Correlates of small screens play in 6-10 years old Chinese children

doi:10.21203/rs.3.rs-4688921/v1

Background With development of the electronic technology, the use of small or mobile devices has been widely popularized among children. The aim of this study was to explore the factors associated with small screen use and its duration among elementary school students.

Methods A total of 1121 Chinese students aged 6-10 years were recruited for this study. Logistic regression model was used to analyze the influencing factors of whether students use small screen devices and linear regression model was used to analyze the influencing factors of students' small screen time.

Results Girls (OR=0.74, p=0.035), having their own small screen devices (OR=3.66, p<0.001), unclear screen rules (OR=1.45, p<0.001), father's education level (OR=0.49, p=0.033), and mother's weekend screen time (<1 h/d as the reference group) 1-2 h/d (OR=2.49, p=0.001), 2-3 h/d (OR=2.70, p=0.001), ≥3 h/d (OR=2.27, p=0.009) were significantly associated with students’ use on screens. For total time, girls spent more time on small screens compared to boys (β=58.88, p=0.043); having their own small screen devices (β=65.47, p=0.026), the less clear the family's screen time rules (β=60.55, p<0.001), and the longer mother's weekend screen time (β=142.61, p=0.027) were associated with longer total screen time for students. Having their own small devices (OR=2.08, p=0.026) and having less clear family ST rules (OR=1.61, p=0.004) were significantly associated with a total ST on small devices of ≥ 1 hour/day.

Conclusion Availability of their own small electronic devices, clarity of family screen rules, father's education levels, and mother's weekend screen time were significantly correlated with 6-10-year-old students' screen time on small devices in China.

screen time

mobile electronic devices

smart phone

risk factors

parents

The advent of the information age and socioeconomic development has filled children's lives with electronic screens and digital media, and children spend more time on screens than ever before[1]. WHO's guidelines on physical activity levels and sedentary behavior in children and adolescents recommend that children and adolescents spend no more than 2 hours a day on a video screen.[2] A national report in China shows that the proportion of children in grades 4-12 who spend more than 2 hours a day on screen time (ST) has reached 36.8%[3]. The phenomenon of excessive ST for Chinese children (more than 2 hours) is widespread[4][5]. Previous studies have shown that excessive ST can have adverse consequences on children's health, such as a positive correlation between ST and mental health problems (depression, anxiety symptoms, and suicide tendency)[6, 7]. An article published in the Lancet in 2021 pointed out that sedentary behavior based on electronic screens is associated with obesity[8]. Excessive ST is also associated with poor sleep quality in children[9-11], cognitive development[12], and delayed development[13].

However, most existing studies focus on fixed screens, emphasizing sedentary behavior[14] or watching TV[15], and pay less attention to mobile media devices[16-18]. However, due to technological advancements, changes in lifestyles, and the widespread availability of small electronic screen devices, the devices chosen by the younger generation have gradually changed[19]. The use of mobile electronic screen devices, such as smartphones and tablets, is increasing. As early as a study in 2015, it was found that children aged 2-12 prefer watching videos on mobile electronic screen devices rather than on TV[20]. The increase in ownership and usage patterns suggests that mobile electronic screen devices have become the primary media used by children[21-23]. The potential harm of excessive mobile ST may be greater. Some recent studies have shown that the use of mobile devices may be associated with children's emotional instability, poor self-regulation[24], and delayed language development[25].

Existing research has found that children with poorer academic performance, from single-parent families, lower risk awareness of mobile devices, and parents who spend more time using computers and mobile devices will spend more time using mobile devices[26-28]. According to surveys, differences in household income can affect the types of ST spent by students. Most children from high-income families tend to watch educational content on mobile screens, while only a small proportion of children from low-income families do so[29]. Therefore, this study explored the related factors of small electronic screens use (such as mobile/smart phones, tablets, handheld video game console, etc.) and its usage time among first and second grade primary school students based on cross-sectional data, providing scientific evidence for subsequent intervention measures.

Design and participants

This study recruited a total of 1121 first and second grade primary school students. Firstly, after excluding 105 children who answered "uncertain" to the question "Have you participated in using small screen devices (such as mobile phones, tablets, etc.)", we analyzed 1016 children. Secondly, after excluding participants with missing information on the use of small screens during the school week and weekend (n=27) and outliers (>+3SD, n=9), we ultimately analyzed 325 children to explore the factors that affect their use of small screen devices. All participating parents signed an informed consent form, and the study protocol was approved by the ethics committee of Jiaxing First Hospital (2023-LY-024).

Questionnaire

The questionnaire was performed to collect relevant information, which includes: (1) Students’ gender, age, date of birth, age spent using small electronic screens se small screens, whether they own electronic products such as mobile phones, or tablets, and how much time they spend on it; (2) Parental information, including their education levels (primary school and below, junior high school, high school, college and above), ST at home on weekdays/weekends (≤1h, 1-2 hours, 2-3 hours, ≥3h), and family rules regarding children's ST (whether there are clear rules for children's ST, such as "limiting the duration of watching cartoons").The questionnaires were distributed and collected through the internet (www.wjx.cn). Considering the physical and mental development of the first and second graders, the questionnaires were filled out by their parents on their behalf.

Statistical analyses

Categories were expressed as percentages and continuous variables were expressed as mean and standard deviation. Multiple calculations (5 times) were conducted for missing values of small ST during the school week or on weekends; the inter-group comparisons of categorical variables and continuous variables were performed using the chi-square test and independent sample t-tests, respectively; logistic regression model was used to analyze the influencing factors of whether students use small screen devices or its duration ≥1 hour per day; linear regression model was used to analyze the influencing factors of students' small electronic ST. The SPSS 26.0 was used for statistical analysis and the significance level was set at p< 0.05 (two-side).

The average age of students who used and did not use small electronic screen devices was 7.35±0.55 years and 7.27±0.49 years, respectively, and there was a significant difference between the groups (t=2.36, p=0.018), see Table 1. Through chi-square tests, it was found that students who did not own their own electronic devices were more likely to not use screen devices (X²=76.15, p<0.001). Families that limited ST had a significantly higher proportion of students not using small screen devices compared to families that did not limit ST (X²=39.73, p<0.001). Additionally, parents of students who used small electronic screens were more likely to have more ST on weekends (mother: X²=26.03, p<0.001; father: X²=15.94, p=0.003).

Gender (with boys as the reference group, OR=0.74, p=0.035), having their own mobile phone (OR=3.66, p<0.001), the clarity of screen rules (unclear vs. clear, OR=1.45, p<0.001), father's education level (bachelor's degree or above, OR=0.49, p=0.033), and mother's weekend ST (<1 h/d as the reference group) 1-2 h/d (OR=2.49, p=0.001), 2-3 h/d (OR=2.7, p=0.001), ≥3 h/d (OR=2.27, p=0.009) were statistically significant in the logistic regression model, see Table 2.

In the linear regression models, for weekdays (model 1), the clarity of screen rules (β=3.69, p=0.047) and mother's education level (β=-19.41, p=0.031) were statistically significant, see Table 3. For weekends (model 2), age (β=12.49, p=0.03), the clarity of screen rules (β=18.03, p<0.001), mother's education level (β=-30.76, p=0.049), and mother's weekend ST (β=31.57, p=0.020) were statistically significant in the model. For total time (weekdays + weekends, model 3), girls spent more time on small screens on average compared to boys (β=58.88, p=0.043); having their own mobile phone or tablet (β=65.47, p=0.026), the less clear the family's ST rules (β=60.55, p<0.001), and the longer mother's weekend ST (β=142.61, p=0.027) were associated with longer total ST on small devices for students. Having their own small devices (OR=2.08, p=0.026) and having less clear family ST rules (OR=1.61, p=0.004) were significantly associated with a total ST on small devices of ≥ 1 hour/day, while father's education level (junior college vs. elemental or less, OR=0.26, p=0.042) was a protective factor against excessive ST on small devices.

The study found that having their own small electronic devices, the clarity of screen usage rules, parents' education level, and parents' own ST were significantly associated with both the use of small electronic screens and daily usage of ≥1 hour by 6-10-year-old children in China. This finding is significant for the development of future interventions aimed at limiting excessive ST on small devices among children.

In this study, it was found that whether children had their own mobile devices significantly influenced their use of mobile devices. Among the students who had their own mobile devices, the proportion of students who used small electronic screens was as high as 54.7%, while among the students who did not have their own mobile devices, only 26.4% used mobile devices. Previous studies have found that parents may give mobile electronic devices (such as tablets) to their children as a form of comfort or reward[20]. However, to limit children's use of mobile devices, alternative rewards (such as a trip) can be used. In several previous studies, it was found that parental rules were negatively associated with ST in children or their parents' reports[30, 31], which is similar to the results of this study. In this study, it was found that students with very clear screen rules in their families had a higher proportion of non-mobile device use (52.4%), and as the ambiguity of the rules increased, the proportion of students who did not use mobile devices gradually decreased. Thus, it can be seen that clear screen rules are important for controlling children's use of mobile electronic screens. Parental ST is associated with high participation in children's screen activities. In this study, students whose parents had ST of over 3 hours on weekends had a higher proportion of small electronic ST (father: 37.7%; mother: 28.3%). The family can have a significant impact on children's ST and the establishment of preventative behaviors, and parents serve as role models whose screen behaviors constantly influence their children.

The findings of this study suggest that students who had their own mobile phones spent significantly more total ST on small screens compared to other students, which is consistent with previous research findings[32]. Unlike adolescents, who spend more time on mobile electronic screens for peer communication[33], children around the age of 7 may spend more time watching cartoons or playing games.

The results of this study also show that clear family rules limiting ST are beneficial in reducing students' mobile ST, which is supported by previous research[27]. A review pointed out that limiting children's ST can not only effectively reduce ST, but also benefit their body mass index[34]. Parents who do not set limits on ST believe that the use of screens is beneficial to their children's education, the use of smart devices can increase their opportunities to receive knowledge[35]. However, children are in a critical period of development of inhibitory control ability[36]. If they do not take preventive measures such as limiting ST, it may increase their addiction rate to electronic screens such as mobile phones[37]. Therefore, it is necessary to weigh the pros and cons of setting limits on ST and make certain restrictions on ST.

The role of parents is pivotal in the growth of their children. As the closest role models for their children, their cultural literacy and behaviors constantly influence them. In our study, parental education (especially the father's) was also associated with student ST. Students whose fathers had a bachelor's degree or higher had relatively less ST, which is contrary to the findings of a study in Sri Lanka[38] but consistent with a study in Australia[39]. In the former study, the high educational level of fathers and family income may have increased the accessibility of electronic screen devices for children (affordability). However, in this study, parents with higher education levels may be more aware of the adverse effects of excessive electronic device use on children and spend more time on outdoor activities or hobbies. A previous study has also shown similar results[40]. This study also found that parental ST (especially mothers') was significantly associated with student ST. Students whose mothers had less ST on weekends spent less time on small screens, which is consistent with previous research findings[39, 41]. Compared to the father's weekend ST, the mother's weekend ST is more closely related to the child's ST. This result may reflect the gender-based parenting roles in traditional Chinese families.

Limitations and Strengths

The limitations of this study mainly lie in the use of self-reported questionnaires to measure ST and related factors, which may have problems of memory bias and potential social desirability bias. However, this method is also commonly used in other studies[16]. Future studies may increase the use of electronic tracking devices to improve the accuracy of research. The second limitation is that existing research rarely explores the standards for children's small screen viewing duration, making it impossible to identify a definitive time threshold, beyond which excessive exposure would significantly harm children's health or development. Nonetheless, one study has suggested that for toddlers (aged 1.5 years), each additional half-hour of mobile screen time is associated with a 133% increase in the likelihood of delayed language development[25]. The strength of this study is that it mainly focuses on children's small screen behavior, which is a population and recent behavior lacking research, and divides it into participation and behavioral duration to investigate related factors separately.

We concluded that the mobile screen usage and its duration of primary school students in grades one and two is related to whether they have their own corresponding electronic devices, whether there are clear regulations on screen time, the educational level of their father, and the mother's weekend screen time. This result can help parents clarify the importance of scientifically setting the time for their children to use mobile devices, strengthen their own and their children's screen management awareness, and lay the foundation for further developing policies on the management and usage time of family mobile screen behavior.

Ethics approval and consent to participate

Ethics approval was obtained from the Ethics Committee of The First Hospital of Jiaxing (2023-LY-024). All methods were performed in accordance with the relevant guidelines and regulations (Declaration of Helsinki).

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was funded by the Zhejiang Women and Children's Foundation (00623037)and the Major Humanities and Social Sciences Research Projects in Zhejiang higher education institutions (2023QN019).

Authors’ contributions

LC, JL and SY conceptualized and designed the study, drafted the initial manuscript, and critically reviewed and revised the manuscript. LC and SY were responsible for data collection and data analysis. All authors have read and approved the final manuscript.

Acknowledgments

Not applicable.

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Table 1 Characteristics in 6-10-year-old Chinese children

Variables	Playing small screen device		t-test or X²	P value
Variables	Yes, N=361	No, N=655	t-test or X²	P value
Age (years), mean (SD)	7.35(0.55)	7.27(0.49)	2.36	0.018
Sex, n (%)			3.33	0.068
boy	204(56.5)	331(50.5)
girl	157(43.5)	324(49.5)
Small screen play*, mean (SD)
School day, minute/day	31.53(30.53)
Weekend, minute/day	77.50(57.02)
Total, minute/week	310.96(232.79)
Own small screens, n (%)			76.15	<0.001
yes	180(49.9)	151(23.1)
no	181(50.1)	504(76.9)
Screen rules, n (%)			39.73	<0.001
Very clear	117(32.4)	343(52.4)
Clear	153(42.4)	211(32.2)
Equivalent	66(18.3)	76(11.6)
Unclear	21(5.8)	19(2.9)
Very unclear	4(1.1)	6(0.9)
Caregiver, n (%)
School day			1.37	0.242
parents	259(71.7)	492(75.1)
others	102(28.3)	163(24.9)
Weekend			2.51	0.113
parents	298(82.5)	565(86.3)
others	63(17.5)	90(13.7)
Maternal education, n (%)			7.61	0.107
Elemental or less	27(7.5)	74(11.3)
High school	84(23.3)	118(18.0)
Junior college	89(24.7)	150(22.9)
University or more	116(32.1)	220(33.6)
Missing	45(12.5)	93(14.2)
Paternal education, n (%)			6.87	0.143
Elemental or less	39(10.8)	73(11.1)
High school	71(19.7)	112(17.1)
Junior college	89(24.7)	128(19.5)
University or more	105(29.1)	234(35.7)
Missing	57(15.8)	108(16.5)
Maternal screen time, mean (SD)
School day			7.56	0.109
<1 hour/day	79(21.9)	185(28.2)
1-2 hour/day	85(23.5)	126(19.2)
2-3 hour/day	36(10.0)	62(9.5)
≥3 hour/day	113(31.3)	181(27.6)
Missing	48(13.3)	101(15.4)
Weekend			26.03	<0.001
<1 hour/day	48(13.3)	164(25.0)
1-2 hour/day	89(24.7)	139(21.2)
2-3 hour/day	74(20.5)	95(14.5)
≥3 hour/day	102(28.3)	149(22.7)
Missing	48(13.3)	108(16.5)
Paternal screen time, mean (SD)
School day			3.59	0.464
<1 hour/day	67(18.6)	149(22.7)
1-2 hour/day	76(21.1)	119(18.2)
2-3 hour/day	43(11.9)	75(11.5)
≥3 hour/day	116(32.1)	196(29.9)
Missing	59(16.3)	116(17.7)
Weekend			15.94	0.003
<1 hour/day	40(11.1)	111(16.9)
1-2 hour/day	51(14.1)	126(19.2)
2-3 hour/day	73(20.2)	98(15.0)
≥3 hour/day	136(37.7)	203(31.0)
Missing	61(16.9)	117(17.9)

*: n=325, after excluding participants with missing information and outliers.

Table 2 Logistic regression model analysis on factors of attending small screens play

Variables	Small screens play (no=0, yes=1)			Wald X²	P value
	OR	95% CI
	OR	Lower	Upper
Age (years)	1.23	0.93	1.62	2.13	0.144
Sex (girls vs. boys)	0.74	0.55	0.98	4.46	0.035
Own screens (yes vs. no)	3.66	2.70	4.96	69.78	<0.001
Screen rules	1.45	1.24	1.70	21.02	<0.001
Caregiver (non-parents vs. parents)
School day	1.15	0.82	1.63	0.66	0.415
Weekend	1.00	0.66	1.52	0.00	0.991
Maternal education
Elemental or less	Ref.
High school	1.82	0.99	3.35	3.72	0.054
Junior college	1.52	0.79	2.93	1.55	0.213
University or more	1.43	0.71	2.87	1.01	0.316
Missing	1.65	0.55	4.94	0.80	0.370
Paternal education
Elemental or less	Ref.
High school	0.80	0.45	1.43	0.56	0.454
Junior college	0.95	0.52	1.76	0.02	0.878
University or more	0.49	0.25	0.94	4.53	0.033
Missing	0.96	0.32	2.84	0.01	0.934
Maternal screen time
School day
<1 h/d	Ref.
1-2 h/d	1.02	0.63	1.65	0.01	0.934
2-3 h/d	0.71	0.39	1.31	1.19	0.276
≥3 h/d	0.80	0.45	1.44	0.55	0.460
Missing	1.19	0.45	3.16	0.12	0.732
Weekend
<1 h/d	Ref.
1-2 h/d	2.49	1.49	4.18	11.95	0.001
2-3 h/d	2.70	1.50	4.86	10.97	0.001
≥3 h/d	2.27	1.22	4.22	6.75	0.009
Missing	1.09	0.36	2.98	0.03	0.874
Paternal screen time
School day
<1 h/d	Ref.
1-2 h/d	0.96	0.56	1.63	0.03	0.870
2-3 h/d	0.67	0.35	1.28	1.48	0.224
≥3 h/d	0.57	0.30	1.10	2.84	0.092
Missing	0.45	0.17	1.23	2.44	0.119
Weekend
<1 h/d	Ref.
1-2 h/d	0.81	0.44	1.49	0.48	0.490
2-3 h/d	1.72	0.88	3.34	2.53	0.112
≥3 h/d	1.94	0.98	3.83	3.63	0.057
Missing	1.87	0.67	5.22	1.45	0.229

Table 3 Linear regression model analysis on factors of screen time on small screens

	Screen time on small screens
	School day				Weekend				Total
	beta	SE	t	p	beta	SE	t	p	beta	SE	t	p
age	3.78	3.10	1.22	0.223	12.49	5.74	2.18	0.030	35.92	26.28	1.37	0.172
sex	4.68	3.44	1.36	0.174	6.15	6.30	0.98	0.329	58.88	29.09	2.02	0.043
Own small screens	4.79	3.68	1.30	0.194	12.07	6.38	1.89	0.058	65.47	29.39	2.23	0.026
Rules	3.69	1.85	1.99	0.047	18.03	3.37	5.35	<0.001	60.55	15.14	4.00	<0.001
Caregiver
school day	5.19	3.82	1.36	0.174					-5.74	33.34	-0.17	0.863
weekend					15.98	8.75	1.83	0.068	45.18	40.11	1.13	0.260
Maternal education
Elemental or less	Ref.				Ref.				Ref.
High school	-10.58	7.48	-1.42	0.157	-19.14	13.55	-1.41	0.158	-47.69	58.63	-0.81	0.416
Junior college	-15.44	7.88	-1.96	0.050	-21.00	14.39	-1.46	0.145	-63.97	62.71	-1.02	0.308
University or more	-19.41	8.94	-2.17	0.031	-30.76	15.61	-1.97	0.049	-95.34	70.82	-1.35	0.178
Missing	-32.01	14.44	-2.22	0.027	-33.19	26.61	-1.25	0.212	-285.69	138.83	-2.06	0.040
Paternal education
Elemental or less	Ref.				Ref.				Ref.
High school	0.35	6.73	0.05	0.959	-0.12	12.38	-0.01	0.992	-33.82	53.54	-0.63	0.528
Junior college	4.45	7.09	0.63	0.530	-8.95	12.98	-0.69	0.491	-56.08	57.61	-0.97	0.330
University or more	2.15	8.15	0.26	0.792	-6.58	14.59	-0.45	0.652	-46.94	65.84	-0.71	0.476
Missing	35.48	15.60	2.28	0.023	-13.67	28.83	-0.47	0.636	224.47	134.84	1.67	0.096
Maternal screen time
School day
<1 h/d	Ref.				Ref.				Ref.
1-2 h/d	-0.72	5.41	-0.13	0.894	-5.80	9.88	-0.59	0.557	-10.75	45.92	-0.23	0.815
2-3 h/d	4.63	7.72	0.60	0.549	5.30	13.33	0.40	0.691	2.11	62.93	0.03	0.973
≥3 h/d	3.52	7.15	0.49	0.622	-0.72	13.06	-0.06	0.956	-16.76	60.36	-0.28	0.781
Missing	25.30	13.95	1.81	0.070	24.66	24.99	0.99	0.324	208.93	110.51	1.89	0.059
Weekend
<1 h/d	Ref.				Ref.				Ref.
1-2 h/d	-4.09	6.43	-0.64	0.526	19.52	11.26	1.73	0.083	21.83	52.27	0.42	0.676
2-3 h/d	-0.35	7.09	-0.05	0.960	14.32	12.71	1.13	0.260	22.26	59.72	0.37	0.709
≥3 h/d	5.31	7.57	0.70	0.484	31.57	13.62	2.32	0.020	142.61	64.69	2.20	0.027
Missing	-15.43	15.12	-1.02	0.308	-28.55	27.59	-1.04	0.301	-98.23	128.44	-0.77	0.444
Paternal screen time
School day
<1 h/d	Ref.				Ref.				Ref.
1-2 h/d	2.62	6.71	0.39	0.696	14.49	11.70	1.24	0.215	58.66	53.43	1.10	0.272
2-3 h/d	4.49	7.67	0.59	0.559	4.05	14.04	0.29	0.773	36.97	63.21	0.59	0.559
≥3 h/d	-1.75	8.19	-0.21	0.831	5.40	15.11	0.36	0.721	-14.11	68.32	-0.21	0.836
Missing	-8.41	13.57	-0.62	0.535	33.98	25.31	1.34	0.180	-4.41	121.48	-0.04	0.971
Weekend
<1 h/d	Ref.				Ref.				Ref.
1-2 h/d	7.25	7.73	0.94	0.348	4.15	14.14	0.29	0.769	43.56	63.50	0.69	0.493
2-3 h/d	7.22	8.27	0.87	0.383	9.27	15.34	0.61	0.545	31.81	70.93	0.45	0.654
≥3 h/d	0.46	8.64	0.05	0.958	-6.62	15.94	-0.42	0.678	-7.05	74.11	-0.10	0.924
Missing	-3.27	13.63	-0.24	0.811	17.00	25.17	0.68	0.499	-38.49	118.15	-0.33	0.745

No competing interests reported.

Correlates of small screens play in 6-10 years old Chinese children

Status:

Version 1

Abstract

Background

Methods

Results

Discussion

Conclusion

Declarations

References

Tables

Additional Declarations

Status:

Version 1