This descriptive cross-sectional study was carried out from July 2022 to June 2024. Six schools were purposively chosen from the list of schools in the Dhaka North City Corporation and Dhaka South City Corporation. Following a screening process based on the students’ exposure to digital screens and viability, 3 English-language and 3 Bangla-language schools were chosen. After obtaining permission from the school authority, a public notice was posted on the notice boards of the schools requesting students and their parents to schedule a meeting with the person conducting the research. Students who met the inclusion criteria—age between 6 and 14 years (grade 2 to grade 8) and having or not having access to gadgets such as portable gaming devices, smartphones, tablets, televisions, PCs, laptops, and gaming consoles—were chosen for the study. Following a thorough explanation of the study and provision of parents’ informed written agreement, both eligible students and their parents were invited to participate. Students who had psychological impairments, including depression, anxiety, or attention-deficit/hyperactivity disorder, that impacted their well-being or who had certain preexisting mental health disorders were excluded.

We recruited 420 students in total, 70 (16.7%) from each school and 10 (2.4%) from each grade level (2‐8), using a stratified random sampling method. The 420 participants were divided into 2 groups: one group had 70 (16.7%) students who spent less than 2 hours a day in front of devices, and the other group included 350 (83.3%) students who spent more than 2 hours a day in front of devices. The WHO and other international health regulatory agencies established the cutoff of less than 2 hours a day for children older than 5 years [15]. To collect data at the school premises, a trained team consisting of 2 field research assistants and 1 field research supervisor was involved.

Data were imported into Microsoft Excel for statistical analysis, cleaned, and then exported into SPSS (version 20; IBM Corp) and Stata (version 15.1; StataCorp). Two main groups were formed among the participants: those with high exposure (>2 hours a day) and those with low exposure (<2 hours a day). A comparative analysis was then carried out across several variables, such as demographic characteristics, screen time, and health metrics. For categorical data, chi-square tests for independence were used to evaluate differences between groups, and for continuous data with nearly normal distributions, an unpaired 2-tailed t test for differences between proportions was used. A significance threshold of a P value of less than .05 was used to assess statistical significance.

This study was approved by the institutional review board of icddr,b (protocol PR-22002). Confidentiality and anonymity were maintained throughout the study. Parental permission was obtained through informed written consent for all participants aged 6 to 14 years. Additionally, assent was obtained from students aged between 11 and 14 years. Every respondent received information in Bangla on their rights regarding their voluntary involvement in the study and their ability to leave the interview at any point while it was being conducted.

The study included 420 students based on screening criteria, of whom 350 (83.3%) were categorized in the high-exposure group (using digital devices for more than 2 hours daily) and 70 (16.7%) were categorized in the low-exposure group. The students were aged between 6 and 14 years, with a mean age of 10.9 (SD 1.9) years, with just over half of them (n=213, 50.7%) being male. The average daily screen time of the parents was 3.9 (SD 2.7) hours, and the average daily screen time of the students was 4.6 (SD 2.3) hours according to their own statement. Table 1 presents detailed information on the sociodemographic characteristics of the study population.

The prevalence of physical symptoms among study participants with high and low exposure is shown in Table 2. Of the 420 students included in the study, 150 (35.7%) had eye problems. Of these 150 affected students, 144 (96%) belonged to the high-exposure group, whereas only 6 (4%) were from the low-exposure group, showing a statistically significant association (P<.001). Among all participants, 80% (336/420) reported headaches, 65.7% (276/420) experienced indigestion, and 81.2% (341/420) reported abdominal pain. Additionally, 45.7% (192/420) reported neck pain, 31.9% (134/420) reported back pain, and 48.6% (204/420) reported changes in appetite. These symptoms were more prevalent in the high-exposure group, although the differences were not statistically significant. Hearing difficulties (14/420, 3.3%) and diabetes (4/420, 1%) were the least frequently reported symptoms among the high-exposure group.

The mean BMI for the study population was 19.3 (SD 4.7) kg/m² (Figure 1). Students with high exposure to digital screens had an average BMI of 20.0 (SD 4.7) kg/m² compared to 15.96 (SD 2.08) kg/m² in the low-exposure group, which was statistically significant (P<.001). Additionally, students categorized as being overweight (42/420, 10.1%), obese (16/420, 3.8%), or severely obese (4/420 (0.9%) were predominant in the high-exposure group (P<.001) compared to the low-exposure group.

The SDQ analysis revealed that, of the 420 students, 119 (28.3%) exhibited conduct problems, 121 (28.8%) had peer relationship problems, 66 (15.7%) reported emotional issues, 73 (17.4%) experienced hyperactivity, and 28 (6.7%) exhibited prosocial behaviors. Overall, most students fell within the normal range for these domains. However, among students classified as borderline or abnormal, most were in the high-exposure group. For example, in the peer relations domain, 28.8% (121/420) of the students were classified as abnormal, of whom 87.6% (106/121) were in the high-exposure group, whereas only 12.4% (15/121) were in the low-exposure group. Despite these trends, none of the SDQ domains showed statistically significant associations with screen time. Table 3 illustrates the relationship between screen time and the SDQ among the low- and high-exposure groups.

The correlation between sleep and screen time in the low- and high-exposure groups according to the PSQI is shown in Table 4. The overall average sleep latency for all participants was 20.3 (SD 14.7) minutes, with the high-exposure group showing significantly longer latency (mean 21.1, SD 15.4 minutes) than the low-exposure group (mean 16.3, SD 10.1 minutes; P=.01). Additionally, the average sleep duration was significantly shorter in the high-exposure group (mean 7.3, SD 1.4 hours) than in the low-exposure group (mean 9.0, SD 1.4 hours; P<.001), indicating poorer sleep quality among students with higher screen exposure. An evaluation of the PSQI components revealed significant differences in sleep duration between the 2 groups (P<.001). Other components, such as breathing difficulties, bad dreams, sleep disturbances, and daytime dysfunction, were also more prevalent in the high-exposure group than in the low-exposure group.

The correlation between student mental health and screen time in the low- and high-exposure groups according to the DAWBA scale is shown in Table 5. The DAWBA scale revealed that 31% (130/420) of the students reported at least one mental health issue, including specific phobia, generalized anxiety, depression, deliberate self-harm, hyperactivity, awkward behavior, and troublesome behavior. Additionally, 9.8% (41/420) of the students were identified as having more than one mental health problem. Notably, of the students with at least one mental health issue, 86.9% (113/130) were from the high-exposure group (screen use exceeding 2 hours per day). Similarly, among those with more than one mental health problem, 92.7% (38/41) belonged to the high-exposure group. The association between screen time and mental health problems showed borderline statistical significance, with a P value of .05.

We found that a large majority of students (350/420, 83.3%) were exposed to digital screens for more than 2 hours per day and that higher screen exposure was strongly associated with poorer health outcomes. Nearly all students with eye problems (144/150, 96%) belonged to the high-exposure group (P<.001). Students with high screen time also had significantly higher BMI, with overweight (42/420, 10.1%) and obese (16/420, 3.8%) status concentrated almost entirely in this group (P<.001). In addition, high screen exposure was linked to poorer sleep, characterized by longer sleep latency and significantly shorter sleep duration (mean 7.3, SD 1.4 hours vs mean 9.0, SD 1.4 hours; P<.001). Finally, almost one-third of the students (130/420, 31%) had at least one mental health problem, with the vast majority (113/130, 86.9%) occurring among students with high screen exposure (P=.05).

In this study, the mean age of the participants was 10.9 (SD 1.9) years, with 49.3% (207/420) of the students being female. In a similar study, participants had a mean age of 10.9 (SD 1.16) years, and 47.7% were female [20]. Our study also found that the mean screen time per day was 4.6 (SD 2.3) hours from the students’ perspective, which was similar to the parents’ perspective (mean 4.5, SD 2.4 hours). Seguin et al [21] reported similar findings, which were a mean screen time of 5.9 (SD 3.4) hours per day. In addition, a systematic review showed that, overall, screen time among children aged 6 to 10 years and adolescents increased by 1.4 hours per day and 0.91 hours per day (in the year 2020-2021), respectively, compared to the pre–COVID-19 era [22]. The lockdown regimen during the pandemic brought a huge change to screen time duration and patterns in the daily routines of children. With regard to physical symptoms, 80% (336/420) of students in our study were found to have headaches. A recent study reported that there was a statistically significant association between increased screen time duration and headache, as well as dry eyes (P=.04 and P=.02, respectively) [23].

We found statistically significant associations between screen time duration and BMI. Similar findings were reported in Austria, where screen time was significantly associated with a higher BMI (P=.002) [24]. In contrast, a study in Pakistan demonstrated that there was no association between mean screen time and BMI (P=.64) [25]. The disparities may be attributable to various confounding factors such as food traditions and lifestyle.

In this study, as per the SDQ, in terms of prosocial behaviors, it was observed that only 6.7% (28/420) of the students were in the category of abnormal scores overall, with 7.1% (5/70) and 6.6% (23/350) in the lower- and higher-exposure groups, respectively. However, a study conducted on rural Chinese school-going children revealed that 10.5% of the participants belonged to the abnormal prosocial behavior category [26]. These differences may be due to other mental health problems as the community where the aforementioned study was conducted may have had various familial conflicts with lower levels of social support. In addition, previous research does show that screen time above the threshold is linked with increased abnormalities in behavior.

Regarding sleep habits and patterns, we found that duration of sleep was associated with screen time duration (P<.001). In a previous study in India, it was observed that both sleep efficiency and sleep duration were associated with screen time duration (P=.003 and P=.001, respectively) [27]. Another study reported that, among children who were exposed to screens for more than 2 hours a day, 61.8% had a PSQI score lower than 5 [28]. Multiple mechanisms suggest that screen time and media use are linked to sleep disturbances. There are several stimulating programs and contents that increase the activity level of the nervous system, inhibiting relaxation and leading to anxiety and/or resulting in raised alertness and trouble falling asleep [29].

In the last decade, changes in screen use patterns and duration, type of content, type of device used, and parental monitoring have occurred. As a result, various types of studies have assessed the relationship between multiple aspects of screen time and/or device use and different facets of physical, mental, and social health in children, adolescents, and young adults, as well as academic performance outcomes and overall well-being. A study published in 2024 among children aged 6 to 10 years on screen addiction revealed that the group with high screen exposure showed statistically significant differences in screen addiction, distraction, and sedentary factors (P<.05) [30]. Another study reported that children who had greater exposure to screens, along with shorter sleep duration and lower physical activity levels, had poorer health-related quality of life [31]. In addition, a relevant study illustrated that children with exposure to screens for more than 2 hours per day had an increased likelihood of reported behavioral problems and poorer vocabulary [32].

It is worth mentioning that screen use widely varies across contexts. For instance, for academic purposes, screen time can exceed the recommended duration on certain days. This can be observed in the case of meeting deadlines or acquiring knowledge, where the screen is the only medium available. Another point to be kept in mind is the type of media being “overused” [33]. All in all, the context, platform, regimen, and secular trends should play a role in determining screen time duration.

First, the 6 schools included in this study (3 in Bangla and 3 in English) may not adequately reflect the wider differences in resources between urban and rural environments. Second, there may have been recall bias because data on technological interactions were gathered through in-person interviews. Future studies on the effects of screen time ought to consider a wider range of settings and demographics. Study designs other than cross-sectional should be used, and extensive analyses involving other covariates should be conducted.

Despite the aforementioned limitations, the study’s strength lies in its innovative examination of the association between varying levels of screen exposure (low vs high) and the physical, mental, and social well-being of Bangladeshi students, particularly given that children with low exposure to digital screens are increasingly difficult to find. Furthermore, this study offers an insightful comparative analysis because it included students from Bangla- and English-language schools. The findings can inspire and inform parents, legislators, and educational authorities, emphasizing supporting students’ healthier use of digital devices and more balanced lifestyles. More investigation is needed, possibly using longitudinal or experimental designs to examine causal relationships.

The findings of this study improve our knowledge of strategies to lessen the detrimental effects that excessive digital screen time has on children’s mental health and well-being. Educators, parents, legislators, and children themselves must all be involved to create effective screen use guidelines. By holding workshops and seminars, schools can effectively teach children about responsible screen use and enforce a balanced screen time policy. To improve their children’s well-being, parents must be aware of the dangers of excessive screen time as well as the advantages of active supervision. Accessible mental health resources, such as support groups and counseling, can also assist students in reducing the stress and anxiety associated with screen time. Additional research must be conducted to promote the development of comprehensive guidelines for screen time.