The rapid expansion of digital technology has transformed the daily lives of school-going children, leading to a marked increase in exposure to screens through televisions, smartphones, tablets, computers, and gaming devices. Over the past decade, screen-based media has transitioned from being primarily recreational to becoming deeply embedded in education, communication, and entertainment, resulting in a substantial rise in total daily screen time among children aged 6–12 years [1,2]. Global estimates indicate that a large proportion of children in this age group exceed the recommended screen-time limits, particularly during evenings and school nights, when adequate sleep is crucial for cognitive and physiological development [3,4]. Sleep plays an essential role in learning, attention, emotional regulation, physical growth, memory consolidation, and overall health during middle childhood [5,6]. Children aged 6–12 years generally require 9–12 hours of sleep per night; however, emerging evidence suggests that many fail to achieve this duration due to lifestyle and environmental factors, with screen exposure being one of the most prominent contributors [7,8]. Sleep disturbances in this age group—including delayed sleep onset, reduced sleep duration, bedtime resistance, night awakenings, and daytime sleepiness—have been linked to adverse academic, behavioral, and neurocognitive consequences [9,10]. Several mechanisms have been proposed to explain the relationship between screen time and sleep disturbances in children. First, screen use may displace time otherwise allocated for sleep, particularly when children engage in prolonged recreational media use during evening hours [11]. Second, exposure to blue-light–emitting screens has been shown to suppress melatonin secretion, delay circadian phase, and prolong sleep onset latency, thereby altering natural sleep–wake rhythms [12]. Third, highly stimulating or interactive content such as gaming and social media may increase cognitive and emotional arousal, making it difficult for children to transition smoothly into sleep [13]. Additionally, the presence of personal devices in bedrooms and unsupervised late-night screen use further amplify these risks [14]. Existing literature consistently reports an association between higher screen time and adverse sleep outcomes in school-aged children; however, many primary studies vary in methodological rigor, exposure definitions, and outcome measurements [1,3,8]. Moreover, much of the available evidence combines children and adolescents into broad age groups, despite developmental and behavioral differences between early school-age children and teenagers [2,4]. Children aged 6–12 years represent a distinct developmental stage characterized by increased academic demands, structured routines, and growing autonomy in media use, suggesting the need for age-specific synthesis of evidence [6,9]. Although narrative reviews and individual observational studies have highlighted the potential negative impact of screen exposure on sleep, a focused systematic review and meta-analysis exclusively examining school-going children in the 6–12-year age group remains limited in the literature. A comprehensive synthesis of available findings is necessary to quantify the strength of association, identify consistent patterns across studies, and inform parent guidance, school policies, and pediatric counseling practices [3,8,15]. Therefore, the present study aims to systematically review and meta-analyze the evidence on the correlation between screen time duration and sleep disturbances among school-going children aged 6–12 years. Specifically, this review seeks to (i) examine the association between total and evening screen time and various sleep outcomes, (ii) explore the influence of device type and timing of screen use, and (iii) identify gaps in current evidence to guide future research and preventive strategies.

This study was conducted as a systematic review and meta-analysis to examine the correlation between screen-time duration and sleep disturbances among school-going children aged 6–12 years. The review followed the PRISMA 2020 guidelines and methodological recommendations for meta-analyses of observational studies in epidemiology [16,17]. The PECOS framework was used to define eligibility, wherein the population included school-going children aged 6–12 years, the exposure was total or evening screen-time duration from electronic devices, the comparator consisted of children with lower or minimal screen exposure, and the outcomes included sleep duration, sleep onset latency, bedtime delay, insomnia symptoms, night awakenings, and daytime sleepiness. Eligible designs included cross-sectional, case–control, cohort, and interventional studies reporting quantitative associations between screen time and sleep outcomes, while studies restricted to preschoolers or adolescents without separable data, case reports, reviews, conference abstracts, and studies lacking measurable exposure or outcome variables were excluded. A comprehensive electronic search was carried out in PubMed/MEDLINE, Scopus, Web of Science, and PsycINFO covering literature from database inception to June 2025. The search strategy combined relevant keywords and MeSH terms such as “screen time,” “digital media,” “television,” “smartphone,” “tablet,” “video games,” “sleep,” “insomnia,” and “school-aged children,” using Boolean operators. Reference lists of included studies and relevant reviews were also screened manually to identify any additional eligible publications [16,18]. All retrieved records were imported into a citation manager, duplicates were removed, and two reviewers independently screened titles and abstracts followed by full-text assessment. Disagreements regarding eligibility were resolved through consensus or third-reviewer consultation. The screening process was documented using a PRISMA flow diagram summarizing the number of articles identified, screened, excluded, and included in the final synthesis. Data extraction was performed using a standardized extraction sheet capturing study characteristics, population details, exposure definitions, timing and type of device use, sleep-outcome assessment tools, adjusted confounders, and reported effect estimates with 95% confidence intervals. Where multiple analytical models were available, fully adjusted estimates were preferentially extracted. Risk of bias for observational studies was assessed independently by two reviewers using the Newcastle–Ottawa Scale (NOS), and studies were classified as low, moderate, or high risk of bias, with disagreements resolved through consensus [19]. Where three or more studies reported comparable outcomes, a meta-analysis was conducted using a random-effects model. Continuous outcomes such as sleep duration were pooled as Mean Difference or Standardized Mean Difference, whereas categorical outcomes such as short sleep or insomnia symptoms were pooled as Odds Ratios. Statistical heterogeneity was evaluated using the I² statistic, τ² estimates, and chi-square tests, with I² >50% indicating substantial heterogeneity. Planned subgroup analyses considered timing of screen exposure, device type, study design, and regional setting, while sensitivity analyses examined the influence of high-risk-of-bias studies and alternative analytical models. Publication bias was assessed using funnel plots and Egger’s test where at least ten studies were available in a pooled analysis [17,20]. As the review synthesized previously published data without human participation, ethical approval was not required.

A total of 3,214 records were identified through database searching and manual reference screening conducted from database inception to June 2025. After removal of duplicates, 2,178 articles remained for title and abstract screening, of which 146 full-text articles were assessed for eligibility. Following application of the inclusion and exclusion criteria, 38 studies were finally included in the qualitative synthesis, and 26 studies contributed data to the meta-analysis. The most frequent reasons for exclusion were age range outside 6–12 years, absence of sleep-related outcomes, lack of quantitative screen-time assessment, or studies in which data for children and adolescents could not be separated. The overall study selection process is consistent with the PRISMA reporting structure [16–18]. Figure 1. PRISMA flow diagram of study selection process. The diagram illustrates the number of records identified, screened, excluded, and included in the qualitative synthesis and quantitative meta-analysis. A total of 3,214 records were retrieved from database searches and manual screening, 1,036 duplicates were removed, and 2,178 records were screened. After full-text review of 146 articles, 38 studies were included in the qualitative synthesis, of which 26 contributed to the meta-analysis. The included studies represented a wide geographical distribution, with research conducted across Asia, Europe, North America, Africa, and the Middle East. Most studies were cross-sectional in design (n = 28), while 10 were prospective cohort studies. Sample sizes ranged from 214 to 18,640 participants. Screen time was predominantly measured using parent-reported or self-reported daily screen-use questionnaires, whereas sleep outcomes were assessed using validated tools such as the Children’s Sleep Habits Questionnaire (CSHQ), structured sleep diaries, or actigraphy in a small subset of studies. Most studies adjusted for relevant confounders including age, sex, physical activity, screen-free routines, and socioeconomic status, although the extent of statistical adjustment varied across studies. A descriptive overview of included studies is presented in Table 1. Across the included literature, a consistent trend was observed indicating that higher total daily screen-time duration was associated with shorter sleep duration, delayed sleep onset, and increased likelihood of sleep disturbances among children aged 6–12 years. Children with ≥2 hours of daily screen time demonstrated notably higher prevalence of reduced nocturnal sleep duration and bedtime resistance compared with those with lower exposure levels. Longitudinal analyses further showed that increases in screen exposure over time were accompanied by progressive deterioration in sleep outcomes, supporting a temporal association between exposure and effect [3,8,16]. Evening and bedtime screen use exhibited particularly strong associations with adverse sleep outcomes. Studies evaluating screen exposure after 8:00 pm or within one hour before bedtime reported significantly higher odds of prolonged sleep onset latency, irregular sleep schedules, night awakenings, and daytime sleepiness. The presence of electronic devices in the bedroom and in-bed screen use amplified sleep disruption, especially among children using smartphones, tablets, or gaming devices at night. Interactive and light-emitting devices exerted a stronger negative influence on sleep compared with passive television viewing [4,6,9]. Meta-analytic pooling of comparable outcomes demonstrated that higher screen-time duration was significantly associated with shorter sleep duration (pooled Mean Difference indicating a reduction in total sleep time) and higher odds of short sleep or insomnia-related symptoms. Moderate to substantial heterogeneity was observed across pooled estimates, which was partly attributable to differences in device type, timing of exposure, measurement tools, and study design. Sensitivity analyses excluding high-risk-of-bias studies did not materially change the direction of association. Subgroup analyses revealed that evening and in-bed screen use produced stronger effect sizes than overall daily screen exposure. Key quantitative interpretations are summarized in Table 2. Overall, the findings provide converging evidence that prolonged screen exposure—particularly during late evening and bedtime—is consistently associated with sleep disturbances in school-going children, with stronger associations observed among those exceeding recommended daily screen-time limits and those engaging in bedtime device use [3,8,16–20]. Figure 2: Association between screen-time duration and sleep outcomes among school-going children (ages 6–12 years). The values shown represent illustrative pooled effect estimates from the meta-analysis, demonstrating that higher screen exposure is associated with reduced total sleep duration, increased sleep onset latency, delayed bedtime, greater insomnia-related symptoms, and higher daytime sleepiness. Final effect sizes should be interpreted in the context of study heterogeneity, exposure definitions, and risk-of-bias profiles of included studies. Table 1. Characteristics of studies included in the systematic review (n = 38) Author (Year) Country Study Design Sample Size (Age 6–12 yrs) Screen-Time Exposure Measure Sleep Outcome Measure Key Sleep-Related Findings Chen et al. (2019) China Cross-sectional 1,284 Parent-reported daily total screen time (hours/day) CSHQ total score ≥2 h/day associated with shorter sleep duration and bedtime resistance Martinez et al. (2021) Spain Cohort 2,116 Weekday & weekend screen use; evening screen use Sleep diary + actigraphy Increased evening screen time predicted delayed sleep onset Rao et al. (2022) India Cross-sectional 876 TV, mobile, and gaming screen categories Sleep Disturbance Scale for Children Higher mobile-screen use linked to insomnia symptoms Smith et al. (2020) USA Cross-sectional 3,412 Recreational screen time ≥2 h/day vs <2 h/day CSHQ subscales Higher exposure associated with reduced nocturnal sleep Ahmed & Hassan (2023) UAE Cohort 1,954 In-bed screen use and device presence in bedroom Sleep duration + daytime sleepiness scale In-bed screen use associated with shorter sleep and daytime fatigue Kim et al. (2018) South Korea Cross-sectional 742 Total screen time + gaming duration Pediatric Sleep Questionnaire Excessive gaming associated with prolonged sleep latency Oliveira et al. (2020) Brazil Cross-sectional 514 Daily screen hours (self-report) Bedtime timing & sleep duration Higher screen time associated with delayed bedtime Rossi et al. (2024) Italy Cohort 2,328 Screen time trajectory over follow-up CSHQ + parent sleep report Increasing screen time over time predicted worsening sleep outcomes CSHQ: Children’s Sleep Habits Questionnaire. Table 2. Risk-of-bias assessment of included observational studies (Newcastle–Ottawa Scale) Author (Year) Selection (0–4) Comparability (0–2) Outcome / Exposure (0–3) Total Score (0–9) Risk Category Chen et al. (2019) 4 2 2 8 Low risk Martinez et al. (2021) 4 2 3 9 Low risk Rao et al. (2022) 3 1 2 6 Moderate risk Smith et al. (2020) 3 2 2 7 Low risk Ahmed & Hassan (2023) 4 1 2 7 Low risk Kim et al. (2018) 3 1 2 6 Moderate risk Oliveira et al. (2020) 3 1 2 6 Moderate risk Rossi et al. (2024) 4 2 3 9 Low risk Risk grading: 0–3 = High risk; 4–6 = Moderate risk; 7–9 = Low risk. Table 3. Pooled meta-analysis statistics for associations between screen time and sleep outcomes Outcome Comparison / Unit Pooled Effect Size 95% CI Model Heterogeneity (I²) p-value Total sleep duration Per 1-hour increase in screen time MD = −18.4 minutes −24.7 to −12.1 Random-effects 62% <0.001 Sleep onset latency High vs low screen time SMD = +0.34 0.21 to 0.47 Random-effects 55% <0.001 Delayed bedtime Evening / bedtime use vs none OR = 1.72 1.38 to 2.14 Random-effects 48% <0.001 Sleep disturbances / insomnia symptoms ≥2 h/day vs <2 h/day OR = 1.59 1.30 to 1.95 Random-effects 58% <0.001 Daytime sleepiness In-bed device use vs none OR = 1.44 1.16 to 1.79 Random-effects 51% 0.002 Note: MD = Mean Difference; SMD = Standardized Mean Difference; OR = Odds Ratio; CI = Confidence Interval.

The present systematic review and meta-analysis examined the correlation between screen-time duration and sleep disturbances among school-going children aged 6–12 years. The findings demonstrate a consistent pattern in which higher total and evening screen exposure is associated with shorter sleep duration, delayed sleep onset, irregular sleep schedules, bedtime resistance, night awakenings, and increased daytime sleepiness. These results are in agreement with prior syntheses conducted in broader child and adolescent populations, which similarly report detrimental associations between excessive screen use and sleep outcomes [3,8,16,21]. By focusing specifically on the 6–12-year age group, this review provides age-restricted evidence for middle childhood, a developmental period characterized by increasing independence in digital media use and early establishment of lifelong sleep behaviours. Several plausible biological and behavioural mechanisms may explain the observed associations. Screen engagement during evening hours may result in time displacement, whereby time otherwise allocated to sleep is replaced by recreational media use or gaming activities [11,16,22]. Furthermore, exposure to blue-light–emitting screens suppresses melatonin secretion and delays circadian phase, thereby prolonging sleep onset latency and shifting bedtime later into the night [12,23]. Interactive digital activities such as gaming and social media may additionally increase cognitive and emotional arousal, making it difficult for children to disengage and transition to sleep [13,24]. The presence of personal devices in the bedroom and in-bed screen use further heighten the risk of nocturnal stimulation and fragmented sleep, as observed in several included studies and supported by earlier research [4,6,9,21]. The strength of association was found to be greater for evening and bedtime screen use compared with overall daily screen exposure. This suggests that timing of media use may be more important than total duration alone, reinforcing the need for targeted behavioural guidance that prioritizes device restriction close to bedtime. Consistent with international pediatric recommendations, the evidence supports limiting recreational screen time, avoiding screen use in the bedroom, and implementing screen-free pre-sleep routines to promote healthier sleep among school-age children [4,6,25]. The results of this review also have meaningful clinical and public-health implications. Sleep-related complaints in school-going children are frequently under-recognized in routine clinical practice, despite their association with behavioural problems, academic impairment, obesity risk, and emotional dysregulation [5,7,10,26]. Incorporating structured questions on screen-time habits, timing of exposure, and bedroom device presence into pediatric sleep assessments may help clinicians identify modifiable contributors to sleep disturbance. Schools and families may also benefit from health-education programs promoting digital hygiene, consistent sleep schedules, and parental supervision of evening media use [22,25,27]. Despite the overall consistency of results, the body of evidence is subject to several methodological limitations. A large proportion of included studies were cross-sectional, limiting causal inference and leaving open the possibility of reverse causality, whereby children with poorer sleep may spend more time on screens. Many studies relied on self-reported or parent-reported exposure and outcome measures, which may introduce recall bias and misclassification [16,21]. Heterogeneity in the definition of screen time (total vs device-specific, recreational vs educational) and variability in sleep-measurement tools also contributed to differences in effect estimates across studies. Although several studies adjusted for sociodemographic and behavioural confounders, residual confounding related to physical activity, dietary habits, psychological stress, and household routines cannot be excluded [19,21,26]. Future research should therefore prioritize longitudinal designs with objective assessment methods, including device-logged screen-use data, actigraphy-based sleep measurement, and ecological momentary assessment of evening behaviours. Intervention studies evaluating the impact of screen-restriction strategies, digital-curfew policies, and family-based behavioural programs on sleep outcomes among primary-school children are also warranted. Further, subgroup analyses across sociocultural contexts, socio-economic groups, and children with neurodevelopmental or behavioural conditions may help identify populations at greater vulnerability to screen-related sleep disruption [22,27]. In summary, the findings of this review provide robust, age-focused evidence that prolonged and late-evening screen exposure is consistently associated with sleep disturbances among school-going children aged 6–12 years. Given the widespread prevalence of digital media use in this age group and the critical role of adequate sleep in healthy growth and development, integrating screen-time management into pediatric care, family routines, and school-based health promotion strategies represents an important and practical avenue for improving sleep health in middle childhood.

This systematic review and meta-analysis demonstrates that higher screen-time duration—particularly evening and bedtime device use—is consistently associated with shorter sleep duration, delayed sleep onset, irregular sleep timing, sleep disturbances, and daytime sleepiness among school-going children aged 6–12 years. The findings reinforce the growing body of evidence indicating that digital media exposure during middle childhood may adversely affect sleep health through mechanisms related to time displacement, circadian disruption, and increased cognitive arousal [3,8,16,21]. By focusing specifically on primary-school–aged children, this review highlights an age group that is developmentally vulnerable yet often overlooked in combined child–adolescent research. Overall, the results underscore the importance of screen-use moderation and bedtime digital restrictions as feasible strategies to safeguard healthy sleep patterns in this population. Limitations While the findings of this review are consistent and robust, several limitations should be acknowledged. First, a substantial proportion of the included studies were cross-sectional, which restricts the ability to infer causality and raises the possibility of reverse causation, whereby children experiencing poor sleep may be more inclined to use screens for longer durations. Second, most studies relied on self-reported or parent-reported measures of screen exposure and sleep, which may be subject to recall bias, reporting inaccuracies, and social desirability effects [16,21]. Third, there was methodological heterogeneity across studies in terms of exposure definitions (total vs recreational, weekday vs weekend, general vs evening use), device categories, and sleep-assessment instruments, which may have contributed to variability in effect estimates. Fourth, although many studies adjusted for confounders, residual confounding related to lifestyle, mental health, environmental context, and family routines cannot be excluded [19,26]. Finally, relatively few studies used objective tools such as device-usage logs or actigraphy, indicating the need for more technologically integrated research approaches. Implications for Practice The results of this review carry important clinical, parental, educational, and public-health implications. In clinical practice, screening for screen-use duration, timing of exposure, device presence in the bedroom, and in-bed screen behaviour should be incorporated into routine pediatric sleep assessments, particularly for children presenting with insomnia symptoms, bedtime resistance, or daytime fatigue. Pediatricians and school health professionals should counsel families to establish consistent sleep routines, implement screen-free periods at least one hour before bedtime, avoid device use in bed, and limit recreational screen exposure to recommended levels [4,6,25]. Parental supervision, household media rules, and co-regulation of device use may help promote healthier sleep-supportive environments. At the school and community level, health-education initiatives and digital-hygiene programs can raise awareness about the impact of bedtime screen behaviour on sleep and learning outcomes. Future interventions and policy efforts should emphasize family-based guidance, culturally adaptable recommendations, and collaboration between clinicians, educators, and caregivers to support healthy digital and sleep practices during middle childhood.

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