This cohort study analyzes whether children’s screen time exposure between ages 6 and 72 months is associated with their cognitive and social-emotional development.
Key Points
Question
Is early screen exposure associated with children’s cognitive, language, and social-emotional development?
Findings
In this cohort study of 152 children aged 6 to 72 months, children’s screen time was classified into 3 trajectories of continued low, late increasing, and early increasing. Excessive screen time (ie, late increasing and early increasing trajectories vs continued low trajectory) was found to be associated with worse cognitive and social-emotional development outcomes.
Meaning
The findings of this study suggest that both the duration and the onset of screen exposure matters in terms of children’s cognitive and social-emotional development.
Abstract
Importance
Screen time has become an integral part of children’s daily lives. Nevertheless, the developmental consequences of screen exposure in young children remain unclear.
Objective
To investigate the screen time trajectory from 6 to 72 months of age and its association with children’s development at age 72 months in a prospective birth cohort.
Design, Setting, and Participants
Women in Shanghai, China, who were at 34 to 36 gestational weeks and had an expected delivery date between May 2012 and July 2013 were recruited for this cohort study. Their children were followed up at 6, 9, 12, 18, 24, 36, 48, and 72 months of age. Children’s screen time was classified into 3 groups at age 6 months: continued low (ie, stable amount of screen time), late increasing (ie, sharp increase in screen time at age 36 months), and early increasing (ie, large amount of screen time in early stages that remained stable after age 36 months). Cognitive development was assessed by specially trained research staff in a research clinic. Of 262 eligible mother-offspring pairs, 152 dyads had complete data regarding all variables of interest and were included in the analyses. Data were analyzed from September 2019 to November 2021.
Exposures
Mothers reported screen times of children at 6, 9, 12, 18, 24, 36, 48, and 72 months of age.
Main Outcomes and Measures
The cognitive development of children was evaluated using the Wechsler Intelligence Scale for Children, 4th edition, at age 72 months. Social-emotional development was measured by the Strengths and Difficulties Questionnaire, which was completed by the child’s mother. The study described demographic characteristics, maternal mental health, child’s temperament at age 6 months, and mental development at age 12 months by subgroups clustered by a group-based trajectory model. Group difference was examined by analysis of variance.
Results
A total of 152 mother-offspring dyads were included in this study, including 77 girls (50.7%) and 75 boys (49.3%) (mean [SD] age of the mothers was 29.7 [3.3] years). Children’s screen time trajectory from age 6 to 72 months was classified into 3 groups: continued low (110 [72.4%]), late increasing (17 [11.2%]), and early increasing (25 [16.4%]). Compared with the continued low group, the late increasing group had lower scores on the Full-Scale Intelligence Quotient (β coefficient, –8.23; 95% CI, –15.16 to –1.30; P < .05) and the General Ability Index (β coefficient, –6.42; 95% CI, –13.70 to 0.86; P = .08); the early increasing group presented with lower scores on the Full-Scale Intelligence Quotient (β coefficient, –6.68; 95% CI, –12.35 to –1.02; P < .05) and the Cognitive Proficiency Index (β coefficient, –10.56; 95% CI, –17.23 to –3.90; P < .01) and a higher total difficulties score (β coefficient, 2.62; 95% CI, 0.49-4.76; P < .05).
Conclusions and Relevance
This cohort study found that excessive screen time in early years was associated with poor cognitive and social-emotional development. This finding may be helpful in encouraging awareness among parents of the importance of onset and duration of children’s screen time.
Introduction
Increasing screen exposure and many unfavorable associations with physical health problems (eg, greater risk of obesity, sleep disturbance), decreased mental well-being (eg, depression, decrease in self-esteem), and poor academic performance have been well documented, mainly in school-aged children and adolescents.1,2 The increase in early-life screen exposure, from birth to age 6 years, however, has raised the greatest concern,3 particularly because of rapid brain development, the brain’s susceptibility to early environmental experiences,4 and the increasing volume of media products targeting young children.5 Previous research suggests that screen exposure is associated with cognitive and noncognitive development, including poor attention,6,7,8,9 lack of behavioral control,10,11 delayed language,12,13,14,15,16,17 and deficits in executive functions in young children.18 Nevertheless, most previous studies collected data at 1 or 2 time points. The association between age and screen exposure has been understudied.19 Because the experience-dependent synapses formation of different brain regions occurs at different age periods,4 the consequences of screen exposure on developmental outcomes may vary by age. Zimmerman and Christakis20 found that the association between early screen exposure and school-age cognitive performance differed between children who were exposed before or after 3 years of age. A recent study by McArthur et al21 also revealed that greater screen use at age 24 months, rather than at ages 36 and 60 months, was associated with lower reading levels later in life. Because children’s screen use may change over time, it is important to study screen time trajectories using a longitudinal framework and repeated measures during the early years, which may provide a stronger indication of longitudinal screen habits.
The existing research often lacks baseline measures and other important factors that are necessary to be controlled for in studies of the association between screen exposure and developmental outcomes.19 For instance, Stevens and Mulsow22 and Schmidt et al23 reported no meaningful association between screen exposure and developmental outcomes when relevant characteristics of study participants, such as the heterogeneity in socioeconomic status, were taken into account.
To address these knowledge gaps, the current study used a longitudinal birth cohort with frequent follow-up points in an urban area of Shanghai, China, to answer the following questions: (1) What is the trajectory of screen exposure from age 6 to 72 months? (2) Is early screen exposure associated with cognitive, language, and social-emotional development? (3) Does this association vary by age period?
Methods
Study Design and Participants
The ongoing Shanghai Sleep Birth Cohort Study aims to identify the association of perinatal and early life environments and behavioral factors with child development.24 In this cohort study, we screened the obstetrical records of late pregnant individuals (36 to 38 weeks’ gestation) who came to consultation sessions on maternal care at Renji Hospital in Shanghai, China, from May 2012 to July 2013. Data were analyzed from September 2019 to November 2021. A total of 431 healthy pregnant individuals were eligible (eTable 5 and eFigure 1 in the Supplement). We then approached the candidates to confirm their eligibility. A total of 277 pregnant individuals agreed to participate in this study, and, after delivery, 262 individuals with full-term newborns were enrolled and attended the prescheduled follow-up visits. The study was approved by the Shanghai Children’s Medical Center Human Ethics Committee, and written informed consent was obtained from the participants. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Measures
Screen Time
Trained pediatric postgraduate students interviewed the participants to indicate the screen time of their children. When children were aged 6, 9, 12, 18, 24, and 36 months, their mothers responded to the question, “How long does your child spend on the screen-based electronic medium (e.g., television, computer, tablet, smartphone) in a typical day during the last month?” Participants reported the mean number of hours and minutes per day their child spent on screen time. When children were aged 48 and 72 months, their mothers reported the time that children spent watching educational, entertainment, and non–child directed programs; playing video games; and searching online on a typical weekday and weekend, from which the total screen time was derived. The daily mean screen time was calculated using the following formula: ([weekday screen time × 5] + [weekend screen time × 2]) ÷ 7.
Cognitive Development
The Wechsler Intelligence Scale for Children, 4th edition (WISC-IV) was used to evaluate the general intellectual ability of children when they were aged 72 months. The raw scores from the subtests can be converted to scaled scores based on a Chinese normative sample.25 The Full-Scale Intelligence Quotient (FSIQ) is derived from the scores of 4 domains: verbal comprehension, perceptual reasoning, processing speed, and working memory. The General Ability Index is a composite score derived from the Verbal Comprehension Index and the Perceptual Reasoning Index subtests that reflect reasoning abilities. The Cognitive Proficiency Index is composed of the Working Memory Index and the Processing Speed Index subtests and provides a summary of cognitive efficiency and proficiency.
The assessment was administered by pediatric postgraduate students who were trained by qualified assessors, using the Chinese WISC-IV technical manual. All forms were initially checked for data quality by trained research assistants and double-checked by a research assistant who was not involved in the primary data collection before data entry. The test room was set in the Shanghai Children’s Medical Center and was free of distraction.
Social-Emotional Development
When the children were aged 48 and 72 months, their mothers completed the Strengths and Difficulties Questionnaire (SDQ). The Chinese version of the SDQ has shown good reliability and validity in the population-based study.26 The questionnaire comprises 5 scales with 5 items each, generating scores for emotional symptoms, conduct problems, hyperactivity and inattention, peer problems, and prosocial behavior; all scales but the last are summed to yield a total difficulties score (range, 0-40). In general, a high score represents greater difficulties, except for the prosocial behavior score, for which a lower score indicates greater difficulties. In the current study, we used the data of SDQ scores at age 72 months only.
Covariates
The participant’s highest educational attainment (≤ high school diploma, college or bachelor’s degree, or ≥ master’s degree), family income (≤139 000 RMB [renminbi; to convert to US dollars, multiply by 0.15], 140 000-199 000 RMB, or ≥200 000 RMB), and child sex (male or female) were included.
The Edinburgh Postnatal Depression Scale (score range, 0-30, with higher scores indicating more symptoms of depression) was used to assess whether participants had symptoms of postnatal depression at 42 days after delivery.27 The participants’ mental health was categorized as normal or abnormal based on the score.
At 6 months of age, each child’s temperament type was assessed using the Chinese Infant Temperament Scale (in which infants are classified into 5 types: difficult [arrhythmic, withdrawing, low adaptability, intense, and negative], easy [opposite characteristics of difficult], slow to warm up [inactive, low in approach and adaptability, mild, and negative], intermediate low, and intermediate high), completed by the mother.28 Temperament was classified into 2 types: easy and noneasy (including difficult, slow to warm up, intermediate low, and intermediate high).
At 12 months of age, the Bayley Scales of Infant Development mental scale was administered to children individually by trained pediatric postgraduate students.29 The Mental Development Index (MDI) is a standardized score with a mean (SD) of 100 (16), calculated with a Chinese norm. A higher score indicates better mental development.
Statistical Analysis
Analyses were restricted to participants with complete data for demographic characteristics, maternal mental health, child’s temperament at age 6 months, mental development at age 12 months, WISC-IV and SDQ scores at age 72 months, and screen time data available for at least 3 points from ages 6 to 72 months (152 children) (eFigure 1 in the Supplement).
Screen exposure changes over time and differs among individuals.30 Yet screen exposure at different time points is interrelated with each individual. The group-based trajectory model was used to identify clusters of individuals who followed similar progressions of screen exposure over different ages,31 which enabled us to detect the dose-accumulative association of screen exposure with developmental outcomes using a longitudinal framework. The screen time trajectories of children at ages 6, 9, 12, 18, 24, 36, 48, and 72 months were identified using the group-based trajectory model. Several goodness-of-fit and model adequacy indexes, such as bayesian information criterion, were used to select the best model (eMethods in the Supplement).
We described demographic characteristics, maternal mental health, child’s temperament at age 6 months, and mental development at age 12 months by subgroups clustered by the group-based trajectory model. Group difference was examined by analysis of variance. Mean effect size was estimated to explore the association of screen time trajectory groups with developmental outcomes at age 6 years after adjustment for demographic characteristics, maternal mental health at 42 days after delivery, child’s temperament type at age 6 months, and mental development at age 12 months using inverse-probability weighting. All statistical analyses were performed with Stata, version 17 (StataCorp, LLC), and a 2-sided P < .05 was considered statistically significant.
Results
There were no significant differences in the distribution of sex, mother’s educational attainment, or family income between those included in the analysis and all 262 children in the original cohort (eTable 1 in the Supplement). Among the 152 children included in the study, 50.7% (77) were girls and 49.3% (75) were boys. The mean (SD) age of the 152 mothers included in the study was 29.7 (3.3) years. Furthermore, 92.1% (140) of the mothers had a bachelor’s degree or above (Table 1).
Table 1. Characteristics of Children in 3 Groups.
| Characteristic | Total, No. (%) (n = 152) | Screen time trajectory group, No. (%) | P value | ||
|---|---|---|---|---|---|
| Continued low (n = 110) | Late increasing (n = 17) | Early increasing (n = 25) | |||
| Sex | |||||
| Male | 75 (49.3) | 50 (45.5) | 9 (52.9) | 16 (64.0) | .23 |
| Female | 77 (50.7) | 60 (54.5) | 8 (47.1) | 9 (36.0) | |
| Mother’s educational attainment | |||||
| ≤High school diploma | 12 (7.9) | 6 (5.5) | 2 (11.8) | 4 (16.0) | .47 |
| College or bachelor’s degree | 114 (75.0) | 85 (77.3) | 12 (70.6) | 17 (68.0) | |
| ≥Master’s degree | 26 (17.1) | 19 (17.3) | 3 (17.6) | 4 (16.0) | |
| Annual family incomea | |||||
| <139 000 RMB | 54 (35.5) | 36 (32.7) | 11 (64.7) | 7 (28.0) | .05 |
| 140 000-199 000 RMB | 44 (28.9) | 30 (27.3) | 4 (23.5) | 10 (40.0) | |
| ≥200 000 RMB | 54 (35.5) | 44 (40.0) | 2 (11.8) | 8 (32.0) | |
| Maternal mental health by EPDS | |||||
| Normal (score <13) | 134 (88.2) | 97 (88.2) | 14 (82.4) | 23 (92.0) | .64 |
| Abnormal (score ≥13) | 18 (11.8) | 13 (11.8) | 3 (17.6) | 2 (8.0) | |
| Type of temperament by CITS at 6 mo | |||||
| Easy | 63 (41.4) | 42 (38.2) | 8 (47.1) | 13 (52.0) | .40 |
| Noneasy | 89 (58.6) | 68 (61.8) | 9 (52.9) | 12 (48.0) | |
| Mental development by BSID-MDI score at 12 mo, mean (SD) | 113.9 (12.3) | 112.9 (12.9) | 120.2 (7.8) | 113.8 (11.0) | .08 |
Abbreviations: BSID-MDI, Bayley Scales of Infant Development–Mental Development Index; CITS, Chinese Infant Temperament Scale; EPDS, Edinburgh Postnatal Depression Scale; RMB, renminbi (Chinese currency).
To convert RMB to US dollars, multiply by 0.15.
The optimal group-based trajectory model was selected based on the goodness-of-fit and model adequacy indexes (eTable 2 and eFigure 2 in the Supplement). Children were classified into 3 distinct groups based on their screen time trajectories at 6, 9, 12, 18, 24, 36, 48, and 72 months of age (Figure 1). As illustrated in Figure 2, the continued low trajectory group (n = 110 [72.4%]) was characterized by a relatively stable amount of screen time, starting at a mean (SD) time of 6.8 (16.0) minutes at 6 months of age and leveling off at 68.1 (37.9) minutes by 72 months of age. The late increasing trajectory group (n = 17 [11.2%]) had a mean (SD) screen time of 15.6 (32.6) minutes at 6 months of age, with a similar pattern to the continued low trajectory group in the early stages but exhibited a much sharper increase after 36 months of age, with the largest mean (SD) time of 230.1 (45.5) minutes among the 3 groups at 72 months of age. The early increasing trajectory group (n = 25 [16.4%]) had a large amount of screen time in the early stages, with a mean (SD) time of 150.3 (50.6) minutes at 24 months of age, but remained stable after 36 months of age, with a mean (SD) time of 123.8 (68.6) minutes at 72 months of age. The actual pattern of individual screen time was similar to the fitted curve based on the group-based trajectory models (eFigures 3-5 in the Supplement).
Figure 1. Screen Time Trajectories of the 3 Groups.
Solid lines indicate estimated trajectories, and shaded areas indicate 95% pointwise CIs using the group-based trajectory model.
Figure 2. Mean Screen Time of the 3 Groups.
Mean screen time and 95% CIs from age 6 to 72 months in each group.
Table 1 presents a comparison of the descriptive characteristics of the children in the 3 groups. Children in the late increasing group were more likely to be from families with a low income and scored marginally higher on the Bayley Scales of Infant Development–Mental Development Index at age 12 months. There was no significant difference in sex, mother’s educational attainment, maternal mental health, or child’s temperament type at age 6 months among the 3 groups.
In unadjusted analyses (eTable 3 in the Supplement), children in the late and early increasing trajectory groups were more likely to have a lower FSIQ score in the WISC-IV and a higher total difficulties score in the SDQ at age 72 months. In the adjusted models (Table 2), compared with the continued low group and after adjusting for sex, mother’s educational attainment, family income, maternal mental health, child’s temperament type at age 6 months, and mental development at age 12 months, the late increasing group was significantly associated with a lower score for the FSIQ (β coefficient, –8.23; 95% CI, –15.16 to –1.30; P < .05), General Ability Index (β coefficient, –6.42; 95% CI, –13.70 to 0.86; P = .08), verbal comprehension (β coefficient, –5.55; 95% CI, –11.66 to 0.57; P = .08), perceptual reasoning (β coefficient, –6.35; 95% CI, –12.63 to –0.69; P < .05), Cognitive Proficiency Index (β coefficient, –7.02; 95% CI, –13.87 to –0.16; P < .05), and working memory (β coefficient, –6.75; 95% CI, –11.43 to –2.06; P < .01) as well as a higher score for hyperactivity and inattention (β coefficient, 1.22; 95% CI, 0.01-2.43; P < .05) at age 72 months. The early increasing group was significantly associated with a lower score for the FSIQ (β coefficient, –6.68; 95% CI, –12.35 to –1.02; P < .05), Cognitive Proficiency Index (β coefficient, –10.56; 95% CI, –17.23 to –3.90; P < .01), working memory (β coefficient, –11.25; 95% CI, –15.47 to –7.03; P < .001), and processing speed (β coefficient, –8.00; 95% CI, –16.26 to 0.27; P = .06) and a higher score on total difficulties (β coefficient, 2.62; 95% CI, 0.49-4.76; P < .05) and hyperactivity and inattention (β coefficient, 1.70; 95% CI, 0.70-2.71; P < .01) at age 72 months.
Table 2. Screen Time Trajectory and Child Development Measured by Adjusted β Coefficient From Inverse Probability–Weighted Analysis at Age 72 Months.
| Development score | Late increasing trajectory group | Early increasing trajectory group | P valueb | ||
|---|---|---|---|---|---|
| β coefficienta (95% CI) | P value | β coefficienta (95% CI) | P value | ||
| WISC-IV | |||||
| Full-Scale Intelligence Quotient | –8.23 (–15.16 to –1.30) | <.05 | –6.68 (–12.35 to –1.02) | <.05 | .71 |
| General Ability Index | –6.42 (–13.70 to 0.86) | .08 | –1.88 (–7.40 to 3.64) | .50 | .28 |
| Verbal comprehension | –5.55 (–11.66 to 0.57) | .08 | –0.45 (–4.37 to 3.48) | .82 | .13 |
| Perceptual reasoning | –6.35 (–12.63 to –0.69) | <.05 | –3.45 (–9.17 to 2.28) | .24 | .45 |
| Cognitive Proficiency Index | –7.02 (–13.87 to –0.16) | <.05 | –10.56 (–17.23 to –3.90) | <.01 | .43 |
| Working memory | –6.75 (–11.43 to –2.06) | <.01 | –11.25 (–15.47 to –7.03) | <.001 | .10 |
| Processing speed | –5.80 (–13.64 to 2.05) | .15 | –8.00 (–16.26 to 0.27) | .06 | .69 |
| SDQ | |||||
| Total difficulties | 2.11 (–0.67 to 4.90) | .14 | 2.62 (0.49 to 4.76) | <.05 | .76 |
| Emotional symptoms | 0.20 (–0.80 to 1.20) | .70 | 0.12 (–0.68 to 0.92) | .77 | .90 |
| Conduct problems | 0.43 (–0.08 to 0.95) | .10 | 0.43 (–0.19 to 1.04) | .17 | .99 |
| Hyperactivity and inattention | 1.22 (0.01 to 2.43) | <.05 | 1.70 (0.70 to 2.71) | <.01 | .51 |
| Peer relationship problems | 0.26 (–0.58 to 1.10) | .54 | 0.37 (–0.17 to 0.91) | .18 | .81 |
| Prosocial behavior | 0.47 (–0.53 to 1.47) | .36 | 0.43 (–0.33 to 1.19) | .27 | .95 |
Abbreviations: SDQ, Strengths and Difficulties Questionnaire; WISC-IV, Wechsler Intelligence Scale for Children, 4th edition.
Continued low group used as reference. Adjusted for sex, mother’s educational attainment, family income, and maternal mental health, evaluated using the Edinburgh Postnatal Depression Scale at age 42 days; adjusted for child’s temperament types, evaluated using the Chinese Infant Temperament Scale at age 6 months; and adjusted for mental development, evaluated using the Bayley Scales of Infant Development–Mental Development Index at age 12 months.
P value compares early increasing vs late increasing groups.
Discussion
To our knowledge, this study is among the first to describe associations between screen time trajectories and development in the first 6 years of life by using multipoint data. We found that children’s screen exposure from age 6 to 72 months can be characterized into 3 trajectories: continued low, early increasing, and late increasing. The screen exposure trajectory was associated with cognitive and social-emotional outcomes at 72 months of age.
In terms of cognitive outcomes, similar levels of mental development were observed at age 12 months across all 3 groups, whereas there was a significantly lower FSIQ score in the late increasing and early increasing groups at age 72 months compared with the continued low group. Furthermore, the results of this study indicate that the association between screen exposure and developmental outcomes may vary by age periods.19,20,21 That is, compared with children in the continued low group, those in the late increasing group had lower scores on the verbal comprehension and perceptual reasoning scales. These 2 scales constitute the General Ability Index that is learning related.26 Accumulating evidence indicates that parental participation in cognitively stimulating activities, such as reading, provision of child-appropriate learning materials, and sensitive and responsive interactions between caregiver and child, is a contributor to optimal general ability development.32,33 Children in the late increasing group had excessive screen exposure (up to 4 hours per day) between ages 36 and 72 months. It is likely that time- and energy-dependent general ability development, including verbal and reasoning skills, is restricted by their screen use.34
Furthermore, working memory and processing speed appear to be compromised among children in both late and early increasing trajectory groups, especially for those in the early increasing group. This change may be attributable to the adverse implications of screen exposure during infancy for the development of brain regions related to cognitive control. That is, as early as the first 3 years of life, environmental stimuli evoke children’s active cognitive processing, enabling the establishment of functional connectivity between the prefrontal cortex and various brain regions and, therefore, the top-down network required for cognitive control.35,36,37 Screen exposure, such as watching television, typically takes the form of auditory and visual stimulation that is characterized by passive processing38 and, hence, is likely to lead to underdevelopment of brain networks related to cognitive control and low cognitive proficiency. Furthermore, researchers recently have found that even in top downloaded educational apps, the quality of interactive features was low. Apps currently on the market encouraged less “minds-on” learning with high levels of advertising and distracting animations and few embedded opportunities for in-person or mediated social interaction.39 This finding further supported our hypothesis that excessive screen use might impede children’s opportunities for active cognitive processing in daily lives. Future studies are warranted to further investigate the mechanisms of such an association.
In terms of social-emotional outcomes, we found that, compared with children in the continued low group, those in the early increasing group had a significantly higher total difficulties score on the SDQ. Although associations between screen exposure and social-emotional outcomes have been widely reported,7,8,9,10,11,40,41 it is critical to note the lack of baseline measures in most of these studies. Children with social-emotional difficulties are likely to experience increased screen exposure,21,42,43 but without a valid baseline measure, whether screen exposure is a contributor to these difficulties remains inconclusive. Indeed, studies that took baseline measures into consideration reported similar results40,41 to those of the present study with regard to outcomes of children in the early increasing trajectory group. It is worth noting that the association is mainly associated with the domain of hyperactivity and inattention, which is also considered an external behavior associated with cognitive control. Taken together, the association of screen exposure on cognitive control has been supported by parent-reported measures and performance-based assessment (ie, WISC-IV).
Limitations
This study has several limitations. First, the relatively small sample size may compromise the statistical power of the results and may, therefore, limit our capacity to detect a significant difference between early and late increasing groups. Nevertheless, the findings revealed associations between screen exposure during early years and developmental outcomes at age 6 years. Second, the current study measured the amount of screen time but not the content. Future studies are encouraged to take into consideration the content of screen exposure, especially for children with late increases in screen time. Third, the current study relied on parent reports of child screen exposure time, which may overestimate the screen exposure. Nevertheless, parent reports have been widely used in the literature. Anderson et al44 reported a correlation between parent reports and objective measures of screen exposure time. Fourth, although we measured the temperament and mental development of the children at baseline, we did not assess hyperactivity and inattention. Thus, it is possible that the association between early increasing screen exposure and hyperactivity and inattention symptoms might be confounded, as children with hyperactivity and inattention crave stimulation and can be satisfied only by more screen activity. Fifth, confounders such as parenting sensitivity and parent-child interaction were not taken into account in the models, which will be considered in future studies. Sixth, the study population had a relatively high educational level (eTable 4 in the Supplement), potentially limiting the generalizability of the results. As previous research has noted, the heterogeneity of socioeconomic status may be a contributor to the association between screen exposure and developmental outcomes.19,22 Although the homogeneity of the socioeconomic status distribution in the current sample may have reduced the potential confounding effect, future studies with families of different socioeconomic status need to be conducted.
Conclusion
This cohort study found that excessive screen exposure in early years is associated with poorer cognitive and social-emotional development, especially working memory capacities. These results showed that the association between screen exposure and developmental outcomes varies by age, and it substantiated the argument that the practice of nurturing care should be guided by the sensitive-periods paradigm.33,45 With the current pervasiveness of digital products, the findings of the study may help encourage parents to be aware of the importance of both the onset and duration of screen exposure in early life, which aligns with the current guidelines on screen use.46,47 Future studies are needed to evaluate the long-term association between early screen exposure and development outcomes and lifespan well-being.
eMethods. Trajectory Analysis
eTable 1. Participant Characteristics of Sample Included in the Analysis
eTable 2. Statistical Parameters for 2-, 3-, and 4-Group-Based Trajectory Models
eTable 3. Cognitive and Psychosocial Development of Children at 72 Months by Screen Time Trajectory Group
eTable 4. Comparison of Demographic Characters Between Current Study and SCHDULE-P Study
eTable 5. Eligibility Criteria of Sample in Birth Cohort
eFigure 1. Flowchart of the Study Participants
eFigure 2. Group-Based Trajectory Models for 2-, 3-, and 4-Group Adherence Trajectory Solution
eFigure 3. Screen Time Trajectories of Individuals in the Continued Low Group
eFigure 4. Screen Time Trajectories of Individuals in the Late Increasing Group
eFigure 5. Screen Time Trajectories of Individuals in the Early Increasing Group
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eMethods. Trajectory Analysis
eTable 1. Participant Characteristics of Sample Included in the Analysis
eTable 2. Statistical Parameters for 2-, 3-, and 4-Group-Based Trajectory Models
eTable 3. Cognitive and Psychosocial Development of Children at 72 Months by Screen Time Trajectory Group
eTable 4. Comparison of Demographic Characters Between Current Study and SCHDULE-P Study
eTable 5. Eligibility Criteria of Sample in Birth Cohort
eFigure 1. Flowchart of the Study Participants
eFigure 2. Group-Based Trajectory Models for 2-, 3-, and 4-Group Adherence Trajectory Solution
eFigure 3. Screen Time Trajectories of Individuals in the Continued Low Group
eFigure 4. Screen Time Trajectories of Individuals in the Late Increasing Group
eFigure 5. Screen Time Trajectories of Individuals in the Early Increasing Group