Excessive screen time is predominantly associated with sedentary behaviors in children and adolescents [3]. Excessive screen time is considered as one of the major role players in causing non-communicable diseases (NCDs) [4] and health risks [5] later in life. A longitudinal study reported that there was a rapid increase in TV-time by one year of age, and children who had screen time <1 hour per day at 14 months of age, started watching screens for >2 hours per day when they are aged 30 months [1]. A Japenese study reported that 29.4% of children of age 18 months, 24.5% of age 30 months, and 21% at both ages watched TV for 4 hours or more per day [6]. Children below the age of two years who watched TV for any duration per day, and children aged >2 years who watched TV for >2 hours per day were more likely to show a delay in motor skill development [7]. Further, screen time has been associated with impairments in language development [7,8], and behavioral [6], psychosocial, academic and physical wellbeing [9].

There is limited published data on the duration of screen time, its associated factors and intervention studies on reducing it in the low- and middle-income countries (LMIC). The purpose of this review is to document the burden of screen time, its associated factors and correlates, outline the health impact, and summarize the interventions developed to reduce screen time among under-five children.

Search strategy: A literature review of published articles from January 2009 to June 2018 was performed through searches in PubMed, Clinical Key, Scopus, Embase, and Google Scholar. Medical Subject Headings (MeSH) words used were ‘preschooler’, ‘infant’, ‘kid’, and ‘toddler’ for child-related terms; and ‘screen-time’, ‘screen-viewing’, electronic media related- ‘electronic media’, ‘digital-media’, ‘TV’, ‘smartphone’, ‘mobile phone’ for screen-time related terms. When relevant articles were identified, cross-references were searched for related studies.

Inclusion criteria for a searched article included (i) peer-reviewed article published in English language in the scientific journals; (ii) cross-sectional studies on prevalence of digital-media use, adherence to screen time guidelines, correlates of digital-media use among under-five children; (iii) cohort or case control studies assessing association between at least one digital-media gadget and behavioral outcome or demographic correlate among under-five children; (iv) interventional studies in a school-, clinic-, hospital-, family-, home-, or community-based setting to reduce screen time as one of the outcome; and (v) studies measuring (proportion or mean) the use of atleast one type of digital-media gadget (like TV, computer or videogames etc) by children. The articles reporting digital-media exposure of caretakers or parents or diseased children or older children were not included in the analysis.

Potentially relevant articles were screened by their titles, and abstracts. When the abstract was not available or had incomplete findings, the entire article was retrieved. Articles describing study protocols, reports, dissertations, models and conference abstracts were excluded. Data extraction form was used to obtain the study information, study design, country, age of participants; exposure i.e., screen-based characteristics (e.g., duration, frequency, pattern, and measurement and/or description of intervention); outcome/health indicators (e.g., measurement type); results (e.g., odds ratio, difference in means); and covariates included in the analyses (e.g., eating behaviors, emotional outcomes, sleep outcomes, psychological outcomes, nutrition, parental perceptions, parental behaviors, parenting skills, home environment, physical activity of the children). The search was done by two authors, and it was cross checked by the third author for correctly excluding the studies. Any discrepancies were resolved by the fourth author.

Fig. 1 Flow diagram depicting the inclusion and exclusion criteria for selecting the articles at each stage.

We identified 19,833 articles, 19511 were either duplicates or irrelevant, among these 322 articles were screened based on their title and abstract (Fig. 1). Of the 322 studies, 171 articles were excluded based upon the exclusion criteria, and 151 full text articles were assessed. Of these 101 articles were excluded due to a context other than the review. Finally, 50 studies were reviewed including 14 cross-sectional studies [4,7,8,10-20], on prevalence, associated factors, correlates and consequences of excessive digital-media exposure (Table I) [1,6,9,21-28]; 11 overlapping studies and two systematic reviews [29,30] on the associated factors, correlates and consequences of excessive digital-media exposure [1,6,9,21-28]; 16 intervention studies [31-46], three systematic reviews [3,5,47] and four digital-media guidelines [2,48-50] among under-five children. Among the 16 interventions studies, two were pilot-RCTs [31,32], four cluster-RCTs [39-42], and ten RCTs [33-38,43-46] (Table II). All studies relied on the information given by the parents.

TABLE I Summary of Prevalence Studies, Associated Factors, Correlates of Screen Time Among Children Aged 0-5 years.

TABLE II Summary of Intervention Studies on Screen Time in Children Aged 0-5 years

ST: screen-time; TV: television; RCT: randomized control trial; PA: physical activity; BMI: body mass index.

The results of 14 cross-sectional studies for estimating the prevalence are summarized in Table I. Prevalence of excess screen time varies from 10% to 93.7% across the high-income countries, and 21% to 98% in the middle-income countries. Four out of 14 cross-sectional studies considered screen time more than 2 hours per day as excessive [4,17,19,20], six used screen time more than >1 hour per day as excessive [6,8,11,14,16,24], whereas three studies reported average screen time [7,12,14,18]. Overall, the screen time ranged from 0.1-5 hours per day among under-fives. Younger children (0-2 years) from the middle-income countries [26] and older ones (0-5 years) from the high-income countries [14] had screen time of >1 hour per day. The maximum duration of screen time was reported among 3-5 years old children in home-based care [16,23]. Four studies [4,15,20,24] reported a higher prevalence of screen time of >1 hour per day during weekends (25% to 63%), as compared to weekdays (10% to 48%). All the studies measured screen time while watching TV, which was perferred over other digital-media devices [11,12,14,15,17,19-21,24]. Three studies also reported the average screen time from using smartphone [17,20,24] and five studies on computer usage [11,12,14,15,19,21] separately or along with the TV. However, they have not documented the screen time of these gadgets separately, and have provided the aggregated time.

The differences in the prevalence rate of excessive screen time among under-fives can also be attributed to the associated factors like, digital-media environment [14,17,18,23], parental behaviors [1,4,12–14,17] and government regulations [2,48–50]. The preference of TV over other digital-media devices is evident among under-fives [11,12,14,15,17,19–21,24]. A systematic review reported that computers are preferred by older children [5]. All the studies have reported screen time through watching TV; in addition, a pevious [19] and some recent studies have measured screen time on using computers, smartphone, iPad, or hand-held games [7,11,12,17,24]. However, the screen time from watching TV far exceeds than that from new-age gadgets. Earlier the device is introduced, there is an increased propensity to exaggerated use with an increase in age [8,24,26].

Twenty-eight studies including 14 cross-sectional studies, 11 overlapping studies, 3 systematic reviews [1,3,4,6–30] and one guideline [2] were reviewed to document the factors associated with screen time. A systematic review identified 36 correlates of children (0-8 years) specifically with mobile screen exposure [29]. Another review identified 33 correlates in children under the age of three years [30]. Both these systematic reviews have used bio-ecological model to explain various correlates at five levels: (i) child biological and demograpic factors; (ii) family biologic and demographic factors; (iii) family structure; (iv) behavioral factors; and (v) socio-cultural/environmantal factors. These reviews reported the associations with screen time to be either positive, negative or none. We have used the social ecological model [10,19] to explain all the 40 factors (23 from 28 studies and 17 additional factors from systematic reviews) to be associated with digital-media exposure among children at four levels. As per this model, there is an interplay (bidirectional) of the factors affecting the behaviors at four levels including intrapersonal level (child-related factors), interpersonal level (caregiver-related factors), immediate environmental level (child care environment) and macro-environment level (socio-cultural environment) [12,14,30]. We have clubbed the child and family level behavioral factors with child and family factors, respectively (Fig. 2).

Fig. 2 The interactions of associated factors and correlates of screen-time among under-five children using the Social-Ecological model.

At intrapersonal level, the factors associated with digital-media exposure include child’s demographic, behavioral and biological factors. As the child grows older, his screen time accentuates [4,6,11,14,26]. Hyperactivity-inattention [6], daily sleep duration, and sedentary preferences [12] were found to be positively associated with a child’s digital-media exposure. Boys were more hyperactive [6] and watching more screens [14] in comparison to girls. However, three studies did not report any gender-based differences in screen time [11,12,23]. Another study concluded that the child’s demographic factors [23] have no associations with child’s digital media exposure.

These factors play a role during interactions between the parent/caregiver and the child. Paternal age [12], time spent on work by mothers [22], maternal stress [1,30], parental screen time [1,4,13,14,17,29,30], mother’s place of delivery [1,15], and shorter breastfeeding [30] were positively related to child’s screen time. Children of first-time mothers had increased in screen time [1]. Parental income [14], parent’s occupation [29], socioeconomic status of the family [6,15], maternal ethnicity [12], maternal body mass index [30], decreased level of education [7,14] and physical activity [29] of the parents’/caregivers were negatively associated with average digital-media exposure of the child. Parents’ perceptions [1,17], attitudes, beliefs towards the importance of digital-media exposure and the amount of time they spent with the child [29] played a pivotal role in a child’s digital-media exposure. Mother’s relational and personal well-being, parent’s sex, country of birth [29], and cognitive stimulation at home [30] were also associated with child’s screen time. However, there were no associations reported with parental demographic characteristics [23], ethnicity of the family [17,23], two-parent household, number of children at home, or non-parental child-care [30].

The digital-media micro-environment is the home environment within which the family lives i.e., the micro digital-ecosystem of the house. The access to digital-media gadgets [13,14,17,29,30], screen time rules at home [12,14], TV switched-on in the background at home [1,14,17], home-based care [16,23], parenting skills [14], computers placed outside the child’s bedroom and TV on during dinner [29], infant crying duration and heavy TV use [30] are positively related to digital-media exposure in children. Parental self-efficacy [12], and type of care [29] were negatively associated with screen time of the child. The TV time/content restrictions had no association with the child’s screen time [30].

The socio-cultural, geographical and environment factors are the macro-environmental factors that affect the digital-media usage of the family. These represent the macro digital-ecosystem of the community surrounding the house. Interactions at the macro-digital ecosystem cannot be controlled and may vary from region-to-region. The place of residence [4,15,20,29,30], season (winter) [30] and the government services that are available in that area [2] affect the digital media exposure of the children. A study reported that boys of rural areas had higher screen time than in the urban areas [20]. Another study reported that it was higher among girls belonging to lower socioeconomic status as compared to those of higher status [15].

The consequences of augmented screen time may be early/preliminary and late/long-standing [1,4,6-12,14-26,28] as shown in Fig. 3. Early consequences are considered as those that are reported during under-five development period among infants, toddlers and preschoolers; and late are those that are reported after this period.

Fig. 3 Associations and consequences of excessive screen time in under-five children.

The watching of indiscriminate media content [9], especially if unsupervised [2], might hamper a child’s behavioral outcomes. Moreover, restricting children in one position for >1 hour has additional negative health outcomes [2]. Sedentary behaviors related to screen time among children might be induced by the parents [1,12,18] as they are the role models for the children [1,4,12], or due to the parents’ perceptions about the importance of screen time [12,14,26], physical environment-induced (access, presence of bedroom TV, number of gadgets at home etc.) [1,4,12,14,15,17,20]. However, it is reported that not all digital media is bad as a child’s level of physical activity [47], skill development [28], gain in knowledge [21] early learning, cognitive and functional development [10] improved with specific contingent videos. American Academy of Pediatrics 2016 guidelines [2] reinforce that one-to-one interaction may, in turn, lead to improved parent-child engagement, and quality of social interaction for healthy development.

The child’s frequency of TV watching was found to be significantly associated with delayed motor skills, cognitive [7] and language [7,8] development. The content of TV has a detrimental effect on cognitive development [7]. A Japanese study observed that children aged 30 months, had increased chances of being hyperactive/inattentive due to excessive TV-viewing [6]. Augmented digital media usage leads to reduced sleep, which in turn leads to increased TV exposure that seems to have a wider impact on the sleep quality [12]. Greater household chaos leading to excessive screen time is also related to disrupted nighttime sleep [18]. An Indian study reported a delay in achieving cognitive milestones of children (below 2 years) with respect to digital media exposure [25]. There are less parent-child interactions [27] and increased chances of conflicts [13] when the parents’ attention is absorbed. Children try to mimic their parental screen time behaviors [1,4,14,17] and/or the programs they watch on screens [10]. Child’s aggressive [6,10] and antisocial behaviors [10] are related to augmented screen time. Due to a lack of positive role models, and indiscriminate watching of media content, children might have behavioral problems [10].

Long-standing consequences of digital media use predict worsened behavioral outcomes in the children when they grow older [26]. Development path of the children exposed to excessive digital-media may lead to unhealthy adolescence [9]. In the school, they are less likely to get engaged, and may be prone to victimization [9]. Children with accentuated screen time have a predominantly higher prevalence of overweight [22], obesity [19] and NCDs [3].

The setting for delivering the interventions was mainly at family [31,32,35-37,39,43,44], and/or home level [31,38,40,43-45], with a few at school [34,35,41,42,46], or clinic- [39,43], or community-level [33]. Most of the interventions were based on behavior change theories such as; social cognitive theory [31,32,34,35,38,42,44], social determination theory [34,35] family systems theory [32], social ecological model [36], health belief model [35], chronic care model [39], attitude social influence self-efficacy model, precaution process model, elaboration likelihood model, the stages of change model [40] or none [33,37,41,43,46]. The intervention packages specifically focused on increasing the information related to digital-media, by holding counseling sessions or using educational material. Educational materials were mostly shared with parents [31-33,36-41,43,45], followed by teachers [34,35,42,46] children [37,46] and community members [33]. Seven studies had focused primarily on screen time reduction [31,32,38,39,41-43], and six studies [33,35-37,40,41] additionally included a follow-up with the participants post-intervention to assess the adherence to the intervention. Some studies had interventions to increase the physical activity [34,37,40,45,46] and reduce the sedentary time [42], body mass index [33,35,36,44,46], sedentary behavior [42,44], violent behaviors, tobacco smoking, [44], and modify the eating behaviors of children [33,34,37,45,46]. The reduction in screen time among under-five children varied from 0.3 (SE=13.3) minutes to 47.16 (SE=2.01) minutes in the high-income countries. The most effective intervention strategy was theory-based and delivered at the family level [44]. The child’s knowledge regarding engagement in screen-based activities [31,34-36,42,43,45,46], home-based rules regarding TV turnoff time [38], and the alternatives used by parents for reducing digital-media use had a significant effect on reducing the screen time. The comparator group in most of the studies received the usual health care services except in two studies, where session on media use were held and national guidelines on media use among children were shared. [33,45] .

Intervention studies to reduce screen time has been reported from high-income countries only [31-46]. (Web Table II). There is no published intervention studies from LMICs. The intervention strategy of utilizing a child’s knowledge to engage in sedentary behavior [31,34-36,42,43,45,46] was found to be effective in reducing the excessive ST. Also, primary caretaker’s role to mediate [31,33,36-41,43,44] the digital media exposure among children was central in regulating the screen time.

The results of this review have highlighted that there is a high prevalence of excessive screen time among under-five children in the high - and middle-income countries. There are several health impacts of excessive screen time including emotional, sleep, behavioral issues impairing the growth and cognitive development of under-five children. Most of the high-income countries have made guidelines for limiting the excessive digital-media usage for all age groups including Canada [48], Australia [50], and Itlay [49] while, several LMICs have no such guidelines. The findings of this review might be useful for the policymakers in formulating such guidelines in these countries.

Based upon the results of this review, we recommend that pediatricians should explore the history of screen time from the parents of all under-five children visiting them in the clinics and about the digital-media home environment, and advise to not to use digital gadgets for children less than 2 years and limit it to one hour for children age 2-5 years. The policy-makers and associations like Indian Academy of Pediatrics should formulate guidelines on permissible limits of screen time among children. As, there is a paucity of data on the prevalence of screen time among under-fives from LMICs, such studies should be planned to understand the cultural context of screen time use in these settings. Also, culturally appropriate interventions to reduce the same in the LMICs should be designed. Such studies are of utmost importance considering the worsening mental [5-7,10] and physical health of children [4,5,9], and to prevent NCDs.

Acknowledgement: Dr. Kamal Kishore, Lecturer, Department of Biostatistics, PGIMER for providing technical inputs in the methods of this review.

Contributors: MG: contributed to the methods and discussion section; NK, MG: jointly conceived the idea; NK, MG, SG, PM: assessed the studies for inclusion in the review; NK, MG: extracted the data; SG, PM: contributed in describing the related text of the studies; NK: wrote the first draft of the manuscript. All the authors provided technical inputs to improve the intellectual content of the manuscript and approved the final version of manuscript.

Funding: None; Competing interest: None stated.

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