Internet-Communication Disorder: It’s a Matter of Social Aspects, Coping, and Internet-Use Expectancies (2016)

Elisa Wegmann¹ and Matthias Brand^1,2,*

Online communication applications such as Facebook, WhatsApp, and Twitter are some of the most frequently used Internet applications. There is a growing amount of individuals suffering diminished control over their use of online communication applications which leads to diverse negative consequences in offline life. This could be referred to as Internet-communication disorder (ICD). The current study investigates the role of individual characteristics (e.g., psychopathological symptoms, feelings of loneliness) and specific cognitions. In a sample of 485 participants a structural equation model was tested to investigate predictors and mediators which may predict an excessive use. The results emphasize that a higher level of social loneliness and less perceived social support enhance the risk of a pathological use. The effects of psychopathological symptoms (depression and social anxiety) as well as individual characteristics (self-esteem, self-efficacy, and stress vulnerability) on ICD symptoms are mediated by Internet-use expectancies and dysfunctional coping mechanisms. The results illustrate mediation effects which are in line with the theoretical model by Brand et al. (2016). As suggested in the model social aspects seem to be key predictors of ICD symptoms. Further research should investigate convergent and divergent factors of other types of specific Internet-use disorders.

Participants

Four hundred eighty-five participants aged between 14 and 55 years (M = 23.95, SD = 4.96 years) took part in the study. Three hundred fifty-eight were females, 125 were males, and two gave no information on gender. Regarding other relevant sociodemographic information, 252 participants reported that they were in a relationship or were married, 366 were students, 115 had a regular job. All participants have participated before in the study of Brand et al. (2014a), in which a sample of 1019 participants was used to test the structural equation model on generalized Internet addiction. The current sample was selected on the basis of the participants first-choice Internet use. We asked the participants to select the specific online application they personally use and that they find most attractive. After the decision was made, participants administered the one version of the short Internet Addiction Test that was specific for their first-choice application. We only included participants who used the Internet mainly for online communication. The analyses using Internet-communication disorder as dependent variable were not part of the former study by Brand et al. (2014a). The participants spend in average 562.10 min (SD = 709.03) per week using online communication applications. The sample was recruited at the University of Duisburg-Essen via mailing-lists, flyers, and word-of-mouth recommendations. The assessment was done by an online-survey and the participants could take part in raffle where they have the chance to win an iPad, iPad mini, iPod nano, iPod shuffle, or Amazon gift cards. The local ethics committee approved the study.

Instruments

Statistical analyses

The statistical analyses were carried out using SPSS 23.0 for Windows (IBM SPSS Statistics, released 2014). To test bivariate relationships between two variables we calculated Pearson correlations. The confirmatory factor analysis (CFA) and structural equation model (SEM) analyses were computed with Mplus 6 (Muthén and Muthén, 2011). There were no missing data. We evaluated the model fit with the standard criteria: standardized root mean square residual (SRMR; values < 0.08 indicate a good fit with the data), comparative fit indices (CFI/TLI; values >0.90 indicate an acceptable and >0.95 an good fit with the data), and root mean square error of approximation (RMSEA; values < 0.08 indicate a good and 0.08–0.10 an acceptable model fit) (Hu and Bentler, 1995, 1999). The χ² test was used to check, if the data derivate from the defined model. To contrast different models, we considered the Bayesian Information Criterion (BIC) while values lower ten points indicate a better fit with the data (Kass and Raftery, 1995). All relevant variables for the mediation were required to correlate with each other (Baron and Kenny, 1986).

Description and correlations

The sample’s mean score in the s-IAT-com and the scores of the questionnaires applied and the bivariate correlations can be found in Table ​Table1.1. In comparison with the reported cut-off scores by Pawlikowski et al. (2013) 39 participants (8.04%) indicated a problematic but not pathological use (cut-off scores >30 but ≤37) and 15 participants (3.09%) a pathological use (cut-off scores >37) of online communication activities.

  

Table 1

Descriptive statistics and bivariate correlations between the scores of the short Internet Addiction Test and the applied scales.

Structural equation model

The proposed structural equation model on latent variable with ICD symptoms (s-IAT-com) as dependent variable showed a good fit with the data. The RMSEA was 0.060 (p = 0.054), CFI was 0.957, TLI was 0.938, and the SRMR was 0.040, BIC was 15072.15. The χ²—test was significant, χ² was 174.17 (p < 0.001) and χ²/df was 2.76.

Overall, 50.8% of the variance in the ICD symptoms could be explained by the proposed model (R² = 0.508, p < 0.001). The structural equation model with the factor loadings and β-weights are represented in Figure ​Figure22.

  

Figure 2

Results of the structural equation model including factor loadings on the described latent variables and the accompanying β-weights, p-values, and residuals.

The latent variable social aspects had a direct effect on the dependent latent variable ICD while the other latent variables showed no direct effect (all β’s < 0.169, all p‘s > 0.263). However, both mediator variables Internet-use expectancies and coping were significant predictors of ICD. In addition, personality aspects were a significant predictor of coping with a negative β-weight. The indirect effect from personality aspects over coping to ICD was significant (β = −0.166, SE = 0.077, p = 0.031). The indirect effect from psychopathological symptoms to ICD symptoms over Internet-use expectancies was also significant (β = 0.199, SE = 0.070, p = 0.005). Both results indicated mediation effects.

Additional analyses

To better understand further underlying mechanisms of ICD some additional models or parts of the model were tested.

The first issue we addressed was the effect of the social aspects on ICD. Compared with the empirical model by Brand et al. (2014a), the latent variable social aspects were conceptualized with the manifest variables perceived social support and the latent variable social loneliness of the Loneliness Scale by De Jong Gierveld and Van Tilburg (2006) instead of the subscale emotional loneliness in the current study. When using the same manifest variables for the latent variable social aspects, as done in Brand et al. (2014a), there was an acceptable model fit (CFI = 0.955, TLI = 0.936, RMSEA 0.063, SRMR = 0.040, BIC = 15142.03). However, the difference between this model and the main model of the current study is that there was no direct effect of social aspects or mediation effect of personality aspects and ICD by coping. Demographic variables were also considered as potential variables which may have an effect on the structural equation model. We first calculated bivariate correlations between the manifest variables and age and found only correlations with low effect size (Cohen, 1988) between age and self-esteem, self-efficacy, stress vulnerability, coping variables, and Internet-use expectancies (r‘s < |0.212|). Overall, the requirements for integrating age in the proposed model were not fulfilled (Baron and Kenny, 1986). To control for gender biases, a group comparison was calculated with all variables and significant differences between male and female participants were found in respect of interpersonal sensitivity, self-efficacy, stress vulnerability, coping subscale substance use, and both Internet-use expectancies factors (t = |0.06–4.32|, p = 0.035– < 0.001). After this, a structural equation model with additional differentiation by gender using a mean structure analysis was analyzed. This way of proceeding is often used to compare the group means (male vs. female) on the proposed constructs (Dimitrov, 2006). The fit indices were acceptable (CFI = 0.942, TLI = 0.926, RMSEA 0.066, SRMR = 0.070, BIC = 15179.13). Overall, we found same relationships between coping, Internet-use expectancies, and ICD for male and female participants. For females the direct effect from social aspects to ICD was not significant (β = −0.148, p = 0.087) nor for men (β = −0.067, p = 0.661), although the effect size was higher descriptively. The effect of psychopathological symptoms to ICD mediated by Internet-use expectancies was only found for women (β = 0.192, SE = 0.086, p = 0.025). Nevertheless, due to the small sample size for the structural equation models the results should be discussed with caution. The different structural equation models for the female and male sample with the factor loadings and β-weights are represented in Figure ​Figure33.

  

Figure 3

Results of the structural equation model separated for the female and male sample including factor loadings on the described latent variables and the accompanying β-weights, p-values, and residuals.

General discussion of the results

The current study analyzed potential mechanisms such as person’s characteristics, coping style, and Internet-related cognitive bias associated with ICD symptoms. The proposed structural equation model was based on the theoretical model of a specific Internet-use disorder by Brand et al. (2016) and an empirical model on generalized Internet addiction by Brand et al. (2014a). Overall, the model with ICD as dependent variable yielded a good fit with the data. The hypothesized model explained 50.8% of the variance of ICD symptoms. The results showed that the relationship between person’s characteristics and ICD were partially mediated by coping style and Internet-use expectancies. Furthermore, a direct effect of social aspects such as social loneliness and perceived social support to ICD symptoms was found.

At first, we calculated bivariate correlation between all variables and the s-IAT-communication score, which were significant. This is in line with previous research on ICD. The findings also confirm the hypothesis, that stress vulnerability and self-efficacy correlate with ICD (for the first time).

Second, the hypothesized structural equation model was analyzed. The study found that social aspects play a central role in ICD. High social loneliness and less perceived social support predicted ICD symptoms. Persons who perceive themselves as socially lonely and less socially supported experience more negative consequences due to their online communication behavior, which is in line with previous research (Baker and Oswald, 2010; De Cock et al., 2013; Omar and Subramanian, 2013; Song et al., 2014). The individuals who selected online communication applications as their main online activity seem to gratify social needs online more than in real-life situations (Song et al., 2014). This indicates that online communication applications fulfill a social function and possibly compensate perceived real-life deficits, which seem to be an essential mechanism for problematic communication behavior (Kim et al., 2009; Yadav et al., 2013; Huang et al., 2014). Interestingly, this effect was not mediated by coping strategies or expectancies regarding the helpfulness of the Internet for solving problems or escaping from reality. Hence, the experienced gratification or the compensation of social deficits, which lead to an excessive use of Internet, describes a direct effect without an impact of further cognitive biases.

The current study aimed at identifying mediation effects and at checking the results with previous empirical findings regarding the mechanisms of a generalized Internet addiction (Brand et al., 2014a). There was neither a direct nor a mediated effect of social aspects on a general Internet addiction. Consequently, it can be assumed that the addictive use of Facebook, WhatsApp, or Twitter is associated with social real-life deficits, like perceived social loneliness and less perceived social support. This is not the case for a general overuse of the Internet when no specific application is preferred. Therefore, the preference of online communication applications as a safe, anonymous, controlled environment for communication is associated with less integration in real-life social networks, which is supposed to lead to a dysfunctional use.

The study also showed that dysfunctional coping style and Internet-use expectancies are significant predictors of ICD, which is consistent with other studies about predictors of Internet addiction (Tonioni et al., 2012; Turel and Serenko, 2012; Xu et al., 2012; Tang et al., 2013; Brand et al., 2014a; Kardefelt-Winther, 2014; Lee et al., 2015). Individuals with high expectancies toward the Internet as helpful tool to distract from annoying duties or to experience pleasure as well as with dysfunctional coping strategies such as denial or behavioral disengagement have a higher risk to develop an ICD. The relevance of psychopathological symptoms like social anxiety and depression for an ICD is supported by the suggested model and compatible with other research on the relationship between psychopathological aspects and SNS use (De Cock et al., 2013; Panek et al., 2013; Hong et al., 2014; Bhagat, 2015; Bodroza and Jovanovic, 2015; Laconi et al., 2015; Moreau et al., 2015; Guedes et al., 2016). The effect of psychopathological symptoms to ICD was mediated by the Internet-use expectancies which is consistent with the study by Wegmann et al. (2015). Persons with depressive symptoms, social anxiety, and the expectancies toward the Internet as a helpful tool for escaping from negative feelings and for gratifying social needs, have a higher risk to develop a problematic use of online communication services (Wegmann et al., 2015). Similar to the psychopathological symptoms, the effect of personality aspects like self-esteem, self-efficacy, and stress vulnerability to ICD were mediated by specific cognitions, in this case a dysfunctional coping style. Low self-esteem, self-efficacy, and higher stress vulnerability leads to the denial or problems, substance use, and behavioral disengagement. These individuals have no further strategies to cope with low self-esteem or feelings of loneliness or depression. This association could influence individuals to go online in order to escape from real life problems. Former research already indicated the relationship between self-esteem and the preference for online communication (Chak and Leung, 2004; Steinfield et al., 2008; Panek et al., 2013; Bhagat, 2015; Laconi et al., 2015; Guedes et al., 2016). Consistent with the theoretical approach by Brand et al. (2016), it is assumed that individuals with higher stress vulnerability and deficits concerning their self-confidence in combination with dysfunctional/impulsive coping strategies have a higher need for mood regulation (Whang et al., 2003; Tonioni et al., 2014; Brand et al., 2016). The interaction between these person’s characteristics and the individual way to react to difficult situations could result in the use of the “first-choice”-application, i.e., communication applications, in which individuals communicate with others. This behavior can be a very helpful strategy given that individuals discuss their problems with others online. On the other hand, this behavior could be problematic if other problem-solving strategies are neglected and real-life contact is ignored, which could result in higher social isolation. The results indicate that real-life problem-solving strategies play an important role online as well. Conveying functional coping strategies, such as active coping, seems to be an essential preventive mechanism in decreasing the risk to use the Internet or the “first-choice”-application as a dysfunctional coping strategy (Kardefelt-Winther, 2014).

Controlling the results after searching for gender bias, we found some differences in the results for men and women. The results merely revealed that the use of online communication applications when feeling lonely or the perception of less social support was more distinctive for women. Some differences between male and female participants for different Internet-use disorders or SNS use patterns were reported previously (Ko et al., 2005; Meerkerk et al., 2006; Kuss and Griffiths, 2011a; Laconi et al., 2015). Ang (2017) for example, emphasized that females with a stronger Internet habit are more likely to engage in online communication than male participants. Possible differences for ICD have to be investigate in further studies.

In summary, the findings are in line with the theoretical model of Internet-use disorder (Brand et al., 2016) indicating that the relationship between person’s characteristics and symptoms of an Internet-use disorder are mediated by specific cognitions. Additionally, the mediation effects which were found in the course of this study have already been supposed for a generalized Internet addiction (Brand et al., 2014a) and cybersex addiction (Laier and Brand, 2014). Nevertheless, the relevance of individual aspects like psychopathological, personality, and social aspects differs. While personality aspects and psychopathological symptoms were mediated by cognitive dimensions assessing a generalized Internet addiction and ICD, social cognitions did not play a role in the development and maintenance of generalized overuse of the Internet. In the current study, social aspects had a direct effect to symptoms of ICD.

Consequently, the current study emphasizes convergent and divergent mechanisms of different forms of Internet-use disorders, as shown by Montag et al. (2015), Laconi et al. (2015), Pawlikowski et al. (2014), and Wang C. W. et al. (2015). While there seems to be an overlap between potential mechanisms of a general overuse of Internet and online communication behavior, evidence was found that allows to differentiate between specific Internet-use disorders. Therefore, it could be concluded that generalized Internet addiction and ICD share common mechanisms but are not synonymous (Hormes et al., 2015). Some investigations show growing evidence that suggests similarities between excessive use of Internet-communication applications and further behavioral addictions. These studies illustrate the relevance of reinforcement mechanisms as well as evidence for several diagnostic criteria, which emphasizes the own construct of an ICD (Kuss and Griffiths, 2011b; Andreassen and Pallesen, 2014; Hormes et al., 2015).

A main conclusion is that the theoretical model of Internet-use disorder (Brand et al., 2014b) could be transferred to ICD, similar to the cybersex addiction case (Laier and Brand, 2014). The modification of this theoretical model into a specific Internet-use disorder, which emphasizes the use of specific, preferred applications, could facilitate the understanding of individual mechanisms. The modified model for an ICD should focus on the role of social aspects and the assumption that persons with perceived social deficits use online communication applications to compensate these deficits directly. This is in contrast with further person’s characteristics, which are mediated by specific cognitions. Additionally, the empirical model of the current study should be controlled for other forms like Internet-gaming disorder, Internet-pornography-use disorder, or pathological online buying behavior. For Internet-gaming disorder, individuals could also use the function to communicate online and stay in contact with other gamers while gaming. Consequently, in this case, the potential role of social aspects needs to be discussed as well.

Limitations

Finally, there are some limitations to be mentioned. First, the study is based on an online survey in a non-clinical sample. Although the data was carefully controlled and removed participants, which answered the questionnaires in an excessively long or short time, we could not exclude potential bias in the data due to the relationship between the online environment of the survey and its content. Second, the Brief COPE by Carver (1997) showed low reliability, which is still comparable to former studies (Carver, 1997; Brand et al., 2014a). However, future studies should consider using another questionnaire or controlling the data and the subscales concerning their reliability. However, we used these subscales to model coping as latent dimension, which means that the effects in the structural equation model were free of measurement errors, although the reliability of the single scales measuring coping were not optimal. Regarding the discussion about the common method bias, a strength of the current study is the heterogeneity of the Likert scales. Podsakoff et al. (2003) emphasize that using common scale formats would refer to artificial covariation. They recommend the use of different scales and constructs to enhance variances and to reduce the common method bias. Thirdly, in the current study the term “Internet-communication application” or “online communication applications” was used. Since this term includes a broad range of different technologies, the effect of the different technologies may be addressed in further research. Nevertheless, to limit this issue, all participants of the study have been given a clear definition, of the term “Internet-communication applications.” Additionally, variables such as self-efficacy could be specified for the dependent variables and the underlying mechanisms, for example using Internet self-efficacy or self-efficacy toward these different online communication applications.

Future research

Future research should investigate direct convergent and divergent mechanisms of different types of Internet-use disorders. In the current study a structural equation model was used and the results were compared to other empirical findings in the literature. However, a direct empirical comparison should expand our knowledge about the different contributions of social aspects in the development and maintenance of different types of Internet-use disorders.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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