Why Do Parenting Styles Matter? The Relation Between Parenting Styles,Cyberbullying,and Problematic Internet Use Among Children With and Without SLD/ADHD

Abstract

This study focuses on the pervasive issues of cyberbullying and problematic internet use (PIU) among youth, particularly in children with disabilities. To elucidate the role of parents in mitigating these challenges, the study examines the prevalence of three parenting styles (permissive/authoritarian/authoritative), and their correlation with cyberbullying and PIU among children with or without specific learning disorder (SLD) or attention-deficit/hyperactivity disorders (ADHD). The study consisted of 300 Israeli participants: 150 children—9 to 12 years old, matched with their 150 parents, divided into two groups—SLD/ADHD and those with typical development. Comparative analysis revealed that the SLD/ADHD group scored higher in the authoritarian style compared with the typical-development group. Furthermore, authoritative parenting style correlated with lower incidences of cyberbullying and PIU, and foster a more positive parent–child relationship, which in turn contributed to reduced cyberbullying and PIU. These findings underscore the importance of adopting an authoritative parenting style among parents, particularly among parents of children with SLD/ADHD.

Keywords

parenting styles cyberbullying PIU SLD learning disability ADHD

Parents play a key role in imparting knowledge about safe internet practices to their children (Feijo et al., 2021). Given the established link between parenting styles and their effect on cyberbullying (Legate et al., 2018) and problematic internet use (PIU) (Nielsen et al., 2020), there is a pressing need to delve deeper into this relationship, especially among younger age groups. This study examined the effects of parenting styles on cyberbullying and PIU among children, with or without specific learning disability (SLD) or attention-deficit/hyperactivity disorder (ADHD), since these populations are characterized by challenges in both social and academic functioning, as well as tendencies toward impulsive, aggressive, and anti-social behavior (Aro et al., 2019; Pineda-Alhucema et al., 2018; Tarawneh, 2017). To our knowledge, this study represents the first attempt to examine the interplay between parenting styles, PIU, and cyberbullying among children with SLD/ADHD and compare them to their counterparts with typical-development (TD).

Relevant to this issue is Belsky’s theory of differential susceptibility (Belsky et al., 2007, 2022), which stipulates that some children are more susceptible than others to both positive and negative impacts of developmental experiences, such as supportive or harsh parenting, and environmental factors, like living in a dangerous neighborhood (Ellis et al., 2011). This theory is examined in this study.

Cyberbullying and PIU

Nowadays, children and adolescents are increasingly exposed to cyberbullying, a phenomenon characterized by bullying utilizing various technologies and distinguished by features such as anonymity, distant and rapid communication, an indefinite number of bystanders, and easily accessible audiences (Marczak & Coyne, 2015). Studies indicate a rising prevalence of cyberbullying among children and adolescents, with perpetration rates documented at 25.03% and victimization rates at 33.08% (Zhu et al., 2021). In Israel, the setting of this study, 14.4% of adolescents reported experiencing victimization, 12.6% admitted to perpetrating cyberbullying, and 35% acknowledged their role as bystanders (Heiman et al., 2015).

These findings are concerning given the profoundly negative impact on both cyber-victims and cyber-perpetrators, potentially resulting in a myriad of internalized and externalized problems including depression, anxiety, suicidal ideation and attempts, sleep disorders and mental health issues (Quintana-Orts et al., 2020). Thus, early identification and intervention for cyberbullying is imperative. Notably, 46.4% of children and adolescents, nearly half of whom were elementary school students as young as 9 years old, have reported experiences as cyber-bystanders (Olenik-Shemesh et al., 2017).

Beyond cyberbullying, PIU poses significant risks, characterized by the inability to control one’s internet usage, resulting in adverse outcomes include (Spada, 2014). PIU adverse outcomes uncontrolled, distressing, and time-consuming behavior. Prevalence rates of PIU among European Internet users range from 14% to 55% (Laconi & Kuss, 2018).

The literature underscores children’s extensive engagement with social media platforms (Eden et al., 2023; Yıldız-Durak, 2018). Moreover, children lacking essential e-literacy skills are more susceptible to online risks. In addition, characteristics such as hypersensitivity, social naivety, and a tendency for obsessive behavior, common among children with SLD or ADHD, render them particularly vulnerable to online risks (Barringer-Brown, 2015; Olenik-Shemesh et al., 2012).

Cyberbullying and PIU Among Children With SLD/ADHD

Specific learning disorder and ADHD are high-comorbid, prevalent neurodevelopmental disorders frequently observed among students in educational systems globally, with SLD affecting approximately 5% to 15% (characterized by difficulties in reading, writing, arithmetic or mathematic), and ADHD impacting 3.5% to 5% (marked by persistent lack of attention, impulsivity, and hyperactivity). Although these disorders do not inherently cause one another, research suggests a substantial comorbidity rate—with an estimated 30% to 50% of children diagnosed with ADHD also exhibiting symptoms of SLD (American Psychiatric Association [APA], 2022). Both disabilities often contribute to diminished academic performance (Arnold et al., 2020), and are frequently accompanied by social-emotional and behavioral challenges (Pineda-Alhucema et al., 2019; Tarawneh, 2017), including an increased risk of experiencing externalized and internalized problems, feelings of loneliness and diminished self-esteem (Aro et al., 2019). Therefore, considering the association between SLD and ADHD with social, emotional, and behavioral issues, it was hypothesized that cyberbullying would be more prevalent among this population compared with TD children.

Indeed, individuals with disabilities are known to be more vulnerable to cyberbullying. For instance, cyberbullying victimization is more pronounced among children with SLD compared with their TD counterparts (Barringer-Brown, 2015). Similarly, adolescents with ADHD report higher incidences of cyber-victimization, perpetration and bystander experiences in comparison to TD peers (Heiman et al., 2015). In addition, literature suggests that PIU, another important variable in this study, is more prevalent among adolescents with SLD/ADHD than those with TD. Children with ADHD exhibit heightened internet and Facebook addiction (Gul et al., 2017), and demonstrate more frequent instances of PIU (Hulya-Cakmak & Gul, 2018).

Parenting Styles and Internet Use

Due to the immediate accessibility of the internet and continuous emergence of new media formats, parents often encounter challenges in monitoring the content and individuals their children encounter online (Symons et al., 2017). Parenting encompasses various components that influence or are related to children’s internet usage. This study focused on one such crucial component in children’s development—parenting styles. Initially categorized by Baumrind (1971), parenting styles have undergone refinement and elaboration in literature over time (e.g. Hutchison et al., 2016): (a) Permissive parenting— Parents tend to accommodate all their children’s requests and grant them with excessive autonomy with minimal supervision. They establish few boundaries, impose limited expectations, and offer unconditional support, acceptance and involvement (b) Authoritarian parenting— Involves imposing high demands on children, enforcing strict rules, supervision, and expecting complete obedience. Parents often resort to punishment with minimal support, involvement period and acceptance. (c) Authoritative parenting—Setting clear boundaries, rules, and expectations, while also prioritizing explanation, acceptance, support, and attentive listening. In addition to those three primary styles, Maccoby and Martin (1983) introduced the concept “neglectful parenting style,” where parents exhibit indifference, detachment, and nonpromoting. They demand nothing from their children, fail to respond to their needs, and provide limited emotional support or assistance while also being low on both supervision and involvement.

Parents of children with ADHD often tend to adopt more permissive or authoritarian parenting styles, possibly stemming from the heightened stress they experience compared with parents of TD children (Hutchison et al., 2016; Teymouri, 2019). Conversely, parents of TD children exhibit a greater inclination toward authoritative parenting, contrasting with parents of children with ADHD (Teymouri, 2019). Similar findings emerge concerning children with SLD, where the authoritative style demonstrates greater engagement and supportiveness compared with the permissive and authoritarian styles (Rupesh et al., 2020).

Several previous studies have explored the relationship between parenting styles and cyberbullying among children, revealing that permissive and authoritarian parenting styles are associated with heightened susceptibility to cyberbullying compared with the authoritative style (Broll & Reynolds, 2020; Moreno–Ruiz et al., 2019). For example, Martinez et al. (2019) discovered that authoritarian parenting serves as a risk factor for both traditional bullying and cyberbullying victimization, as well as internet addiction (Serna et al., 2023). Conversely, they also observed that indulgent parenting can serve as a protective factor. However, authoritative parents, linked with increased vulnerability, possess the ability to respect others and cultivate a healthy parent–child relationship (Charalampous et al., 2018). Parental influence extends to PIU, with authoritarian and permissive parenting style correlating with elevated PIU prevalence, whereas the authoritative style is linked to lower prevalence rates among adolescents (Lakavska et al., 2020; Yaffe & Seroussi, 2019). Good parenting practices in the digital age often align with the authoritative parenting style, as summarized by Yusuf et al. (2020).

Furthermore, the parent–child relationship, another facet associated with parenting styles, may influence cyberbullying and PIU. Positive parent–child interaction fosters healthy self-perception, reducing internet addiction problems, while strained relationships may exacerbate PIU (Huang et al., 2019). It seems that stressful environments, such as experiencing bullying or cyberbullying and poor parental relationships, can directly and indirectly contribute to PIU among children. Inadequate communication between parents and children heightens the risk of PIU (Boniel-Nissima & Sasson, 2018). Moreover, parental mediation serves as a protective factor against cyberbullying, contrasting with avoidant parenting, which exacerbates its occurrence (Triantoro & Hadi, 2020).

Parent–child interactions are considered central to the various family factors affecting children with ADHD. These interactions, due to their close and immediate influence on the child, have the potential to serve as significant protective or risk factors (Johnston & Chronis-Tuscano, 2015). Al-Yagon et al. (2020) for example, found differences in attachment patterns in Israeli families between children with ADHD and TD children. However, the association between the parent–child relationship, as well as parenting style, cyberbullying and PIU among this population has not yet been examined.

Rationale and Study Questions

Parenting style serves as a pivotal factor in children’s development, particularly those with special needs. While existing research studies have explored the relationship between parenting styles and children’s online behaviors, especially concerning negative phenomena such as cyberbullying and PIU (e.g. Broll & Reynolds, 2020; Lakavska et al., 2020; Nielsen et al., 2020), little attention has been directed specifically toward the special needs’ population concerning each variable (parenting styles, cyberbullying, and PIU) individually, especially at such a young age. This gap is notable given that children with SLD/ADHD are more susceptible to cyberbullying and PIU compared with TD children, due to social and academic challenges and impulsive behavior (Tarawneh, 2017). A possible theoretical framework to address is Belsky et al.’s (2007, 2022) theory of differential susceptibility, which posits that certain individuals exhibit greater susceptibility than others to both positive and negative effects of supportive or adverse developmental experiences (e.g., harsh parenting) and environmental exposures. Thus, we propose that children with SLD/ADHD are more vulnerable to negative parenting practices and are more likely to engage in cyberbullying and PIU compared with TD children. Contrary to prior research, this study also aimed to examine the impact of parenting styles on younger children’s internet exposure, alongside examining its association with TD children.

Consequently, this study is the first to examine, as far as we know, the interaction between parenting styles, cyberbullying, and PIU, while comparing TD children to those with SLD/ADHD. Moreover, we aimed to examine the moderating effect of SLD/ADHD status on the associations between these relationships.

Corresponding with these aims, the study addressed four major questions:

Research Question 1 (RQ1): Is there a difference in the association between parenting styles and parent–child relationship when comparing the two study groups?

Research Question 2 (RQ2): Is there a difference in the association between parenting styles and parent–child relationship quality and PIU and cyberbullying when comparing the two study groups?

Research Question 3 (RQ3): Do parental and children’s background characteristics contribute to explaining children’s PIU and cyberbullying? And do parenting styles, parent–child relationships, and information and communications technology (ICT) frequency and skills provide unique contributions to explaining children’s PIU and cyberbullying beyond these background characteristics?

Research Question 4 (RQ4): Does the subject group act as a moderator variable in the association between parenting style and children’s cyberbullying?

We also examined the relationship between parenting styles and parent–child relationships, and differences between the study’s group in their parenting style, parent–child relationships, cyberbullying and level of PIU.

Method

Sample

The study comprised of 300 participants, including 150 children with and without SLD/ADHD and their parents, who were recruited from 25 schools situated in the central region of Israel. The parent sample consisted of 18 males and 132 females between the ages of 28 and 58 years (M = 41.35, SD = 4.62). The children’s sample included 90 boys and 60 girls between 9 and 12 years of age (M = 10.64, SD = 1.10). Among them, 79 children were TD, while 71 recently received formal diagnoses of disabilities (46 ADHD, 12 SLD, 13 both SLD and ADHD). In alignment with the policy of the Israeli Ministry of Education, ADHD diagnoses were conducted based on Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; APA, 2013) criteria. As Al-Yagon et al. (2020) observes, this process involved psychiatric and/or neurological evaluations (clinical interviews, computerized tests, and measures of ADHD symptom severity). Similarly, diagnoses of SLD were also made following DSM-5 criteria and involved psychiatric and/or neurological evaluations.

The demographic and ICT background characteristics of the parents and children are summarized in Table 1.

Table 1.

Parents’ and Children’s Demographic Characteristics and ICT Background According to Subject Group.

Variables	Values	Total sample (N = 150)	TD (n = 79)	SLD/ADHD (n = 71)	χ ²	p
Parents’ demographic characteristics
Gender	Male	18 (12.0%)	8 (10.1%)	10 (14.1%)
	Female	132 (88.0%)	71 (89.9%)	61 (85.9%)	.55	.456
Education level^a	High School	38 (25.3%)	16 (20.3%)	22 (31.0%)
	Bachelor’s degree	82 (54.7%)	46 (58.2%)	36 (50.7%)
	Master’s or PhD degree	30 (20.0%)	17 (21.5%)	13 (18.3%)	2496.50	.198
Marital status	Married	129 (86.0%)	70 (88.6%)	59 (83.1%)
	Not married/single	21 (14.0%)	9 (11.4%)	12 (16.9%)	.94	.332
Age^b	Parents’ age, M (SD)	41.35 (4.62)	40.75 (4.82)	42.03 (4.33)	1.70	.090
Children^b	Number of children, M (SD)	3.06 (0.95)	3.08 (0.97)	3.04 (0.93)	.22	.829
Children’s demographic characteristics
Gender	Boys	90 (60.0%)	39 (49.4%)	51 (71.8%)
	Girls	60 (40.0%)	40 (50.6%)	20 (28.2%)	7.86**	.005
Grade^a	Fourth grade (9–9:11 years old)	56 (37.3%)	28 (35.4%)	28 (39.4%)
	Fifth grade (10–10:11 years old)	41 (27.3%)	18 (22.8%)	23 (32.4%)
	Sixth grade (11–12 years old)	53 (35.3%)	33 (41.8%)	20 (28.2%)	2493.00	.212
Class type	Mainstream class	126 (84.0%)	79 (100.0%)	47 (66.2%)
	Special education class	12 (8.0%)	0 (0.0%)	12 (16.9%)
	Special education school	12 (8.0%)	0 (0.0%)	12 (16.9%)	31.79***	.001
Age^b	Children’s age, M (SD)	10.64 (1.10)	10.58 (1.17)	10.70 (1.02)	.68	.497
ICT background characteristics
Cell phone	No	25 (16.7%)	14 (17.7%)	11 (15.5%)
	Yes	125 (83.3%)	65 (82.3%)	60 (84.5%)	.13	.715
Computer/tablet/iPad	No	14 (9.3%)	10 (12.7%)	4 (5.6%)
	Yes, at home	72 (48.0%)	37 (46.8%)	35 (49.3%)
	Yes, personal	64 (42.7%)	32 (40.5%)	32 (45.1%)	2.21	.332
ICT skills	Unskilled, needs help	17 (11.3%)	6 (7.6%)	11 (15.5%)
	Skilled	133 (88.7%)	73 (92.4%)	60 (84.5%)	2.32	.128
Filtering software	Does not know	29 (19.3%)	16 (20.3%)	13 (18.3%)
	No	57 (38.0%)	32 (40.5%)	25 (35.2%)
	Yes	64 (42.7%)	31 (39.2%)	33 (46.5%)	.81	.668

Note. ICT = information and communications technology; TD = typically developing group; SLD = specific learning disability.

Mann-Whitney analyses were conducted since the variables are in an ordinal scale. ^bt-test for two independent samples were conducted since the variables are in a ratio scale.

*p < .01. ***p < .001.

As depicted in Table 1, there were no significant differences observed in demographic background characteristics between the parents of the SLD/ADHD group and those of the TD group. Furthermore, the parental sample showed no disparities in age and number of children in the family, t(148) = 1.70, p = .090 and t(148) = .22, p = .829, respectively. Similarly, there were no significant differences in the early adolescent sample, t(148) = .68, p = .497. However, notable distinctions were evident between the groups of TD children and those with SLD/ADHD in gender and school type distributions. As expected, the proportion of boys was notably higher among the SLD/ADHD group, and a lower percentage of children with SLD/ADHD attended mainstream classes compared with the TD group (71.8% compared with 49.4% and 66.2% compared with 100.0%, respectively). The children from both groups exhibited no significant differences in age t(148) = .68, p = .497.

Instrument

The study included six questionnaires for the children and three for the parents:

Demographic questionnaire (parents; children)—Gender, age, education, developmental problems, and so on.

ICT frequency and skills questionnaire (children)—ICT frequency of use –Children were asked to evaluate their online usage time on various platforms using a 29 item 6-point Likert scale: never (1), occasionally- a little and not every day (2), about an hour every day (3), 2–4 hours every day (4), 5–7 hours every day (5), 8 hours or more each day (6). The internal consistency of Cronbach’s α was .92. ICT skills (part of the online survey of adolescents in the EU; Livingstone et al., 2011)—Children were asked to evaluate their level of social network skills using a 17-item 5-point Likert scale ranging from never (1) to very much (5). The internal consistency of Cronbach’s α was .93.

Social Media Use Questionnaire (SMUQ; Xanidis & Brignell, 2016) (children)—Assesses problematic and excessive use of social media, and comprises of nine items covering network usage, web browsing frequency, computer control skills assessment, and student engagement. Children were asked to indicate their level of agreement with each statement using a 5-point Likert scale from do not agree at all (1) to strongly agree (5). The internal consistency of Cronbach’s α was .89.

Cyberbullying Questionnaire (Smith et al., 2008, translated and validated by Eden et al., 2016) (children) –The questionnaire consisted of 8 items focusing on individual experiences as victims, perpetrators or bystanders of cyberbullying across various online platforms such as email, social media, chat rooms, instant messaging software, blogs, and videos. Participants were asked to assess the frequency of bullying occurrences across these different social platforms on a 5-point Likert scale from never (1) to 10 times per month (5). The internal consistency of Cronbach’s α was .84.

The Network of Relationship Inventory (NRI RQV; Furman & Buhrmester, 1985) (parents; children)—Children/parents report regarding their relationship with their parents/children, through 9-items that represent the total score of positive qualities of relationships (intimate disclosure, emotional support, and satisfaction). All items are evaluated on a 5-point Likert scale from not at all (1) to very (5). The items are summed up into a single measure that represents the quality of the relationship. The internal consistency of Cronbach’s α was .93.

Parental Authority Questionnaire (Buri, 1991) (parents; children)—Comprised of 30 items designed to categorize parents into one of the three parenting styles: authoritarian, authoritative, or permissive (10 items for each parenting style). An adapted version of this questionnaire was employed for children. Responses were rated on a 5-point Likert scale ranging from do not agree at all (1) to strongly agree (5). The overall score for each scale ranged from 10 to 50, with a high score expressing a high characterization of that style. The internal consistency of Cronbach’s α was .83 (authoritarian), .82 (authoritative), and .63 (permissive).

Procedure

A comprehensive request, mindful of the participants’ vulnerability and methodological intricacies, was submitted to the University Research Ethics Board and the Chief Scientist of the Ministry of Education. Upon obtaining their approval and parental consent, online questionnaires were distributed to both parents and children. Each of the children and their corresponding parent were assigned identical participant numbers to facilitate matching and comparison. The questionnaires were administered confidentially, with each participant responding privately. The response rate was notably high: 80%.

Data Analysis Plan

The sample size was determined a priori using the G*power software. For the analysis of variance (ANOVA) with repeated measures (within-between factors) analyses and considering the test parameters (low effect size = 0.15, α error = 0.05, power = 0.90, and moderate correlation among repeated measures = 0.40), the total sample size required was 114 participants. In addition, for hierarchical regression encompassing 12 parents and children’s demographic characteristics, ICT (Information and Communication Technologies) background and 10 additional tested predictors, in conjunction with measures of three parent’s parenting styles, three children’s parenting styles, parent–child relationships as assessed by the parents and children, and children’s ICT frequency and skills (total number of predictors = 22), analyses and the test parameters (low effect size = 0.15, α error = 0.05, power = 0.90), and total sample size required was 148 participants.

Prior examining the study questions and hypotheses, Shapiro-Wilk tests were conducted to assess the normal distribution of the dependent variables, including the parent’s and children’s background characteristics, parenting styles, parent–child relationships, the children’s ICT frequency and skills, children’s PIU level, and children’s exposure to cyberbullying. Given significant deviations from normal distribution (p < .05), both parametric and nonparametric tests were conducted to address the research questions (Friedman and Mann-Whitney). The findings and the significance level from both analyses corresponded, leading to the presentation of findings from ANOVA analyses along with mean and SD values.

It is important to note that prior to conducting the statistical analyses required to examine the research questions and hypotheses, we initially examined whether significant differences existed among the 71 participants of the SLD/ADHD group, comprising of 12 participants with SLD, 46 participants with ADHD, and 13 participants with both SLD and ADHD. The ANOVA analyses indicated no significant differences between these groups (F-values between .09 and 1.48 and p-values between .249 and .976). Therefore, we proceeded to explore the research questions and hypotheses by comparing the 71 pairs of parents and children from the SLD/ADHD group with the 79 pairs of parents and children from the TD group.

Also, before examining the first study question regarding the association between parenting styles and parent–child relationship quality among the two study groups, we examined the differences between TD and SLD/ADHD children regarding parenting styles, using a three-way (2 × 2 × 3) mixed ANOVA analysis. The subject group (TD, SLD/ADHD) was designated as the between-subject factor, while the respondent (parents, children) and style (authoritarian, authoritative, permissive) were the within-subject factors. In addition, to examine the differences in parent–child relationships, a factor associated with parenting styles, between TD and SLD/ADHD children, a two-way (2 × 2) mixed ANOVA analysis was conducted. The subject group served as the between-subject factor, while the respondent (parents, children) served as the within-subject factor. After examining the differences, to examine the correlations between parenting styles and parent–child relationships, Pearson correlation analyses were conducted for each study group and each respondent. Fisher r-to-z transformation analyses were conducted to compare correlation coefficients between the two study groups.

Prior to examining the second study question regarding the association between parenting styles and parent–child relationship quality and PIU and cyberbullying among the two study groups, we examined the differences between TD and SLD/ADHD children regarding ICT frequency and skills, cyberbullying, and PIU between the two groups, using one-way ANOVAs. To examine the correlations between parenting styles, the parent–child relationship (as perceived by the children), and the children’s cyberbullying and PIU, Pearson correlation analyses were conducted for each subject group. Fisher r-to-z transformation analyses were conducted to compare correlation coefficients between the two study groups.

To address the third research question regarding the parental and children’s background characteristics contribution to explaining children’s PIU and cyberbullying and regarding the unique contribution of the parenting styles, parent–child relationships, and ICT frequency and skills to explaining children’s PIU and cyberbullying beyond these background characteristics, four hierarchical regression analyses were conducted.

To address the fourth research question whether the subject group acts as a moderator variable in the association between the parenting style and children’s cyberbullying, Model 1 in PROCESS software was employed (Hayes, 2018).

Results

Parenting Styles and Parent–Child Relationships

Prior to examining the first research question, we examine the differences between TD and SLD/ADHD children regarding parenting styles, using a three-way (2 × 2 × 3) mixed ANOVA analysis. Before conducting the mixed ANOVA analysis, Mauchly’s test of sphericity was conducted to assess the sphericity assumption. Results indicated a violation of the sphericity assumption in parenting style questionnaire. Therefore, F values were reported using the Greenhouse–Geisser correction, and the degrees of freedom were presented in decimal numbers (see Table 2).

Table 2.

Mean (and Standard Deviations) of the Level of the Parenting Styles According to Subject Group, Respondent, and Style.

Parenting style & parent–child relationships		TD (n = 79)		SLD/ADHD (n = 71)
Parenting style & parent–child relationships	Respondent	M	SD	M	SD
Parenting styles
Authoritarian style	Parents	2.59	0.60	2.96	0.73
Authoritarian style	Children	2.85	0.65	2.91	0.71
Authoritative style	Parents	3.78	0.55	3.70	0.51
Authoritative style	Children	3.46	0.63	3.45	0.62
Permissive style	Parents	2.11	0.47	2.16	0.55
Permissive style	Children	2.42	0.51	2.46	0.44
Parent–child relationships
	Parents	4.16	0.61	4.06	0.57
	Children	4.12	0.81	3.94	0.78

Note. TD = typically developing group; SLD = specific learning disability.

A significant main effect was observed for the subject group, F(1,148) = 4.08, p = .045, η_p² = .03, indicating higher scores on the parenting style questionnaire among the SLD/ADHD group compared with the TD group, regardless of the respondent or parenting style. In addition, a significant main effect for parenting style was found: F(1.873, 277.138) = 309.61, p < .001, η_p² = .68. Bonferroni analysis indicated that the authoritative style scored significantly higher than the authoritarian and permissive styles (p < .001), regardless of the study group and respondent. Furthermore, the permissive style scored higher than the authoritarian style (p < .001). No significant main effect was found for the respondent, F(1,148) = 1.50, p = .222, η_p² = .01. However, a significant two-way interaction was noted between the study group and parenting style, F(2,296) = 3.14, p = .045, η_p² = .02.

A t-test for two independent samples was conducted to examine the simple effect of differences between the two subject groups in each parenting style, regardless of the respondent. Results revealed that the SLD/ADHD group scored higher on the authoritarian style compared with the TD group, t(148) = 2.66, p = .009. However, no significant differences were found between the two study groups in either authoritative or permissive style, t(148) = .64, p = .521 and t(148) = .91, p = .365, respectively.

Moreover, the two-way interaction of respondent and parenting style was significant, F(1.694, 250.709) = 20.32, p < .001, η_p² = .12. Paired-samples t-tests examined the simple effect of differences between the two respondents in each parenting style, regardless of the subject groups. They revealed that parents scored higher on the authoritative style compared with their children, whereas children scored higher on the permissive style, t(149) = 4.90, p < .001 and t(149) = 5.14, p < .001, respectively. No significant differences were found between the two respondents in the authoritarian style, t(149) = 1.54, p = .126.

Finally, the two-way interaction of subject group and respondent and the three-way interaction of subject group, respondent, and parenting style were not significant, F(1,148) = 1.22, p = .271, η_p² = .01 and F(2,296) = 2.33, p = .099, η_p² = .01, respectively.

To examine the differences in parent–child relationships, a factor associated with parenting styles, between TD and SLD/ADHD children, a two-way (2 × 2) mixed ANOVA analysis was conducted (see Table 2). No main effects of subject group and respondent, nor interactions of study group and respondent, were found, F(1,148) = 2.82, p = .095, η_p² = .02, F(1,148) = 1.69, p = .196, η_p² = .01 and F(1,148) = .10, p = .758, η_p² = .00, respectively.

To address the first research question, we examined the correlations between parenting styles and parent–child relationships using Pearson correlation analyses for each study group and each respondent. Also, Fisher r-to-z transformation analyses were conducted to compare correlation coefficients between the two study groups (see Table 3). As anticipated, Table 3 indicates significant positive correlations between the children-perceived authoritative style and the quality of the parent–child relationship for both respondents. These findings suggest that an increase in the level of authoritative style perceived by both respondents is associated with an enhancement in the quality of the parent–child relationship. Moreover, the positive correlation coefficient between the children-perceived authoritative style and the quality of the parent–child relationship was significantly higher among children with SLD/ADHD compared with TD children (r = .61 compared with r = .32). Concerning the parent’s-perceived authoritative style, significant positive correlations with the parent–child relationship were observed in both subject groups, with no significant difference in the coefficient level. Furthermore, the results indicated significant negative correlations between the parent’s-perceived authoritarian style and the parent–child relationship. These findings suggest that an increase in the level of authoritarian style perceived by parents is linked to a decline in the quality of the parent–child relationship. These correlations reached significance among the SLD/ADHD group but not among the TD group, with no significant differences found between the two groups in the coefficient level. Finally, no significant correlations were found between the permissive style and the parent–child relationship in both subject groups.

Table 3.

Pearson Correlation Coefficients Between Parenting Styles and Parent–Child Relationship According to Subject Groups.

	Authoritarian style				Authoritative style				Permissive style
Subject Groups	TD (n = 79)	SLD/ADHD (n = 71)	Fisher	p	TD (n = 79)	SLD/ADHD (n = 71)	Fisher	p	TD (n = 79)	SLD/ADHD (n = 71)	Fisher	p
Parents’ measurements
Parent–child relationship	–.35***	–.43***	0.57	.569	.47***	.31**	1.14	.254	–.20	–.11	0.55	.582
Children’s measurements
Parent–child relationship	–.17	–.28*	0.70	0.48	.32**	.61***	2.26*	.024	–.07	–.01	0.36	.719

Note. TD = typically developing group; SLD = specific learning disability; Fisher = r-to-z transformation analyses.

p < .05. **p < .01. ***p < .001.

ICT, Cyberbullying, and PIU

Prior to examining the second research question, we examined the differences between TD and SLD/ADHD children regarding ICT frequency and skills, cyberbullying, and PIU using one-way ANOVA analyses (see Table 4). As Table 4 shows there were no significant differences found between TD and SLD/ADHD children in terms of ICT frequency and skills, PIU, and cyberbullying. It should be noted that these variables exhibited low to moderate levels in both study groups (mean ranges 1.21–2.56 out of 5-points Likert scales).

Table 4.

Mean, Standard Deviations, and F-Values of ICT’s Frequency and Skills, Cyberbullying, and PIU According to Subject Group.

	TD (n = 79)		SLD/ADHD (n = 71)
Study measurements	M	SD	M	SD	F	p	η_p²
ICT frequency	1.92	0.57	2.00	0.58	.62	.431	.00
ICT skills	2.56	0.83	2.33	0.87	.26	.611	.00
PIU
Total score	2.52	0.91	2.51	0.93	.01	.923	.00
Withdrawal	2.56	0.91	2.52	0.93	.11	.745	.00
Compulsion	2.47	1.08	2.50	1.11	.02	.874	.00
Cyberbullying
Victim	1.30	0.43	1.42	0.62	1.95	.165	.01
Perpetrator	1.21	0.40	1.29	0.52	1.02	.313	.01
Bystanders	1.57	0.64	1.63	0.69	.29	.590	.00

Note. ICT = information and communications technology; PIU = problematic internet use; TD = typically developing group; SLD = specific learning disability.

To address the second research question, we examined the correlations between parenting styles, the parent–child relationship (as perceived by the children), and the children’s cyberbullying and PIU using Pearson correlation analyses for each subject group. Fisher r-to-z transformation analyses were conducted to compare correlation coefficients between the two study groups (see Table 5).

Table 5.

Pearson Correlation Coefficients Between Parenting Styles, Parent–Child Relationship and PIU and Cyberbullying According to Subject Groups.

	Parent–child relationship				Authoritarian style				Authoritative style				Permissive style
Study measurements	TD (n = 79)	SLD/ADHD (n = 71)	Fisher	p	TD (n = 79)	SLD/ADHD (n = 71)	Fisher	p	TD (n = 79)	SLD/ADHD (n = 71)	Fisher	p	TD (n = 79)	SLD/ADHD (n = 71)	Fisher	p
PIU
Total score	–.29**	–.44***	1.04	.298	.09	–.07	0.96	.337	–.09	–.26*	1.05	.294	.18	.10	0.49	.624
Withdrawal	–.32**	–.40***	0.55	.582	.10	–.11	1.26	.208	–.11	–.29*	1.13	.258	.18	.09	0.55	.582
Compulsion	–.22	–.40***	1.20	.230	.07	–.01	0.48	.631	–.05	–.18	0.79	.429	.16	.09	0.43	.667
Cyberbullying
Victim	–.47***	–.49***	0.16	.873	–.09	.04	0.78	.435	–.26*	–.54***	2.03*	.042	.23*	.06	1.04	.298
Perpetrator	–.45***	–.44***	0.07	.944	.05	.05	0.00	1.00	–.20	–.40***	1.32	.187	.22*	.12	0.62	.535
Bystanders	–.48***	–.49***	0.08	.936	.02	.13	0.66	.509	–.09	–.37***	1.79	.073	.35**	.17	1.16	.246

Note. PIU = problematic internet use; TD = typically developing group; SLD = specific learning disability; Fisher = r-to-z transformation analyses.

p < .05. **p < .01. ***p < .001.

Table 5 reveals significant negative correlations in both study groups between the parent–child relationship and the child’s level of PIU and cyberbullying, with no significant differences in the coefficients. These results suggest that as the quality of the parent–child relationship increases, the level of PIU and cyberbullying among the children decrease. Negative correlation coefficients were also observed between the authoritative parenting style, the children’s level of PIU, and cyberbullying were also found among those with SLD/ADHD. Among TD children, a significant negative correlation was found between the authoritative style and the degree of cyberbullying as a victim. Notably, the negative correlation coefficient between the authoritative style and the degree of cyberbullying as a victim was significantly higher among children with SLD/ADHD compared with TD children: Fisher z = 2.03, p = .042 (r = -.54, r = -.26, respectively).

Finally, a significant positive correlation was identified between the level of permissive style and the degree of cyberbullying as a victim, perpetrator, or bystanders among children. These results were significant within the TD group but not within the SLD/ADHD group, with no significant differences found between the two groups in the coefficient level.

Study Variables Contribution to the Explained Variance of PIU and Cyberbullying

The third research question focused on how parental and children’s background characteristics contribute to explaining children’s PIU and cyberbullying. In examining the correlation between parenting styles, the parent–child relationship (as perceived by the children), and children’s cyberbullying and PIU, we also aimed to determine whether parenting styles, parent–child relationships, and ICT frequency and skills offer unique contributions to explaining children’s PIU and cyberbullying beyond these background characteristics. To address this question, four hierarchical regression analyses were conducted. One analysis focused on the children’s PIU level, while the other three analyses targeted the different types of cyberbullying. In the first block of the regression model, parents and children’s demographic characteristics and ICT background were included. In the second block, the interpersonal relationship variables—parenting styles, parent–child relationship (as perceived by both parents and children)—were added to examine their unique contribution beyond the contribution of the demographic characteristics and ICT background. Finally, in the third block, children’s ICT frequency and skills were incorporated to examine their unique contribution beyond the demographic characteristics, ICT background and interpersonal relationship between each parent and child (see Table 6).

Table 6

Hierarchical Regression Analysis of PIU and Cyberbullying According to Demographic Characteristics, ICT Background, Parenting Styles, Parent–Child Relationship, ICT Frequency and Skills.

	Standardized coefficient β
Explanatory variables in each block	Block I	Block II	Block III
PIU
Grade level	.29***	.28***	.10
School type^a	–.19*	–.15*	–.04
Personal computer/Tablet/iPad^b	.16*	.10	.06
Parent–child relationship (child)		–.30***	–.15*
ICT frequency			.46***
ICT skills			.20**
F	9.01***	11.57***	25.18***
R ²	.156***	.242***	.514***
∆R ²		.086***	.272***
Cyber-victimization
School type^a	–.18*	–.06	.03
Personal computer/Tablet/iPad^b	.18*	.09	.08
Parents–child relationship (children)		–.27***	–.19**
Authoritative style (children)		–.30***	–.20**
Permissive style (children)		.22**	.10
Parents–child relationship (parents)		–.14*	–.14*
ICT frequency			.42***
F	5.68**	12.58***	18.38***
R ²	.072**	.345***	.475***
∆R ²		.273***	.130***
Cyber-perpetrator
Grade level	.22**	.19*	.08
Personal computer/Tablet/iPad^a	.19*	.10	.07
Children’s gender^c	–.18*	–.11	–.06
Parent–child relationship (children)		–.39***	–.27***
ICT frequency			.40***
F	5.51***	11.52***	16.81***
R ²	.102***	.241***	.369***
∆R ²		.139***	.127***
Cyber-bystanders
School type^a	–.20*	–.11	.02
Children’s gender^c	–.16*	–.07	–.03
Parent–child relationship (children)		–.45***	–.29***
Permissive style (children)		.23***	.12*
Frequency of use of ICT			.54***
F	5.50**	16.63***	33.48***
R ²	.070**	.314***	.538***
∆R ²		.244***	.224***

Note. PIU = problematic internet use; ICT = information and communications technology.

School type: 0 = Public school, 1 = Religious school. ^b Personal computer/Tablet/iPad: 0 = No, 1 = Yes. ^c Children’s gender: 0 = Boy, 1 = Girl.

p < .05. **p < .01. ***p < .001.

Table 6 reveals that parent’s and children’s demographic characteristics and ICT background significantly contributed to the EPV of the children’s PIU and cyber-victim, cyber-perpetrator, and cyber-bystander events (15.6%, 7.2%, 10.2%, and 7.0%, respectively). Specifically, the children’s class contributed to the EPV of the child’s PIU and cyber-perpetrator events with positive β coefficients, indicating lower degree of cyberbullying among younger participants. The school type contributed to the EPV of the children’s PIU and cyber-victim and cyber-bystander occurrences with negative β coefficients. The children’s possession of a personal computer/tablet/iPad contributed to the EPV of the child’s PIU and cyber-victim and cyber-perpetrator events with positive β coefficients, indicating lower PIU and cyberbullying levels among children who do not have a personal computer/tablet/iPad. Notably, possession of a personal digital device by children was a significant predictor, highlighting its role in explaining higher PIU and cyberbullying levels. Finally, gender contributed to the EPV of the children’s cyber-perpetrator and cyber-bystander events, with negative β coefficients, indicating a lower degree among girls. In the second block of the regression model, a significant unique contribution of the parent–child relationship quality to the EPV of children’s PIU and cyberbullying exposure, beyond the demographic characteristics and ICT background, was found (8.6%, 27.3%, 13.9%, and 24.4%, respectively). Children who reported a higher quality parent–child relationship displayed lower levels of PIU and cyberbullying. In addition, regarding the degree of cyber-victimization, significant contributions were also found for the level of authoritative and permissive parenting style. The negative β coefficient of the authoritative style and the positive β coefficient of the permissive style indicated that the child’s level of cyber-victimization tended to be lower among children who perceived their parents as less permissive and more authoritative. Moreover, a significant contribution of the quality of the parents-perceived parent–child relationship to the EPV of exposure to cyber-victimization was found. The negative β coefficient indicated that the child’s level of cyber-victimization tended to be lower among children whose parents perceived their relationship as more positive. Finally, regarding the incidence of cyber-bystander events, a significant contribution was also found for the level of permissive parenting style. The positive β coefficient of the permissive style indicated that the child’s level of cyber-bystander tended to be lower among children who perceived their parents as less permissive.

In the final block of the regression model, ICT frequency and skills, along with the parent–child relationship, made a significant unique contribution to the EPV of the child’s PIU and cyberbullying beyond demographic characteristics (27.2%, 13.0%, 12.7%, and 22.4%, respectively). Children’s ICT frequency of use contributed to the EPV of the PIU and cyberbullying level with positive β coefficients, indicating lower levels among children who use ICT less frequently. Also, children’s ICT skills contributed to the EPV of the PIU level with positive β coefficients, indicating that children with lower ICT skills reported a lower PIU and cyberbullying level.

Subject Group as Moderator Variable in the Association Between Parenting Style and PIU and Cyberbullying

As can be seen in Table 5, a notable discrepancy in the coefficient level between subject groups emerged solely concerning the authoritative parenting style and the extent of the children’s cyberbullying as victims. Specifically, the coefficient was significantly higher among children with SLD/ADHD, compared with TD counterparts. Furthermore, the results of the regression analysis on the degree of cyberbullying as victims revealed significant contributions from the school type and whether early adolescent possessed a personal computer/tablet/iPad, both significantly contributed to the EPV of the initial block of the regression model. To examine whether the subject group acts as a moderator variable in the association between the authoritative parenting style and children’s cyberbullying as victims, Model 1 in PROCESS software was employed (Hayes, 2018), while controlling for the two background variables (school type and possession of personal computer/tablet/iPad). The results indicated a significant interaction between the authoritative parenting style and children’s cyberbullying as victims (∆R² = 3.59%, p = .009, 95% CI [-0.57, -.08]).

Discussion

The goal of this study was to examine the relationship between parenting style, cyberbullying and PIU among TD children compared with children with SLD/ADHD. Results revealed that while the authoritative parenting style was predominant in both study groups, the authoritarian style was more prevalent among children with SLD/ADHD. This finding aligns with prior research indicating that authoritative parenting style is the more supportive and involved in TD children’s online activities (Yusuf et al., 2020), whereas authoritarian parenting tends to be more common among those with SLD/ADHD (Hutchison et al., 2016; Teymouri, 2019).

Several factors may account for these disparities in parenting styles and children’s online behaviors between the two groups. First, the unique characteristics of individuals with SLD/ADHD, including hypersensitivity, social innocence, and a tendency toward obsessive behavior, render them more vulnerable to online risks such as cyberbullying and PIU, compared with TD counterparts (Barringer-Brown, 2015; Olenik-Shemesh et al., 2012). Second, research links the authoritarian parenting style to increased exposure to cyberbullying and PIU (Broll & Reynolds, 2020; Lakavska et al., 2020; Rupesh et al., 2020). Lastly, Belsky’s et al. (2007, 2021) theory of differential susceptibility posits that certain individuals are more susceptible than others to both positive and negative effects of developmental experiences, including harsh parenting. This study also found positive correlations between children’s perceived authoritative parenting style and the quality of the parent–child relationship, particularly notable within the SLD/ADHD group. This observation might elucidate the absence of significant differences in ICT usage frequency, cyberbullying incidences (whether as victims, perpetrators, or bystanders), and PIU between the two groups. In addition, the findings revealed that a higher prevalence of authoritarian parenting style detrimentally impacts the quality of the parent–child relationship, and conversely. This underscores the contrasting needs of children with SLD/ADHD and underscores the pivotal role of parental support for this population.

Drawing from these findings, it can be tentatively inferred that parents striving for a positive relationship with their children should adopt an authoritative stance while minimizing permissive tendencies. The authoritative approach exhibited a favorable influence on the parent–child relationship for both the children and parents who espouse it. Moreover, children experienced lower level of cyber-victimization when their parents perceived their relationship more positively. In contrast, children of permissive parents seems to perceive that lenient boundaries and adopting an overly friendly approach do not enhance their relationship with their parents (Hutchison et al., 2016). Interestingly, no significant differences were found between TD children and children with SLD/ADHD concerning the various forms of cyberbullying and PIU. Although previous research has underscored the heightened susceptibility of children with SLD/ADHD to cyberbullying and PIU (e.g. Barringer-Brown, 2015; Heiman et al., 2015; Hulya-Cakmak & Gul, 2018), these studies primarily focused on children ages 12 to 19. The oversight in these studies is particularly noteworthy as internet usage, cyberbullying, and PIU often commence as early as ages 7 to 9 (Olenik-Shemesh et al., 2017; Restrepo et al., 2020). In addressing this gap, our study focused on examining these phenomena in younger children. Furthermore, the discovery that cyberbullying and PIU levels were notably lower among our young participants may account for the similar outcomes observed across both groups.

However, several potential explanations exist for the absence of distinction in these variables between the two groups. Given the young age of the children examined in this study, it is likely that some had not yet received a diagnosis of SLD/ADHD and were thus categorized within the TD group, potentially influencing the results. In addition, while previous studies may have examined children attending special educational-settings, which typically accommodate most SLD/ADHD children, in Israel, these children usually attend mainstream educational-settings. Children enrolled in special educational settings, likely characterized by more complex disability levels compared with our study’s participants. Another factor to consider is that, even at such young ages, disabilities may manifest less expressed in the negative aspects of internet usage, such as cyberbullying and PIU. Therefore, further research should delve into internet use dynamics among ages 9 to 11 to offer insights into cyberbullying and PIU among those with and without SLD/ADHD. The findings revealed no correlations between parenting styles and the frequency of use, the three types of cyberbullying, and PIU, both in TD and SLD/ADHD children, despite previous studies highlighting the heightened vulnerability of children with SLD/ADHD to online risks (e.g. Heiman et al., 2015; Hulya-Cakmak & Gul, 2018). They also suggested that authoritarian or permissive parenting styles influence cyberbullying and PIU (e.g. Broll & Reynolds, 2020; Lakavska et al., 2020; Martínez et al., 2019; Rupesh et al., 2020). This observation may be elucidated by both this study’s finding and previous research indicating that a higher quality parent–child relationship diminishes cyberbullying and PIU (Huang et al., 2019; Triantoro & Hadi, 2020). Thus, children reporting a better-quality parent–child relationship also reported lower level of all cyberbullying types and PIU. Similarly, children whose parents perceived their relationship positively exhibited reduced levels of cyber-victimization exposure. Another possible explanation is the positive correlation observed between the parent–child relationship and the authoritative parenting style among the SLD/ADHD group compared with the TD group. In addition, the prevalence of the level of the three cyberbullying types and PIU among children without access to a computer/tablet/iPad was notably lower. This may be due to the fact that children as young as those in our study are primarily exposed to the negative impacts of cyberbullying and PIU through computer-based activities. Further research focusing on these age groups will help to enrich the existing literature on the subject.

Despite its interesting results, this study is not without limitations—notably the relatively small sample size of 120 pairs of children and their parents. However, it is important to consider the challenges associated with recruiting participants for such studies. Second, the majority of respondents in the parent group were mothers. Third, the sample of children was primarily drawn from mainstream educational-settings, and including children from special education-settings should also be examined. Fourthly, even though the diagnosis of SLD/ADHD were recently given, the study did not obtain data to confirm the diagnosis. Future studies should consider it. Furthermore, it is important to note that this study is correlational in nature and does not imply causality.

Conclusion

Giving the absence of literature on the influence of parenting styles on TD children, particularly at a young age, this study offers valuable insights into the dynamics of parenting styles, cyberbullying and PIU in this population compared with children with SLD/ADHD. While the study found a correlation between the authoritative parenting style, the quality of the parent–child relationship, and cyberbullying and PIU across both subject groups, it is also highlighted a higher prevalence of the authoritarian style among the SLD/ADHD group. This underscores the divergence in parenting styles between the two groups and underscores the pivotal role of the parenting style in shaping children’s responses to online threats. In addition, a noteworthy finding relates to the parent–child relationship, wherein the authoritative parenting style and the quality of the parent–child relationship were found to exert a positive impact on cyberbullying and PIU. Although this correlation was evident in both study groups, it was significantly stronger among the SLD/ADHD group. It is worth noting that the parent–child relationship has been found to correlate positively with the adoption of the optimal parenting style (authoritative), fostering education on safe internet usage and facilitating moderate engagement in cyberbullying and PIU, while equipping children with strategies to address online threats effectively. These findings underscore the significance of embracing an authoritative parenting style among parents, particularly those with SLD/ADHD.

Future studies focusing on the prevailing parenting style among children, both with and without TD, will enrich the field, offering deeper insights into the disparities between the population groups and informing the development of intervention programs aimed at mitigating cyberbullying and PIU.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Sigal Eden

References

Al-Yagon

Forte

Avrahami

(2020). Executive functions and attachment relationships in children with ADHD: Links to externalizing/internalizing problems, social skills, and negative mood regulation. Journal of Attention Disorders, 24(13), 1876–1890. https://doi.org/10.1177/1087054717730608

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing.

American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev.).

Arnold

L. E.

Hodgkins

Kahle

Madhoo

Kewley

(2020). Long-term outcomes of ADHD: Academic achievement and performance. Journal of Attention Disorders, 24(1), 73–85. https://doi.org/10.1177/1087054714566076

Aro

Eklund

Eloranta

A. K.

Närhi

Korhonen

Ahonen

(2019). Associations between childhood learning disabilities and adult age mental health problems, lack of education, and unemployment. Journal of Learning Disabilities, 52(1), 71–83. https://doi.prg/10.1177/0022219418775118

Barringer-Brown

(2015). Cyber bullying among students with serious emotional and specific learning disabilities. Journal of Education and Human Development, 4(2), 50–56. https://doi.prg/10.15640/jehd.v4n2_1a4

Baumrind

(1971). Current patterns of parental authority. Developmental Psychology Monograph, 4(1), 1–103.

Belsky

Bakermans-Kranenburg

van Ijzendoorn

(2007). For better and for worse: Differential susceptibility to environmental influences. Current Directions in Psychological Science, 16, 305–309. https://doi.org/10.1111/j.1467-8721.2007.00525.x

Belsky

Zhang

Sayler

(2022). Differential susceptibility 2.0: Are the same children affected by different experiences and exposures? Development and Psychopathology, 34(3), 1025–1033. https://doi.org/10.1017/S0954579420002205

10.

Boniel-Nissima

Sasson

(2018). Bullying victimization and poor relationships with parents as risk factors of problematic internet use in adolescence. Computers in Human Behavior, 88, 176. https://doi.org/10.1016/j.chb.2018.05.041

11.

Broll

Reynolds

(2020). Parental responsibility, blameworthiness, and bullying: Parenting style and adolescents’ experiences with traditional bullying and cyberbullying. Criminal Justice Policy Review, 32(5), 447–468. https://doi.org/10.1177/0887403420921443

12.

Buri

J. R.

(1991). Parental authority questionnaire. Journal of personality assessment, 57(1), 110–119. https://doi.org/10.1207/s15327752jpa5701_13

13.

Charalampous

Demetriou

Tricha

Ioannou

Georgiou

Nikiforou

Stavrinides

(2018). The effect of parental style on bullying and cyber bullying behaviors and the mediating role of peer attachment relationships: A longitudinal study. Journal of Adolescence, 64, 109–123. https://doi.prg/10.1016/j.adolescence.2018.02.003

14.

Eden

Heiman

Olenik-Shemesh

(2016). Bully versus victim on the Internet: The correlation with emotional-social characteristics. Education and Information Technologies, 21(3), 699–713. https://doi.prg/10.1007/s10639-014-9348-2

15.

Eden

Heiman

Olenik-Shemesh

Yablon

Y. B.

(2023). Cyberbullying and PIU among adolescents before and during COVID-19 pandemic: the association with adolescents relationships. Youth & Society, 55(7), 1367–1390. https://doi.org/10.1177/0044118X231169493

16.

Ellis

Boyce

Belsky

Bakermans-Kranenburg

van Ijzendoorn

(2011). Differential susceptibility to the environment: An evolutionary–neurodevelopmental theory. Development and Psychopathology, 23, 7–28. https://doi.prg/10.1017/S0954579410000611

17.

Feijo

Foody

O’Higgins-Norman

Pichel

Rial

(2021). Cyberbullies, the cyberbullied, and problematic internet use: Some reasonable similarities. Psicothema, 33(2), 198–205. https://doi.prg/10.7334/psicothema2020.209

18.

Furman

Buhrmester

(1985). Children’s perceptions of the personal relationships in their social networks. Developmental Psychology, 21, 1016–1024. https://doi.org/10.1037/0012-1649.21.6.1016

19.

Gul

Yurumez Solmaz

Gul

Oner

(2017). Facebook overuse and addiction among Turkish adolescents: Are ADHD and ADHD-related problems risk factors? Psychiatry and Clinical Psychopharmacology, 28(1), 80–90. https://doi.prg/10.1080/24750573.2017.1383706

20.

Hayes

A. F.

(2018). Partial, conditional, and moderated mediation: Quantification, inference, and interpretation. Communication Monographs, 85(1), 4–40. https://doi.org/10.1080/03637751.2017.1352100

21.

Heiman

Olenik-Shemesh

Eden

(2015). Cyberbullying involvement among students with ADHD: Relation to loneliness, self-efficacy and social support. European Journal of Special Needs Education, 30(1), 15–29. https://doi.org/10.1080/08856257.2014.943562

22.

Huang

Qin

Lü

(2019). Parent-children relationship and internet addiction of adolescents: The mediating role of self-concept. Current Psychology, 40(3), 2510–2517. https://doi.org/10.1007/s12144-019-00199-9

23.

Hulya-Cakmak

Gul

(2018). Factors associated with problematic internet use among children and adolescents with attention deficit hyperactivity disorder. Northern Clinics of Istanbul, 5(4), 302–313. https://doi.org/10.14744/nci.2017.92668

24.

Hutchison

Feder

Abar

Winsler

(2016). Relation between parenting stress, parenting style and child executive functioning for children with ADHD or Autism. Journal of Child and Family Studies, 25, 3644–3656. https://doi.org/10.1007/s10826-016-0518-2

25.

Johnston

Chronis-Tuscano

(2015). Families and ADHD. In Barkley

R. A.

(Ed.), Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment (4th ed., pp. 191–209). The Guilford Press.

26.

Laconi

Kuss

D. J.

(2018). Cross-cultural study of problematic Internet use in nine European countries. Computers in Human Behavior, 84, 430–440. https://doi.org/10.1016/j.chb.2018.03.020

27.

Lakavska

Vacek

Gabhelik

(2020). The effects of parental control and warmth on problematic internet use in adolescents: A prospective cohort study. Journal of Behavioral Addictions, 9(3), 664–675. https://doi.org/10.1556/2006.2020.00068

28.

Legate

Weinstein

Przybylski

A. K.

(2018). Parenting strategies and adolescents’ cyberbullying behaviors: Evidence from a preregistered study of parent–child dyads. Journal of Youth and Adolescence, 48, 399–409. https://doi.org/10.1007/s10964-018-0962-y

29.

Livingstone

Haddon

Görzig

Ólafsson

(2011). Risks and safety on the internet: the perspective of European children: full findings and policy implications from the EU Kids Online survey of 9-16 year olds and their parents in 25 countries. EU Kids Online, Deliverable D4. EU Kids Online Network, London, UK.

30.

Maccoby

E. E.

Martin

J. A.

(1983). Socialization in the context of the family: Parent-Child interaction. In Mussen

P. H.

Hetherington

E. M.

(Eds.), Handbook of child psychology: Vol. 4. Socialization, personality, and social development (pp. 1–101). Wiley.

31.

Marczak

Coyne

(2015). A focus on online bullying. In Attrill

(Ed.), Cyberpsychology (pp. 145–163). Oxford University Press.

32.

Martínez

Murgui

Garcia

O. F.

Garcia

(2019). Parenting in the digital era: Protective and risk parenting styles for traditional bullying and cyberbullying victimization. Computers in Human Behavior, 90, 84–92. https://doi.org/10.1016/j.chb.2018.08.036

33.

Moreno–Ruiz

Martínez–Ferrer

García–Bacete

(2019). Parenting styles, cyberaggression, and cybervictimization among adolescents. Computers in Human Behavior, 93, 252–259. https://doi.org/10.1016/j.chb.2018.12.031

34.

Nielsen

Favez

Rigter

(2020). Parental and family factors associated with problematic gaming and problematic Internet use in adolescents: A systematic literature review. Current Addiction Reports, 7(3), 365–386. https://doi.org/10.1007/s40429-020-00320-0

35.

Olenik-Shemesh

Heiman

Eden

(2012). Cyberbullying victimization in adolescence: Relationship with loneliness and depressive mood. Emotional & Behavioral Difficulties, 17(3/4), 361–374.

36.

Olenik-Shemesh

Heiman

Eden

(2017). Bystanders’ behavior in cyberbullying episodes: Active and passive patterns in the context of personal–socioemotional factors. Journal of Interpersonal Violence, 32(1), 23–48. https://doi.org/10.1177/0886260515585531

37.

Pineda-Alhucema

Aristizabal

Escudero-Cabarcas

Acosta-López

J. E.

Vélez

J. I.

(2018). Executive function and theory of mind in children with ADHD: A systematic review. Neuropsychology Review, 28(3), 341–358. https://doi.org/10.1007/S11065-018-9381-9

38.

Quintana-Orts

Rey

Neto

(2020). Beyond cyberbullying: Investigating when and how cybervictimization predicts suicidal ideation. Journal of Interpersonal Violence, 37, 935–957. https://doi.org/10.1177/0886260520913640

39.

Restrepo

Scheininger

Clucas

Alexander

Salum

G. A.

Georgiades

Paksarian

Merikangas

K. R.

Milham

M. P.

(2020). Problematic internet use in children and adolescents: Associations with psychiatric disorders and impairment. BMC Psychiatry, 20(1), 252. https://doi.org/10.1186/s12888-020-02640-x

40.

Rupesh

Singh

Subramanyam

A. A.

Kamath

R. M.

(2020). Study of parenting styles, family functioning and its relation to coping strategies in children of specific learning disorder. International Journal of Contemporary Pediatrics, 7(2), 230–235. https://doi.org/10.18203/2349-3291.ijcp20200096

41.

Serna

García-Perales

Martínez

(2023). Protective and risk parenting styles for internet and online gambling addiction. Human Behavior and Emerging Technologies, 2023(1), 6674541. https://doi.org/10.1155/2023/6674541

42.

Smith

P. K.

Mahdavi

Carvalho

Fisher

Russell

Tippett

(2008). Cyberbullying: Its natureand impact in secondary school pupils. Journal of Child Psychology and Psychiatry, 49, 376–385. https://doi.org/10.1111/j.1469-7610.2007.01846.x

43.

Spada

M. M.

(2014). An overview of problematic Internet use. Addictive Behaviors, 39(1), 3–6. https://doi.org/10.1016/j.addbeh.2013.09.007

44.

Symons

Ponnet

Emmery

Walrave

Heirman

(2017). Parental knowledge of adolescents’ online content and contact risks. Journal of Youth & Adolescence, 46(2), 401–416. https://doi.org/10.1007/s10964-016-0599-7

45.

Tarawneh

(2017). Friendship skills of students with learning disabilities in Jordan from the perspectives of their teachers and the effect of some variables on it. Open Journal of Social Sciences, 5, 136–150. https://doi.org/10.4236/jss.2017.58011

46.

Teymouri

(2019). Investigation of stress level and parenting style among parents of children diagnosed as attention deficit and hyperactivity disorder [Master’s thesis]. Near East University.

47.

Triantoro

Hadi

(2020). The role of parent-child relationship, school climate, happiness, and empathy to predict cyberbullying behavior. International Journal of Evaluation and Research in Education, 9(3), 548–557. https://doi.org/10.11591/ijere.v9i3.20299

48.

Xanidis

Brignell

C. M.

(2016). The association between the use of social network sites, sleep quality and cognitive function during the day. Computers in Human Behavior, 55, 121–126. https://doi.org/10.1016/j.chb.2015.09.004

49.

Yaffe

Seroussi

D. E.

(2019). Problematic internet use in Israeli-Arab adolescent males: Do parenting styles matter? Cyberpsychology, 13(4), 5. https://doi.org/10.5817/CP2019-4-5

50.

Yıldız-Durak

(2018). What would you do without your smartphone? Adolescents’ social media usage, locus of control, and loneliness as a predictor of nomophobia. Addicta: The Turkish Journal on Addictions, 5(2), 151–163. https://doi.org/10.15805/addicta.2018.5.2.0025

51.

Yusuf

Witro

Dian

Apra-Santosa

Alwiya-Alfikri

Jalwis

(2020). Digital parenting to children using the internet. Pedagogic Journal of Islamic Elementary School, 3(1), 2615–3904. https://doi.org/10.24256/pijies.v3i1.1277

52.

Zhu

Huang

Evans

Zhang

(2021). Cyberbullying among adolescents and children: A comprehensive review of the global situation, risk factors, and preventive measures. Frontiers in Public Health, 9, Article 634909. https://doi.org/10.3389/fpubh.2021.634909