
  192. View Article
  193. PubMed/NCBI
  194. Google Scholar
  195. View Article
  196. PubMed/NCBI
  197. Google Scholar
  198. 12. Ko CH, Hsieh TJ, Chen CY, Yen CF, Chen CS, Yen JY, et al. Altered brain activation during response inhibition and error processing in subjects with Internet gaming disorder: a functional magnetic imaging study. European archives of psychiatry and clinical neuroscience. 2014:1–12. doi: 10.1007/s00406-013-0483-3
  199. View Article
  200. PubMed/NCBI
  201. Google Scholar
  202. View Article
  203. PubMed/NCBI
  204. Google Scholar
  205. 13. Wu X, Chen X, Han J, Meng H, Luo J, Nydegger L, et al. Prevalence and factors of addictive Internet use among adolescents in Wuhan, China: interactions of parental relationship with age and hyperactivity-impulsivity. PloS one. 2013;8(4):e61782. doi: 10.1371/journal.pone.0061782. pmid:23596525
  206. View Article
  207. PubMed/NCBI
  208. Google Scholar
  209. 14. Roberts JA, Pirog SF. A preliminary investigation of materialism and impulsiveness as predictors of technological addictions among young adults. Journal of Behavioral Addictions. 2013;2(1):56–62. doi: 10.1556/jba.1.2012.011
  210. View Article
  211. PubMed/NCBI
  212. Google Scholar
  213. View Article
  214. PubMed/NCBI
  215. Google Scholar
  216. View Article
  217. PubMed/NCBI
  218. Google Scholar
  219. View Article
  220. PubMed/NCBI
  221. Google Scholar
  222. View Article
  223. PubMed/NCBI
  224. Google Scholar
  225. 15. Cao F, Su L, Liu T, Gao X. The relationship between impulsivity and Internet addiction in a sample of Chinese adolescents. European Psychiatry. 2007;22(7):466–71. pmid:17765486 doi: 10.1016/j.eurpsy.2007.05.004
  226. 16. Wierzbicki AS, Hubbard J, Botha A. A renaissance for cardio-metabolic surgery: better outcomes and lower costs? International journal of clinical practice. 2011;65(7):728–32. doi: 10.1111/j.1742-1241.2011.02696.x. pmid:21676116
  227. 17. Wiers RW, Gladwin TE, Hofmann W, Salemink E, Ridderinkhof KR. Cognitive bias modification and cognitive control training in addiction and related psychopathology mechanisms, clinical perspectives, and ways forward. Clinical Psychological Science. 2013;1(2):192–212. doi: 10.1177/2167702612466547
  228. 18. Zika S, Chamberlain K. On the relation between meaning in life and psychological well-being. British Journal of Psychology. 1992;83(1):133–45. doi: 10.1111/j.2044-8295.1992.tb02429.x
  229. 19. Steger MF, Oishi S, Kashdan TB. Meaning in life across the life span: Levels and correlates of meaning in life from emerging adulthood to older adulthood. The Journal of Positive Psychology. 2009;4(1):43–52. doi: 10.1080/17439760802303127
  230. 20. Caplan S, Williams D, Yee N. Problematic Internet use and psychosocial well-being among MMO players. Computers in Human Behavior. 2009;25(6):1312–9. doi: 10.1016/j.chb.2009.06.006
  231. 21. Kardefelt-Winther D. A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior. 2014;31:351–4. doi: 10.1016/j.chb.2013.10.059
  232. 22. Baumeister RF. Meanings of life: Guilford Press; 1991.
  233. 23. Ryff C, Singer B. The Role of Purpose in Life and Personal Growth in Positive Human Health. U: Wong, PTP, Fry. PS The Human Quest for Meaning. A Handbook of Psychological Research and Clinical Applications, str. 213–235. Lawrence Erlbaum Associates, Publishers; 1998.
  234. 24. Ryan RM, Deci EL. On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. Annual review of psychology. 2001;52(1):141–66. doi: 10.1146/annurev.psych.52.1.141
  235. 25. Laudet AB, Morgen K, White WL. The role of social supports, spirituality, religiousness, life meaning and affiliation with 12-step fellowships in quality of life satisfaction among individuals in recovery from alcohol and drug problems. Alcoholism treatment quarterly. 2006;24(1–2):33–73. pmid:16892161 doi: 10.1300/j020v24n01_04
  236. 26. Kleftaras G, Katsogianni I. Spirituality, meaning in life, and depressive symptomatology in individuals with alcohol dependence. Journal of Spirituality in Mental Health. 2012;14(4):268–88. doi: 10.1080/19349637.2012.730469
  237. 27. Newcomb MD, Harlow L. Life events and substance use among adolescents: mediating effects of perceived loss of control and meaninglessness in life. Journal of personality and social psychology. 1986;51(3):564. pmid:3489832 doi: 10.1037/0022-3514.51.3.564
  238. 28. Melton AM, Schulenberg SE. On the relationship between meaning in life and boredom proneness: examing a logotherapy postulate. Psychological reports. 2007;101(3F):1016–22. doi: 10.2466/pr0.101.3f.1016-1022
  239. 29. Peterson C, Park N, Seligman ME. Orientations to happiness and life satisfaction: The full life versus the empty life. Journal of happiness studies. 2005;6(1):25–41. doi: 10.1007/s10902-004-1278-z
  240. 30. Thomas KW, Velthouse BA. Cognitive elements of empowerment: An “interpretive” model of intrinsic task motivation. Academy of management review. 1990;15(4):666–81. doi: 10.5465/amr.1990.4310926
  241. 31. Aboujaoude E. Problematic Internet use: an overview. World Psychiatry. 2010;9(2):85–90. pmid:20671890
  242. 32. Frankl VE. Man’s search for meaning: Simon and Schuster; 1985.
  243. 33. Brassai L, Piko BF, Steger MF. Meaning in life: Is it a protective factor for adolescents’ psychological health? International journal of behavioral medicine. 2011;18(1):44–51. doi: 10.1007/s12529-010-9089-6. pmid:20960241
  244. 34. Rosenberg M. Society and the adolescent child. Princeton, NJ: Princeton University Press; 1965.
  245. 35. Greenberg J. Understanding the vital human quest for self-esteem. Perspectives on Psychological Science. 2008;3(1):48–55. doi: 10.1111/j.1745-6916.2008.00061.x
  246. 36. Harter S. The Self. Damon U W. & Lerner R. (Eds.) Handbook of child development (Vol 3). New Jersey, Wiley and Sons, Inc; 2006.
  247. 37. Brent Donnellan M, Kenny DA, Trzesniewski KH, Lucas RE, Conger RD. Using trait-state models to evaluate the longitudinal consistency of global self-esteem from adolescence to adulthood. Journal of research in personality. 2012;46(6):634–45. pmid:23180899 doi: 10.1016/j.jrp.2012.07.005
  248. 38. Kernis MH. Toward a conceptualization of optimal self-esteem. Psychological Inquiry. 2003;14(1):1–26. doi: 10.1207/s15327965pli1401_01
  249. 39. Chen X, Ye J, Zhou H. Chinese male addicts’ drug craving and their global and contingent self-esteem. Social Behavior and Personality: an international journal. 2013;41(6):907–19. doi: 10.2224/sbp.2013.41.6.907
  250. 40. Babington LM, Malone L, Kelley BR. Perceived social support, self esteem, and pregnancy status among Dominican adolescents. Applied Nursing Research. 2014;28(2):121–6. doi: 10.1016/j.apnr.2014.08.001. pmid:25262424
  251. 41. Raskauskas J, Rubiano S, Offen I, Wayland AK. Do social self-efficacy and self-esteem moderate the relationship between peer victimization and academic performance? Social Psychology of Education. 2015:1–18. doi: 10.1007/s11218-015-9292-z
  252. 42. Baxtiyar A, Abdullah T. Relate to improving self-esteem at a special needs school for emotionally disturbed adolescents in Turkey. Psychology, sociology and pedagogy. 2014;6.
  253. 43. Whang LS, Lee S, Chang G. Internet over-users’ psychological profiles: a behavior sampling analysis on internet addiction. CyberPsychology & Behavior. 2003;6(2):143–50. doi: 10.1089/109493103321640338
  254. 44. Yao MZ, He J, Ko DM, Pang K. The influence of personality, parental behaviors, and self-esteem on Internet addiction: a study of Chinese college students. Cyberpsychology, Behavior, and Social Networking. 2014;17(2):104–10. doi: 10.1089/cyber.2012.0710
  255. 45. Yao MZ, He J, Ko DM, Pang K. The influence of personality,parental behaviors, and self-esteem on internet addiction: A study of Chinese college students. Cyberpsychology, Behavior, and Social Networking. 2013;17(2):104–10. doi: 10.1089/cyber.2012.0710
  256. 46. Fioravanti G, Dèttore D, Casale S. Adolescent Internet addiction: testing the association between self-esteem, the perception of Internet attributes, and preference for online social interactions. CyberPsychology, Behavior, and Social Networking. 2012;15(6):318–23. doi: 10.1089/cyber.2011.0358
  257. 47. Bozoglan B, Demirer V, Sahin I. Loneliness, self-esteem, and life satisfaction as predictors of Internet addiction: A cross-sectional study among Turkish university students. Scandinavian journal of psychology. 2013;54(4):313–9. doi: 10.1111/sjop.12049. pmid:23577670
  258. 48. Kim HK, Davis KE. Toward a comprehensive theory of problematic Internet use: Evaluating the role of self-esteem, anxiety, flow, and the self-rated importance of Internet activities. Computers in Human Behavior. 2009;25(2):490–500. doi: 10.1016/j.chb.2008.11.001
  259. 49. Wang Y, Ollendick TH. A cross-cultural and developmental analysis of self-esteem in Chinese and Western children. Clinical Child and Family Psychology Review. 2001;4(3):253–71. pmid:11783741
  260. 50. Baumeister RF, Campbell JD, Krueger JI, Vohs KD. Does high self-esteem cause better performance, interpersonal success, happiness, or healthier lifestyles? Psychological science in the public interest. 2003;4(1):1–44. doi: 10.1111/1529-1006.01431
  261. 51. Mruk CJ. Self-esteem research, theory, and practice: Toward a positive psychology of self-esteem: Springer Publishing Company; 2006.
  262. 52. Youngs BB. How to develop self-esteem in your child: 6 vital ingredients: Ballantine Books; 1992.
  263. 53. Sattler S, Sauer C, Mehlkop G, Graeff P. The rationale for consuming cognitive enhancement drugs in university students and teachers. PloS one. 2013;8(7):e68821. doi: 10.1371/journal.pone.0068821. pmid:23874778
  264. 54. McCabe SE. Screening for drug abuse among medical and nonmedical users of prescription drugs in a probability sample of college students. Archives of pediatrics & adolescent medicine. 2008;162(3):225–31. doi: 10.1001/archpediatrics.2007.41
  265. 55. Young KS. Internet addiction: The emergence of a new clinical disorder. CyberPsychology & Behavior. 1998;1(3):237–44. doi: 10.1089/cpb.1998.1.237
  266. 56. Sussman S, Lisha N, Griffiths M. Prevalence of the addictions: a problem of the majority or the minority? Evaluation & the health professions. 2011;34(1):3–56. doi: 10.1177/0163278710380124
  267. 57. Yang H. The Chinese version of the Barratt impulsiveness scale 11th version (BIS-11) in college students: Its reliability and validity. Chinese Mental Health Journal. 2007;21(4):223.
  268. 58. Crumbaugh JC, Maholick LT. An experimental study in existentialism: The psychometric approach to Frankl’s concept of noogenic neurosis. Journal of clinical psychology. 1964;20(2):200–7. doi: 10.1002/1097-4679(196404)20:2<200::aid-jclp2270200203>3.0.co;2-u
  269. 59. Rosenberg M. Society and the adolescent self-image: Princeton University Press Princeton, NJ; 1965.
  270. 60. Blascovich J, Tomaka J. Measures of self-esteem. Measures of personality and social psychological attitudes. 1991;1:115–60. doi: 10.1016/b978-0-12-590241-0.50008-3
  271. 61. Hedges LV. Distribution theory for Glass’s estimator of effect size and related estimators. Journal of Educational and Behavioral Statistics. 1981;6(2):107–28. doi: 10.2307/1164588
  272. 62. Zhonglin W, Lei Z, Jietai H. Mediated Moderator and Moderated Mediator. Acta Psychologica Sinica. 2006;38(3):448–52.
  273. 63. Edwards JR, Lambert LS. Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis. Psychological methods. 2007;12(1):1–22. pmid:17402809 doi: 10.1037/1082-989x.12.1.1
  274. 64. Preacher KJ, Rucker DD, Hayes AF. Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate behavioral research. 2007;42(1):185–227. doi: 10.1080/00273170701341316
  275. 65. Muller D, Judd CM, Yzerbyt VY. When moderation is mediated and mediation is moderated. Journal of personality and social psychology. 2005;89(6):852. pmid:16393020 doi: 10.1037/0022-3514.89.6.852
  276. 66. Baron RM, Kenny DA. The moderator—mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology. 1986;51(6):1173. pmid:3806354 doi: 10.1037/0022-3514.51.6.1173
  277. 67. Aiken LS, West SG. Multiple regression: Testing and interpreting interactions: Sage; 1991.
  278. 68. Dearing E, Hamilton LC. Contemporary advances and classic advice for analyzing mediating and moderating variables. Monographs of the Society for Research in Child Development. 2006;71(3):88–104.
  279. 69. Holmbeck GN. Post-hoc probing of significant moderational and mediational effects in studies of pediatric populations. Journal of pediatric psychology. 2002;27(1):87–96. pmid:11726683 doi: 10.1093/jpepsy/27.1.87
  280. 70. Goel D, Subramanyam A, Kamath R. A study on the prevalence of internet addiction and its association with psychopathology in Indian adolescents. Indian Journal of Psychiatry. 2013;55(2):140. doi: 10.4103/0019-5545.111451. pmid:23825847
  281. 71. Bao-juan Y, Dong-ping L, Qi-shan C, Yan-hui W. Sensation seeking and tabacco and alcohol use among adolescents: A mediated moderation model. Psychological Development and Education. 2011;27(4):417–24.
  282. 72. Cheng AS, Ng TC, Lee HC. Impulsive personality and risk-taking behavior in motorcycle traffic offenders: A matched controlled study. Personality and Individual Differences. 2012;53(5):597–602. doi: 10.1016/j.paid.2012.05.007
  283. 73. Frankl VE. Man’s search for meaning (Rev. ed.). New York, NY: Washington Square. 1984.
  284. 74. Li J, Zhao D. The Relationship among Positive Emotion, Meaning in Life and Life Satisfaction in Master Students. Advances in Psychology (21607273). 2014;4(1):1–4. doi: 10.12677/ap.2013.41001
  285. 75. Schaefer SM, Boylan JM, van Reekum CM, Lapate RC, Norris CJ, Ryff CD, et al. Purpose in Life Predicts Better Emotional Recovery from Negative Stimuli. PloS one. 2013;8(11):e80329. doi: 10.1371/journal.pone.0080329. pmid:24236176
  286. 76. Erikson EH. Identity and the life cycle: WW Norton & Company; 1980.
  287. 77. Lee S, & Jung T. How retaking the entrance examination can enhance student quality of life at university. Social Behavior and Personality: an international journal. 2014;42(2):331–40. doi: 10.2224/sbp.2014.42.2.331
  288. 78. Jackson MR. Self-esteem and meaning: A life historical investigation: SUNY Press; 1984.
  289. 79. Yan L, Xian Z, Lei M, HongYu D. Correlation research on loneliness, self-esteem, Internet addiction disorder in college students. Chinese Journal of School Health. 2013;34(008):949–51.
  290. 80. Duckworth AL, Steen TA, Seligman ME. Positive psychology in clinical practice. Annual review of clinical psychology. 2005;1:629–51. pmid:17716102 doi: 10.1146/annurev.clinpsy.1.102803.144154
  291. 81. Kleiman EM, Adams LM, Kashdan TB, Riskind JH. Gratitude and Grit Indirectly Reduce Risk of Suicidal Ideations by Enhancing Meaning in Life: Evidence for a Mediated Moderation Model. Journal of Research in Personality. 2013;47:539–46. doi: 10.1016/j.jrp.2013.04.007
  292. 82. Seligman ME, Rashid T, Parks AC. Positive psychotherapy. American psychologist. 2006;61(8):774. pmid:17115810 doi: 10.1037/0003-066x.61.8.774
  293. 83. Dijksterhuis A. I like myself but I don’t know why: enhancing implicit self-esteem by subliminal evaluative conditioning. Journal of personality and social psychology. 2004;86(2):345. pmid:14769089 doi: 10.1037/0022-3514.86.2.345
  294. 84. Wong K-y, Melody , Qien H. Self-worth and internet addiction among Chinese youths in Hong Kong: The University of Hong Kong (Pokfulam, Hong Kong); 2012.