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Psychology, Society & Education

versión On-line ISSN 1989-709X

Psychology, Society & Education vol.15 no.3 Córdoba sep./dic. 2023  Epub 18-Mar-2024

https://dx.doi.org/10.21071/psye.v15i3.16077 

Articles

Parental control measures to regulate smartphones use by children

Pablo-César Muñoz-Carril*  , Conceptualization, Formal analysis, Investigation, Supervision, Writing - original draft, Writing - review & editing; Alba Souto-Seijo, Writing - original draft, Writing - review & editing; Isabel Dans-Álvarez-de-Sotomayor, Writing - original draft, Writing - review & editing; Eduardo-José Fuentes-Abeledo, Resources, Writing - review & editing

2Universidade de Santiago de Compostela, Santiago de Compostela (Spain)

Abstract

The complexity of the current digital ecosystem calls for the development of parental control mechanisms to guide minors in their use of technology. This study aims to identify the type of parental control measures used by parents to monitor the use that school-age children (6 to 12 years old) make of smartphones. An ex post facto design was prepared after conducting a survey in which 885 people (68.7% mothers) took part. The results showed that 93.7% of the parents surveyed used some type of parental control system to regulate the use of the smartphone. The most frequently strategies were limiting the time when the device could be used and restricting access through passwords. The analysis revealed that parents with higher education used a greater number of control mechanisms. Similarly, the length of time the children were connected was related to the level and intensity of the parental control strategies used. Parents applied a greater number of parental control strategies with pre-adolescent children, in the last years of primary education. Finally, the challenges and opportunities that the use of smartphones can bring to children are discussed, and also the active role that the family should play in digital training and education.

Keywords: Mobile devices; Primary education; Minors; Parental mediation

Smartphones have become omnipresent devices in our day to day lives. They are now a predominant technology that has begun to affect many aspects of the rhythm of daily life, where the borders between the physical and the virtual have narrowed in a perpetually hyperconnected society (Gaines, 2019; Hansen, 2021). In this context, the significant level of intrusion of smartphones into the family arena means that children are nowadays exposed to screens more and more. Studies such as Smahel et al. (2020) have shown that the average time minors spend online in Spain is 180 minutes a day (double the time spent ten years ago), with 76% of that access to the internet via smartphones. In addition, various studies have indicated that the age at which children start to use smartphones continues to drop (Andrade et al., 2021; Sola et al., 2019). This early use is also reflected in the high percentage of children who have their own mobile devices (Rideout & Roob, 2020).

Within this complex multifaceted ecosystem, in which smartphones feature prominently, parents face significant challenges that affect how they raise their children (Cánovas, 2021; Livingstone & Blum-Ross, 2020). Among the challenges to consider in children's digital education, the scientific literature has paid particular attention to the importance of suitable parental monitoring and control mechanisms to prevent the problematic situations children may have to face if they abuse or make irresponsible use of smartphones (Kim & Jahng, 2019). In this regard, one of the family's main responsibilities is to establish clear rules and limits that help to mitigate the dangers and risky behaviors arising from improperly using this technology. In addition, the family should provide a safe environment in which children can explore opportunities to interact with other people, learn, and improve their digital skills (Rodríguez-de-Dios et al., 2018).

Within this action framework, it is important to emphasize that the latest European guidelines and resolutions about children's digital rights (European Commission, 2018, 2021 2022) recommend that parental control of devices meet appropriate norms of protection, respecting the principle of proportionality and transparency for the child, making them into an active participant, aware of monitoring, data-gathering, and tracking applications used by digital services online. From this perspective, notable initiatives such as the BIK+ strategy, adopted by the European Union on 11 May 2022, aim to develop a battery of measures to ensure children are protected in the digital arena, enhancing their skills, empowering them and giving them the ability to safely shape and enjoy their lives on the internet. This ambitious project requires various educational agents (teachers and parents) to be trained in order to achieve young people's digital wellbeing.

Factors that influence parents' strategies for mediation and control in children's digital education

Parental mediation is a strategy that influences how children use technology and is useful not only for preventing problem behaviors and conflict online (Matthes et al., 2021), but also for providing learning opportunities and acquisition of critical skills (Sánchez-Valle et al., 2017).

There is broad consensus in the literature on the identification of two main categories of parental styles (Chen & Chng, 2016; Livingstone et al., 2017): enabling or active mediation, linked to positive use of technology, in which parents offer guidance and recommendations; and restrictive mediation, which controls children's activities through rules and limiting screen time. Along with these two types, Smahel et al. (2020) expanded the classification in the report EU Kids Online 2020, adding technical strategies (which involve parents using programs or mobile applications to control time, set tracking systems, apply filters, etc.), monitoring or tracking (tracing children's activities on various platforms), and inverse mediation strategies (where the children ask adults for help or intervention).

Nonetheless, studies have not produced conclusive results when it comes to establishing the ideal parental control style in children's digital education (Sánchez-Valle et al., 2017). Results vary in terms of how the level of parental monitoring and supervision can play an important role in smartphone use (Chang et al., 2019; Shin & Li, 2017). Some experts, such as Kalmus et al. (2015), believe that monitoring measures are more effective when children are younger and face unpleasant experiences online, reducing the harm they may be exposed to. These authors noted that parental mediation based on monitoring and tracking have notable effects in reducing the risk of cyberbullying. However, these types of measures have been criticized as being intrusive and potentially invading privacy (Symons et al. 2017), as well as for holding to a reductionist view that focuses mainly on dangers, without considering alternatives such as active mediation (Shin & Lwin, 2016). Active mediation encourages children's digital wellbeing through dialog, where parents assertively discuss the use of technology with their children, sharing activities online, and explaining how to deal with problematic or unexpected situations (Dedkova & Smahel, 2020). Another reason for various authors to consider active mediation a suitable measure in digital education is because it improves children's understanding about technology, allowing them to improve their self-regulation with ICT and modeling healthier and more responsible coping skills (Dedkova & Smahel, 2020).

Recent studies have noted various factors that influence the levels of parental mediation and control styles applied to the use of technology, particularly smartphones (Dedkova & Smahel, 2020; Geržičáková et al., 2022; Warren & Aloia, 2019). The children's age is a key variable, families use more rules and are more inflexible with younger children than with adolescents (Glatz et al., 2018; Smahel et al., 2020). The age of the parents is also an important aspect that affects how they regulate their children's online activities. The older the parents, the more lax the monitoring and control of their offspring, while younger parents tend to be more involved in support, guidance, and social interaction with their children (Livingstone et al. 2017; Padilla et al., 2015; Talves & Kalmus, 2015).

Parents' socio-educational level is also an important factor affecting supervision. Recent studies have shown that variables such as parents' professional category and educational attainment influence the type of mediation they engage in around their children's use of smartphones and online consumption (Martínez et al., 2020; Ramírez-García et al., 2023). More specifically, higher educational attainment and higher status employment increase the likelihood of applying diverse mechanisms for parental control and monitoring. This control is more commonly executed by mothers than fathers, which indicates women's significant role and responsibility in their children's digital education (Dedkova & Smahel, 2020; Jiménez-Morales et al., 2020).

Gender has also been identified as an important variable if we focus on the child, as there is greater control over girls than boys, something that some authors have attributed to greater concern that girls may talk to strangers or fear of cyberbullying (Pastor Ruiz et al., 2019; Ramos-Soler et al., 2018).

In addition, families' socio-economic status is associated with how much children are exposed to screens (Männikkö et al., 2020). Parents from lower socio-economic backgrounds use fewer parental control strategies over their children's digital activities (Smahel et al., 2020).

More recently, new research trends have been looking more deeply into parents' perceived lack of control due to children being hyper-connected. This entails a sense of resignation and frustration around the loss of control over the activities children engage in with their mobile devices (Charisi et al., 2022).

Academics have also paid particular attention to parents' low levels of digital skills, time spent online, and excessive use of smartphones. These variables may have a notable impact on children developing problematic behaviors in their use of digital devices (Matthes et al., 2021; Schmuck et al., 2023; Yang et al., 2023), with significant repercussions on their school lives, academic performance, and wellbeing (Eoh et al., 2022).

As noted previously, children are gaining access to smartphones at increasingly younger ages (Andrade et al., 2021; Rideout & Roob, 2020; Sola et al., 2019). However, most research has so far focused on the adolescent population (e.g., Andrade et al., 2021; Smahel et al., 2020). In addition, although recent years have seen the beginnings of analysis of the role families play in their children's digital education, compared to other lines of research, the results so far have been limited. Our current study aims to contribute to improving this theoretical corpus and the research in this field. More specifically, the objective of the study was to identify the parental control measures employed by parents over their primary-school-aged (6 to 12 years old) children's use of smartphones. The specific objectives were: 1) to determine the types of parental control mechanisms parents used to regulate what their children do with their smartphones, 2) to examine whether the parents' educational attainment was related to the level of parental control over the children's smartphone use, 3) to determine if there was a relationship between the amount of time children spent online each day and the level of parental control, and 4) to assess whether the primary school year the children were in influenced the number of parental control mechanisms used to regulate children's smartphone use.

Method

The study used a quantitative methodology. More specifically, an ex post facto, descriptive, transversal design via a survey (McMillan & Schumacher, 2005).

Participants

A total of 1,135 parents with children in primary education participated in the study. The children attended 23 schools (private, public, and independent) in the city of Lugo (Spain).

We used convenience sampling in two phases. In the first phase, a pilot study was performed with 250 subjects, which allowed us to validate the questionnaire used to collect the information. The second phase involved applying the survey to the parents making up the final sample, made up of 885 people.

Just under a third (31.3%; n = 277) of the participants were men, 68.7% (n = 608) were women, and the mean age of the participants was 42.28 years (SD = 5.56). The majority of the participants (71.6%; n = 634) were married, 7% (n = 62) were single, 6.7% (n = 59) were separated, while 7.1% (n = 63) were divorced, and 1% (n = 9) were widowed. A small number (6%; n = 53) were in civil partnerships or cohabiting, while only 0.1% (n = 1) were in a polygamous marriage. Finally, 0.5% (n = 4) of the sample did not provide their civil status.

In terms of educational attainment, 6.2% (n = 55) had a primary education or equivalent, 20.1% (n = 178) had compulsory or higher secondary education, 30.5% (n = 270) had vocational training qualifications, while 42.8% (n = 379) had university-level or equivalent education. Lastly, 0.3% (n = 3) stated that they did not have any qualifications.

The vast majority of the parents were in employment (87.7%; n = 776), and a much smaller proportion (11.2%; n = 99) were unemployed. A small number (0.8%; n = 7) reported being retired, while only 0.3% (n = 3) of the subjects did not respond about their employment.

Table 1. Sociodemographic characteristics of the study participants' primary-school aged children 

Variables Categories n %
Gender Boy 425 48
Girl 460 52
Type of school attended Public (state funded) 463 52.3
Independent 319 36.1
Private 103 11.6
School years Initial Phase (1st and 2nd year primary school, ages 6-7) 168 19
Middle Phase (3rd and 4th year primary school, ages 8-9) 236 26.7
Upper Phase (5th and 6th year primary school, ages 10-12) 481 54.3

The mean age of the participants' children was 9.28 years old (SD = 1.75) and The mean age of starting to use smartphones was 6.77 years (SD = 2.3). It is worth noting that, as Table 1 indicated. Table 1 shows the main sociodemographic characteristics of the study participants' children.

Instrument

The data were collected using a questionnaire created for the study in various topic blocks: identification of smartphone use, time spent using the device, activity and tasks done using the smartphone, parental rules and control of smartphone use, smartphone use habits, and benefits and dangers of smartphones. These blocks were preceded by a section for collecting the parent's and child's sociodemographic data.

The multiple choice items analyzed in the present study were in the block about parental controls and rules for smartphone use (see Table 2).

Table 2. Descriptive statistics with frequencies and percentages about the types of parental control mechanisms use in relation to their children's smartphone use 

Yes No
n % n %
Choose when children can or cannot use their device 615 69.49 270 30.51
Set limits on internet use, searches, and applications 432 48.81 453 51.19
Use applications or messages the can block unwanted or adult content 252 28.47 633 71.53
Control or blocking calls and SMS messages 91 10.28 794 89.72
Use device tracking and location services 86 9.72 799 90.28
Produce daily reports of children's smartphone activity 106 11.98 779 88.02
Use passwords, PINs, or passcodes for smartphone access 460 51.98 425 48.02

The validation process for the instrument addressed questions such as content validity, construct validity, and internal consistency. The questionnaire was validated by a panel of eight international specialists who were experts in research methodology and educational technology. They examined aspects such as each item's uniqueness, relevance, and importance (Fleiss' Kappa = .848), and provided various comments that helped us to modify, restructure, and optimize the initial content of the questionnaire. We also performed a pilot study (n = 250) that helped improve the final instrument via the respondents' observations and responses. In addition, we performed various exploratory and confirmatory factor analyses on the items in the questionnaire that met the necessary measurement requirements (Muñoz-Carril et al., 2022). We also calculated the index of internal consistency using Cronbach's alpha, which gave an adequate level of reliability (α = .797).

Procedure

The questionnaires were administered during January and February 2020 to parents of primary-school children to ascertain the types of parental control mechanisms that were being applied to children's smartphone use. They were applied before and after school, when parents accompanied their children to and from the school gates. We also contacted parent groups, and where access was needed to school premises, we sought permission from the school authorities.

After confirming that the person being surveyed had children of the required age who used smartphones, we explained the study aim in detail (as a prior step to applying the questionnaire), and asked for voluntary participation, making it clear that the data would be collected completely anonymously and in line with data protection legislation and ethics. Parents were assured that the questionnaire would not collect any identifying or personal information and that they were free to not give an answer to any of the questions. They were also told that they could freely decide to stop answering at any time or even revoke their informed consent (in which case the collected answers would be destroyed).

Data analysis

To address the study objectives, and given the categorical nature of the study variables, we performed a descriptive analysis (frequencies and percentages) and bivariate analysis via Chi-squared tests (setting the significance level at 5%). Cramer's V statistics and the Gamma test were used to measure effect size. The statistical treatment was done using Microsoft Excel for Office 365, SPSS v.20, and JASP v.0.14.0.0.

Results

Results of the descriptive analysis of parental control mechanisms

As Table 2 shows, the most commonly-reported mechanisms by the parents were Choosing when children could and could not use the device (69.49%); Using passwords, PINs, or passcodes to control access to smartphones (51.98%), and Setting limits on internet use, searches and applications (48.81%).

The least-commonly used parental control mechanisms were Device tracking and location systems (9.72%), Blocking or control of calls and SMS messages (10.28%), Producing daily reports of their children's smartphone activity (11.98%), and finally Using applications or mechanisms for blocking unwanted or adult content (28.47%).

A more detailed analysis (see Table 3) shows that 93.7% of the parents used some kind of parental control mechanism (indicated in Table 2) to regulate their children's smartphone use. The data confirms the importance parents place on implementing mediation strategies to supervise the content their children are exposed to, as well as the types of interactions they have about using their devices.

Table 3. Frequencies and percentages for the number of parental control mechanisms used 

n %
No parental control mechanism used 56 6.3
Uses one parental control mechanism 255 28.8
Uses two parental control mechanisms 248 28
Uses three parental control mechanisms 210 23.8
Uses four parental control mechanisms 72 8.1
Uses five or more parental control mechanisms 44 5
Total 885 100

Results of bivariate analysis of parental control mechanisms for smartphone use

In order to identify statistically significant differences between the variables in Table 4, we performed bivariate analysis via the Chi-squared test for independence.

Table 4. Test variables used in the study with their respective re-coded categories 

Independent variables Dependent variables
Time spent connected with a smartphone <=3 hours Level of parental control Low parental control
>3 hours Medium parental control
High parental control
Parents' educational attainment Low
Moderate
High
Children's school year Initial phase (1st and 2nd year primary)
Middle phase (3rd and 4th year primary)
Upper phase (5th and 6th year primary)

The results indicate that there was a significant relationship between the Time spent connected with a smartphone and the Level of parental control, χ2(2) = 9.57, p = .008, with a small effect size (Cramer's V = .106). Children whose parents were less strict in applying control measures tended to use their smartphones for more than three hours a day, unlike children whose parents applied more control mechanisms Table 5.

Table 5. Contingency table: Time spent connected with a smartphone * Level of parental control 

Level of parental control
LOW MODERATE HIGH
Time spent connected with a smartphone <= 3 hours Count 250 395 111
Expected frequency 259.9 393.9 102.2
% within Time spent using smartphone 33.1 52.2 14.7
% within Level of parental control 84.7 88.4 95.7
Corrected residuals -2.2 0.2 2.7
> 3 hours Count 45 52 5
Expected frequency 35.1 53.1 13.8
% within Time spent using smartphone 44.1 51 4.9
% within Level of parental control 15.3 11.6 4.3
2.2 -0.2 -2.7

There were also statistically significant differences in the Level of parental control according to Parents' educational attainment2(4) = 15.394, p = .004). These differences are shown in Table 6. To measure the strength of the association between the two variables, the Gamma test gave a value of Gamma = .117 (p < .05), which is a small effect size.

Table 6. Contingency table: Parents' educational attainment * Level of parental control 

Level of parental control
LOW MODERATE HIGH
Parents' Educational attainment LOW Count 30 20 8
Expected frequency 20.4 30.0 7.6
% within Parental educational attainment 51.7 34.5 13.8
% within Level of parental control 9.6 4.4 6.9
Corrected residuals 2.7 -2.7 0.2
MODERATE Count 154 248 46
Expected frequency 157.4 231.8 58.7
% within Parental educational attainment 34.4 55.4 10.3
% within Level of parental control 49.5 54.1 39.7
Corrected residuals -.5 2.2 -2.5
HIGH Count 127 190 62
Expected frequency 133.2 196.1 49.7
% within Parental educational attainment 33.5 50.1 16.4
% within Level of parental control 40.8 41.5 53.4
-0.9 -0.8 2.5

Finally, there were statistically significant differences in the level of parental control according to the children's school year, χ2(4) = 10.906, p < .05, with a small effect size (Gamma = -.021). As Table 7 shows, parents applied more control mechanisms with pre-adolescent children who were in the last two years of primary education (5th and 6th year).

Table 7. Contingency table for the variables: School year * Level of parental control 

Level of parental control
LOW MODERATE HIGH
School year Initial phase (1st and 2nd year primary) Count 64 71 33
Expected frequency 59 86.9 22
% within School year 38.1 42.3 19.6
% within Level of parental control 20.6 15.5 28.4
Corrected residuals 0.9 -2.7 2.8
Middle phase (3rd and 4th year primary) Count 81 127 28
Expected frequency 82.9 122.1 30.9
% within School year 34.3 53.8 11.9
% within Level of parental control 26 27.7 24.1
Corrected residuals -0.3 0.7 -0.7
Upper phase (5th and 6th year primary) Count 166 260 55
Expected frequency 169 248.9 63
% within School year 34.5 54.1 11.4
% within Level of parental control 53.4 56.8 47.4
Corrected residuals -0.4 1.5 -1.6

It is worth noting that, as Table 1 indicated, the six school years were re-coded in three categories: initial phase (1st and 2nd years), middle phase (3rd and 4th years), and upper phase (5th and 6th years). There is a link with age, as the initial phase covers ages 6 to 7, the middle phase covers 8 to 9 year-olds, and the upper phase is for 10 and 11 year-olds.

Discussion

Smartphones have become largely intrinsic and integral to family life. This means a significant challenge for parents, who are responsible for setting up mechanisms of parental mediation and control that not only help to avoid problems, but also provide a safe digital environment for their children, as well as seeking education based on critical, responsible use of the technology (Livingstone & Bloom-Ross, 2020; Sánchez-Valle et al., 2017).

Bearing that in mind, the results of our study showed that 93.7% of parents used a variety of strategies to regulate their children's smartphone use, which shows the importance parents attach to setting guidelines on using these devices. The most commonly used mechanisms were limiting screen time, setting times for device use, and using passwords for smartphone access. The importance of parental mediation in digital society is also reflected by other studies, such as Condeza et al. (2019) in Chile, where a large proportion of surveyed parents showed that the main parental mediation practices in Information and communications technology (ICT) use included checking what their children did on the internet (89.7%) and using applications to block what they felt was inappropriate content (63.7%).

Our study was able to identify various factors that affect the extent of parental control, such as parents' educational attainment, how long the children spend online on their smartphones, and what year the children are in at school. More specifically, and in line with previous research (Jiménez-Morales et al., 2020), greater parental educational attainment increases the likelihood of using various parental mediation and control measures, with the educational level of the parents being closely related to their digital competence, which is another predictor of mediation (Dedkova & Smahel, 2020). In this regard, greater levels of digital self-efficacy in the parents mean putting different types of mediation actions into practice, including those involving control and tracking (Nikken & Schols, 2015; Talves & Kalmus, 2015).

This alerts us to a digital socio-educational divide, which is why it should be a priority to provide digital skilling to all families, especially those in vulnerable situations. In line with this, other studies (Glatz et al., 2018) have reported that parents educational levels are positively related to all of the strategies that they use to mediate their children's online activity, except for active mediation. Those authors noted that when parents used mediation strategies they were able to gain a deeper understanding of the possible risks their children faced online, and that this understanding could be linked to the perception of how much influence they had over their children's online activity.

Our results in relation to how long children spend connected each day show that there was a significant relationship between the number of hours children were online via smartphone each day and the level of parental control. Children whose parents used more parental control mechanisms tended to use their smartphones for less time that children whose parents were less strict in applying controls. A recent study by Álvarez et al. (2020) concluded that the time children spent in front of screens had negative effects on the development of their social skills, which shows how important it is for families to monitor times and establish certain strategies to control screen time. However, it is also important not to demonize or focus solely on risks and possible harm that might come to children from irresponsible smartphone use, as these devices also offer notable educational, cultural, and communicative potential (Criollo-C et al., 2002). It is a technology that also offers applications where children can, among other things, develop their creativity, improve their digital skills, forge their own identities, and project their own personalities and concerns. As Martín-Ramallal and Ruiz-Mondaza (2022) put it, “Minors must enjoy all rights and freedoms, and they must be provided with guarantees for their self-realisation” (p. 31). From this point of view, the family's role is key in providing active measures (not only restrictive, control, or tracking measures) that reinforce the child's autonomy and personal growth within a framework of trans-media literacy.

Finally, we found that parents applied more control mechanisms to children aged 10 to 12 years old, in the final years of primary education (5th and 6th years). In line with this, the study by Glatz et al. (2018) identified the school year (as an indicator of age) as a variable that was correlated to the level of parental mediation, with parents of adolescent children in later school years (17 and 18 years old) taking fewer control-based mediation actions compared to the higher level of monitoring parents did of children in lower school years (11 to 12 years old). The study by Smahel et al. (2020) similarly noted that families used more rules and were more inflexible with younger children than adolescents. This may be because of greater respect for older children's privacy and autonomy, who are also considered to be more digitally competent (López-De-Ayala et al., 2019; Ramos-Soler et al., 2018) and therefore supposedly able to avoid negative consequences of their smartphone or digital device use (Rodríguez-de-Dios et al., 2018; Sonck & de Haan, 2014).

It is clear that parental mediation is a reality for families, evidence of a growing social concern. However, children's digital education must include measures of co-responsibility that incorporate schools, public administrations, and the companies that design the technology; and it must have the children's active participation in the process (Livingstone & Bloom-Ross, 2020). Similarly, educating parents in the skills needed to properly use these technologies is crucial (Condeza et al., 2019). This will allow them to positively assess the technology's benefits, not just its risks, make decisions about parental styles to apply and, in short, more effectively guide their children's development towards autonomy in a hyperconnected world.

Acknowledgements

This article was produced as part of the “IV Convocatoria de Proyectos de Innovación Educativa en Aprendizaje-Servicio (ApS)” by the University of Santiago de Compostela.

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Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Received: May 09, 2023; Revised: September 12, 2023; Accepted: October 03, 2023

* Corresponding author: Pablo-César Muñoz-Carril. Facultade de Formación do Profesorado, Universidade de Santiago de Compostela, Avda. Ramón Ferreiro, s/n, 27002, Lugo, Spain. pablocesar.munoz@usc.es

Declaration of interests

The authors declare that there is no conflict of interest.

Data availability statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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