ABSTRACT
Aim
To assess prospective associations between media parenting practices and screen time and problematic screen use in early adolescents.
Methods
We used data from the Adolescent Brain Cognitive Development Study, a prospective cohort of 7947 adolescents [M age 12.9 years]. Media parenting practices from Year 3 (2019–2021) and adolescent‐reported screen time, app‐reported smartphone time (subsample N = 840), and problematic screen use from Year 4 were analyzed using linear regression models adjusted for potential confounders.
Results
Use of screens to control behaviour (e.g., as a reward or punishment) and adolescent bedroom screen use were associated with greater screen and smartphone time. Parental screen time modelling and family mealtime screen use were associated with greater screen time. Parental monitoring and limiting of screen time were associated with lower adolescent screen time. Parental monitoring was also associated with lower smartphone time. Parental screen time modelling and use of screens to control behaviour were associated with problematic social media use, while family mealtime screen use, adolescent bedroom screen use, and use of screens to control behaviour were associated with problematic mobile phone use.
Conclusion
These findings suggest that counselling families on specific media parenting practices may help reduce adolescent screen exposure and problematic screen use.
Keywords: adolescent, digital media, media, parenting, screens, technology, youth
Summary
Media parenting practices play a central role in shaping adolescents' digital behaviour, but there remains a lack of prospective studies.
While all media parenting practices were linked to self‐reported screen time, only select practices (e.g., bedroom restrictions, screens to control behavior) were associated with lower app‐reported smartphone use and problematic screen behaviours.
These findings highlight actionable parenting strategies that paediatricians can counsel families on to help reduce screen exposure and problematic use.
Abbreviations
- ABCD
Adolescent Brain Cognitive Development
- COVID‐19
Coronavirus disease
- EARS
Effortless Assessment Research System
- IRB
institutional review board
- MPIQ
Mobile Phone Involvement Questionnaire
- SMAQ
Social Media Addiction Questionnaire
1. Introduction
The widespread use of mobile phones and social media has sparked concern about their effects on children and adolescents. Problematic adolescent screen use has been linked to depression, eating disorders, sleep disturbance, obesity, and other health challenges [1, 2, 3, 4]. Less parental oversight of screen use may make adolescents more vulnerable to risky behaviours, such as binge drinking and marijuana use [5]. Patterns of problematic screen use mirror features of behavioural addiction, with symptoms such as loss of control, tolerance, withdrawal, and interpersonal conflict when screen access is restricted [6, 7]. These behaviours often interfere with academic performance, sleep, and daily routines [7, 8].
As digital technology evolves, understanding the role of “media parenting practices,” strategies parents use to guide their children's technology use, has become increasingly important [9]. Existing studies on media parenting practices have primarily focused on infants [10] and young children (ages 3–8) [9, 11, 12, 13, 14, 15, 16, 17]. In these studies, positive media parenting practices, such as parental screen‐time modelling and avoidance of screen use during mealtimes, have been found to reduce screen time in early childhood [9, 14, 18]. Although there are weaker correlations between media parenting practices and screen time among older children and teens [19], past studies suggest that parental media practices can mitigate problematic social media use among adolescents [20].
Given the crucial role parents play in shaping their children's development, factors such as parenting styles, the parent–child relationship, and the home environment are critical areas of focus for understanding and intervening in screen use patterns [11, 20]. Previous studies demonstrated that internet‐specific rules were associated with reduced problematic screen use [21], while parental monitoring was associated with lower overall screen time among both children and adolescents [22]. In contrast, punitive strategies, such as using screen restriction as a form of discipline, have been tied to increased rates of problematic screen use [20, 21]. Despite these insights, existing studies are limited by their cross‐sectional design and their reliance on self‐reported data.
In prior analyses using data from the Adolescent Brain Cognitive Development (ABCD) Study, a large, prospective study of a diverse sample of adolescents in the United States (U.S.), we found that some media parenting practices, such as parental screen time monitoring and limiting of adolescent screen time, were associated with lower total screen time, problematic use, and exposure to mature media content in early adolescence [23, 24]. However, the cross‐sectional design of these analyses limited our ability to infer the directionality and temporality of the relationships. Additionally, the findings relied exclusively on self‐reported data, presenting a need for further evaluation of these variables with objective data to reduce response bias and present a more accurate assessment of adolescents' screen use.
Using prospective data from the ABCD Study, we aimed to assess the relationship between media parenting practices (e.g., screen time modelling, mealtime screen use, bedroom screen use, use of screens for behavioural control, and parental monitoring and limiting of screen time) and adolescent screen use (e.g., self‐reported screen time, app‐reported smartphone time, problematic social media use, and problematic mobile phone use) 1 year later.
2. Methods
2.1. Study Population
The data were collected from the Adolescent Brain Cognitive Development (ABCD) Study, a large prospective cohort study with 11 875 adolescents from 21 sites across the U.S. The study used data from the ABCD 6.0 release, which included the Year 3 follow‐up (2019–2021, ages 11–14 years) and Year 4 follow‐up (2020–2022, ages 12–16 years). The sample included 7947 adolescents with data for media parenting practices and any indicator of adolescent screen use (adolescent‐reported screen time, app‐reported smartphone time, problematic social media use, or problematic mobile phone use). Differences in sociodemographic characteristics of those who were included in any part of the analysis (N = 7947) and those excluded due to missing data are outlined in Table S1. The ABCD Study received centralised institutional review board (IRB) approval from the University of California, San Diego, and the participating study sites received local IRB approval. Written informed consent was provided by parents/guardians, and written assent was provided by each study participant.
2.2. Media Parenting Practices
Parents of adolescent participants completed a self‐reported survey regarding their screen time parenting practices. The 14‐item questionnaire was grouped into six categories [(1) parental screen time modelling (two questions): assessing parents' own screen use in front of the adolescent; (2) family mealtime screen use (two questions): assessing screen use of the family during meals; (3) bedroom screen use (three questions): assessing adolescents' screen use in the bedroom; (4) parental control of screen use (two questions): assessing the parental control of adolescent screen time for rewards or punishments; (5) parental monitoring of screen use (two questions): assessing parental monitoring of the adolescent's screen use during the week and weekend; and (6) parental limiting of screen use (three questions): assessing parental limit‐setting of the adolescent's screen use during the week and weekend] [9]. Likert‐type scale responses ranged from 1 (Strongly Disagree) to 7 (Strongly Agree). Responses to questions in each category were averaged to obtain a mean score for that question, and responses to all items in each category were averaged to obtain a mean score for each media parenting practice. If any response was missing, the mean score was derived using the available responses. The question, “I try to limit how much I use a screen‐based device when I am with my child,” was reverse‐coded to preserve the directionality of the responses within the screen time modelling category, as done in previous studies [23].
2.3. Adolescent‐Reported Screen Use
Total recreational screen time was calculated using adolescents' self‐reported hours and minutes of typical weekday and weekend screen time use [25]. Daily screen time (h/day) was calculated as a weighted sum [(weekday average × 5) + (weekend average × 2)]/7 as done in prior literature [26]. Participants were specifically asked to include recreational screen use, such as watching TV, shows or videos, texting or chatting, playing games, or visiting social networking sites (e.g., Facebook, Twitter, Instagram), but not to include screen use for school‐related work.
2.4. App‐Reported Smartphone Use
Total smartphone time was only assessed in a portion of the sample starting in Year 4 (N = 840) using a phone app called Effortless Assessment Research System (EARS) [27]. Differences in sociodemographic characteristics of those who had app‐reported data (n = 840) and those who did not (n = 7107) are outlined in Table S2. The EARS app, used in previous paediatric research, was adjusted for the ABCD Study and passively collects smartphone data on the duration and time of day of specific apps' use for Android users only [28].
The ABCD‐EARS app was tested in a pilot study during Year 2 follow‐up and offered as an opt‐in program to all participants starting from Year 4 [28]. The ABCD‐EARS app runs in the background and records the times when an application is opened, closed, or minimised from the foreground of the device [28]. The average duration of daily smartphone use across all apps was collected in minutes. Daily smartphone time was converted from minutes per day to hours per day.
2.5. Problematic Screen Use
Problematic social media use was assessed using the Social Media Addiction Questionnaire (SMAQ) [25]. The six questions of the SMAQ assess six components of behavioural addiction (salience, mood modification, tolerance, withdrawal, conflict, and relapse) and were adapted from the well‐validated Bergen Facebook Addiction Scale [8]. Examples include, “I spend a lot of time thinking about social media apps or planning my use of social media apps,” and “I've tried to use my social media apps less but I can't.” Likert‐type scale responses ranged from 1 (Never) to 6 (Very Often).
Problematic mobile phone use was assessed using the Mobile Phone Involvement Questionnaire (MPIQ) [25]. The eight questions of the MPIQ assess behavioural addiction components, such as interpersonal conflict, salience, relapse, and withdrawal. Likert‐type scale responses ranged from 1 (Strongly Disagree) to 7 (Strongly Agree).
For each problematic use scale, responses were averaged to obtain a mean score. If any response was missing, the mean score was derived using the available responses. The number of adolescents who responded to the SMAQ and MPIQ during Year 4 follow‐up was 7727 and 8653, respectively. Subsequently, for participants who reported not having a social media account or zero self‐reported social media time (n = 1913), or who did not own a mobile phone (n = 976), we assigned a value of 1 (Never) and 1 (Strongly Disagree) for the SMAQ and MPIQ, respectively, which is consistent with previous literature [29]. An additional analysis, excluding those who reported not having a social media account or not owning a mobile phone, is included as a Table S3. The sample size for problematic social media use and problematic mobile phone use was 7937 and 7911 adolescents, respectively, after excluding participants with missing covariates.
2.6. Statistical Analyses
The analyses were performed in Stata 18.0 (StataCorp, College Station, TX). Linear regression models were conducted to estimate the associations between six media parenting practice variables collected at Year 3 and four outcome variables at Year 4 (self‐reported total screen time, app‐reported smartphone time, and problematic screen use mean scores). The predictor and outcome in every model were standardised using survey‐weighted means and standard deviations. As Year 3 (2019–2021) follow‐up occurred before and during the Coronavirus disease (COVID‐19) pandemic, participants had varying follow‐up times. All regression models were adjusted for the following covariates: age, sex, race/ethnicity, household income, parental education, study site, whether Year 3 follow‐up occurred before or during the COVID‐19 pandemic, and the respective baseline outcome variables at Year 3. Since EARS data was only available starting in Year 4, app‐reported smartphone time linear regression models were adjusted for Year 3 adolescent‐reported screen time.
As a sensitivity analysis, sociodemographic characteristics (age, sex, race/ethnicity, household income, and parental education) were examined as potential moderators of the associations between the primary media parenting practice and each of the four outcome variables. Moderation was evaluated using joint tests of the interaction terms corresponding to each sociodemographic characteristic. Specifically, for each moderator, the null hypothesis that all interaction terms involving that moderator were equal to zero was tested. Results are presented as an F‐test statistic and associated p‐values for each combination of the sociodemographic characteristic and media parenting practice. To test the reverse directionality, linear regression models were used to estimate the associations between the screen time variables at Year 3 (self‐reported total screen time and problematic screen use mean scores) and six media parenting practice variables collected at Year 4, adjusted for the same covariates mentioned above, and the respective media parenting practice variable collected at Year 3. All analyses were conducted with sampling weights to approximate the American Community Survey [30]. p < 0.05 was considered statistically significant.
3. Results
In our sample (N = 7947), the average age at Year 3 was 12.9 years (SD = 0.65), and 51.6% were male (Table 1). Table 2 shows the response distribution of media parenting practices. When asked about screen‐time modelling habits, most parents (74.4%) reported using screens around their adolescents; however, a majority of parents (86.1%) tried to limit their own screen use when with their adolescents. Over a third of families (35.1%) reported often watching a screen during meals, and nearly half of adolescents (45.6%) had access to a mobile screen‐based device in bed. More than half of the parents (67.1%) monitored their adolescents' screen time during the week, while fewer parents (59.7%) did so during the weekend. Most parents (76.8%) limited their adolescents' screen time during the week, while fewer parents (59.0%) limited it during the weekend.
TABLE 1.
Sociodemographic and youth screen time characteristics of Adolescent Brain Cognitive Development (ABCD) Study participants at Year 3 (N = 7947).
| Sociodemographic characteristics | Mean (SD)/% |
|---|---|
| Age (years) | 12.92 (0.65) |
| Sex (%) | |
| Female | 48.4% |
| Male | 51.6% |
| Race/Ethnicity (%) | |
| Asian | 5.5% |
| Black | 13.9% |
| Latino | 18.3% |
| Native American | 3.0% |
| White | 58.1% |
| Other | 1.2% |
| Household income (%) | |
| Less than $25 000 | 12.5% |
| More than $25 000 and less than $50 000 | 15.3% |
| More than $50 000 and less than $75 000 | 15.2% |
| More than $75 000 and less than $100 000 | 15.4% |
| More than $100 000 and less than $200 000 | 30.3% |
| Equal to and greater than $200 000 | 11.4% |
| Parents' highest education (%) | |
| Less than high school education | 12.9% |
| College or more | 87.1% |
| Media parenting practices | |
| Screen time modelling (mean score) | 2.31 (0.61) |
| Mealtime screen use (mean score) | 1.89 (0.95) |
| Bedroom screen use (mean score) | 1.85 (0.90) |
| Screens to control behaviour (mean score) | 2.57 (0.87) |
| Monitoring screen time (mean score) | 2.74 (0.95) |
| Limiting screen time (mean score) | 3.15 (0.69) |
| Adolescent screen use | |
| Self‐reported total screen time (h/day) a | 4.94 (3.20) |
| App‐reported total smartphone time (h/day) b | 4.89 (2.83) |
| Problematic social media use (mean score) c | 1.81 (0.94) |
| Problematic Mobile phone use (mean score) d | 3.13 (1.29) |
Note: ABCD Study sampling weights were applied based on the American Community Survey from the US Census.
Asked among a subset who reported total screen time (n = 7944).
Asked among a subset with app‐reported total smartphone time (n = 840).
Asked among a subset with a problematic social media use mean score (n = 7937).
Asked among a subset with a problematic mobile phone use mean score (n = 7911).
TABLE 2.
Media parenting practices in the Adolescent Brain Cognitive Development (ABCD) Study (N = 7947).
| Media parenting practice category and individual questions | Parent responses | |||
|---|---|---|---|---|
| % | % | % | % | |
| Strongly disagree | Somewhat disagree | Somewhat agree | Strongly agree | |
| Screen time modelling | ||||
| “When I am with my child, I use a screen‐based device” | 10.0 | 15.6 | 52.0 | 22.4 |
| “I try to limit how much I use a screen‐based device when I am with my child” | 6.0 | 7.9 | 41.0 | 45.1 |
| Mealtime screen use | ||||
| “Our family often watches a screen during meals” | 46.0 | 18.9 | 22.5 | 12.6 |
| “Family members are allowed to use screen‐based devices during meals” | 56.1 | 19.0 | 17.2 | 7.7 |
| Bedroom screen use | ||||
| “My child falls asleep while using a screen‐based device” | 63.0 | 14.3 | 16.2 | 6.5 |
| “A screen‐based device is usually playing in the room when my child falls asleep” | 64.8 | 11.2 | 16.0 | 8.0 |
| “My child has access to a mobile screen‐based device in bed” | 44.2 | 10.2 | 25.2 | 20.4 |
| Screens to control behaviour | ||||
| “I offer screen time to my child as a reward for good behaviour” | 46.0 | 15.5 | 27.4 | 11.1 |
| “I take away screen time from my child as a punishment for bad behaviour” | 14.8 | 7.1 | 31.0 | 47.2 |
| Monitoring screen time | ||||
| “I keep track of my child's screen time during the week” | 14.1 | 18.8 | 38.2 | 28.9 |
| “I keep track of my child's screen time during the weekend” | 16.5 | 23.8 | 36.6 | 23.1 |
| Limiting screen time | ||||
| “I limit my child's screen time during the week” | 10.3 | 12.9 | 38.8 | 38.0 |
| “I limit my child's screen time during the weekend” | 15.3 | 25.8 | 37.3 | 21.7 |
| “I encourage my child to do activities other than screen time” | 2.2 | 1.5 | 14.9 | 81.4 |
Note: ABCD Study sampling weights were applied based on the American Community Survey from the US Census.
Table 3 shows the prospective associations between media parenting practices and adolescent‐reported screen time, app‐reported smartphone time, and problematic use of social media and mobile phones, adjusting for sociodemographic characteristics. Greater parental screen time modelling (e.g., parents' own use of a screen‐based device when with their child) was weakly associated with greater adolescent‐reported screen time (Standardised coefficient [β]: 0.04, 95% confidence interval [CI]: 0.02, 0.07) and greater problematic social media use mean score (β: 0.03, 95% CI: 0.005, 0.06). Family mealtime screen use was weakly associated with greater adolescent‐reported screen time (β: 0.05, 95% CI: 0.03, 0.07) and greater problematic mobile phone use mean score (β: 0.04, 95% CI: 0.01, 0.07). Adolescents' bedroom screen use was weakly associated with greater adolescent‐reported screen time (β: 0.07, 95% CI: 0.05, 0.09), greater app‐reported smartphone time (β: 0.18, 95% CI: 0.11, 0.25), and greater problematic mobile phone use mean score (β: 0.06, 95% CI: 0.03, 0.10). Parental use of screens to control adolescents' behaviour (e.g., offering screen time as a reward for good behaviour) was weakly associated with greater adolescent‐reported screen time (β: 0.03, 95% CI: 0.01, 0.06), greater app‐reported smartphone time (β: 0.09, 95% CI: 0.003, 0.17), greater problematic social media use mean score (β: 0.03, 95% CI: 0.002, 0.05), and greater problematic mobile phone use mean score (β: 0.04, 95% CI: 0.01, 0.07). Parental monitoring of adolescent screen use was weakly associated with lower adolescent‐reported screen time (β: −0.05, 95% CI: −0.07, −0.02) and lower app‐reported smartphone time (β: −0.08, 95% CI: −0.15, −0.002). Parental limiting of adolescent screen use was weakly associated with lower adolescent‐reported screen time (β: −0.07, 95% CI: −0.09, −0.04).
TABLE 3.
Prospective associations between media parenting practices at Year 3 and adolescent screen use at Year 4 in the Adolescent Brain Cognitive Development (ABCD) Study (N = 7947).
| Media parent practice categories | Screen time (h/day) | Problematic screen use (mean score) | ||||||
|---|---|---|---|---|---|---|---|---|
| Self‐reported total recreational screen time (n = 7944) | App‐reported total smartphone time (n = 840) | Social media (n = 7937) | Mobile phone (n = 7911) | |||||
| β (95% CI) | p | β (95% CI) | p | β (95% CI) | p | β (95% CI) | p | |
| Parental screen time modelling a | 0.04 (0.02, 0.07) | 0.004 | −0.002 (−0.10, 0.10) | 0.96 | 0.03 (0.005, 0.06) | 0.02 | 0.01 (−0.002, 0.03) | 0.09 |
| Mealtime screen use | 0.05 (0.03, 0.07) | < 0.001 | −0.02 (−0.09, 0.04) | 0.48 | 0.02 (−0.003, 0.04) | 0.09 | 0.04 (0.01, 0.07) | 0.01 |
| Bedroom screen use | 0.07 (0.05, 0.09) | < 0.001 | 0.18 (0.11, 0.25) | < 0.001 | 0.03 (−0.01, 0.07) | 0.14 | 0.06 (0.03, 0.10) | 0.002 |
| Screens to control behaviour | 0.03 (0.01, 0.06) | 0.004 | 0.09 (0.003, 0.17) | 0.04 | 0.03 (0.002, 0.05) | 0.03 | 0.04 (0.01, 0.07) | 0.006 |
| Parental monitoring of screen time | −0.05 (−0.07, −0.02) | 0.002 | −0.08 (−0.15, −0.002) | 0.04 | −0.02 (−0.05, 0.01) | 0.22 | −0.02 (−0.05, 0.002) | 0.07 |
| Limiting screen time | −0.07 (−0.09, −0.04) | < 0.001 | −0.06 (−0.14, 0.02) | 0.17 | −0.03 (−0.07, 0.003) | 0.07 | −0.03 (−0.06, 0.004) | 0.09 |
Note: All media parenting practices and screen‐related outcome variables were standardised using survey‐weighted means and standard deviations. Linear regression models were estimated using survey‐weighted methods. ABCD Study sampling weights were applied based on the American Community Survey from the US Census. Bold indicates p < 0.05.
Screentime modelling: Question 2 was reversed to standardise answer.
A sensitivity analysis, excluding those who reported not having a social media account or not owning a mobile phone, is presented in Table S3. Results of joint interaction tests for all sociodemographic characteristics across the four media parenting practices are presented in Table S4. Age demonstrated significant moderation effects for multiple outcomes, whereas race/ethnicity showed limited evidence of interaction. No consistent interaction effects were observed for sex, household income, and parental education across screen‐related variables. Stratified models are shown in Tables S5 and S6. Prospective associations between adolescent screen use at Year 3 and media parenting practice variables at Year 4 are presented in Table S7. The screen‐related variables (self‐reported total screen time and problematic screen use mean scores) were weakly associated with certain media parenting practices.
4. Discussion
In this large, demographically diverse sample of adolescents, we found significant associations between media parenting practices and adolescent screen use habits. These findings suggest that parental practices may influence adolescents' screen use behaviours. However, the strengths of these associations were generally small and varied by parenting practice and behavioural outcome, suggesting that certain adolescent screen behaviours may be more responsive to parental intervention than others.
4.1. Parental Screen Time Modelling
Parental screen time modelling was positively associated with adolescents' total screen time and, to a lesser extent, with problematic social media use. These findings align with prior cross‐sectional studies that have linked parental screen time modelling to higher total screen time among children and adolescents [9, 14, 23, 31]. Prior ABCD cross‐sectional studies at Year 3 also showed associations between parental screen time monitoring, problematic mobile phone use, [23] and problematic social media use [23]. This prospective cohort study builds upon prior work by demonstrating that parental behaviour correlates with and temporally precedes greater adolescent screen time, suggesting that parental modelling influences adolescent screen use behaviours.
The observed associations between parental screen time modelling, adolescent screen time, and adolescent problematic social media use may be explained through the lens of Social Learning Theory, which posits that behaviours are learned through the observation of others [32]. For example, an adolescent who observes their parent watching TV and playing games on their mobile phone as a self‐soothing practice may be more likely to adopt the same screen use habits, whereas an adolescent who observes their parent engaging in non‐screen‐based self‐regulatory behaviours, such as meditation or physical activity, may be more likely to adopt similar coping mechanisms. Thus, given the association between parental behaviour and adolescent screen time demonstrated in this study, parental behaviour may be a modifiable target and an opportunity to intervene in screen overuse and problematic screen use among adolescents.
4.2. Family Mealtime and Adolescent Bedroom Screen Use
Family mealtime screen use and adolescent bedroom screen use were associated with higher self‐reported total screen time and weakly associated with problematic mobile phone use. Furthermore, adolescent bedroom screen use was also associated with higher app‐reported smartphone screen time, an objective measure used in a small subsample of participants. These results are consistent with previous research, which found positive associations between family mealtime screen use, adolescent bedroom screen use, and total screen time [33, 34]. One study found that a lower frequency of family meals and the presence of a TV in the bedroom were associated with higher screen time hours per day [35]. Family meals are an alternative activity to screen use, so less time spent with family may be associated with greater screen time. However, our findings suggest that the quality of interaction or media use during these family meals also needs to be considered. Since bedrooms have reduced parental visibility, adolescents are free from parental monitoring or natural stopping cues that typically occur in shared home spaces (e.g., living room or kitchen). Exposure to screens before bedtime increases alertness and decreases sleepiness [36], so adolescents with access to screen‐based devices in bed may displace their sleep with increased screen time. While the observed associations were statistically significant, their strength was weaker than findings from our prior cross‐sectional analysis, especially for problematic mobile phone use [23], likely due to the temporal gap between exposure and outcome data point collection. Nonetheless, because of the temporality of this prospective cohort study, a stronger relationship is suggested between mealtime/bedroom screen use and adolescents' total screen time than in previous cross‐sectional studies. Adolescent access to devices in the bedroom was significantly associated with app‐reported smartphone time, adolescent‐reported total screen time, and both problematic screen use variables 1 year later, which suggests that regulation of adolescents' bedroom screen use may decrease total screen use, presenting another potential opportunity for intervention.
4.3. Use of Screens to Control Behaviour
The use of screens by parents as either a reward or punishment for adolescent behaviour was associated with higher self‐reported screen time, higher app‐reported screen time, and greater problematic social media and mobile phone use. These findings align with existing literature [9, 23, 37], and may reflect adolescent pushback against parental control that may be perceived as intrusive or punitive, leading to greater overall screen use [19, 23]. Another mechanism is that parents with adolescents who have high levels of screen use may be more likely to use screens as a reward or punishment for adolescent behaviour. As the implementation and adherence to the use of screens to control behaviour were not assessed, future studies should investigate the specifics of these media parenting practices to fully understand the mechanism of the association. The weaker associations with problematic social media and mobile phone use are likely due to the temporal gap between the measurements of the exposure and the outcome variables. However, the prospective nature of the study suggests that the use of screens by parents as a reward or punishment is associated with higher screen use, problematic social media use, and problematic mobile phone use.
4.4. Parental Monitoring of Screen Time and Limiting Screen Time
Higher parental monitoring of screen time was associated with lower self‐reported total screen time and app‐reported smartphone time among adolescents. Past studies, including our previous cross‐sectional study, similarly demonstrated that greater parental monitoring of screen time was associated with lower child screen time [9, 23]. The confirmation of this negative association with app‐reported smartphone data is crucial, as it mitigates the social desirability bias inherent in self‐reported screen time. By leveraging objective data utilizing a prospective cohort model, the present study provides even stronger evidence that parental monitoring may reduce adolescent screen use. Furthermore, the establishment of temporality through the study's prospective design is valuable because it demonstrates that parental monitoring of screen use 1 year prior can have lasting impacts on adolescent screen use.
Parental use of screen time limits was associated with reduced self‐reported total screen time and problematic social media use among adolescents 1 year later. These findings suggest that structured screen use rules may have a lasting impact on reducing problematic screen use behaviours. Building upon prior studies [9, 14, 23], this prospective cohort study demonstrates that parental limits on screen use are associated with lower adolescent screen time and lower problematic social media use 1 year later. Similarly, an authoritative parenting style has been associated with lower levels of sedentary screen time use among adolescents [38]. Parental monitoring and parental use of screen time limits may be considered examples of this style, which balances high parental involvement and control with understanding and support.
4.5. Limitations
One limitation of this study is the reliance on self‐reported screen time, which is vulnerable to social desirability bias and may not accurately reflect true screen use [39]. Despite multiple significant findings, the effect sizes were generally small. Sensitivity analyses demonstrated associations in the reverse direction, suggesting potentially bidirectional associations, which could be an area of future research. Additionally, the objective data sample size (N = 840) is significantly smaller than that of the self‐reported data, reducing the power of the results drawn from the objective data. Because the objective data was only collected from Android users, the objective data sample may not be representative of ABCD adolescents as a whole. Although we assigned the lowest problematic use scores to participants without access to social media or mobile phones, lack of access may not necessarily equate to the absence of underlying addictive symptomatology. Finally, a portion of Year 3 and all Year 4 data were collected during the COVID‐19 pandemic. There may be significant changes in screen use and parenting practices during and after the pandemic. Daily adolescent screen time increased during the pandemic, potentially affecting these results [40].
5. Conclusion
In this study of a large, demographically diverse sample of U.S. adolescents, we prospectively analysed associations between parenting practices, screen time, and problematic screen use. Objective smartphone data revealed that parental limits on bedroom screen use and active parental monitoring of screen use had prospective associations with lower smartphone use, while the parental practice of using screens to control behaviour was associated with greater adolescent screen time. Self‐reported data mirrored these patterns, as mealtime screen use limits, bedroom screen use limits, and parental monitoring were associated with reduced adolescent screen use. In contrast, parental modelling of excessive screen use and the use of screens as disciplinary tools were associated with greater screen use among adolescents. Overall, this study suggests that certain media parenting practices may facilitate healthy screen use, while others may inadvertently promote problematic use among adolescents.
Author Contributions
Jason M. Nagata: writing – original draft, writing – review and editing, methodology, formal analysis, data curation, supervision, funding acquisition, investigation, conceptualization. Derek Sportsman: formal analysis, writing – original draft, writing – review and editing. Kristen E. Kim: formal analysis, writing – original draft, writing – review and editing. Oliver H. Huang: formal analysis, writing – original draft, writing – review and editing. Christiane K. Helmer: formal analysis, writing – original draft, writing – review and editing. Elizabeth J. Li: writing – original draft, writing – review and editing. Kyle T. Ganson: writing – review and editing. Alexander Testa: writing – review and editing. Fiona C. Baker: writing – review and editing, methodology.
Funding
The research was funded by the National Institutes of Health (K08HL159350, RF1MH135492, R01DA064134); Rise Together, a donor‐advised fund sponsored and administered by National Philanthropic Trust and established by Richard Reeves, founding president of the American Institute for Boys and Men; and the Doris Duke Charitable Foundation (2022056). The ABCD Study was supported by the National Institutes of Health and additional federal partners under award numbers (U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, and U24DA041147). A full list of supporters is available at https://abcdstudy.org/federal‐partners/. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/principal‐investigators.html. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report.
Consent
Caregivers provided written informed consent, and each child provided written assent.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Table S1: Comparison of participants included vs. excluded from the Adolescent Brain Cognitive Development (ABCD) Study.
Table S2: Comparison of participants with and without app‐reported smartphone use from the full sample (N = 7947).
Table S3: Prospective associations between media parenting practices at Year 3 and problematic screen use at Year 4 in the Adolescent Brain Cognitive Development (ABCD) Study excluding social media or mobile phone non‐users.
Table S4: Joint tests of interaction between sociodemographic covariates and screen‐related variables across media parenting practices.
Table S5: Prospective associations between bedroom screen use at Year 3 and self‐reported total recreational screen time at Year 4, stratified by age (n = 7944).
Table S6: Prospective associations between bedroom screen use at Year 3 and app‐reported total smartphone time at Year 4, stratified by race/ethnicity (n = 840).
Table S7: Prospective associations between adolescent screen use at Year 3 and media parenting practices at Year 4 and in the Adolescent Brain Cognitive Development (ABCD) Study.
Acknowledgements
The authors thank Anthony Kung for editorial assistance.
Data Availability Statement
Data used in the preparation of this article were obtained from the ABCD Study (https://abcdstudy.org), held in the NIH Brain Development Cohorts (NBDC) Portal.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Comparison of participants included vs. excluded from the Adolescent Brain Cognitive Development (ABCD) Study.
Table S2: Comparison of participants with and without app‐reported smartphone use from the full sample (N = 7947).
Table S3: Prospective associations between media parenting practices at Year 3 and problematic screen use at Year 4 in the Adolescent Brain Cognitive Development (ABCD) Study excluding social media or mobile phone non‐users.
Table S4: Joint tests of interaction between sociodemographic covariates and screen‐related variables across media parenting practices.
Table S5: Prospective associations between bedroom screen use at Year 3 and self‐reported total recreational screen time at Year 4, stratified by age (n = 7944).
Table S6: Prospective associations between bedroom screen use at Year 3 and app‐reported total smartphone time at Year 4, stratified by race/ethnicity (n = 840).
Table S7: Prospective associations between adolescent screen use at Year 3 and media parenting practices at Year 4 and in the Adolescent Brain Cognitive Development (ABCD) Study.
Data Availability Statement
Data used in the preparation of this article were obtained from the ABCD Study (https://abcdstudy.org), held in the NIH Brain Development Cohorts (NBDC) Portal.