Why do we resolutely prevent minors from indulging in online games

1 INTRODUCTION

In China, the Internet penetration rate of minors was 99.3% in 2020, much higher than the overall country level of 64.5% (Ji & Shen, 2020), and 41.8% of the juvenile netizens play online games. Another report estimated a much higher ratio of minors playing online games: 62.5% (Department for the Protection of Youth Rights and Interests of the Central Committee of the Communist Youth League and China Internet Network Information Center, 2021). In 2018, the National Health Commission of the People's Republic of China announced that the prevalence of Internet overdependence among adolescents in China was 10%, higher than the global average of 6% (National Health Commission of the PRC, 2018). In the same year, some scholars found that the prevalence rates of problematic online gaming in China ranged from 3.5% to 17%, significantly higher than the global average of 0.7%–15.6% (Long et al., 2018).

All of these indicate that Chinese minors have been deeply involved in online games. It is a consensus in the scientific community and is also in line with our common sense that online games may bring negative effects on players. In 2008, China issued the Proposed Diagnostic Criteria for Internet Addiction, formally incorporating game addiction into the diagnosis scope of mental diseases. In 2013, the American Psychiatric Association recognized Internet gaming disorder (IGD) as a mental disease.

In 2018, the World Health Organization (WHO) recognized gaming disorder as a mental health condition, describing it to be a clinically recognizable and clinically significant syndrome that may lead to notable mental pain and cause significant impairment in personal, family, social, educational, occupational or other important areas of functioning. The WHO also noted that health concerns associated with gaming behavior are not limited to gaming disorder, but also include insufficient physical activity, unhealthy diet, problems with eyesight or hearing, musculoskeletal problems, sleep deprivation, aggressive behavior and depression, and psychosocial functioning (WHO, 2018).

In particular, online games are more addictive than single-player games. In the pre-Web era, game makers mainly profited by selling game software. In the Web 2.0 era, when fee-based games are giving way to free games, game makers mainly profit from purchasing items in free-to-play online games. This profit model determines that addiction becomes the only goal of online games, which are designed to keep players investing time, energy, and money in exchange for resources in the games. Moreover, compared to paid games, free online games are more attractive to underage players without free access to money.

Given the unprecedented deep involvement of minors in online games with hazards that cannot be underestimated, parents are generally worried that online game addiction will harm the physical and mental health as well as the overall development of their children.

Yet preventing minors from indulging in online games is not only urgent but also arduous as game makers cast about for packaging the games as harmless or even beneficial. For example, a number of famous scholars were ever engaged as historical advisors to crown the Honor of Kings with academic elements. Some “academic” journals published studies that were neutral to or supportive of video games, for example, proving game addiction as a fallacy through literature research (Cover, 2006). Han and Shu (2015) found that the increasingly tolerant public opinion on online games from 2004 to 2013 in China influenced parents' attitudes and thus eased the pressure of parental objection on minors while they were playing games. Even the government recommended “suitable online game products for minors” to the society (Xinhua News Agency, 2008). There is no denying that much credit goes to years of capital propaganda.

Parents are the primary guardians of minors' physical and mental health. However, they as individuals are not able to wrestle with powerful game makers, thus the government must step in to regulate the capital. Recently, China has been vigorously rectifying the online game industry. On August 3, 2021, Economic Information Daily, one of the authoritative comprehensive economic media in China, published an article entitled A “Spiritual Opium” Has Grown into an Industry Worth Hundreds of Billions of Dollars, calling attention to the negative effects of online games on minors; on August 30, 2021, the National Press and Publication Administration issued the Notice on Further Strict Management to Effectively Prevent Minors from Being Addicted to Online Games (hereinafter referred to as “the Notice”), requiring that online game providers should be allowed to offer only 1-h services to minors from 8 p.m. to 9 p.m. on Fridays, Saturdays, and Sundays, as well as on official holidays, and that families, schools and all other sectors of society should practically fulfill the duties for guardianship of minors and thus create synergy in preventing minors from indulging in online games.

The Notice demonstrates the Chinese government's boldness and execution in restricting capital for the benefit of the people and its original intention of government administration for citizens. In such a policy context, by quantitatively portraying the mechanism for negative effects of video games on minors, this paper assesses the possible interaction between the national policy of restricting online games and families, and makes recommendations on how families and schools create an antiaddiction synergy with the government to effectively protect the physical and mental health of minors.

The rest of the paper is organized as follows. Section 2 reviews the relevant literature. Section 3 provides an empirical analysis on the correlation between children's school performance and their addiction to online games. Section 4 conducts the analytic hierarchy process and Section 5 concludes.

2 LITERATURE

Literature in the field of law includes studies on the legislation for online games from the viewpoint of minor protection, the impact of online games on minor crime, and countermeasures. For example, Liang and Chen (2021) constructed a legal regulation system for online games in China from the perspective of children's right to development: a “multiple, subtle and unified” identity authentication mechanism, a “green and healthy” hierarchical management system, a refined timing restriction system, standardized charging restriction measures, and a relief mechanism for refund. After analyzing the typical cases of minors committing crimes due to indulgence in online gambling games, Zhang and Hu (2021) pointed out that the following problems existed in preventing minor crime caused by online games: a conflict between special protection for minors and the criminal policy featuring severe punishment for cybercrime, the immature legal mechanism for handling minors' cases, a defective disposition of the cascading and recursive function of minors' crimes, and so on. They proposed to start with creating an Internet governance pattern of coconstruction, cogovernance and sharing to prevent minors from online game crimes by such means as promoting an effective linkage between specialized handling of cases and socialized assistance and education, encouraging professional social work organizations to participate in the governance of online game crimes by juveniles, urging the government, network information service providers and premises for Internet access services to strengthen monitoring and protection of minors, giving play to the role of procuratorial suggestion, and drawing on “Fengqiao Experience.”

Studies in the field of communication use communication theory to analyze how online games attract minors. For example, Yan and Huang (2013) pointed out that violent online games may imperceptibly change the mindset and behavior of adolescents (i.e., cultivation), leading them to violence. Psychological roots of such cultivation include the social neglect of violence in the online environment and the disguise of violence in games as heroic, chivalrous, and other socially and culturally appropriate things; the psychological effectiveness of social entertainment and psychological anesthesia in violent online games; and the capital engagement driven by profiteering of violent online games, which is a strong catalyst for the violent cultivation of adolescents.

Research in the field of teaching mainly discuss the feasibility and means of using online games to serve teaching. For example, Song (2006) argued that online games can be used for ideological and political education. Ma and He (2005) believed that online games can be used as a supplementary curriculum resource as long as they are designed with vivid plots around the theme and are morally in line with the real social culture.

Quantitative research focus on psychometrics and medicine. In particular, psychometric research mainly analyze scale data with (moderated) mediated models to study the psychosocial factors influencing gaming addiction among minors which mainly include family, school, peers, and subjective factors of minors, along with a corresponding prevention mechanism.

In terms of family, Deng et al. (2021) found that parental autonomy support may create a safe and free family environment that is correlated with children's low-level online game addiction, while parental psychological control may increase addiction of adolescents to online games as their autonomy needs are not met, and that the effect of the latter is stronger than that of the former. Yin and Xian (2021) found that parental psychological malaise increases the likelihood of children's online game addiction. Liang et al. (2019) found that parental psychological control exacerbates the risk of adolescents' online game addiction by reducing their academic self-efficacy, undermining their confidence in learning, and increasing the likelihood of their escaping reality through online games, while a healthy and positive parent–child relationship is a requisite for high academic self-efficacy and reduces the negative effects of parental psychological control to some extent. Similar studies recommend parents establish a healthy parent–child relationship, properly maintain psychological health of themselves and their children, and avoid the adverse effects of negative parenting styles such as over-control.

In terms of school and peers, Wang et al. (2020) found that peer victimization might lead to adolescents' indulgence in online games by reducing satisfaction of their psychological needs, while high emotional intelligence can buffer the negative effects of peer victimization to a limited extent. Zhang et al. (2018) found that a benign teacher–student relationship encourages students to invest more time and energy in school affairs, thus reducing the risk of students' online game addiction, and students with high future orientation tend to care more about the impact of their current behavior on the future and have certain ability to resist online game addiction. Zhu et al. (2015) found that a positive school climate encourages adolescents to engage in school affairs, which leads to low pathological online game use; a good mother–child relationship enhances the positive effects of school climate on adolescents' school engagement, while a poor father–child relationship magnifies the negative effects of low school engagement. These studies indicate that intervention measures should be taken to reduce peer victimization, positive peer effects should be fostered to produce positive incentives for youngsters, teachers' care for students should be strengthened so as to create a positive and healthy school climate, thus engaging students in more school activities and minimizing their inappropriate use of online games.

Regarding subjective factors of minors, Wei et al. (2016) found that left-behind children with a stronger sense of gratitude have a higher sense of school belonging and are less likely to pathological online game use. Zhang et al. (2015) found that adolescents with low self-esteem tend to obtain virtual self-esteem from online games and are thus more inclined to indulge in online games.

Studies in the field of medicine focus on two aspects: (1) Exploring the mechanism for online game addiction by use of magnetic resonance and other techniques. For instance, Qian et al. (2008) found a much higher activation level of specific brain regions in addicted adolescents than ordinary adolescents while they are watching game videos, and located the brain regions that constitute the “reward system” of addiction to online games through functional magnetic resonance imaging (fMRI). (2) Seeking for treatment methods for online game addiction. For instance, through clinical trials Wang et al. (2014) found psychological intervention combined with medication more effective than medication or general psychological talk alone in the treatment of Internet addiction.

Based on analyses of existing literature, we have found that studies on the effects of online games on Chinese adolescents, more often than not, are qualitative rather than quantitative. Existing quantitative studies mainly explore the characteristics of the mechanism for online game addiction of adolescents and propose countermeasures based on the data of psychometric scale, with subjective and psychological factors of the adolescents, family, school, peers and the like taken into consideration.

This paper provides data on parental perception of how severe online games affect the study and life of adolescents, which is missing in existing studies. To exercise joint management by schools and families, we need to clearly understand the parental psychological perception of and expectation for children's addiction to online games. Moreover, out of blood linkage, parents naturally care for their children and are convenient to know their children's daily life. As the first teachers of their children, they are irreplaceable models during the growth of their children. Driven by both subjective and objective factors, their opinions are valuable and indispensable in addressing adolescent Internet addiction. The data and empirical analysis in this paper can serve these purposes.

3 CHILDREN'S ADDICTION TO ONLINE GAMES AND THEIR SCHOOL PERFORMANCE: AN EMPIRICAL ANALYSIS

To probe into the correlation between children's school performance and their addiction to online games, we collect the data from China Family Panel Studies (CFPS) in 2016. CFPS is a nationally representative, biannual longitudinal survey of Chinese communities, families, and individuals launched in 2010 by the Institute of Social Science Survey (ISSS) of Peking University, China. CFPS has been widely adopted to study the wellbeing of the Chinese population, with a wealth of information covering education outcomes, family dynamics and relationships, migration, and health.

The data provide information on how often a child accesses to online entertainment (measured as seven levels: almost every day, 3–4 times per week, 1–2 times per week, 2–3 times per month, once a month, once several months and never), his/her school performance (measured by grade rank in class, that is, top 10%, 11%–25%, 26%–50%, 51%–75%, and beyond 75%), and his/her parents' response to “do you think it is important to accompany your children” (measured as five levels: definitely agree, agree, neutrally, do not agree and do not agree at all). The information on his/her state of health and province of origin is also collected. About 30% of children in the sample have online entertainment almost every day, and only 8.9% never have online entertainment. Obviously, the online entertainment penetration rate is high among children in China.

We then regress children' school performance on their frequency of accessing to online entertainment with both linear regression model and ordered-probit model, and the results are reported in Columns (1) and (2) of Table 1, respectively. The coefficients estimated on children' frequency of accessing online entertainment are both negative and statistically significant, indicating that a higher frequency in getting online entertainment would lead to worse school performance. We further re-estimate the model by adding more control variables, such as parents' opinions on accompanying their kids, state of health fixed effect, and origin province fixed effect. The estimation results are reported in Columns (3) and (4) of Table 1. Even with the control variables, the coefficients estimated on children's frequency of accessing online entertainment remain negative and statistically significant, further confirming the basic results that more frequent online entertainment leads to worse school performance. In addition, better school performance is achieved when parents think it is important to accompany their children. Robust standard errors are applied in all estimations.

4 ANALYTIC HIERARCHY PROCESS (AHP)

4.1 Theory

AHP is used in the empirical analysis of this paper. AHP is a multicriteria decision-making approach proposed by the American scholar Thomas L. Saaty (1977), where weights can be assigned to multiple factors simultaneously to facilitate decision-making. Since its premiere, AHP has found wide applications in many natural and social science fields. For the purpose of practical application, the elements of a judgment matrix are generally taken from a finite set, which is called a finite scale.

Mao et al. (2020a) considered a family of finite scales

()

where denotes the set of judgment matrices whose elements take values from the finite scale set of Equation (1) that satisfy the positive reciprocity property. The matrices in are referred to as the procrustean judgment matrices, abbreviated as PJ matrices1.

Mao et al. (2020a) proved that any PJ matrix is either derived by an infinite number of or cannot be derived by any . A PJ matrix that cannot be derived by any is called a contradiction matrix (Mao et al., 2020b, 2020c). A contradiction matrix cannot provide any useful information about weight vectors, thus we should avoid using it in hierarchical analysis.

4.2 Empirical analysis

4.2.1 Hierarchy description

Using convenience sample, this paper collects some data on parental perception of how severe video games affect the study and life of Shanghai senior high school students, to assess the mechanism for and the severity of negative effects of video games on them.

There are four major negative effects: physical health, academic performance, family relationships, and teacher–student relationship. Each of them is subdivided into several subcategories.

• (1)

  Damage to Physical Health

• [1]

  Eyesight problems, such as nearsightedness, dryness, and soreness of eyes due to long screen time;

• [2]

  Sleep problems, such as sleep deprivation and disruption of body clock due to game play by sacrificing sleep;

• [3]

  Diet problems, such as irregular meals and even gastrointestinal digestive disorders due to indulgence in games;

• [4]

  Muscle strain, such as muscle damage to the waist, wrist, elbow, cervical spine, and so on due to maintaining a tense posture for a long time;

• [5]

  Exercise problems, such as reduction or absence of sports and loss of sports habit due to indulgence in games;

• (2)

  Decline in Academic Performance

• [6]

  Difficulty in completing homework on time;

• [7]

  Poorer quality of homework;

• [8]

  Reduction in extracurricular reading;

• [9]

  Delay in extracurricular tutoring;

• (3)

  Deterioration of Family Relationship:

• [10]

  Little participation in housework;

• [11]

  Quarrels with parents;

• [12]

  Avoidance of parental criticism;

• [13]

  Disruption of family atmosphere, such as less verbal communication and fewer family outdoor activities due to tension with parents and elders.

• (4)

  Deterioration of Teacher–student Relationship

• [14]

  Lack of attention in class, such as failure to understand the in-class content due to absent-mindedness and doze;

• [15]

  Inactivity in class, as evidenced by reluctance to raise hands to ask or answer questions posed by the teacher;

• [16]

  Avoidance of after-class communication with headteachers, class teachers, grade deans, school leaders, and so on.

The questionnaire is so designed that the two aspects in comparison (e.g., “Decline in academic performance” and “Damage to physical health”) are put on the left and right, respectively, and parents then check the textual expression that best matches their own judgment. There are nine textual expressions: “The left is absolutely severe,” “The left is significantly severe,” “The left is quite severe,” “The left is slightly severe,” “Both sides are equally severe,” “The right is slightly severe,” “The right is quite severe,” “The right is significantly severe,” and “The right is absolutely severe.” These textual expressions correspond to a limited scale . The questionnaire hierarchy is shown in Figure 1.

4.2.2 Description of calculation methods

We calculate the weight vectors under a total of eight scenarios (Table 2) based on the methods used to aggregate the opinions of multiple decision makers (quasi-AIP and AIJ, which are defined below Table 2) and the processing of original data (no processing, adjusted to consistent matrices and removing inconsistent matrices, and removing contradictory matrices).

Table 2. Eight scenarios for calculating importance weight vectors

	Opinion aggregation method		Original data processing method
No.	Quasi-AIP	AIJ	No processing	Adjusted to consistent matrices	Removing inconsistent matrices	Removing contradiction matrices
1	✓		✓
2	✓			✓
3	✓				✓
4	✓					✓
5		✓	✓
6		✓		✓
7		✓			✓
8		✓				✓

Additional notes to the calculation of weight vectors:

• (1)

  Opinion aggregation method

  AIJ, or aggregate individual judgments, refers to aggregating the judgment matrices of multiple decision makers into one by geometric averaging, and treating all the judgment matrices obtained by aggregation as a new hierarchy to calculate weight vectors.

  AIP, or aggregate individual priorities, refers to calculating the weight vectors of all decision makers' bottom solutions to the top objective separately, and then aggregating these total weight vectors into one by geometric or arithmetic averaging.

  Quasi-AIP also aggregates the weight vectors of multiple decision-makers. Instead of aggregating the weights of all decision makers' bottom solutions to the top objective, it aggregates the weight vectors of all decision-makers derived from each judgment matrix by arithmetic averaging, and finally calculates the final weight vectors by weighted averaging using a series of aggregated weight vectors. Quasi-AIP was used because there were some decision makers with incomplete hierarchy after the removal of inconsistent and contradictory matrices. If AIP is used, all matrices not removed from an incomplete hierarchy will be invalidated. To make full use of data, we used the quasi-AIP in scenarios 1 to 4. For a detailed comparison of AIJ and AIP, see Forman and Peniwati (1998).

• (2)

  Consistency

In this paper, the consistency ratio (CR) of Saaty (1977) is used to test matrix consistency. Method of adjusting an inconsistent matrix to a consistent matrix:

• [1]

  Treating one element of the judgment matrix as a missing value, and determining what value it should be corrected to by use of the method of Harker (1987) to fill in the missing value.

• [2]

  Calculating the corresponding replacement value for each element of the judgment matrix, and the CR value under the corresponding replacement value.

• [3]

  Implementing the replacement scheme. In the case that replacing a certain element can make the corrected judgment matrix consistent (i.e., CR < 0.1), the scheme is selected for implementation, which both minimizes the difference between the replacement judgment and meets the condition that the original judgment and the judgment matrix obtained after the replacement is consistent; in the case that replacing any element cannot make the corrected judgment matrix consistent, the scheme that makes the greatest decrease in is selected for implementation.

• (3)

  In each scenario, we use three common methods to calculate the weights, that is, eigenvector method (Saaty, 1977), the geometric mean method (Crawford & Williams, 1985), and product method (Zahedi, 1986). Weights estimated by all three methods are similar in a given scenario. Therefore, we only present the results using eigen vector (EV) method in the main text section.

4.2.3 Calculation results and interpretation

Table 3 lists the number and proportion of base consistent matrices and noncontradictory matrices.

Table 3. Number and proportion of consistent matrices and noncontradictory matrices in game data

Judgment matrix No.	1	2	3	4	5
Consistent matrices	23	18	25	21	21
	0.74	0.58	0.81	0.68	0.68
Noncontradictory matrices	12	15	9	8	4
	0.39	0.48	0.29	0.26	0.13

Table 4 lists the three most and least affected aspects.

Table 4. Middle school students' most and least affected aspects by video games, and corresponding weights

Scenario No.	Top 3			Last 3
1	Lack of attention in class	Avoidance of after-class communication with teachers	Inactivity in class	Diet problems	Muscular strain	Little participation in housework
	0.085	0.073	0.069	0.048	0.05	0.053
2	Lack of attention in class	Avoidance of after-class communication with teachers	Poorer quality of homework	Diet problems	Muscular strain	Little participation in housework
	0.074	0.073	0.072	0.05	0.052	0.053
3	Lack of attention in class	Eyesight problems	Inactivity in class	Diet problems	Little participation in housework	Muscular strain
	0.078	0.078	0.076	0.047	0.051	0.054
4	Lack of attention in class	Avoidance of after-class communication with teachers	Inactivity in class	Diet problems	Muscular strain	Sleep problems
	0.1	0.088	0.079	0.043	0.05	0.05
5	Lack of attention in class	Poorer quality of homework	Reduction in extracurricular reading	Diet problems	Muscular strain	Little participation in housework
	0.082	0.073	0.073	0.047	0.051	0.052
6	Poorer quality of homework	Reduction in extracurricular reading	Lack of attention in class	Diet problems	Muscular strain	Little participation in housework
	0.078	0.078	0.07	0.049	0.051	0.052
7	Lack of attention in class	Inactivity in class	Eyesight problems	Diet problems	Little participation in housework	Muscular strain
	0.077	0.076	0.075	0.046	0.049	0.054
8	Lack of attention in class	Avoidance of after-class communication with teachers	Inactivity in class	Diet problems	Muscular strain	Sleep problems
	0.099	0.086	0.081	0.043	0.049	0.05

“Lack of attention in class” is the only element in Top 3 in all eight scenarios, and is unanimously considered to be the most affected aspect by video games. Other aspects in Top 3 in many scenarios include “Avoidance of after-class communication with teachers,” “Inactivity in class” and “Poorer quality of homework.”

“Diet problems” is unanimously considered to be the least affected aspect, and “Muscular strain” and “Little participation in housework” are also considered to be the least affected aspects.

According to the calculation results, we obtain the following findings:

• (1)

  According to Table 3, there is a considerable number of contradiction matrices that cannot provide useful information about weight vectors. To improve data quality, interventions may be taken in the data collection process to prevent contradiction matrices. A feasible method is to intervene at the data collection stage by such means as real-time feedback and graphical aids to ensure that the judgment matrices provided by the decision makers are noncontradictory. For example, when judgments among experts are contradictory, experts will be prompted in real time the simultaneous existence of which judgments causes contradiction and provided with suggestions for correction. How to eliminate contradiction matrices in the data collection process is one of the future research directions of AHP theory.

• (2)

  Teacher–student relationship is considered to be most negatively affected by games. Low weights for events that occur outside of home or school, including family relationships, diet and sleep associated with physical health, and extracurricular reading, directly indicate that parents highly value their children's performance at school and worry that addiction to games will affect their children's interaction with teachers and thus affect their children's normal learning. This indirectly reflects the mindset of parents who feel out of control of their children's school education.

  Game addiction can exert a severe negative impact on physical and mental health of students; it is possible for the game players to skip a meal or two, or to suffer muscle strain and injuries. Time and again there are also news reports of extreme cases of youngsters gaming to death for lack of self-control. Generally, parents would not be indifferent to their children's physical and mental health, but the relevant weight is rather low. Possibly, when children are at home, parents have the ability to control them effectively and prevent them from game addiction so that their normal life will not be affected.

  However, they cannot intervene when their children are at school. Factors with low weights including the avoidance of after-class communication with teachers, inactivity in class, and poorer quality of homework, all occur at school and parents can hardly intervene (for lack of sufficient test-taking skills, many parents could not help address the problem of poor quality of their children's homework). People are always anxious about what is beyond their control. Therefore, parents are particularly worried about their children's performance at school and thus regard school-related activities as a weak link vulnerable to the negative effects of game addiction.

• (3)

  The competence of control over their children's behavior at home is related to which cities the parents are from. Parents of Shanghai high school students usually live with their children, and even with their parents to help with household chores. They have the objective conditions to prevent their children from being overly addicted to games at home. The situation is different for left-behind countryside children whose parents work in cities. Their guardians (maternal) grandparents have limited knowledge of new things such as online games and tend to spoil their grandchildren, making it difficult to implement effective discipline for children. The physical health of left-behind children addicted to games merits attention. For example, Xin et al. (2019) found through a sample survey that left-behind children in rural areas of western Hunan had higher reported rates of poor dietary habits such as skipping breakfast and partial eating than general children, and there were higher reported rates of Internet access among left-behind boys and lack of exercise among left-behind girls than general children.

• (4)

  The low weight of housework is attributed to the fact that high school students rarely undertake housework. Parents generally value academic performance and do not require their children to do housework. In dual-earner families in urban areas, housework is often done by (maternal) grandparents or domestic helpers. Even if not engaged in video games, high school students do not do much housework and therefore video games have little impact on their participation in housework.

• (5)

  Adjusting the inconsistent matrices to consistent matrices and removing inconsistent matrices results in a large difference in the final ranking of the weight of “Eyesight problems.” Specifically, “removing inconsistent matrices” contributes to a high weight of “Eyesight problems,” which is above 0.07 and ranked in Top 3, while in other scenarios it is between 0.05 and 0.07, at a middle to low level. This indicates that matrices not up to the consistency defined by CR contain judgments with a significant impact on the weight of “Eyesight problems.” These judgments remain to have an impact after consistency correction. Since noncontradiction is a better criterion for judging fitness matrices compared to CR values, we should accept the estimated weight vectors without removing inconsistent matrices, that is, the ranking of eyesight problems is generally lower in the eyes of parents.

5 CONCLUSIONS AND RECOMMENDATIONS

This paper clarifies the necessity and arduousness of preventing minors from being addicted to online games, and points out that the only way out is for the government and the family to work in tandem. The recent policy adopted by the central government directly makes restrictive requirements on the operation of game providers so as to reduce the exposure of minors to online games at the source. This key step to address the problem at root and to act in a mutually beneficial way provides a favorable policy environment for preventing minors from indulging in online games.

AUTHOR CONTRIBUTIONS

Moye Li: Conceptualization; Data curation; Formal analysis; Methodology; Visualization; Writing – original draft. Mingxiong Zhu: Conceptualization; Methodology; Project administration; Supervision; Writing – review & editing.

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

ETHICS STATEMENT

Not applicable.