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  • 1 Department of Psychology, Faculty of Education, Charles University, Prague, Czech Republic
  • | 2 Department of Addictology, First Faculty of Medicine, Charles University, Prague, Czech Republic
  • | 3 Department of Addictology, General University Hospital in Prague, Prague, Czech Republic
Open access

Abstract

Background and aims

Problematic internet use (PIU) is a highly prevalent condition with severe adverse effects. The literature suggests that parent-child bonding and parental behavioral control exert protective effects against PIU. However, the most relevant studies rely on simplistic measurement of parenting, cross-sectional designs and mixed-aged samples. Our study analyzed the effect of maternal and paternal parenting on PIU by using a prospective design and a cohort sample of same-aged children.

Methods

Data from 1,019 Czech 12-year-old sixth-graders who were followed until ninth grade were used. Maternal and paternal responsiveness and strictness were reported by children using the Parental Acceptance-Rejection Questionnaire (PARQ) and the Parental Control Scale (PCS). PIU was measured by the Excessive Internet Use Scale (EIUS).

Results

The self-reported PIU prevalence in nine-graders (15-year-old) was 8.1%. Parenting, reported by adolescents 18 months before PIU screening, showed significant relationships with PIU: parental responsiveness was negatively and moderately associated, while maternal strictness showed a weak positive association; the authoritative parenting style in both parents decreased PIU, with a PIU probability of 3.21%, while a combination of maternal authoritarian and paternal neglectful parenting was associated with PIU probability as high as 20.9%.

Discussion and conclusions

The self-reported prevalence of PIU in Czech adolescents was found to be high. The effects of parenting on PIU were similar to the effects of parenting on other problematic behavior among adolescents. Our findings showed the need for interventions to prevent PIU by helping parents to apply optimal parenting styles.

Abstract

Background and aims

Problematic internet use (PIU) is a highly prevalent condition with severe adverse effects. The literature suggests that parent-child bonding and parental behavioral control exert protective effects against PIU. However, the most relevant studies rely on simplistic measurement of parenting, cross-sectional designs and mixed-aged samples. Our study analyzed the effect of maternal and paternal parenting on PIU by using a prospective design and a cohort sample of same-aged children.

Methods

Data from 1,019 Czech 12-year-old sixth-graders who were followed until ninth grade were used. Maternal and paternal responsiveness and strictness were reported by children using the Parental Acceptance-Rejection Questionnaire (PARQ) and the Parental Control Scale (PCS). PIU was measured by the Excessive Internet Use Scale (EIUS).

Results

The self-reported PIU prevalence in nine-graders (15-year-old) was 8.1%. Parenting, reported by adolescents 18 months before PIU screening, showed significant relationships with PIU: parental responsiveness was negatively and moderately associated, while maternal strictness showed a weak positive association; the authoritative parenting style in both parents decreased PIU, with a PIU probability of 3.21%, while a combination of maternal authoritarian and paternal neglectful parenting was associated with PIU probability as high as 20.9%.

Discussion and conclusions

The self-reported prevalence of PIU in Czech adolescents was found to be high. The effects of parenting on PIU were similar to the effects of parenting on other problematic behavior among adolescents. Our findings showed the need for interventions to prevent PIU by helping parents to apply optimal parenting styles.

Introduction

With internet access rapidly increasing over the globe (Kuss & Billieux, 2017), adolescents are currently more online than ever before. The Internet offers many possibilities to learn, socialize, and relax, but it is also associated with risks such as cyberbullying/cybervictimization, exposure to inappropriate content or uncontrollable excessive use (most usually referred to as excessive use of internet (EUI), internet addiction (IA), or problematic internet use (PIU)). PIU, which describes an inability to inhibit online activities despite negative consequences, has an estimated global prevalence of 6.0% (Cheng & Li, 2014) and is known to have detrimental effects on various aspects of life (Fineberg et al., 2018).

Adolescence is a sensitive period for developing both substance use and behavioral addictions (Balogh, Mayes, & Potenza, 2013). It has been shown that PIU prevalence is higher among adolescents than in the general population (Kuss, Griffiths, Karila, & Billieux, 2014). The etiology of PIU seems to be complex, as it includes personality as well as environmental factors. There is a growing body of studies focusing on the role of family factors in adolescent PIU.

It seems that a good parent-child relationship is associated with a lower risk of PIU. Casaló & Escario (2019) found a negative relationship between perceived parental care and excessive internet use in 14- to 18-year-old Spanish adolescents. Having a higher-quality parent-child relationship was found to be negatively associated with PIU in a US sample of 12- to 17-year-olds (Bleakley, Ellithorpe, & Romer, 2016). Chinese high-school students who reported good relationships (instead of bad relationships) with their fathers were less prone to PIU (Dong et al., 2019). Chinese adolescents (aged 11–18 years) with PIU symptoms reported lower quality of family functioning than those without PIU (Shi, Wang, & Zou, 2017). Shanghai adolescents (11–20 years) with worse relationships with mothers or fathers showed higher PIU scores (Xu et al., 2014). A small negative correlation between the quality of the parent-child relationship and PIU was found in Hong Kong adolescents aged 13 years (Shek, Zhu, & Ma, 2018) and 16 years (Shek, Zhu, & Dou, 2019). The only study using data from parents rather than children found a moderate negative association between PIU and parental care but a moderate positive association between PIU and parental overprotection (Siomos et al., 2012). Finally, Chinese adolescents with clinically diagnosed PIU reported lower paternal and maternal emotional warmth and higher rejection and overinvolvement when compared to healthy controls (Xiuqin et al., 2010).

In the case of parental control, the results are less clear. The variability in concepts and measures of parental control is high. Some studies differentiate between behavioral control (monitoring and taking interest in children's activities, modeling appropriate behavior and setting regulative rules) and psychological control (negative parenting practice that includes trying to make children emotionally dependent on a parent using strategies such as guilt induction and love withdrawal). While psychological control is well known to have adverse effects on many aspects of children's development (Siomos et al., 2012), it is not surprising that it has been shown to be positively correlated with PIU (Cetinkaya, 2019; Li, Li, & Newman, 2013; Shek, Zhu, & Dou, 2019; Shek, Zhu, & Ma, 2018). Findings on the relationship between behavioral control and PIU have included a small negative association for both parents (Shek, Zhu, & Ma, 2018), a small negative association significant only for paternal (not maternal) control (Shek et al., 2019), a small protective effect that was fully mediated by the child's self-control (Li et al., 2013), and a small negative nonsignificant association (Cetinkaya, 2019). Regarding the effect of concepts similar to parental behavioral control, Casaló & Escario (2019) found a small negative association between setting regulatory rules and excessive use of the internet, but only in girls. Dong et al. (2019) and Wu et al. (2016) demonstrated the lowest PIU prevalence in a group of adolescents reporting an average level of parental control (compared to “little” and “much”). However, in these two studies, the degree of parental control was measured by a single item. It seems that parental behavioral control can prevent PIU, but its simplistic measurement seriously limits conclusions that may be inferred from currently available research. In related research areas, such as adolescents' substance use, more elaborate measures of parenting can be found. Calafat, García, Juan, Becoña, and Fernández-Hermida (2014), using a two-dimensional conceptualization of parental behavior consisting of responsiveness (warmth, acceptance, involvement) and strictness (control, demandingness, imposition, parental firmness), showed that parenting styles with high responsiveness (indulgent and authoritative parenting styles) are more protective against adolescent substance than styles with low responsiveness (authoritarian and neglectful parenting styles).

The abovementioned studies analyzing the effects of parents on adolescent PIU have limitations. Most studies relied on simple methods to measure parental control, and only a few distinguished between maternal and paternal parenting. In addition, most studies used a cross-sectional design, which does not allow for an estimation of the long-term effect of parental behavior on PIU.

In the current study, we address all these limitations. Our aim was to analyze how adolescent PIU was influenced by parental behavior (both maternal and paternal) as measured by a reliable and valid instrument that distinguishes between responsiveness and strictness.

Methods

Setting

This study utilized data from a project evaluating prevention intervention aimed at substance use in school children. This project took place in schools representing four regions in Czechia between 2013 and 2017. The units of data collection were 6th grade classes (children aged 11–13 years) from participating schools. A total of 3,017 children who attended these classes and their parents were asked to participate in the project. For more details on the project, see Gabrhelík et al. (2014).

Data collection

The first wave (out of seven waves) of data collection in children took place in the fall of 2013 (mean age of children: 11.9, SD = 0.41, N = 1,000). The following six waves of data collection in children were in spring and fall of each year, i.e., at the beginning and end of a school year. The last wave took place in spring 2017 in the ninth grade. A web-based questionnaire was used to collect data from the children. We used data from parents collected between waves 1 and 2 (Fig. 1). The mean age of the parents was 40.9, SD = 4.72, N = 1,011. Parents were asked to fill in questionnaires in a pen-and-paper format.

Fig. 1.
Fig. 1.

The timeline of data collection, flow of participants between waves and variables of interest for the presented study (N = 1,019 child-parent dyads in all waves).

Note. Data from parents were collected only at baseline (between wave 1 and 2). 1931 parents (83% mothers) participated, 912 were excluded. Wave 1 and 2 took place when adolescents were in 6th grade, wave 3 and 4 when they were in 7th grade, wave 5 and 6 when they were in 8th grade and wave 7 when they were in 9th grade. *Time from wave 1.

Citation: Journal of Behavioral Addictions 9, 3; 10.1556/2006.2020.00068

Sample

We analyzed data from a subset of children and their parents participating in the project described earlier. The inclusion criteria for adolescents were as follows: (1) provided data regarding PIU (wave 7), (2) provided data on parental responsiveness and strictness for both parents (mothers and fathers) in at least three waves (1–5), and (3) provided a valid identification code that could be matched with a parental code. The inclusion criteria for parents were as follows: (1) completed parental questionnaires before the start of the second wave of data collection in children, and (2) provided a valid parental self-generated identification code (SGIC ) that could be matched with the child's SGIC (Vacek, Vonkova, & Gabrhelík, 2017). A total of 2,810 children out of 3,017 eligible children (93.14%) participated in at least one wave of data collection (not necessarily in the first wave). First, we excluded 997 children who could not be paired with their parent; second, we excluded 77 children with nonvalid answers (i.e., those who reported the use of the made-up substance called “Semeron” in any wave); third, we excluded 604 children who did not provide valid measurements of the outcome variable (PIU, wave 7); and fourth, we excluded 113 children who did not provide valid responses for the main predicting variables (responsiveness and strictness of mother and father) in at least three waves. A total of 1,019 children met all inclusion criteria. Among 3,017 eligible parents, 1,931 parents (68.7%) completed the parental questionnaire. A total of 118 parents were excluded because they could not be matched with the child (i.e., either a child or a parent did not provide valid SGIC). Another 794 parents were excluded because their child did not meet the inclusion criteria and was excluded. The final sample consisted of 1,019 child–parent dyads that met all inclusion criteria. The characteristics of the final sample are shown in Table 1.

Table 1.

The characteristics of sample (N = 1,019)

NPercentage (%)
Gender of adolescentGirl52251
Boy48047
Missing172
Gender of parentaFemale84383
Male17017
Missing61
Family intactnessaIntact83282
Restructured656
Incomplete12012
Missing20
Family incomeaLess than 600 EUR353
600–800 EUR616
800–1,000 EUR9710
1,000–1,200 EUR13413
1,200–1,600 EUR25125
1,600–2,400 EUR19119
2,400–3,200 EUR778
More than 3,200 EUR465
Missing12712
Education of motherElementary434
Practical13513
High school25825
Incomplete further education394
Completed further education24924
Missing29529
Education of fatherElementary364
Practical15315
High school21521
Incomplete further education404
Completed further education26026
Missing31531

Reported by a parent.

Missing data

Missing values in the main predicting variables (parental behavior) were imputed using the multiple imputation (MI) method (Honaker, King, & Blackwell, 2011). The total amount of imputed data was 9.35%, which was acceptable (Twisk & de Vente, 2002). We did not impute any data in the outcome variable (PIU), and we also did not impute variables measured by one item and/or in one wave (e.g., adolescent's gender, family intactness, family income, and parental education).

Measures

We used a Web-based questionnaire for collecting data from the children; their parents were asked to fill in questionnaires in a pen-and-paper version. Anonymous SGICs were used to allow the baseline questionnaire data collected from the children to be linked to data from their parents (Vacek et al., 2017).

Predicting variables – Parental responsiveness (warmth) and strictness (control)

Parental responsiveness and strictness were reported by children using the Warmth/Affection subscale (WAS) from the Parental Acceptance-Rejection Questionnaire (PARQ) (Rohner, Khaleque, & Cournoyer, 2005) and the Parental Control Scale (PCS) (Rohner & Khaleque, 2003). Both scales proved to be reliable measures of parental behavior in various contexts and cultures, including the Czech Republic (Becoña et al., 2012; Cablova, Csemy, Belacek, & Miovsky, 2016; Khaleque & Rohner, 2012; Rohner & Khaleque, 2003).

The PCS assessed the child's perception of parental behavioral control. It included 13 items describing parental regulative behavior, such as monitoring children's whereabouts and activities, setting rules, and limiting children's freedom (e.g., “My mother tells me exactly what time to be home when I go out”). The shortened PARQ–WAS inventory consisted of eight items describing responsiveness and affection toward the child – expressing interest and positive feelings toward the child, praising the child's opinion, etc. (e.g., “My mother talks to me about our plans and listens to what I have to say”). In both scales, there were two identical sets of items for maternal and paternal behavior. The respondents evaluated how often the described behavior was true for his/her mother or father on a 1 to 4 scale, where 4 meant “always true” and 1 means “never true” (except for a few items that were reversely coded).

We computed four scores for each participant: maternal strictness, paternal strictness, maternal responsiveness, and paternal responsiveness as average scores on the PCS and PARQ–WAS items. Furthermore, following the procedure by Calafat et al. (2014) and others, we identified the four parenting styles of mothers and fathers based on their combination of strictness and responsiveness scores: authoritative (high responsiveness and high strictness), authoritarian (low responsiveness and high strictness), indulgent (high responsiveness and low strictness), or neglectful (low responsiveness and low strictness). High/low categorization was based on the median (50th percentile) split.

Outcome variable – Problematic internet use

PIU was measured by the Excessive Internet Use Scale (EIUS) (Šmahel, Vondráčková, Blinka, & Godoy-Etcheverry, 2009). The EIUS is a 10-item scale evaluating 5 symptoms of PIU: cognitive and behavioral salience, tolerance, withdrawal, conflicts, and problems with limiting time online (i.e., loss of control). Each symptom is measured by two questions on a 4-point Likert scale (1 – never to 4 – very often). A symptom is present if the respondent answered “often” or “very often” to at least one question assessing the symptom. PIU is present if conflict and at least three other symptoms are present (that means that one symptom, excluding conflict, can be missing). The EIUS is widely used in the European context (Škařupová, Ólafsson, & Blinka, 2015). The items were extended to ensure that adolescents would include gaming in their online activities (e.g., “Does it happen to you that you stay online or were gaming for longer time than originally planned?”). This was done to aid adolescents in understanding that internet use included not only browsing the web and using social media, but also gaming. According to the standard procedure (Šmahel et al., 2009), we calculated the PIU score as a sum of positive symptoms (0–5) and determined the PIU status as a nominal variable reflecting whether the participant fulfilled the criteria of PIU (i.e., scored positive in conflict symptoms and at least three of the other four symptoms measured by the EIUS) or not.

Sociodemographic background variables

The number of sociodemographic characteristics was reported by adolescents (age, gender, school grades, family intactness and educational level of mother and father) or by parents (family income, parents' age).

Statistical analysis

The prevalence of PIU was established, and the effect of sociodemographic variables on PIU was examined using the χ2 test of association (adolescent's gender, family intactness, family income, educational level of mother, educational level of father) or by Welch's t-test (adolescent's school grades).

We analyzed the differences between maternal and paternal behavior using paired t-tests, and we analyzed the development of parental strictness and responsiveness over time using repeated measures ANOVA with Bonferroni post hoc tests. We also examined associations between parenting styles and sociodemographic variables by the χ2 test of association and Welch's t-test.

The effects of parental behavior on adolescent IA were analyzed in several steps. First, we computed correlations between the PIU score (wave 7) and maternal and paternal responsiveness and strictness (wave 1–5). Second, we compared maternal and paternal responsiveness and strictness scores in adolescents with and without PIU. Finally, we assessed the combined effect of responsiveness and strictness by using the parenting styles (wave 5) that reflect different combinations of responsiveness and strictness. We examined the incidence of PIU according to parenting styles by the χ2 test of association and then computed the probability of adolescent PIU in groups with various combinations of maternal and paternal parenting styles using logistic regression.

Ethics

The study was approved by the Ethical Committee of the General University Hospital in Prague. All subjects were informed about the study, and all provided informed consent. Parental consent was obtained for those younger than 18 years of age.

Results

PIU prevalence and the effect of sociodemographic variables on PIU

The prevalence of self-reported PIU in our sample was 8.1%. The PIU score ranged between 0 and 5 (M = 1.36, MD = 1, SD = 1.49). The prevalence was slightly higher in boys (9.2%) than in girls (7.3%), but the association between gender and PIU status was not significant (χ2=1.18, P = 0.276, N = 1,002). However, the PIU score (the sum of positive symptoms) was significantly higher in boys (M = 1.50, SD = 1.52) than in girls (M = 1.24, SD = 1.46) with MD = 0.266, Welch's t(986) = 2.82, P = 0.005, and Cohen's d = 0.179.

None of the other examined sociodemographic variables were significantly associated with PIU status, namely, family income (χ2(7) = 4.85, P = 0.678, N = 892), family intactness (χ2(2) = 3.02, P = 0.221. N = 1,017), education of mother (χ2(4) = 2.58, P = 0.630, N = 724), education of father (χ2(4) = 2.37, P = 0.668, N = 704) and parental age (t(85.6) = 0.481, P = 0.632, N = 1,002).

School grades were worse in the PIU group (M = 2.10, SD = 1.93) than in the group without PIU (M = 1.8, SD = 1.15). The difference was not statistically significant (Welch's t(83.8) = −1.38, P = 0.171), but there was a moderate effect size (Cohen's d = −0.247).

Parental behavior

Adolescents' reports on the responsiveness and strictness of their mothers and fathers showed high stability within a two-year period. The between-waves Pearson's correlations for responsiveness and strictness ranged from 0.417 to 0.721.

As shown in Table 2, adolescents in all waves reported significantly higher maternal responsiveness (Student's paired-sample t's ranged from 9.02 to 11.24, all P's<0.001, Cohen's d between 0.282 and 0.352) and strictness (t between 9.77 and 11.53, all P's<0.001, Cohen's d between 0.306 and 0.361) than paternal responsiveness and strictness. Reports on maternal and paternal behavior were strongly correlated both for responsiveness (Pearson's r ranged from 0.539 to 0.593, all P's<0.001) and strictness (Pearson's r ranged from 0.447 to 0.556, all P's<0.001).

Table 2.

Maternal and paternal responsiveness and strictness as measured in waves 1–5, their correlations with each other (maternal–paternal), correlations with PIU (wave 7), and differences between maternal and paternal variables. (N = 1,019)

VariableMaternalPaternalMaternal–Paternal
Mean (SD)Correlation with PIU (wave 7)-Pearson rMean (SD)Correlation with PIU (wave 7)-Pearson rDifference-Student ta (Cohen d)Correlation-Pearson r
Responsiveness – wave 13.51 (0.472)−0.110***3.35 (0.615)−0.101**10.10*** (0.316)0.583***
Responsiveness – wave 23.54 (0.527)−0.152***3.33 (0.686)−0.129***11.10*** (0.348)0.557***
Responsiveness – wave 33.52 (0.522)−0.101**3.33 (0.675)−0.092**11.24*** (0.352)0.593***
Responsiveness – wave 43.46 (0.598)−0.128***3.28 (0.695)−0.147***9.02*** (0.282)0.542***
Responsiveness – wave 53.43 (0.596)−0.120***3.25 (0.706)−0.127***9.30*** (0.291)0.539***
Strictness – wave 13.00 (0.374)−0.0062.86 (0.475)−0.00811.39*** (0.357)0.560***
Strictness – wave 22.98 (0.392)0.0372.82 (0.493)0.00411.53*** (0.361)0.488***
Strictness – wave 32.95 (0.391)0.0042.81 (0.501)0.00510.47*** (0.328)0.566***
Strictness – wave 42.87 (0.412)0.0182.71 (0.530)−0.03310.00*** (0.313)0.483***
Strictness – wave 52.86 (0.406)0.0402.71 (0.504)−0.0299.77*** (0.306)0.402***

**P < 0.01, ***P < 0.001.

df = 1,018 for all analyses.

While analyzing the development of parental behavior over time (Table 2, Figs. 23), we found significant between-wave differences in maternal responsiveness (F(4) = 16.0, P < 0.001), with significant Bonferroni post hoc tests between early waves (1–3) and late waves (4–5) (all P < 0.001, Cohen's d between 0.10 and 0.20). A similar pattern was found for paternal responsiveness – scores were higher in early waves (1–3) than in late waves (4–5). Between-wave differences in paternal responsiveness were significant (F(4) = 9.55, P < 0.001), but only some post hoc comparisons were significant (namely, wave 1 versus wave 4–5; wave 5 versus wave 2–3, all P < 0.001, Cohen d's between 0.10 and 0.15). The differences between early and late waves were even more pronounced in the case of strictness. In maternal strictness, the between-wave differences were significant (F(4) = 67.2, P < 0.001), with all post hoc tests significant (all P's < 0.001, Cohen d's between 0.11 and 0.36) except two: wave 1 versus 2 and wave 4 versus 5. In paternal strictness, the differences were also significant (F(4) = 43.2, P < 0.001) with all significant post hoc tests (all P's < 0.001, Cohen d's between 0.12 and 0.30), except wave 2 versus 3 and wave 4 versus 5.

Fig. 2.
Fig. 2.

The between-waves development of maternal and paternal responsiveness. Means and 95% CI are presented for each wave. N = 1,019 for both variables in all waves. Note. In case of maternal responsiveness, Games–Howell post-hoc tests were significant (P < 0.001) for differences between waves 1–4 (Cohen d = 0.10), 1–5 (d = 0.14), 2–4 (d = 0.15), 2–5 (d = 0.20), 3–4 (d = 0.13), 3–5 (d = 0.17). In case of paternal responsiveness, Games-Howell post-hoc tests were significant (P < 0.001) for differences between waves 1–4 (d = 0.10), 1–5 (d = 0.15), 2–5 (d = 0.13), 3–5 (d = 0.13).

Citation: Journal of Behavioral Addictions 9, 3; 10.1556/2006.2020.00068

Fig. 3.
Fig. 3.

The between-waves development of maternal and paternal strictness. Means and 95% CI are presented for each wave. N = 1,019 for both variables in all waves. Note. In case of maternal responsiveness, Games–Howell post-hoc tests were significant (P < 0.001) for differences between waves 1–3 (Cohen d = 0.15), 1–4 (d = 0.35), 1–5 (d = 0.36), 2–3 (d = 0.11), 2–4 (d = 0.31), 2–5 (d = 0.31), 3–4 (d = 0.24), 3–5 (d = 0.24). In case of paternal strictness, Games–Howell post-hoc tests were significant (P < 0.001) for differences between waves 1–3 (d = 0.12), 1–4 (d = 0.29), 1–5 (d = 0.30), 2–4 (d = 0.22), 2–5 (d = 0.21), 3–4 (d = 0.22), 3–5 (d = 0.22).

Citation: Journal of Behavioral Addictions 9, 3; 10.1556/2006.2020.00068

Parenting styles

The parenting styles (as measured in wave 5) were associated with adolescents' gender for both maternal style (χ2(3) = 17.3, P = 0.001, N = 1,002) and paternal style (χ2(3) = 26.2, P < 0.001, N = 1,002). For maternal parenting, boys, compared to girls, reported a higher incidence of neglectful parenting (33.1% versus 26.6% of girls) and a lower incidence of indulgent parenting (16.3% versus 26.8% of girls). Similarly, for paternal parenting, boys reported a lower incidence of indulgent parenting (16.3% versus 27.6% of girls) and a higher incidence of authoritative parenting (29.6% versus 19.5% of girls).

The parenting style of the mother was also affected by the intactness of the family (χ2(6) = 13.5, P = 0.036, N = 1,017). Adolescents from restructured families showed a higher incidence of authoritarian parenting (37.7% versus 22.1% of intact and 17.5% of incomplete families) and a lower incidence of indulgent parenting (16.9% versus 25.6% of intact and 30.0% of incomplete families).

Associations between parental behavior and PIU

As presumed, we found significant negative correlations between PIU score and both maternal and paternal responsiveness in all five waves (Table 2). Surprisingly, we did not find any significant correlations between PIU score and maternal or paternal strictness as measured either in proximate or distant waves (Table 2).

Adolescents with PIU (N = 83) also reported significantly lower scores in maternal responsiveness and paternal responsiveness and significantly higher scores in maternal strictness when compared to adolescents without PIU (N = 936) (Table 3). The difference between adolescents with PIU and without PIU in paternal strictness was not significant.

Table 3.

Means, standard deviations (SDs) and mean differences for parental responsiveness and strictness (wave 5) in adolescents with self-reported PIU and without PIU (wave 7)

VariablePIU (n = 83)without PIU (n = 936)Difference – Welch t (Cohen d)
Mean (SD)Mean (SD)
Maternal responsiveness – wave 53.24 (0.665)3.45 (0.587)2.74** (0.349)
Paternal responsiveness – wave 53.05 (0.723)3.27 (0.702)2.68** (0.315)
Maternal strictness – wave 52.94 (0.394)2.85 (0.406)−2.02* (−0.226)
Paternal strictness – wave 52.64 (0.547)2.72 (0.500)1.17 (0.144)

*P < 0.05, **P < 0.01.

The effect of parenting styles on PIU

We found a significant association between PIU status and both maternal parenting style (χ2(3) = 20.4, P < 0.001, N = 1,019) and paternal parenting style (χ2(3) = 10.6, P = 0.014, N = 1,019). The incidence of PIU was relatively higher in adolescents who reported maternal authoritarian parenting (Table 4) and a paternal neglectful parenting (Table 5). In mothers as well as in fathers, the authoritative parenting style was associated with the lowest incidence of adolescent PIU.

Table 4.

Crosstabulation of parenting style of mother (wave 5) and PIU status (wave 7)

Maternal parenting stylePIU statusTotal
PIU (n = 83)without PIU (n = 936)
AuthoritativeObserved10215225
Expected18.3207
% of PIU4.4
IndulgentObserved15206221
Expected18.0203
% of PIU6.8
AuthoritarianObserved39231270
Expected22.0248
% of PIU14.4
NeglectfulObserved19284303
Expected24.7278
% of PIU6.3

Note. “Observed” shows the observed number of participants with and without PIU in each category of maternal parenting. “Expected” shows the estimated number of participants based on the null hypothesis (i.e., incidence of PIU is not associated with maternal style). “% of PIU” shows the percentage of participants with PIU in each category of maternal parenting.

Table 5.

Crosstabulation of parenting style of father (wave 5) and PIU status (wave 7)

Paternal parenting stylePIU statusTotal
PIU (n=83)without PIU (n=936)
AuthoritativeObserved11240251
Expected20.4231
% of PIU4.4
IndulgentObserved15208223
Expected18.2205
% of PIU6.7
AuthoritarianObserved21215236
Expected19.2217
% of PIU8.9
NeglectfulObserved36273309
Expected25.2284
% of PIU11.7

Note. “Observed” shows the observed number of participants with and without PIU in each category of paternal parenting. “Expected” shows the estimated number of participants based on the null hypothesis (i.e., incidence of PIU is not associated with paternal style). “% of PIU” shows the percentage of participants with PIU in each category of paternal parenting.

The logistic regression assessing the mutual effect of maternal and paternal parenting styles on PIU showed that both predictors significantly affected PIU status, although they explained only a small proportion of the variability in PIU status (4.87%). In both mothers and fathers, the authoritative parenting style (high responsiveness, high strictness) led to the lowest probability of PIU. In contrast, in mothers the authoritarian parenting style and in fathers the neglectful parenting style led to a significantly higher probabilities of developing PIU than the authoritative parenting style (Table 6). The combination of maternal and paternal authoritative styles, which also was quite prevalent (11.7% of adolescents reported this combination) seemed to be protective against PIU with a probability of PIU equal to 3.21%. The most problematic combination – maternal authoritarian parenting combined with paternal neglectful parenting – showed a 20.9% probability of PIU (Table 7, Fig. 4).

Table 6.

Model Coefficients with Maternal parenting style (wave 5) and Paternal parenting style (wave 5) as predictors and PIU (wave 7) as outcome. N = 1,019, Adjusted r2 = 0.0487

PredictorBSE BOdds ratio95% CI
LowerUpper
Maternal parenting style
 Indulgent0.2380.4351.26850.54082.9752
 Authoritarian1.007*0.3932.73741.26715.9140
 Neglectful−0.1290.4380.87900.37252.0744
Paternal parenting style
 Indulgent0.5300.4251.69950.73853.9113
 Authoritarian0.4870.4061.62820.73503.6068
 Neglectful1.067**0.3862.90621.36446.1901

Note. B represents the log odds of “PIU = 1” versus “PIU = 0 (i.e., without PIU)”. CI = confidence interval of Odds ratio. Authoritative parenting style of both mother and father is the reference category.

*P < 0.05, **P < 0.01

Table 7.

Estimated marginal means of PIU probability (wave 7) for maternal and paternal parenting styles (wave 5). N = 1,019

PaternalMaternalProbability (%)SE95% Confidence interval
LowerUpper
AuthoritativeAuthoritative (N = 119)3.210.01210.01520.0666
Indulgent (N = 52)4.040.01600.01840.0864
Authoritarian (N = 51)8.330.02750.04290.1556
Neglectful (N = 29)2.840.01160.01270.0623
IndulgentAuthoritative (N = 53)5.340.02070.02470.1118
Indulgent (N = 114)6.680.01950.03730.1169
Authoritarian (N = 22)13.380.04130.07140.2370
Neglectful (N = 34)4.730.01770.02240.0969
AuthoritarianAuthoritative (N = 36)5.130.02010.02350.1084
Indulgent (N = 16)6.420.02370.03070.1293
Authoritarian (N = 117)12.890.02730.08420.1925
Neglectful (N = 67)4.540.01470.02380.0846
NeglectfulAuthoritative (N = 17)8.800.03220.04210.1750
Indulgent (N = 39)10.910.03370.05840.1947
Authoritarian (N = 80)20.900.03870.14310.2949
Neglectful (N = 173)7.820.01800.04950.1215
Fig. 4.
Fig. 4.

The probability of PIU (wave 7) in groups with various combinations of maternal and paternal parenting styles (wave 5). The probabilities and 95% CI are presented for each group.

Citation: Journal of Behavioral Addictions 9, 3; 10.1556/2006.2020.00068

All variables that were found to be significantly related to PIU or parenting styles (i.e., school grades, adolescent gender, and family intactness) were gradually included in the model to control for their possible interactions with predictors. None of these background variables significantly improved the predictive power of the model and were excluded from the final model.

Discussion

The self-reported prevalence of PIU was 8.1% for the whole sample. Background variables (adolescent's gender, family income, parent's education, family intactness) did not affect PIU status. Adolescents reported higher scores of responsiveness and strictness for mothers than for fathers. Differences were significant and with moderate effect sizes. The perception of responsiveness and strictness constantly decreased as adolescents became older with a remarkable decrease at approximately 13.5 years of age. Most differences in responsiveness between early waves (1–3) and late waves (4–5) were significant but with small effect sizes. In the case of strictness, the differences between early and late waves were significant and had small to moderate effect sizes. Adolescents with PIU symptomatology reported significantly lower maternal and paternal responsiveness and higher maternal strictness when compared to the group without PIU. Effect sizes of differences were moderate in cases of responsiveness (both maternal and paternal) and small in cases of strictness. For both maternal and paternal parenting, the authoritative style (high responsiveness and high strictness) had the lowest PIU prevalence. The subsequent logistic regression assessing the parenting style of both parents together showed that the combination maternal and paternal authoritative parenting styles was linked to the low prevalence of adolescent PIU (3.21%). The highest PIU prevalence was found in children with a combination of maternal authoritarian and paternal neglectful parenting styles (20.9%).

The prevalence of PIU in the Czech Republic could be considered high. In Northern and Western Europe, the 2014 prevalence was approximately 2.6% (Cheng & Li, 2014). The higher prevalence was reported from the Middle East, with estimates of approximately 10.9% (Cheng & Li, 2014). To the best of our knowledge, no recent data have been published that indicate the prevalence of adolescent PIU in the Czech Republic or Central Europe (Kuss et al., 2014), except for data from Hungary, where a few studies on representative samples of adolescents were recently conducted. Demetrovics et al. (2016), when validating the short form of the PIU Questionnaire, identified 14.44% of 16-year-old adolescents as being at risk of PIU. Bányai et al. (2017) estimated 4.5% of adolescents to be at risk of problematic use of social media, and (Pápay et al., 2013) reported 4.6% of adolescents to be at high risk of problematic online gaming (POG) and 13.3% of adolescents to be at low risk of POG. This study is the first to report the prevalence of PIU in a cohort of 15-year-old Czech students (M = 15.3, SD = 0.41). We did not find a significant gender-based difference in the prevalence of PIU, which is usual in European adolescent samples.

The responsiveness (warmth) of mothers and fathers was negatively associated with the PIU score. Maternal and paternal responsiveness scores were significantly lower in adolescents with PIU than in those without PIU. The effect sizes were moderate. This is in line with studies reporting the negative association between IA and parent-child bonding (Bleakley, Ellithorpe, & Romer, 2016; Casaló & Escario, 2019; Dong et al., 2019; Shek, Zhu, & Dou, 2019; Shek, Zhu, & Ma, 2018; Shi, Wang, & Zou, 2017; Siomos et al., 2012; Xiuqin et al., 2010; Xu et al., 2014). Parental strictness (behavioral control), on the other hand, showed no significant associations with PIU score. There was a higher maternal strictness in adolescents with PIU, but the effect was small. This adds even more variability to the pool of rather inconclusive results of previous studies on the effect of parental control on PIU. Parental responsiveness (warmth) seems to be a more consistent predictor of PIU than strictness (control). However, responsiveness and strictness are inseparable aspects of parental behavior. The authoritative parenting style, characterized by high responsiveness and high strictness, was found to be the most protective against PIU, which is in line with results obtained for other adolescent at-risk behaviors (Cablova et al., 2016; Calafat et al., 2014; Montgomery, Fisk, & Craig, 2008). The benefits of an authoritative parenting style were shown consistently for mothers and fathers. In contrast, the least favorable parenting style with respect to PIU was different for maternal and paternal parenting. The highest incidence of PIU was found in mothers with authoritarian parenting and in fathers with neglectful parenting. This may suggest that strictness (if not accompanied by responsiveness) is more harmful in mothers than in fathers.

Some sociodemographic variables were found to influence the incidence of various parenting styles. Boys reported a significantly lower incidence of indulgent maternal and paternal parenting and a higher incidence of paternal authoritative parenting and maternal neglectful parenting. In contrast, girls showed the opposite perception of parenting styles, i.e., a higher incidence of indulgent parenting in both mothers and fathers and lower incidences of maternal neglectful parenting and paternal authoritative parenting. The intactness of the family also had an effect on parenting styles. Children from restructured families reported a higher incidence of maternal authoritarian parenting. We consider this an important finding, as this parenting style was connected with a higher risk of PIU and generally could be considered the most detrimental for children (Hosokawa & Katsura, 2019).

We found that parental responsiveness and strictness significantly decreased during the study period, suggesting that both parental affection and control were perceived to weaken as adolescents became older. Chen, Liu, and Li (2000), who used a same-aged cohort sample of Chinese sixth-graders, also found a significant decrease in control and warmth between 12- and 14-year-olds. As we had five measurement points instead of only two as Chen et al. (2000), we could identify that this considerable decrease in control and warmth occurred during the 7th grade (i.e., in children aged approximately 13.5 years on average).

Methodological considerations

A major strength of this population-based study was the size of the cohort of same-aged children and that we observed children prospectively. We also used reliable measurements of parental strictness (control) and responsiveness (warmth), which are widely used in other adolescent behaviors but less often in studies on PIU. Using the parent–child dyads meant higher reliability in some sociodemographic variables, e.g., family income. On the other hand, including only children whose parents were willing to participate in the study might limit the generalization of our findings to caring and responsible families. Our data came from a large-scope project that aimed to evaluate the effect of primary prevention programs focused primarily on substance use, not PIU. Therefore, PIU was not assessed within the same waves as parental behavior but instead was assessed 1.5–3.5 years later. Therefore, we measured the longitudinal effect of parenting on PIU. However, this might be seen as an advantage because longitudinal studies on the topic are scarce. On the other hand, it could be a complication for direct comparison with cross-sectional studies. Furthermore, we did not assess the possible influence of the adolescents themselves on their parents' behavior, although it is probable that the relationship was bidirectional (Kerr, Stattin, & Özdemir, 2012). Finally, we were using the term “PIU prevalence” but were aware that PIU was assessed by a self-report screening measure and not clinically diagnosed, which might lead to overestimation of the prevalence (Maráz, Király, & Demetrovics, 2015).

Implications

The self-reported prevalence of PIU was found to be high, which is alarming given the lack of prevention interventions focused on adolescent PIU (Vondráčková & Gabrhelík, 2016). Parents can significantly influence internet use-related problems in their children. Authoritative style with high responsiveness and high strictness was found to be the most protective against PIU. In contrast, the combination of maternal authoritarian and paternal neglectful styles can be considered a high-risk parenting practice, with the probability of PIU reaching 20.9%. Parents should be involved in prevention efforts and should be informed and educated by professionals about the most effective parenting styles. Special attention should also be paid to restructured families with a higher incidence of detrimental maternal authoritarian style.

Conclusions

The effects of parenting on PIU were found to be similar to those of other adolescent problematic behaviors, such as the use of alcohol, tobacco and other drugs. High parental responsiveness (warmth) seems to exert a protective effect against such behavior. The most beneficial parenting style was the authoritative parenting, which includes high responsiveness and high strictness. In contrast, the parenting styles with the highest risk of PIU were maternal authoritarian parenting and paternal neglectful parenting.

Funding sources

This study was supported by the Czech Science Foundation (Grant no. 16-15771S) and the institutional support programme of Charles University in Prague No. PROGRES-Q06.

Authors' contribution

KL had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: RG, KL, JV. Acquisition, analysis, or interpretation of data: KL, JV. Drafting of the manuscript: KL, RG. Critical revision of the manuscript for important intellectual content: RG, KL, JV. Statistical analysis: KL, JV. Obtained funding: RG. Administrative, technical, or material support: RG. Supervision: RG.

Conflict of interest

The author declares no conflict of interest.

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    • Search Google Scholar
    • Export Citation
  • Bleakley, A., Ellithorpe, M., & Romer, D. (2016). The role of parents in problematic internet use among US adolescents, Media and Communication, 2434. https://doi.org/10.17645/mac.v4i3.523.

    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
  • Calafat, A., García, F., Juan, M., Becoña, E., & Fernández-Hermida, J. R. (2014). Which parenting style is more protective against adolescent substance use? Evidence within the European context. Drug and Alcohol Dependence, 138, 185192. https://doi.org/10.1016/j.drugalcdep.2014.02.705.

    • Search Google Scholar
    • Export Citation
  • Casaló, L. V., & Escario, J.-J. (2019). Predictors of excessive internet use among adolescents in Spain: The relevance of the relationship between parents and their children. Computers in Human Behavior, 92, 344351. https://doi.org/10.1016/j.chb.2018.11.042.

    • Search Google Scholar
    • Export Citation
  • Cetinkaya, L. (2019). The relationship between perceived parental control and internet addiction: A cross-sectional study among adolescents. Contemporary Educational Technology, 10(1), 5574. https://doi.org/10.30935/cet.512531.

    • Search Google Scholar
    • Export Citation
  • Chen, X., Liu, M., & Li, D. (2000). Parental warmth, control, and indulgence and their relations to adjustment in Chinese children: A longitudinal study. Journal of Family Psychology, 14(3), 401419. https://doi.org/10.1037/0893-3200.14.3.401.

    • Search Google Scholar
    • Export Citation
  • Cheng, C., & Li, A. Y. (2014). Internet addiction prevalence and quality of (real) life: A meta-analysis of 31 nations across seven world regions. Cyberpsychology, Behavior, and Social Networking, 17(12), 755760. https://doi.org/10.1089/cyber.2014.0317.

    • Search Google Scholar
    • Export Citation
  • Demetrovics, Z., Király, O., Koronczai, B., Griffiths, M. D., Nagygyörgy, K., Elekes, Z., et al. (2016). Psychometric properties of the problematic internet use questionnaire short-form (PIUQ-SF-6) in a nationally representative sample of adolescents. PLoS One, 11(8), e0159409. https://doi.org/10.1371/journal.pone.0159409.

    • Search Google Scholar
    • Export Citation
  • Dong, B., Zhao, F., Wu, X.-S., Wang, W.-J., Li, Y.-F., Zhang, Z.-H., et al. (2019). Social anxiety may modify the relationship between internet addiction and its determining factors in Chinese adolescents. International Journal of Mental Health and Addiction, 17(6), 15081520. https://doi.org/10.1007/s11469-018-9912-x.

    • Search Google Scholar
    • Export Citation
  • Fineberg, N., Demetrovics, Z., Stein, D., Ioannidis, K., Potenza, M., Grünblatt, E., et al. (2018). Manifesto for a European research network into problematic usage of the internet. European Neuropsychopharmacology, 28(11), 12321246. https://doi.org/10.1016/j.euroneuro.2018.08.004.

    • Search Google Scholar
    • Export Citation
  • Gabrhelík, R., Orosová, O., Miovský, M., Vonkova, H., Berništerová, M., & Minařík, J. (2014). Studying the effectiveness of school-based universal prevention interventions in the Czech Republic and Slovakia. Adiktologie, 14(4), 402408.

    • Search Google Scholar
    • Export Citation
  • Honaker, J., King, G., & Blackwell, M. (2011). Amelia II: A program for missing data. Journal of Statistical Software, 45(1), 147. https://doi.org/10.18637/jss.v045.i07.

    • Search Google Scholar
    • Export Citation
  • Hosokawa, R., & Katsura, T. (2019). Role of parenting style in children’s behavioral problems through the transition from preschool to elementary school according to gender in Japan. International Journal of Environmental Research and Public Health, 16(1), 21. https://doi.org/10.3390/ijerph16010021.

    • Search Google Scholar
    • Export Citation
  • Kerr, M., Stattin, H., & Özdemir, M. (2012). Perceived parenting style and adolescent adjustment: Revisiting directions of effects and the role of parental knowledge. Developmental Psychology, 48(6), 15401553. https://doi.org/10.1037/a0027720.

    • Search Google Scholar
    • Export Citation
  • Khaleque, A., & Rohner, R. P. (2012). Pancultural associations between perceived parental acceptance and psychological adjustment of children and adults: A meta-analytic review of worldwide research. Journal of Cross-Cultural Psychology, 43(5), 784800. https://doi.org/10.1177/0022022111406120.

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Dr. Zsolt Demetrovics
Institute of Psychology, ELTE Eötvös Loránd University
Address: Izabella u. 46. H-1064 Budapest, Hungary
Phone: +36-1-461-2681
E-mail: jba@ppk.elte.hu

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2020  
Total Cites 4024
WoS
Journal
Impact Factor
6,756
Rank by Psychiatry (SSCI) 12/143 (Q1)
Impact Factor Psychiatry 19/156 (Q1)
Impact Factor 6,052
without
Journal Self Cites
5 Year 8,735
Impact Factor
Journal  1,48
Citation Indicator  
Rank by Journal  Psychiatry 24/250 (Q1)
Citation Indicator   
Citable 86
Items
Total 74
Articles
Total 12
Reviews
Scimago 47
H-index
Scimago 2,265
Journal Rank
Scimago Clinical Psychology Q1
Quartile Score Psychiatry and Mental Health Q1
  Medicine (miscellaneous) Q1
Scopus 3593/367=9,8
Scite Score  
Scopus Clinical Psychology 7/283 (Q1)
Scite Score Rank Psychiatry and Mental Health 22/502 (Q1)
Scopus 2,026
SNIP  
Days from  38
sumbission  
to 1st decision  
Days from  37
acceptance  
to publication  
Acceptance 31%
Rate  

2019  
Total Cites
WoS
2 184
Impact Factor 5,143
Impact Factor
without
Journal Self Cites
4,346
5 Year
Impact Factor
5,758
Immediacy
Index
0,587
Citable
Items
75
Total
Articles
67
Total
Reviews
8
Cited
Half-Life
3,3
Citing
Half-Life
6,8
Eigenfactor
Score
0,00597
Article Influence
Score
1,447
% Articles
in
Citable Items
89,33
Normalized
Eigenfactor
0,7294
Average
IF
Percentile
87,923
Scimago
H-index
37
Scimago
Journal Rank
1,767
Scopus
Scite Score
2540/376=6,8
Scopus
Scite Score Rank
Cllinical Psychology 16/275 (Q1)
Medicine (miscellenous) 31/219 (Q1)
Psychiatry and Mental Health 47/506 (Q1)
Scopus
SNIP
1,441
Acceptance
Rate
32%

 

Journal of Behavioral Addictions
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge 850 EUR/article
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
Purchase per Title  

Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
Publication
Programme
2021 Volume 10
Volumes
per Year
1
Issues
per Year
4
Founder Eötvös Loránd Tudományegyetem
Founder's
Address
H-1053 Budapest, Hungary Egyetem tér 1-3.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2062-5871 (Print)
ISSN 2063-5303 (Online)

Senior editors

Editor(s)-in-Chief: Zsolt DEMETROVICS

Assistant Editor(s): Csilla ÁGOSTON

Associate Editors

  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • Daniel KING (Flinders University, Australia)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • H. N. Alexander LOGEMANN (ELTE Eötvös Loránd University, Hungary)
  • Anikó MARÁZ (Humboldt University of Berlin, Germany)
  • Astrid MÜLLER (Hannover Medical School, Germany)
  • Marc N. POTENZA (Yale University, USA)
  • Hans-Jurgen RUMPF (University of Lübeck, Germany)
  • Attila SZABÓ (ELTE Eötvös Loránd University, Hungary)
  • Róbert URBÁN (ELTE Eötvös Loránd University, Hungary)
  • Aviv M. WEINSTEIN (Ariel University, Israel)

Editorial Board

  • Max W. ABBOTT (Auckland University of Technology, New Zealand)
  • Elias N. ABOUJAOUDE (Stanford University School of Medicine, USA)
  • Hojjat ADELI (Ohio State University, USA)
  • Alex BALDACCHINO (University of Dundee, United Kingdom)
  • Alex BLASZCZYNSKI (University of Sidney, Australia)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • Beáta BÖTHE (University of Montreal, Canada)
  • Wim VAN DEN BRINK (University of Amsterdam, The Netherlands)
  • Gerhard BÜHRINGER (Technische Universität Dresden, Germany)
  • Sam-Wook CHOI (Eulji University, Republic of Korea)
  • Damiaan DENYS (University of Amsterdam, The Netherlands)
  • Jeffrey L. DEREVENSKY (McGill University, Canada)
  • Naomi FINEBERG (University of Hertfordshire, United Kingdom)
  • Marie GRALL-BRONNEC (University Hospital of Nantes, France)
  • Jon E. GRANT (University of Minnesota, USA)
  • Mark GRIFFITHS (Nottingham Trent University, United Kingdom)
  • Heather HAUSENBLAS (Jacksonville University, USA)
  • Tobias HAYER (University of Bremen, Germany)
  • Susumu HIGUCHI (National Hospital Organization Kurihama Medical and Addiction Center, Japan)
  • David HODGINS (University of Calgary, Canada)
  • Eric HOLLANDER (Albert Einstein College of Medicine, USA)
  • Jaeseung JEONG (Korea Advanced Institute of Science and Technology, Republic of Korea)
  • Yasser KHAZAAL (Geneva University Hospital, Switzerland)
  • Orsolya KIRÁLY (Eötvös Loránd University, Hungary)
  • Emmanuel KUNTSCHE (La Trobe University, Australia)
  • Hae Kook LEE (The Catholic University of Korea, Republic of Korea)
  • Michel LEJOXEUX (Paris University, France)
  • Anikó MARÁZ (Eötvös Loránd University, Hungary)
  • Giovanni MARTINOTTI (‘Gabriele d’Annunzio’ University of Chieti-Pescara, Italy)
  • Frederick GERARD MOELLER (University of Texas, USA)
  • Daniel Thor OLASON (University of Iceland, Iceland)
  • Nancy PETRY (University of Connecticut, USA)
  • Bettina PIKÓ (University of Szeged, Hungary)
  • Afarin RAHIMI-MOVAGHAR (Teheran University of Medical Sciences, Iran)
  • József RÁCZ (Hungarian Academy of Sciences, Hungary)
  • Rory C. REID (University of California Los Angeles, USA)
  • Marcantanio M. SPADA (London South Bank University, United Kingdom)
  • Daniel SPRITZER (Study Group on Technological Addictions, Brazil)
  • Dan J. STEIN (University of Cape Town, South Africa)
  • Sherry H. STEWART (Dalhousie University, Canada)
  • Attila SZABÓ (Eötvös Loránd University, Hungary)
  • Ferenc TÚRY (Semmelweis University, Hungary)
  • Alfred UHL (Austrian Federal Health Institute, Austria)
  • Johan VANDERLINDEN (University Psychiatric Center K.U.Leuven, Belgium)
  • Alexander E. VOISKOUNSKY (Moscow State University, Russia)
  • Kimberly YOUNG (Center for Internet Addiction, USA)

 

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