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Article

Characteristics of Parental Digital Mediation: Predictors, Strategies, and Differences among Children Experiencing Various Parental Mediation Strategies

1
Laboratory of Childhood Psychology and Digital Socialization, Psychological Institute of the Russian Academy of Education, 119991 Moscow, Russia
2
Scientific and Educational Center of the State Institution Academy of Sciences of the Republic of Sakha (Yakutiya), 677007 Yakutsk, Russia
3
Trust Fund of Future Generations in the Republic of Sakha (Yakutia), 677018 Yakutsk, Russia
*
Author to whom correspondence should be addressed.
Educ. Sci. 2023, 13(1), 57; https://doi.org/10.3390/educsci13010057
Submission received: 20 October 2022 / Revised: 23 December 2022 / Accepted: 31 December 2022 / Published: 4 January 2023

Abstract

:
The process of digitalization has become an integral part of the social situation of a child’s growth in the modern world. Child development in the digital environment demands the involvement of adults as mediators. This practice is called parental digital mediation. Previous studies have identified the significant parental and environmental aspects of parental mediation, but there has been little information about the relationships between the children’s characteristics and parental digital mediation. The current study aims to fill this gap by identifying the behavioral (social network and screen time) and emotional (social network addiction and happiness) predictors of the two dimensions of digital mediation: parental support and parental control. The study also examines the differences among children influenced by various parental mediation strategies. A total of 4011 students (42% male and 58% female) ranging in age from 13 to 15 years (M = 14.07; SD = 0.76) took part in the study. The parental mediation of their children’s internet use, social media addiction, social network time, screen time, and happiness were measured. According to the results, both the behavioral and emotional characteristics of the children served as predictors of parental mediation. A small amount of time spent on social networks or screens and low social media addiction and happiness were identified as the predictors of parental support, whereas a large amount of time spent on social networks and screens and low social media addiction were identified as the predictors of parental control. Three groups of children experiencing different parental mediation strategies were determined. The children with parents who enabled mediation were happier than the others. Children under instructive mediation demonstrated the highest tendency to social media addiction. Children under selective mediation spent the most time (of all groups) on gadgets, but they showed a low tendency towards social media addiction.

1. Introduction

The rise of digitalization has altered many aspects of our life [1] and has become an integral part of the social situation of a child’s development in the modern world. The development of the internet created a new environment for socialization and added new features to parent–child interactions [2,3]. In this context, parenthood acquires another function in the digitalization of childhood: parental digital mediation.
The concept of “digital parenting” describes parental behaviors in relation to their children’s activities in digital environments [4]. Within this framework, parental digital mediation includes various communication and interaction practices that may be combined together in different ways to enhance the strategies for the children’s upbringing regarding the use of the internet and digital media [4]. According to previous research, parental digital mediation affects children’s safety, digital skills, and well-being [5], but on the other hand, these parental strategies depend on the individual characteristics of a child [6,7].
Despite the extensively studied role of parental characteristics (age, gender, digital literacy, etc.) and environmental factors (culture, country of residence, etc.) in parental digital mediation (e.g., [8,9,10]), studies on the influence of children’s emotional well-being and their digital behavior on parental digital mediation are limited. Furthermore, there are no data on the differences in the features between digital behavior and the subjective emotional sense of well-being among those children whose parents use different parental mediation strategies. The present study addresses this gap.

1.1. Parental Digital Mediation and Its Strategies

The modern approach to upbringing demands parents to participate in children’s use of the internet and digital media. One of the ways to implement this new parental function is through digital mediation. Parental digital mediation is defined in a variety of ways, from a narrow “the frequency of parental intervention” [11] to an expansive “the construction of the media-ecology system of a child’s environment” [12]. In the current research, parental mediation is viewed as a set of parental practices that aim to direct and regulate the children’s internet and digital media use and to discuss the specifics of this use and the characteristics of media content [13,14]. Our point of view is in line with the recent studies which have added a new aspect (participatory learning) to the study of parental digital mediation [15].
It is suggested that the main goal of this mediation is to protect children from harmful content and dangerous media [16]. Some authors also highlight other goals, such as the parental regulation of the amount and quality of the time that children spend on screens [17] and the development of their children’s digital literacy [18]. They note that parental mediation can be initiated by both children and parents [13,19].
The study of parental digital mediation is a contemporary continuation of parenthood research. It covers a number of parental practices and reveals particular styles and strategies of parental mediation [9]. According to some approaches, a parenting style, in general, has two primary dimensions: demandingness, that is, parental control, and responsiveness, which means parental supportiveness [20]. Parental control includes monitoring the children’s behavior, setting rules and standards, and applying sanctions in case of their violation. Parental support implies emotional and behavioral involvement in a child’s life, assisting in their development and the demonstration of affection and warmth [21].
The first system of parental mediation strategies was based on this dichotomy and included a restriction strategy with high parental control and an instruction strategy with high parental support [from an overview, 8]. Since then, researchers have proposed many other strategies based on combinations of these two dimensions. For example, Lwin and colleagues [22] describe restrictive, promotive (instructive), selective (both restrictive and instructive), and laissez-faire (without regulation) strategies. A recent analytical review identified a restrictive strategy and an active strategy, monitoring child behavior and deference [23]. Recently, several studies have reported on the trichotomy of restrictive-enabling-observant parental digital use mediation [19].
One of the modern lines of research focuses on detailing the digital-specific practices of parental digital mediation [24]. In these studies, parental technical mediation is defined as the use of content filters or software to prevent junk mail, messages, etc., while parental digital monitoring is viewed as the process of gaining information about their children’s digital activities, in particular, their friends and chats on social networks, downloaded apps, visited websites and so on [9,25].
Following Kuzmanović and colleagues [26], we assume that both technical control and monitoring are more often used in those mediation strategies with high levels of parental control, although they could also be applied in strategies with high levels of support to create a safe framework for the use of the internet [19].
The data on the characteristics of parental digital mediation strategies can be collected from children as well as from their parents. Even though the information from both children and their parents, despite the differences in their assessments (e.g., [11]), is preferable, some researchers recommend involving primarily children for a number of reasons. First, parents and children generally agree on the identification of the prevailing strategy. Second, children are influenced by parental mediation, and they are capable of recognizing the strategies applied. Third, they do not tend towards social desirability as their parents do [15].
Any parental practice, including parental digital mediation, strives for a positive outcome. Previous research has established that parental digital mediation improves children’s well-being and prevents unhappiness [5]. Specifically, it was detected that adolescents whose parents use more mediation show fewer symptoms of depression [27] and have smaller problems with sleep if parents set strict rules about the use of gadgets before bedtime [28]. However, it has been demonstrated that different parental styles have different effects on children (e.g., [29]). Although it was found that restrictive mediation decreases children’s screen time and the threat of different online risks [30], it also increases anxiety and depressive symptoms and reduces life satisfaction (e.g., [31]). Moreover, this strategy of mediation might block the development of a child’s autonomy and digital skills and destroy trusting relationships with their parents [5]. Digital mediation with a higher level of support has more or less the opposite effect. In a number of studies, adolescents demonstrated fewer depressive symptoms [32], higher life satisfaction [33], and better social well-being when their parents built supportive communication about the internet and digital media use [34].
The present study continues with a line of research that investigates parental digital mediation based on the data gathered from children. We also suggest that mediation strategies, in the context of children’s use of the internet and digital media, are determined by the ratio of two broad dimensions of parental styles (parental control and parental support).
Based on the previous findings, we assume that children whose parents demonstrate different mediation strategies will show emotional and behavioral differences.

1.2. Predictors of Parental Digital Mediation

The choice of parental digital mediation strategies depends on many factors, such as the individual and sociodemographic features of parents, the socioeconomic characteristics of families, and crosscultural differences. Thus, parents who use the internet on a regular basis are more likely to choose active mediation, while those who rarely connect to the internet tend towards control [8]. Older parents control their children more than younger ones [35]. Less educated and low-income parents prefer restrictive strategies [36]. Parents from conservative continental European countries often apply technical solutions rather than using active mediation [9].
Despite the considerable data on the factors of parental digital mediation that concern parental and environmental features, little is known about the characteristics of children that determine the strategies of any parental mediation. It was found that, as children get older, parents use fewer mediation strategies [4] and that girls’ internet use is mostly mediated by active practices, whereas boys’ usage is regulated restrictively [37]. However, it is unknown how a child’s digital behavior and well-being affect their parent’s choices for digital mediation strategies.
Following Palfrey and Gasser [38], we consider general screen time and time that is spent on social networks to be characteristics of children’s overall digital behavior. Although most studies investigate the effects of parental mediation on reductions in undesirable screen time for their children [39], we assume that the length of a child’s screen time may also determine the choice of parental mediation strategies [7]. During adolescence, parental digital regulation decreases, and teenagers start to manage their online time themselves [40,41], but parental mediation does not disappear entirely. It seems that parents can modify their mediation strategy if they think that their children are spending too much time in front of the screen [42]. Hence, the second aim of this study is to detect whether children’s screen and social network time may serve as predictors for parental mediation.
Social media addiction is a well-known consequence of the problems regarding self-regulation caused by internet use [43]. This addiction is also a negative predictor of emotional well-being [44], and it is related to the amount of time that children spend on social media and on screens [45]. In order to prevent children’s media addiction, parents implement different restrictions [46], but according to previous studies, internet addiction has negative relationships with both active and restrictive mediation strategies [47]. In addition, earlier, the predictive role of children’s smartphone addiction on parental mediation strategies was revealed [6]. The current study aims to transfer these findings to social media addiction.
Emotional characteristics, in addition to behavioral characteristics, may influence parental strategies as well. As in the above cases, the studies in this direction are mostly one-sided. A large body of research explores parents’ happiness as an emotional dimension of well-being during the shaping of their mediation strategies, e.g., [48,49], while data on the effect of children’s happiness on parental mediation strategies is scarce. Such investigations into digital mediation strategies have not been conducted yet; this study fills out this research void.
Based on the presented literature review on parental digital mediation, our study focuses on the question: what relations can be identified between child characteristics and parental mediation?
The answer to this question will be received by completing the following objectives: (1) identifying the role of social networks and screen time as digital behavioral predictors and identifying the role of social media addiction and happiness as the emotional predictors for parental mediation; (2) to identify the groups of children with experiences of different parental mediation strategies, as detected based on the ratio of parental support and parental control, and (3) to explore the differences in social networks and screen time and social media addiction and happiness among children influenced by different parental mediation strategies.

2. Materials and Methods

2.1. Participants and Procedure

The current study was carried out within the framework of complex research that examined the psychological well-being of secondary school students from the Republic of Sakha (Yakutia). All schools listed on the site for the Department of Education of the District Administration of the city of Yakutsk received an invitation to participate in the study (N = 45). A total of 4011 students (42% male and 58% female) ranging, in age, from 13 to 15 years (M = 14.07; SD = 0.76) took part in the study. All participants completed questionnaires about their well-being, use of gadgets and social networks and parental digital mediation. The data collection was performed individually. All research procedures followed the ethical standards of the Russian Psychological Society. The materials were presented to the participants in the official language of the Russian Federation. Brislin’s three-step model for the crosscultural adaptation of research instruments [50] was used to translate the questionnaires from English into Russian.

2.2. Measures

Parental mediation of their children’s internet use was measured in two dimensions: parental support (active mediation) and parental control. Following Kuzmanović and colleagues [26], we used two scales. The active mediation scale has 4 items as answers (e.g., “Suggests ways to use the Internet safely”) to the question “When you use the Internet, how often does your parent/carer do any of these things?”. The children used a 5-point Likert scale for their answers (from 1—“never” to 5—“very often”). The parent control scale had 3 items as answers (e.g., “Parental controls or other means of keeping track of the Internet content I look at or apps I use”) to the question “Does your parent/carer make use of any of the following?” The participants used a 3-point scale to answer it (0—“no”, 1—“I do not know”, 2—“yes”). The confirmatory factor analysis (CFA) showed the two-factor solution for the parental digital mediation measuring the items proposed by Kuzmanović and colleagues [26]: x2(14) = 124.89, p < 0.001; TLI = 0.996; SRMR = 0.027, CFI = 0.997; RMSEA [90% CI] = 0.046 [0.039:0.054]. The two-factor solution demonstrated a better model fit than the one-factor solution (x2(14) = 3763.61, p < 0.001. The Cronbach’s alpha for parental support was 0.836, and 0.755 for parental control.
The Bergen social media addiction scale was used to identify the children’s social media addiction [51]. This scale had 6 items (e.g., “How often during the last year have you felt an urge to use social media more and more?”) which the participants rated on a Likert scale from “1” (very rarely) to “5” (very often). A one-factor solution was confirmed by CFI: x2(9) = 82.85, p < 0.001; TLI = 0.991; SRMR = 0.028, CFI = 0.994; RMSEA [90% CI] = 0.045 [0.037:0.054]. Cronbach’s alpha = 0.754.
Regarding social network time, the children were asked, “How many hours have you spent on social networks (not including online classes) every day over the past week?” to detect how much time they had spent on social networks. The following answers were provided: “less than 10 min”, “from 10 to 30 min”, “from 31 to 60 min”, “one or two hours”, “two or three hours”, “more than three hours”.
The screen time parameter was measured by the question “How much time do you spend on the computer/tablet/smartphone?” The children used a 4-point scale to answer it: “about 1 h per day”, “approximately 2 h a day”, “almost 3 h a day”, “more than 3 h a day”.
Happiness: to measure happiness, following Bruggeman and colleagues [52], two questions were asked of the participants. They were “How happy do you usually feel?” and “How happy did you feel yesterday?” The children were given an 11-point Likert scale for answers ranging from “0” (very unhappy) to “10” (very happy). Cronbach’s alpha = 0.79.

3. Results

3.1. Predictors of Parental Mediation

A Pearson correlation analysis was conducted to determine the relationships between the investigated parameters. According to the findings, there is a negative correlation between parental control and parental support (r = −0.20, p < 0.001). Additionally, parental support has a negative relationship with time spent on social networks (r = −0.12, p < 0.001) and screen time (r = −0.19, p < 0.001) and a positive relationship with social media addiction (r = 0.11, p < 0.001) and happiness (r = 0.25, p < 0.001). Parental control has a positive relationship with the time indices (r = 0.11, p < 0.001 and r = 0.16, p < 0.001) and a negative relationship with social media addiction (r = −0.16, p < 0.001). Happiness shows a negative relationship with social network time (r = −0.09, p < 0.001), screen time (r = −0.13, p < 0.001), and social media addiction (r = −0.21, p < 0.001). Table 1 displays all the correlations.
The predictors of parental digital mediation were identified by hierarchical regression analysis. Two models were evaluated. Parental support was added as a dependent variable to the first model, with parental control added to the second. The age and gender variables were added to both models for the purpose of control. Independent variables were added to both models in the following order: age and gender were included in the models in the first step, social network time and screen time were added in the second step, and social media addiction and happiness were added in the final step (Table 2).
As shown in Table 2, the model in Step 1 includes age and gender, explaining less than 1% of the variations in both parental support and parental control. Age is a negative predictor only for parental support (b = −0.29, p < 0.001); this effect remains virtually constant in all the steps. Gender has a significant positive effect on both of the parental mediation practices in Step 1 (b = 0.26, p < 0.001 for parental support and b = 0.20, p < 0.001 for parental control), this positive effect persists in the subsequent steps. The addition of the time indexes in Step 2 increases the proportion of explained variance for parental support to 5% and parental control to 3%. Social network time and screen time are negative predictors of parental support (b = −0.003, p < 0.001; b = −0.76, p < 0.001, respectively) and positive predictors of parental control (b = 0.002, p < 0.001; b = 0.23, p < 0.01). The inclusion of the happiness and social media addiction indexes in Step 3 increases the proportion of the explained variance by more than two times. It rises up to 13% for parental support and to 7% for parental control. Social media addiction is a positive predictor of parental support (b = 0.15, p < 0.001) and a negative predictor of parental control (b = −0.06, p < 0.001). Happiness (b = 0.25, p < 0.001) contributes significantly and positively to parental support.

3.2. Identification of the Groups of Children Whose Parents Demonstrate Different Mediation Strategies

Neighborhood-based clustering was used to identify the groups of children whose parents demonstrated different levels of support and control over their internet and digital media use. The parental support and parental control indexes were considered to be quasicontinuous variables for the cluster analysis. Following Zhang and colleagues [53] and Rousseeuw [54], the number of clusters was identified based on the analysis of the silhouette index, the likelihood-based information criteria (AIC and BIC), and the elbow method. A number of models with two to five clusters were examined, and they all had comparable AIC, BIC, and silhouette-indices values. The elbow method showed that the three-cluster model explained more of the variation (70%) and was more interpretable.
As is shown in Figure 1, three groups of children were found. The first cluster includes a group of children (40% of the sample) whose parents demonstrate the highest rate of parental support and a moderate rate of parental control (Group 1, with the “enabling mediation” parental strategy). The second cluster describes a group of children (15% of the sample) whose parents have a high rate of support but a low rate of control (Group 2, with the “instructive mediation” parental strategy). The third cluster consists of children (48% of the sample) whose parents demonstrated a low rate of support and a moderate rate of control (Group 3, with the “selective mediation” parental strategy).

3.3. Characteristics of the Children for Whom Their Parents Demonstrate Different Mediation Strategies

A comparison between the children for whom their parents use different mediation strategies was conducted with one-way ANOVA. We considered screen time and social network time as the parameters of the children’s digital behavior [38], while social media addiction and happiness we viewed as the negative and positive characteristics of the children’s emotional condition. All scores in this figure are represented by z-scores; the means for the indexes of digital behavior and emotional well-being in the investigated groups are shown in Figure 2.
The results demonstrate that screen time (F (2 4008) = 73.11, p < 0.001) and social network time (F (2 4008) = 28.59, p < 0.001) were the significant and main effectors on the studied groups. It was found that Group 3 demonstrated the highest level of screen time and social network time in comparison to Group 1 (t = 8.61, p < 0.001 and t = 4.89, p < 0.001, respectively) and Group 2 (t = 10.73, p < 0.001 and t = 6.99, p < 0.001, respectively). The main effect was also significant for social media addiction (F (2 4008) = 50.36, p < 0.001) and happiness (F (2 4008) = 67.72, p < 0.001). The findings show that Group 2 demonstrated a higher level of social network addiction than Group 1 (t = 8.24, p < 0.001) or Group 3 (t = 10.01, p < 0.001). The results for the happiness index indicate that Group 1 had the highest level of this parameter, followed by Group 2 (t = 5.05, p < 0.001) and then Group 3 (t = 11.60, p < 0.001).

4. Discussion

Our study aimed to investigate the behavioral and emotional predictors of parental digital mediation and the differences among children influenced by specific digital mediation strategies of parents.

4.1. The Role of Behavioural (Social Network and Screen Time) and Emotional (Social Media Addiction and Happiness) Characteristics in Parental Mediation

Social network time and screen time were considered to be characteristics of the children’s digital behavior. Both of these parameters decrease parental support and increase parental control. A probable explanation is that spending excessive time on social networks or gadgets leads to behavioral [55], cognitive, and socioemotional problems [56]. Undoubtedly, parents pay attention to these changes and may adapt their mediation practices over their children’s internet use to prevent the situation from getting worse.
In the regression analysis, social media addiction contributed a positive sign to parental support and a negative sign to control. Earlier findings explained the negative correlation between parental mediation and the children’s excessive media use through the rise in the children’s addiction due to low parental attachment and subsequent parental indulgence of excessive time spent on social networks or gadgets [57]. According to our findings, we can speculate that the risk of a child’s social media addiction, which manifests itself in fear of being prohibited from using social media or anxiety about unsuccessful attempts to reduce internet usage, causes parents to shift from passive control towards a more active position and involves such practices as the enabling strategy [13]. But, on the other hand, it is also possible that parents who show more support and less control may still raise children who are social media addicts.
Happiness, in the current study, is a positive and significant predictor only for parental support. It may be that this emotional dimension of well-being increases the involvement of the parents in their children’s internet usage through teaching and explaining internet use rules [48]. This influence may also come from the general family values for children’s well-being and positive child–parent relationships. It is interesting that the emotional condition of children does not necessarily matter in cases where parental digital control is applied. It is almost certain that it is because there is more parental detachment in the process of control through the technical functions of gadgets in contrast to other active practices of digital mediation [24].
Age and gender were also investigated as predictors for parental digital mediation, along with children’s digital behavior and the emotional dimensions of their well-being. Age had a significant impact on parental support but not on parental control, whereas gender had a significant impact on both parental support and control. Therefore, we may conclude that our results are only partially consistent with the previous findings about decreasing parental mediation over children’s internet use with age [33] and the evidence that girls’ internet use is mostly mediated by active practices, while boys’ usage is regulated, restrictively [37].

4.2. Groups of Children Whose Parents Demonstrate Different Mediation Strategies

Based on the children’s answers about their parents’ digital mediation, we detected three strategies. The first group of children reported that their parents explained how to use the internet safely and why some content is good or bad. The parents help them when something on the internet bothers their children; they use parental control functions on gadgets moderately and establish some internet use rules. We assume that this group of children experiences a parental strategy that is similar to the enabling mediation strategy, which was proposed by Livingstone and colleagues [13]. It was described as a set of parental practices that allow children enough space for positive uses of the internet, such as education and communication [4], but at the same time, establish strict limits and, thus, provide safety.
The second group of children reported that their parents occasionally help them use the internet and explain the safe ways to do this, but they do not use parental control functions on gadgets and rarely impose internet use rules. We suppose that these children are under the influence of the mediation strategy that may be called “instructive mediation” because it combines parental guidance and little control [8,22].
The children from the final group reported that their parents do not reject their requests to help them use the internet but rarely help personally, preferring to rely on parental control functions over gadgets, such as blocking or filtering certain types of content and keeping track of the content that children look at or the applications that they use. We presume that the parents of the children in this group demonstrate a selective mediation strategy because they combine restrictive practices with periodically used instructive actions [22].
This study did not find a hard restrictive approach as a separate strategy, as was the case in previous studies (e.g., [4]). Earlier findings showed that absolute control over children’s internet use or extremely strong restrictions do not foster children’s digital skills, which, in turn, lowers their potential for professional development [13]. We believe that the COVID−19 pandemic from 2020–2022, which caused a shift to distance learning, accelerated the digitalization of modern life [58,59,60], so this is probably why a certain number of parents have decreased the level of their digital control and increased their support.

4.3. Differences among Children Influenced by Different Parental Mediation Strategies

The results of our study indicate that children whose parents use the above-described mediation strategies have some differences. Thus, we can guess that children under parental enabling mediation are happier than others, and, in general, they do not spend much time on social networks or on gadgets. Furthermore, they do not seem to tend to social media addiction. A possible explanation for this might be that while technical controls restrict children’s time on the internet and gadgets, the personal involvement of parents in digital mediation and their interactions with children strengthen a positive child–parent relationship, which leads to a higher rate of well-being in the children. Similar findings and explanations were provided by earlier research [13,61]. Another possible interpretation is that those children who demonstrate high levels of happiness and social well-being are not prone to the overuse of digital devices [34].
According to our study, those children whose parents demonstrate instructive mediation spend minimal time on the internet or on social networks, but they demonstrate the highest tendency for social media addiction of all the groups, and, overall, they do not seem to be very happy. This is an intriguing finding that accords with the regression result. The instructive mediation strategies imply a low level of digital control and, as we assume, infrequent personal parental interference, which may explain why the children are unhappy [62] and become addicted to social media [63]. At the same time, the children’s fascination with the internet and digital devices might lead to parental detachment and low control. It is possible that parents will find such keenness of their children convenient and spend their free time on their own needs [12], but the overuse of this pattern may increase the emotional distance between the parents and children and degrade the children’s well-being.
Finally, children whose parents use selective mediation have the lowest level of happiness. Despite spending a lot of time on gadgets, they are characterized by a low level of social media addiction. A possible explanation for these low levels of happiness may be inferred from the positive correlation between parental support and happiness. A lack of parental participation in the children’s internet use may lead to emotional problems [64]. A combination of high levels of screen and social network time and low levels of social media addiction may be explained by the work of gadget filters and by the content that parents select for their children [65].

5. Conclusions

This study investigates the relationship between children’s characteristics and parental digital mediation. We looked at the predictors of parental mediation and the characteristics of children whose parents demonstrate different approaches to the regulation of their children’s internet and gadget use.
Previous research identified significant parental (e.g., age, gender, digital skills, etc.) and environmental (e.g., culture, country of residence, etc.) factors [35,36], but there was little information about the effect of children’s characteristics on parental digital mediation. We found that children’s behaviors and emotional conditions may affect the choice of parental mediation strategies. In particular, we may conclude that parental support is related to children’s happiness, little time on social networks or screens, and low social media addiction. Parental control, in turn, is related to more time spent on social networks and screens, although children may not be addicted to social media. Moreover, parents tend to support and control girls more than boys.
Three parental digital mediation strategies were identified—enabling mediation, instructive mediation, and selective mediation. A restrictive mediation strategy, which is normally included in these classifications, was not found. We can assume that the reason for this comes from the digitalization of life because the internet and social networks have now become an integral part of contemporary life [3]. Besides, it was detected that children whose parents use the strategies identified above demonstrate certain differences in their digital behaviors and emotional conditions. We suppose that this happens due to the experience of various ratios of parental support and control. These differences in parental behavior may stem from different proportions of feelings of attachment and detachment in their relationships with their children. For example, digital control through the technical functions of gadgets has less parental involvement and personal interest in contrast to active practices of digital mediation, such as teaching or co-usage. But this assumption about the effect of child–parent emotional relationships on parental digital mediation needs further investigation.
The findings of the current research have practical implications for parents, as well as for specialists and consultants who develop digital parenting educational programs. It is important to convey to parents that the children need their involvement when using the internet. The enabling mediation strategy appears to be a good way to improve children’s well-being. Parents should know that low parental digital control, the pathological use of the internet, and advanced social media addiction may be the outcomes of child–parent alienation, but at the same time, digital control has to provide children with individual space for study and rest.
The current research has some limitations. Firstly, the cross-sectional design does not provide enough data for a discussion on the age dynamics related to children’s characteristics when the parental digital mediation effect is taken into account. Secondly, selfreported methods provided only the children’s opinions about their digital behaviors, emotional condition, and parental mediation practices. In order to expand the database, future studies must include parents and use more objective measures, such as observation or a daily digital diary. Then these limitations may become the basis for future research.

Author Contributions

Conceptualization, D.K.; methodology, D.K.; software, N.R. and D.K.; validation, N.R., D.K., Y.S. and V.E.; formal analysis, N.R. and D.K.; investigation, D.K., Y.S. and V.E.; resources, N.R., D.K., Y.S. and V.E.; data curation, N.R. and D.K.; writing—original draft preparation, N.R.; writing—review and editing, D.K., Y.S. and V.E.; visualization, N.R.; supervision, D.K.; project administration, N.R.; funding acquisition, D.K., Y.S. and V.E. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study and consent procedures were approved by the Ethics Committee of Faculty of Psychology at Lomonosov Moscow State University (the approval No: 2018/41).

Informed Consent Statement

Written informed consent was obtained from the legal guardians of the children participated in the study.

Data Availability Statement

The full dataset is available upon request to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Dorokhov, E.A.; Gusev, A.N. The evaluation of user’s representation of personal computer. Mosc. Univ. Psychol. Bull. 2021, 3, 122–135. [Google Scholar] [CrossRef]
  2. Mascheroni, G.; Livingstone, S.; Dreier, M.; Chaudron, S. Learning versus play or learning through play? How parents’ imaginaries, discourses and practices around ICTs shape children’s (digital) literacy practices. Media Educ. 2016, 7, 261–280. [Google Scholar] [CrossRef]
  3. Livingstone, S.; Blum-Ross, A. Parenting for a Digital Future: How Hopes and Fears about Technology Shape Children’s Lives; Oxford University Press: Oxford, UK, 2020. [Google Scholar]
  4. Nagy, B.; Kutrovátz, K.; Király, G.; Rakovics, M. Parental mediation in the age of mobile technology. Child. Soc. 2022, 1–28. [Google Scholar] [CrossRef]
  5. Beyens, I.; Keijsers, L.; Coyne, S.M. Social media, parenting, and well-being. Curr. Opin. Psychol. 2022, 47, 101350. [Google Scholar] [CrossRef] [PubMed]
  6. Hwang, Y.; Jeong, S.H. Predictors of parental mediation regarding children’s smartphone use. Cyberpsychol. Behav. Soc. Netw. 2015, 18, 737–743. [Google Scholar] [CrossRef] [PubMed]
  7. Sciacca, B.; Laffan, D.A.; O’Higgins Norman, J.; Milosevic, T. Parental mediation in pandemic: Predictors and relationship with children’s digital skills and time spent online in Ireland. Comput. Hum. Behav. 2022, 127, 107081. [Google Scholar] [CrossRef]
  8. Kirwil, L.; Garmendia, M.; Garitaonandia, C.; Fernandez, G.M. Parental mediation. In Kids Online. Opportunities and Risks for Children; Livingstone, S., Haddon, L., Eds.; The Policy Press: Bristol, UK, 2009; pp. 199–215. [Google Scholar]
  9. Kalmus, V.; Roosalu, T. Parental mediation of EU kids’ internet use revisited: Looking for a complex model of cross-national differences. Int. J. Media Cult. Politics 2022, 7, 55–66. [Google Scholar] [CrossRef] [PubMed]
  10. Kalabina, I.A.; Progackaya, T.K. Formation of digital competence of older preschool children. Presch. Educ. Today 2022, 20222, 58–69. [Google Scholar] [CrossRef]
  11. Valkenburg, P.; Piotrowski, J.; Hermanns, J.; de Leeuw, R. Developing and validating the perceived parental media mediation scale: A self-determination perspective. Hum. Commun. Res. 2013, 39, 445–469. [Google Scholar] [CrossRef]
  12. Nikken, P.; Opree, S.J. Guiding Young Children’s Digital Media Use: SES-Differences in Mediation Concerns and Competence. J Child Fam. Stud. 2018, 27, 1844–1857. [Google Scholar] [CrossRef]
  13. Livingstone, S.; Ólafsson, K.; Helsper, E.J.; Lupiáñez-Villanueva, F.; Veltri, G.A.; Folkvord, F. Maximizing opportunities and minimizing risks for children online: The role of digital skills in emerging strategies of parental mediation. J. Commun. 2017, 67, 82–105. [Google Scholar] [CrossRef] [Green Version]
  14. Warren, R. Parental mediation of media use and effects. In International Encyclopedia of Media Psychology; van den Bulck, J., Ed.; John Wiley & Sons: Hoboken, NY, USA, 2020. [Google Scholar]
  15. Nikken, P. Parental Mediation of Media. In The international Encyclopedia of Media Effects; Rössler, P., Hoffner, C.A., van Zoonen, L., Eds.; John Wiley & Sons: Hoboken, NY, USA, 2017; pp. 1–16. [Google Scholar]
  16. Smahel, D.; Machackova, H.; Mascheroni, G.; Dedkova, L.; Staksrud, E.; Ólafsson, K.; Livingstone, S.; Hasebrink, U. EU Kids Online 2020: Survey Results from 19 Countries; London School of Economics and Political Science: London, UK, 2020. [Google Scholar]
  17. Kucirkova, N.; Livingstone, S. Why the Very Idea of ‘Screen Time’ is Muddled and Misguided. 2017. Available online: https://theconversation.com/whythe-very-idea-of-screen-time-is-muddled-and-misguided-82347 (accessed on 10 October 2022).
  18. Jeffery, C.P. Parenting in the digital age: Between socio-biological and socio-technological development. New Media Soc. 2021, 23, 1045–1062. [Google Scholar] [CrossRef]
  19. Kuldas, S.; Sargioti, A.; Milosevic, T.; Norman, J.O.H. A review and content validation of 10 measurement scales for parental mediation of children’s internet use. Int. J. Commun. 2021, 15, 4062–4084. [Google Scholar]
  20. Eastin, M.S.; Greenberg, B.S.; Hofschire, L. Parenting the Internet. J. Commun. 2006, 56, 486–504. [Google Scholar] [CrossRef]
  21. Yaffe, Y. Systematic review of the differences between mothers and fathers in parenting styles and practices. Curr. Psychol. 2020, 1–14. [Google Scholar] [CrossRef]
  22. Lwin, M.O.; Stanaland, A.J.S.; Miyazaki, A.D. Protecting children’s privacy online: How parental mediation strategies affect website safeguard effectiveness. J. Retail. 2008, 84, 2005–2217. [Google Scholar] [CrossRef]
  23. Kutrovátz, K.; Balogh, T.; Wittinger, B.; Király, G. A technológiával kapcsolatos szülői mediáció. Szisztematikus empirikus áttekintés a 2007 és 2017-es évek között megjelent tanulmányok alapján. Társadalomtudományi Szle 2018, 8, 47–69. [Google Scholar] [CrossRef]
  24. Navarro, J.L.; Fletcher, A.; Jensen, M. A bifactor model of US Parents’ attitudes regarding mediation for the digital age. J. Child. Media 2022, 1–20. [Google Scholar] [CrossRef]
  25. Livingstone, S.; Helsper, E.J. Parental mediation of children’s Internet use. J. Broadcast. Electron. Media 2008, 52, 581–599. [Google Scholar] [CrossRef] [Green Version]
  26. Kuzmanović, D.; Pavlović, Z.; Popadić, D.; Milosevic, T. Internet and Digital Technology Use Among Children and Youth in Serbia: EU Kids Online Survey Results; Institute of Psychology, Faculty of Philosophy: Belgrade, Serbia, 2018. [Google Scholar]
  27. Wright, M.F. Cyber victimization and depression among adolescents with autism spectrum disorder: The buffering effects of parental mediation and social support. J. Child Adolesc. Trauma. 2018, 11, 17–25. [Google Scholar] [CrossRef]
  28. Eijnden, R.V.D.; Geurts, S.; ter Bogt, T.; van der Rijst, V.; Koning, I. Social Media Use and Adolescents’ Sleep: A Longitudinal Study on the Protective Role of Parental Rules Regarding Internet Use before Sleep. Int. J. Environ. Res. Public Health 2021, 18, 1346. [Google Scholar] [CrossRef] [PubMed]
  29. Kocayörük, E.; Tutkun, T.; Gözü, H.; Şimşek, F.; Altintaş, E. An Examination of the Relationships Between Parenting Behaviors and Adolescents Well-being: A Cross-cultural Comparision. Turk. Psychol. Couns. Guid. J. 2021, 11, 487–504. [Google Scholar] [CrossRef]
  30. Naab, T. From Media Trusteeship to Parental Mediation, the Parental Development of Parental Mediation. In Digital Parenting: The Challenges for Families in the Digital Age; Mascheroni, G., Ponte, C., Jorge, A., Eds.; Nordicom University of Gothenburg: Gothenburg, Sweden, 2018; pp. 93–102. [Google Scholar]
  31. Fardouly, J.; Magson, N.R.; Johnco, C.J.; Oar, E.L.; Rapee, R.M. Parental Control of the Time Preadolescents Spend on Social Media: Links with Preadolescents’ Social Media Appearance Comparisons and Mental Health. J. Youth Adolesc. 2018, 47, 1456–1468. [Google Scholar] [CrossRef] [PubMed]
  32. Padilla-Walker, L.M.; Stockdale, L.A.; McLean, R.D. Associations between parental media monitoring, media use, and internalizing symptoms during adolescence. Psychol. Popul. Media 2020, 9, 481–492. [Google Scholar] [CrossRef]
  33. Milosevic, T.; Kuldas, S.; Sargioti, A.; Laffan, D.A.; Norman, J.O. Children’s Internet Use, Self-Reported Life Satisfaction, and Parental Mediation in Europe: An Analysis of the EU Kids Online Dataset. Front. Psychol. 2022, 12, 689176. [Google Scholar] [CrossRef] [PubMed]
  34. Schmuck, D. Following Social Media Influencers in Early Adolescence: Fear of Missing Out, Social Well-Being and Supportive Communication with Parents. J. Comput. Commun. 2021, 26, 245–264. [Google Scholar] [CrossRef]
  35. Brito, R.; Francisco, R.; Dias, P.; Chaudron, S. Family Dynamics in Digital Homes: The Role Played by Parental Mediation in Young Children’s Digital Practices Around 14 European Countries. Contemp. Fam. Ther. 2017, 39, 271–280. [Google Scholar] [CrossRef]
  36. Livingstone, S.; Mascheroni, G.; Dreier, M.; Chaudron, S.; Lagae, K. How Parents of Young Children Manage Digital Devices at Home: The Role of Income, Education and Parental Style; EU Kids Online, LSE: London, UK, 2015. [Google Scholar]
  37. Talves, K.; Kalmus, V. Gendered mediation of children’s internet use: A keyhole for looking into changing socialization practices. Cyberpsychology: J. Psychosoc. Res. Cyberspace 2015, 9, 4. [Google Scholar] [CrossRef] [Green Version]
  38. Palfrey, J.; Gasser, U. Born Digital: Understanding the First Generation of Digital Natives; Basic Books: New York, NY, USA, 2008. [Google Scholar]
  39. Griffiths, M.D.; Benrazavi, R.; Teimouri, M. Parental mediation and adolescent screen time: A brief overview. Educ. Health 2016, 34, 70–73. [Google Scholar]
  40. Sobkin, V.S.; Fedotova, A.V. Adolescents on social media: Aggression and cyberbullying. Psychol. Russ. State Art. 2021, 14, 186–201. [Google Scholar] [CrossRef]
  41. Kuzmina, T.I. Using the Internet user’s self-report diagnostic tool to study specific characteristics of Internet-based socialization among adolescents and young adults with intellectual disabilities. Russ. Psychol. J. 2021, 18, 5–21. [Google Scholar] [CrossRef]
  42. Kanashov, A.E.; Trusova, A.V. The role of family relationships in Internet addiction in adolescents. Natl. Psychol. J. 2021, 2, 76–86. [Google Scholar] [CrossRef]
  43. Caplan, S.E. A social skill account of problematic Internet use. J. Commun. 2005, 55, 721–736. [Google Scholar] [CrossRef]
  44. Quaglieri, A.; Biondi, S.; Roma, P.; Varchetta, M.; Fraschetti, A.; Burrai, J.; Lausi, G.; Martí-Vilar, M.; González-Sala, F.; Di Domenico, A.; et al. From Emotional (Dys)Regulation to Internet Addiction: A Mediation Model of Problematic Social Media Use among Italian Young Adults. J. Clin. Med. 2021, 11, 188. [Google Scholar] [CrossRef]
  45. Lissak, G. Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environ. Res. 2018, 164, 149–157. [Google Scholar] [CrossRef]
  46. Lee, S.-J. Parental restrictive mediation of children’s internet use: Effective for what and for whom? New Media Soc. 2012, 15, 466–481. [Google Scholar] [CrossRef]
  47. Chng, G.S.; Li, D.; Liau, A.K.; Khoo, A. Moderating Effects of the Family Environment for Parental Mediation and Pathological Internet Use in Youths. Cyberpsychol. Behav. Soc. Netw. 2015, 18, 30–36. [Google Scholar] [CrossRef]
  48. Bahrami, A. The Effect of Happiness on Various Aspects of Parenting and Positive Parenting. Psychol. Behav. Sci. Int. J. 2017, 4, 555–627. [Google Scholar] [CrossRef]
  49. McDaniel, B.T.; Adams, E.L.; Hohman, E.E.; Cornet, V.; Reining, L.; Kaiser, Z. Maternal nighttime phone use and impacts on daily happiness and exhaustion. Acta Paediatr. 2021, 111, 584–585. [Google Scholar] [CrossRef]
  50. Brislin, R.W. Back-translation for cross-cultural research. J. Cross-Cult. Psychol. 1970, 1, 187–216. [Google Scholar] [CrossRef]
  51. Andreassen, C.S.; Billieux, J.; Griffiths, M.D.; Kuss, D.J.; Demetrovics, Z.; Mazzoni, E.; Pallesen, S. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study. Psychol. Addict. Behav. 2016, 30, 252–262. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Bruggeman, H.; Van Hiel, A.; Van Hal, G.; Van Dongen, S. Does the use of digital media affect psychological well-being? An empirical test among children aged 9 to 12. Comput. Hum. Behav. 2019, 101, 104–113. [Google Scholar] [CrossRef]
  53. Zhang, T.; Ramakrishnon, R.; Livny, M. BIRCH: An efficient data clustering method for very large databases. In Proceedings of the ACM SIGMOD Conference on Management of Data, Montreal, QC, Canada, 4–6 June 1996; pp. 103–114. [Google Scholar]
  54. Rousseeuw, P.J. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 1987, 20, 53–65. [Google Scholar] [CrossRef] [Green Version]
  55. Xie, G.; Deng, Q.; Cao, J.; Chang, Q. Digital screen time and its effect on preschoolers’ behavior in China: Results from a cross-sectional study. Ital. J. Pediatr. 2020, 46, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Domingues-Montanari, S. Clinical and psychological effects of excessive screen time on children. J. Paediatr. Child Health 2017, 53, 333–338. [Google Scholar] [CrossRef]
  57. Ko, C.-H.; Wang, P.-W.; Liu, T.-L.; Yen, C.-F.; Chen, C.-S.; Yen, J.-Y. Bidirectional associations between family factors and Internet addiction among adolescents in a prospective investigation. Psychiatry Clin. Neurosci. 2015, 69, 192–200. [Google Scholar] [CrossRef]
  58. Drouin, M.; McDaniel, B.T.; Pater, J.; Toscos, T. How Parents and Their Children Used Social Media and Technology at the Beginning of the COVID-19 Pandemic and Associations with Anxiety. Cyberpsychol. Behav. Soc. Netw. 2020, 23, 727–736. [Google Scholar] [CrossRef]
  59. Koinova-Zoellner, J.; Kalimullin, A.; Gospodinov, B.; Procházka, M.; Vasilieva, L. Pedagogical senses of digital learning ion the context of the COVID-19 pandemic: Case studies of several eastern European countries. J. Sib. Fed. Univ. Humanit. Soc. Sci. 2021, 14, 1355–1364. [Google Scholar] [CrossRef]
  60. Veraksa, A.N.; Chichinina, E.A. Comparison of media use among senior preschool children before and during the COVID-19 pandemic. Presch. Educ. Today 2022, 2, 30–39. (In Russian) [Google Scholar] [CrossRef]
  61. Xiao, X.; Zhan, Y.; Zhong, Y. Parental attachment and adolescent internet morality: A moderated mediation model. Eur. J. Dev. Psychol. 2020, 19, 1–21. [Google Scholar] [CrossRef]
  62. Hampton, K.N.; Shin, I. Disconnection more problematic for adolescent self-esteem than heavy social media use: Evidence from access inequalities and restrictive media parenting in rural America. Soc. Sci. Comput. Rev. 2022. [Google Scholar] [CrossRef]
  63. Chang, F.C.; Chiu, C.H.; Miao, N.F.; Chen, P.H.; Lee, C.M.; Chiang, J.T.; Pan, Y.C. The relationship between parental mediation and Internet addiction among adolescents, and the association with cyberbullying and depression. Compr. Psychiatry 2015, 57, 21–28. [Google Scholar] [CrossRef]
  64. Ling, C.; Yee, H.K. Parental mediation: Its impact on contexts of emotional behavioral adjustment among children in Kota Kinabalu district. Cogent Soc. Sci. 2021, 7, 1870070. [Google Scholar] [CrossRef]
  65. Chen, L.; Shi, J. Reducing Harm From Media: A Meta-Analysis of Parental Mediation. J. Mass Commun. Q. 2018, 96, 173–193. [Google Scholar] [CrossRef]
Figure 1. Results of the cluster analysis on parental support and parental control.
Figure 1. Results of the cluster analysis on parental support and parental control.
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Figure 2. Expressiveness of the parameters in the group of children for whom their parents used different digital mediation strategies (z-scores). Group 1 has high parental support and moderate parental control (enabling mediation). Group 2 has high support and low control (instructive mediation). Group 3 has low support and moderate control (selective mediation).
Figure 2. Expressiveness of the parameters in the group of children for whom their parents used different digital mediation strategies (z-scores). Group 1 has high parental support and moderate parental control (enabling mediation). Group 2 has high support and low control (instructive mediation). Group 3 has low support and moderate control (selective mediation).
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Table 1. Results of the correlation analysis.
Table 1. Results of the correlation analysis.
123456
1. Parental support
2. Parental control−0.20 ***
3. Social Network time−0.12 ***0.11 ***
4. Screen time−0.19 ***0.16 ***0.45 ***
5. Social Media addiction0.11 ***−0.16 ***0.26 ***0.12 ***
6. Happiness0.25 ***0.01 ***−0.09 ***−0.13 ***−0.21 ***
Note. *** p < 0.001.
Table 2. Results of the regression analysis.
Table 2. Results of the regression analysis.
Parental SupportParental Control
bSE bBetatbSE bBetat
Step 1R2 = 0.004; F = 8.67 ***R2 = 0.005; F = 9.14 ***
Constant13.21 ***1.17 11.284.45 ***0.44 10.13
Age−0.29 ***0.08−0.06−3.550.030.030.021.05
Gender0.26 **0.130.032.100.20 ***0.050.074.16
Step 2R2 = 0.05; F = 46.10 ***R2 = 0.029; F = 29.59 ***
Constant16.02 ***1.17 13.713.63 ***0.44 8.22
Age−0.28 ***0.08−0.05−3.490.030.030.020.96
Gender0.38 ***0.120.053.030.16 ***0.050.053.50
Social Network time−0.003 ***0.01−0.05−3.020.001**0.0010.042.33
Screen time−0.76 ***0.08−0.17−9.860.22 ***0.030.137.64
Step 3R2 = 0.13; F = 98.29 ***R2 = 0.073; F = 52.17 ***
Constant9.37 ***1.17 8.023.99 ***0.45 8.83
Age−0.21 **0.08−0.04−2.730.040.030.021.32
Gender0.43 ***0.120.053.570.29 ***0.050.096.07
Social Network time−0.004 ***0.00−0.09−5.130.002 ***0.0010.095.28
Screen Time−0.65 ***0.07−0.15−8.760.23 ***0.030.148.00
Social Media addiction0.15 ***0.010.1912.08−0.06 ***0.005−0.21−13.25
Happiness0.25 ***0.010.2717.330.010.010.021.45
Note. ** p < 0.01; *** p < 0.001.
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Rudnova, N.; Kornienko, D.; Semenov, Y.; Egorov, V. Characteristics of Parental Digital Mediation: Predictors, Strategies, and Differences among Children Experiencing Various Parental Mediation Strategies. Educ. Sci. 2023, 13, 57. https://doi.org/10.3390/educsci13010057

AMA Style

Rudnova N, Kornienko D, Semenov Y, Egorov V. Characteristics of Parental Digital Mediation: Predictors, Strategies, and Differences among Children Experiencing Various Parental Mediation Strategies. Education Sciences. 2023; 13(1):57. https://doi.org/10.3390/educsci13010057

Chicago/Turabian Style

Rudnova, Natalia, Dmitry Kornienko, Yuri Semenov, and Vladimir Egorov. 2023. "Characteristics of Parental Digital Mediation: Predictors, Strategies, and Differences among Children Experiencing Various Parental Mediation Strategies" Education Sciences 13, no. 1: 57. https://doi.org/10.3390/educsci13010057

APA Style

Rudnova, N., Kornienko, D., Semenov, Y., & Egorov, V. (2023). Characteristics of Parental Digital Mediation: Predictors, Strategies, and Differences among Children Experiencing Various Parental Mediation Strategies. Education Sciences, 13(1), 57. https://doi.org/10.3390/educsci13010057

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