OBJECTIVES:

Assess how family stressors (including structural stressors, social determinants of health inequities, and parent psychological distress) relate to media rule implementation and problematic child media use during the coronavirus disease 2019 pandemic.

METHODS:

Nationally representative survey of 1000 United States parents with at least one 6 to 17 year old child was conducted in October through November 2020.

RESULTS:

Problematic use was greater in families where parents were employed full time, present in the home (eg, working from home), had low levels or formal educational attainment, and were experiencing more psychological distress. Although there was a small decline in the number of media-related rules implemented during the pandemic (fewer parents enforced screen limits on weekdays or weekends or limited screen use at mealtimes), there was no association between rule implementation and problematic media use.

CONCLUSIONS:

Family stressors were associated with problematic child media use during the coronavirus disease 2019 pandemic. As we emerge from the pandemic, it will be important to help parents adjust their family’s media practices cognizant of the fact that additional children may have developed problematic screen use behaviors. Such efforts should center the role of structural and social determinants of health inequities on the stressors that families experience and that impact media use.

What’s Known on This Subject:

Child and adolescent media use increased during the coronavirus disease 2019 pandemic. Media practices that lead to dysfunction in a major developmental domain (ie, social, behavioral, or academic) are considered problematic.

What This Study Adds:

Problematic media use was higher when parents experienced more stressors and was not associated with family media rules.

Screen-based media is an increasingly ubiquitous part of daily life.1 Uses and gratifications theory proposes that individuals select media that helps fulfill their social, psychological, or biological needs, with needs and uses varying across contexts and changing over time.2 Parenting needs addressed by screen media include: occupying and calming children, rewarding desirable behavior, facilitating meal preparation and bedtime, providing enrichment, and supporting child-parent bonding.35  In the context of the coronavirus disease 2019 (COVID-19) pandemic, many schools and workplaces operated remotely, typical sources of entertainment were closed or restricted, and social distancing guidelines limited in-person interactions.6 Consequently, screen-based media became increasingly central for child learning and enrichment, supervision, recreation, and socialization. Such changes may have strengthened peer norms related to media use and changed the family media landscape such that devices were used across more times and places in the home (eg, as more school, employment, and socialization occurred remotely).

Parenting and other demands led to increased stress for many parents during the pandemic,7 and for some, psychological distress such as elevated internalizing symptomatology.8 Media’s role in family functioning may have been heightened in families structurally exposed to more stressors and with fewer resources for coping through others means. For example, parents exposed to structural and social determinants of health inequities, including structural racism, and lower socioeconomic position, may have had less workplace flexibility (eg, to supervise children at home during the pandemic) and fewer material coping resources (eg, to pay for childcare), and more financial insecurity.9,10 

Amid these inequitable stressors and clear uses of media for families during the pandemic, there is concern about potential adverse consequences of screens on child health. A growing body of research suggests that when screen use interferes with other developmentally important activities (sleep, physical activity, or in-person social interaction), physical and psychosocial health can suffer.11,12 One key pathway through which such negative psychosocial impacts arise is via addictive media use. Recently, addictive child media use practices (eg, preoccupation, withdrawal, or unsuccessful attempts by parents to control use) that lead to dysfunction in a major developmental domain (ie, social, behavioral, or academic) have been conceptualized as problematic media use.13 Greater problematic media use, as measured by the Problematic Media Use Scale,14 is associated with worse psychosocial functioning, above and beyond the influence of screen time alone.14 

In recognition of these potential uses and harms, the American Academy of Pediatrics recommends that families limit and monitor the screen-based media use of children and adolescents.15 Specific recommendations vary by age but broadly address: limiting screen time, restricting media content, promoting sleep hygiene, and designating media-free times (eg, family meals).15 There is empirical support for a rule-based approach: adjusting for demographic factors, screen time is lower among children and adolescents when their families have media use rules.1618  However, at a population-level, very few families are implementing all American Association of Pediatrics media-use guidelines19 and questions remain unanswered about whether families that implement more rules (ie, where there is more parent-mediation) have lower risk of problematic child use. Prepandemic research finds an inverse association between parenting stress and parent mediation of child media use.20 However, the Interactional Theory of Childhood Problematic Media Use13 proposes that more important than the absolute level of media use is how media practices function and are reinforced in the child’s unique social and family context.13 Consistent with prepandemic data suggesting that screen use is an indicator of greater challenges for parents in the home,21 and worse family functioning,22 a change in media use during the pandemic may be an indicator of families experiencing more pandemic-related challenges.

Heightened and inequitable family stressors experienced during the COVID-19 pandemic present an opportunity to learn more about structural and family-level determinants of problematic media use. The goal of the current study was to assess how structural and social determinants of health inequities and parent wellbeing (symptoms of depression and anxiety) during COVID-19 were associated to both family media rules and problematic child media use. We tested the following hypotheses:

  1. Families will report implementing fewer screen use rules during the pandemic as compared with before the pandemic.

  2. Families exposed to more stressors (structural, social determinants of health, and parent wellbeing) will implement fewer media-related rules during the pandemic.

  3. Problematic media use during the pandemic will be greater in families exposed to more stressors and who report greater declines in media rule implementation.

Participants were a nationally representative sample of 1000 parents living in the United States with at least 1 child between the ages of 6 and 17. Recruitment was facilitated by YouGov (a market research company). Detail on YouGov’s procedure to generate nationally representative samples using weighted propensity scores and sample matching has been described elsewhere.2 In brief, 547 parents with a reference child aged 6 to 10, and 535 parents with a reference child aged 11 to 17 completed an online survey between October 22, 2020 and November 2, 2020. Based on the 2017 American Community Survey, propensity scores were used to construct a sample of 500 in each reference child age category that was nationally representative in terms of parent age, race, and education, resulting in a total sample size of 1000 parents. The Seattle Children’s Hospital Institutional Review Board approved all research procedures.

Parents with multiple children between ages 6 and 18 were asked to respond to child-specific questions thinking about the child whose birthday is coming up next. We refer to this as the “reference child.”

Media Rule Implementation

Using questions from the Neighborhood Quality of Life Study,23 which have been adapted to reflect recommendations in the American Academy of Pediatrics Media Use Plan, parents were asked to think about their family’s rules related to media use in 2 periods: before COVID-19 and now. Separately for each period, they indicated whether seven statements were true for their family: (1) mobile devices and other screens or TVs were not allowed in the child’s bedroom; (2) mobile devices were charged outside the child’s bedroom; (3) family members did not use screens or TVs during meal time; (4) child turned off screens at least 1 hour before bedtime; (5) restricted what shows and apps child has access to; (6) rules were enforced about how much screen time child was allowed on weekdays; and (7) rules were enforced about how much screen time child was allowed on weekends. Response options were yes (1) and no (0), and they were summed to create 2 separate 7-item indices of media rule implementation.

Problematic Media Use

Reference child problematic media use was assessed using the 9-item Problematic Media Use Measure- short form,14 which measures elements of additive media use among children, including preoccupation, withdrawal, and unsuccessful attempts to control use by parents. Responses were on a 5-point Likert scale, with a possible range of 9 to 40, with higher scores indicating more problematic media use. This scale has evidence of reliability and validity when completed by mothers of school-aged children; in our data, the Cronbach α for the “problematic media use” scale is 0.927 with 95% CI (0.919 to 0.935). Although there are no established clinical cut-offs, others have used media use that “most of the time” or “always” interferes with daily functioning (item-level mean of ≥3 out of 5, or a total scale score of ≥27 out of 40) as a threshold for problematic use.24 

Parent Mental Health

Parents completed the Patient Health Questionnaire-4 (PHQ-4),25 a commonly used 4-item scale that assesses symptoms of depression or anxiety over the past 2 weeks. Responses are summed to create a scale with a possible range of 0 to 12, with higher scores indicating more frequent symptoms. The Cronbach α for the PHQ-4 in our data are 0.895 with 95% CI (0.878 to 0.910).

Impact of COVID-19 on Parent Self-Care Behaviors

Parents completed the COVID-19 Exposure and Family Impact Survey26 and indicated how COVID-19 impacted their own sleep, exercise, and eating. Response options for each item were: made it a lot better (1); made it a little better (2); made it a little worse (3); and made it a lot worse (4). Responses were summed to create an index with possible range of 3 to 12, where higher scores indicate a more negative impact of COVID-19 on self-care behaviors. The Cronbach α for this scale in our data are 0.829 with 95% CI (0.805 to 0.852).

Child Schooling Modality

Parents indicated whether their reference child is currently attending school in person, remotely, or in a hybrid modality.

Parent Employment

Parents indicated the employment status of the reference child’s parent(s) or guardians(s), with options of full time, part time, and not employed. To reflect the family’s employment status on aggregate and to be inclusive of 1- and 2-parent families, we combined responses into 3 categories: no parents employed, 1 or more parents employed part-time, and all parents employed full time. Parents also reported whether they worked from home (WFH) (none of the time, some of the time, or all of the time). For analytic purposes, these 2 variables (employment and work from home status) were combined to generate a variable reflecting parent home presence. The parent home presence is considered “high” if (1) both parents were unemployed or (2) WFH status is “yes, all of the time;” parent home presence is “moderate” if WFH status is “yes, some of the time” or (WFH is missing but 1 or both parents were working part-time; or home presence is “low” if WFH status is “no” regardless both parents were working full-time or “part-time.”

Demographic Characteristics.

Parents indicated their age, gender, race, and ethnicity using United States Census categories. Parents indicated the highest level of formal education obtained and their insurance status (as a proxy for family income27), with options of public or private insurance. Parents indicated the reference child’s gender and age, which we subsequently grouped into 2 categories reflecting elementary (ages 6 to 10), secondary school (ages 11 to 17).

Descriptive statistics (means and frequency tables) were reported with sampling weights to be nationally representative in terms of parent demographic characteristics. Implementation of media rules was examined separately for children in the 6 to 10 and 11 to 17 year age ranges. McNemar’s χ2 tests with continuity corrections were used to compare implementation of each of the 7 media-related rules, and a paired t test was used to compare the total number of rules, before COVID-19 and during the present period.

Poisson regression was used to examine the association between structural and parent- level variables and media rules implemented during the pandemic, controlling for prepandemic rules and reporting rate ratios (RR). Linear regression was used to assess the association between level of family- and structural conditions as well screen rule implementation and problematic media use. In this model both absolute number of rules and parent-reported change in rules (calculated as prepandemic rule score minus during-pandemic rule score) were included as independent variables. Regression analyses were stratified by age group (6 to 10, and 11 to 17), given potentially different school or peer contexts in primary as compared with secondary school, and potentially different parenting practices in younger children as opposed to adolescents. Posthoc analyses tested interactions between parent mental health and family characteristics (education and employment); these are detailed in electronic Supplemental Tables 57. All P values are adjusted using the Benjamini-Yekutieli method to control the overall false discovery rate at .05.

Weighted descriptive statistics (means and frequency tables) are presented in Table 1. In 36% of families, all parents were employed full-time. The mean parent PHQ-4 score was 3.15 (standard deviation [SD] = 3.26). Twenty-two percent of reference children were attending school in-person. On average, problematic media use scores were 22.95 (SD = 8.58). In this sample, 32.6% 6 to 10 years and 38.8% of 11 to 17 years had problematic media use scores of 27 or more (the previously used threshold for problematic use24).

TABLE 1

Sample Characteristics (N = 1000)

Family CharacteristicsAge 6–10 Mean (SD) or n (%)Age 11–17 Mean (SD) or n (%)
Child age, mean (SD) 8.08 (1.38) 13.96 (2.00) 
Child gender   
 Male 265 (52.58) 252 (50.60) 
 Female 228 (47.42) 239 (49.40) 
Parent age, mean (SD) 40.33 (9.03) 41.91 (8.50) 
Parent gender   
 Male 203 (40.59) 237 (44.08) 
 Female 297 (59.41) 263 (55.92) 
Child race   
 White 353 (67.37) 354 (70.82) 
 Black 59 (12.26) 52 (9.86) 
 Asian 9 (2.89) 14 (2.73) 
 American Indian or Alaska Native 14 (2.63) 5 (1.52) 
 Other races 65 (14.85) 75 (15.06) 
 Child Hispanic 120 (27.57) 113 (30.68) 
 Parent born outside of United States 100 (22.13) 111 (26.76) 
Parent education   
 Less than high school 170 (38.32) 152 (36.83) 
 Some college 156 (27.54) 167 (26.61) 
 4-y college 115 (21.75) 109 (23.14) 
 Postgraduate degree 59 (12.40) 72 (13.42) 
 Public insurance 192 (39.26) 173 (41.08) 
School modality   
 In-person 124 (24.68) 96 (17.06) 
 Hybrid 132 (24.71) 153 (32.36) 
 Remote 243 (50.62) 251 (50.57) 
Parent employment   
 No parents employed 79 (17.52) 81 (17.84) 
 One or more parents part-time 244 (48.98) 235 (44.04) 
 All parents full-time 177 (33.50) 184 (38.11) 
Parent works from home   
 No 127 (38.28) 140 (40.28) 
 Some of the time 126 (29.47) 114 (35.57) 
 All of the time 77 (22.25) 68 (24.15) 
Parent presence in home   
 High 205 (42.67) 195 (39.97) 
 Moderate 168 (32.93) 165 (34.96) 
 Low 127 (24.40) 140 (25.06) 
Parent PHQ-4 score, mean (SD) 3.03 (3.26) 3.52 (3.37) 
Impact of COVID-19 on parent self-care behaviors, mean (SD) 7.88 (2.52) 7.79 (2.47) 
Child problematic media use score, mean (SD) 22.85 (8.39) 24.02 (9.13) 
Problematic use score ≥27 163 (32.6) 178 (38.8) 
Family CharacteristicsAge 6–10 Mean (SD) or n (%)Age 11–17 Mean (SD) or n (%)
Child age, mean (SD) 8.08 (1.38) 13.96 (2.00) 
Child gender   
 Male 265 (52.58) 252 (50.60) 
 Female 228 (47.42) 239 (49.40) 
Parent age, mean (SD) 40.33 (9.03) 41.91 (8.50) 
Parent gender   
 Male 203 (40.59) 237 (44.08) 
 Female 297 (59.41) 263 (55.92) 
Child race   
 White 353 (67.37) 354 (70.82) 
 Black 59 (12.26) 52 (9.86) 
 Asian 9 (2.89) 14 (2.73) 
 American Indian or Alaska Native 14 (2.63) 5 (1.52) 
 Other races 65 (14.85) 75 (15.06) 
 Child Hispanic 120 (27.57) 113 (30.68) 
 Parent born outside of United States 100 (22.13) 111 (26.76) 
Parent education   
 Less than high school 170 (38.32) 152 (36.83) 
 Some college 156 (27.54) 167 (26.61) 
 4-y college 115 (21.75) 109 (23.14) 
 Postgraduate degree 59 (12.40) 72 (13.42) 
 Public insurance 192 (39.26) 173 (41.08) 
School modality   
 In-person 124 (24.68) 96 (17.06) 
 Hybrid 132 (24.71) 153 (32.36) 
 Remote 243 (50.62) 251 (50.57) 
Parent employment   
 No parents employed 79 (17.52) 81 (17.84) 
 One or more parents part-time 244 (48.98) 235 (44.04) 
 All parents full-time 177 (33.50) 184 (38.11) 
Parent works from home   
 No 127 (38.28) 140 (40.28) 
 Some of the time 126 (29.47) 114 (35.57) 
 All of the time 77 (22.25) 68 (24.15) 
Parent presence in home   
 High 205 (42.67) 195 (39.97) 
 Moderate 168 (32.93) 165 (34.96) 
 Low 127 (24.40) 140 (25.06) 
Parent PHQ-4 score, mean (SD) 3.03 (3.26) 3.52 (3.37) 
Impact of COVID-19 on parent self-care behaviors, mean (SD) 7.88 (2.52) 7.79 (2.47) 
Child problematic media use score, mean (SD) 22.85 (8.39) 24.02 (9.13) 
Problematic use score ≥27 163 (32.6) 178 (38.8) 

PHQ-4, Patient Health Questionnaire-4; SD, standard deviation.

Among children ages 6 to 10, there was a small decline in the total number of rules implemented during the pandemic (prepandemic mean = 2.82, SD = 1.90, during pandemic mean = 2.55, SD = 1.86), a statistically significant but small effect (Cohen’s d = 0.14, P <.001). This was driven by change in 4 of the 7 rules: mobile devices charged outside child’s bedroom (49% prepandemic, 45% during, P = .016), no screens during mealtime (46% prepandemic, 43% during, P = .005), weekday screen time limits (29% prepandemic, 21% during, P <.001), and weekend limits (21% prepandemic, 17% during, P = .017). Among children ages 11 to 17, there was a small decline in the total number of rules implemented during the pandemic (mean = 1.74, SD = 1.68) as compared with prepandemic (mean = 2.00, SD = 1.77), a statistically significant but small effect (Cohen’s d = 0.15, P <.001). This was driven by change in 5 of the 7 rules: no screens during meal time (43% prepandemic, 41% during, P = .005), no screens at least 1 hour before bedtime (prepandemic = 36%, during = 28%, P = .012), restrictions on what shows and apps the child has access to (43% prepandemic, 41% during, P = .037), weekday screen limits (17% prepandemic, 11% during, P <.001), and weekend screen limits (10% prepandemic, 7% during, P = .002). All comparisons are presented in Table 2.

TABLE 2

Family Media Rule Implementation Before and During the COVID-19 Pandemic by Child Age Group (N = 1000)

Media ruleAge 6–10, N (%) or Mean (SD)PAge 11–17, N (%) or Mean (SD)P
 N = 500  N = 500  
Mobile devices and other screens not allowed in child’s bedroom     
 Before 166 (33.20) .114 87 (18.90) .883 
 During 150 (29.43) 85 (19.60) 
Mobile devices charged outside child’s bedroom     
 Before 249 (48.68) .016 138 (32.47) .064 
 During 226 (44.83) 123 (26.72) 
No screens during meal time     
 Before 245 (46.49) .005 228 (42.97) .005 
 During 217 (42.52) 201 (40.76) 
No screens for child at least 1 h before bedtime     
 Before 205 (38.51) .688 164 (35.69) .012 
 During 200 (38.67) 139 (27.90) 
Restrictions on what shows and apps child has access to     
 Before 328 (65.86) .059 209 (43.05) .037 
 During 309 (61.25) 192 (41.44) 
Enforced limits on weekday screen time     
 Before 146 (29.08) <.001 86 (16.70) <.001 
 During 108 (21.13) 53 (10.53) 
Enforced limits on weekend screen time     
 Before 102 (20.52) .017 51 (10.15) .002 
 During 85 (16.85) 34 (6.57) 
Total number of rules implemented, mean (SD)     
 Before 2.82 (1.90) <.001 2.00 (1.77) <.001 
 During 2.55 (1.86) 1.74 (1.68) 
Media ruleAge 6–10, N (%) or Mean (SD)PAge 11–17, N (%) or Mean (SD)P
 N = 500  N = 500  
Mobile devices and other screens not allowed in child’s bedroom     
 Before 166 (33.20) .114 87 (18.90) .883 
 During 150 (29.43) 85 (19.60) 
Mobile devices charged outside child’s bedroom     
 Before 249 (48.68) .016 138 (32.47) .064 
 During 226 (44.83) 123 (26.72) 
No screens during meal time     
 Before 245 (46.49) .005 228 (42.97) .005 
 During 217 (42.52) 201 (40.76) 
No screens for child at least 1 h before bedtime     
 Before 205 (38.51) .688 164 (35.69) .012 
 During 200 (38.67) 139 (27.90) 
Restrictions on what shows and apps child has access to     
 Before 328 (65.86) .059 209 (43.05) .037 
 During 309 (61.25) 192 (41.44) 
Enforced limits on weekday screen time     
 Before 146 (29.08) <.001 86 (16.70) <.001 
 During 108 (21.13) 53 (10.53) 
Enforced limits on weekend screen time     
 Before 102 (20.52) .017 51 (10.15) .002 
 During 85 (16.85) 34 (6.57) 
Total number of rules implemented, mean (SD)     
 Before 2.82 (1.90) <.001 2.00 (1.77) <.001 
 During 2.55 (1.86) 1.74 (1.68) 

Poisson regression was used to examine the association between structural and parent variables and the number of media rules implemented during the pandemic (Table 3). In both age groups, the strongest association with during-pandemic rules was prepandemic rules. Among 11 to 17-year-olds, greater pandemic impact on parent self-care (RR = 0.97, 95% CI = 0.94 to 1.00) was associated with implementing fewer rules.

TABLE 3

Poisson Regression Examining Association Between Structural and Family Characteristics and Number of Media Rules Implemented During the COVID-19 Pandemic (N = 1000)

Family CharacteristicsAge 6–10Age 11–17
Rate Ratio (95% CI) Pβ (SE) PRate Ratio, (95% CI) Pβ (SE) P
Child age 0.96 (0.91 to 1.00) .049 0.06 (0.03) .049 0.98 (0.94 to 1.02) .217 −0.05 (0.05) .216 
Child gender     
 Male (ref) (ref) (ref) (ref) 
 Female 1.03 (0.91 to 1.17) .600 0.02 (0.03) .600 1.15 (0.98 to 1.34) .080 0.07 (0.04) .080 
Public insurance 1.07 (0.92 to 1.24) .373 0.03 (0.04) .372 1.00 (0.81 to 1.23) 0.988 −0.001 (0.05) .987 
Parent education     
 ≤High school (ref) (ref) (ref) (ref) 
 Some college or 2 y degree 1.04 (0.88 to 1.23) .646 0.02 (0.04) .646 0.93 (0.75 to 1.15) .508 −0.03 (0.05) .508 
 4 y degree 1.10 (0.92 to 1.34) .280 0.05 (0.04) .280 1.06 (0.83 to 1.35) .627 0.03 (0.05) .627 
 Graduate degree 1.12 (0.89 to 1.40) .339 0.04 (0.04) .338 0.94 (0.71 to 1.23) .628 −0.03 (0.05) .627 
Parent employment     
 All parents unemployed (ref) (ref) (ref) (ref) 
 1 or more parents employed part-time 0.99 (0.79 to 1.23) .902 −0.01 (0.06) .902 1.10 (0.83 to 1.46) .516 0.05 (0.07) .516 
 All parents employed full-time 1.02 (0.82 to 1.28) .853 0.01 (0.06) .852 1.05 (0.78 to 1.41) .757 0.02 (0.07) .757 
 Parent PHQ-4 score 0.99 (0.97 to 1.01) .390 −0.03 (0.04) .390 0.99 (0.97 to 1.01) .355 −0.04 (0.04) .354 
Parent home presence     
 Low (ref) (ref) (ref) (ref) 
 Moderate 0.95 (0.78 to 1.14) .557 −0.03 (0.05) .556 1.08 (0.86 to 1.36) 0.529 0.04 (0.06) .529 
 High 0.99 (0.82 to 1.21) .954 −0.003 (0.05) .954 1.19 (0.94 to 1.52) .154 0.09 (0.06) .153 
Impact of COVID-19 on parent self-care 0.99 (0.97 to 1.02) .606 −0.02 (0.05) .605 0.97 (0.94 to 1.00) .036 −0.08 (0.04) .036 
School modality     
 Remote (ref) (ref) (ref) (ref) 
 Hybrid 1.08 (0.93 to 1.27) .314 0.04 (0.04) .313 1.11 (0.93 to 1.33).230 0.05 (0.04) .229 
 In-person 1.09 (0.93 to 1.28) .287 0.04 (0.04) .286 0.98 (0.77 to 1.24) .877 −0.01 (0.05) .876 
 Prepandemic rules 1.32 (1.28 to 1.37) <.001 0.53 (0.03) <.001 1.43 (1.37 to 1.49) <.001 0.644 (0.04) <.001 
Family CharacteristicsAge 6–10Age 11–17
Rate Ratio (95% CI) Pβ (SE) PRate Ratio, (95% CI) Pβ (SE) P
Child age 0.96 (0.91 to 1.00) .049 0.06 (0.03) .049 0.98 (0.94 to 1.02) .217 −0.05 (0.05) .216 
Child gender     
 Male (ref) (ref) (ref) (ref) 
 Female 1.03 (0.91 to 1.17) .600 0.02 (0.03) .600 1.15 (0.98 to 1.34) .080 0.07 (0.04) .080 
Public insurance 1.07 (0.92 to 1.24) .373 0.03 (0.04) .372 1.00 (0.81 to 1.23) 0.988 −0.001 (0.05) .987 
Parent education     
 ≤High school (ref) (ref) (ref) (ref) 
 Some college or 2 y degree 1.04 (0.88 to 1.23) .646 0.02 (0.04) .646 0.93 (0.75 to 1.15) .508 −0.03 (0.05) .508 
 4 y degree 1.10 (0.92 to 1.34) .280 0.05 (0.04) .280 1.06 (0.83 to 1.35) .627 0.03 (0.05) .627 
 Graduate degree 1.12 (0.89 to 1.40) .339 0.04 (0.04) .338 0.94 (0.71 to 1.23) .628 −0.03 (0.05) .627 
Parent employment     
 All parents unemployed (ref) (ref) (ref) (ref) 
 1 or more parents employed part-time 0.99 (0.79 to 1.23) .902 −0.01 (0.06) .902 1.10 (0.83 to 1.46) .516 0.05 (0.07) .516 
 All parents employed full-time 1.02 (0.82 to 1.28) .853 0.01 (0.06) .852 1.05 (0.78 to 1.41) .757 0.02 (0.07) .757 
 Parent PHQ-4 score 0.99 (0.97 to 1.01) .390 −0.03 (0.04) .390 0.99 (0.97 to 1.01) .355 −0.04 (0.04) .354 
Parent home presence     
 Low (ref) (ref) (ref) (ref) 
 Moderate 0.95 (0.78 to 1.14) .557 −0.03 (0.05) .556 1.08 (0.86 to 1.36) 0.529 0.04 (0.06) .529 
 High 0.99 (0.82 to 1.21) .954 −0.003 (0.05) .954 1.19 (0.94 to 1.52) .154 0.09 (0.06) .153 
Impact of COVID-19 on parent self-care 0.99 (0.97 to 1.02) .606 −0.02 (0.05) .605 0.97 (0.94 to 1.00) .036 −0.08 (0.04) .036 
School modality     
 Remote (ref) (ref) (ref) (ref) 
 Hybrid 1.08 (0.93 to 1.27) .314 0.04 (0.04) .313 1.11 (0.93 to 1.33).230 0.05 (0.04) .229 
 In-person 1.09 (0.93 to 1.28) .287 0.04 (0.04) .286 0.98 (0.77 to 1.24) .877 −0.01 (0.05) .876 
 Prepandemic rules 1.32 (1.28 to 1.37) <.001 0.53 (0.03) <.001 1.43 (1.37 to 1.49) <.001 0.644 (0.04) <.001 

CI, confidence intervals; β, Standardized beta; SE: standard error; PHQ-4, Patient Health Questionnaire-4.

Linear regression was used to assess the association between structural and family factors and problematic media use (Table 4). The absolute number of rules a family implemented was not significantly associated with problematic use in either age group. Among younger children only, a greater decline in media rules was significantly associated with more problematic media use (0.99, 95% CI = 0.33 to 1.66, P = .004). For each 1-point increase in parent PHQ-4 score, problematic media use scores increased by 0.46 points among younger children (95% CI = 0.19 to 0.72, P = .001) and 1.27 points among older children (95% CI = 1.02 to 1.53, P <.001). There was a significant association between decline in parent self-care behaviors and higher problematic media scores in younger children only [B] = 0.71, 95% CI= 0.36 to 1.06). Child gender was significantly associated with problematic media use in only the younger age group, with girls having scores 1.71 points lower than boys (95% CI = −3.30 to −0.12). Among older children only, parent part time employment (B = 3.16, 95% CI = 0.16 to 6.15), full time employment (B = 5.17, 95% CI = 2.25 to 8.09) and high parent presence in home (B = 3.02, 95% CI = 0.60 to 5.44) were associated with higher problematic media use scores. Among older children only, as compared with those whose parents had formal educational attainment of a high school diploma or less, those whose parents with a 2-year degree (B = −4.05, 95% CI = −6.23 to −1.88), 4-year degree (B = −2.93, 95% CI = −5.28 to −0.58), or postgraduate degree (B = −3.01, 95% CI = −5.82 to −0.20) had lower problematic media use scores. As compared with 11 to 17 year olds whose schooling was fully remote, those in a hybrid modality had higher problematic media use scores (B = 2.14, 95% CI = 0.35 to 3.93). Exploratory tests for interactions were not significant and are reported in detail in Supplemental Information.

TABLE 4

Association Between Structural and Family Stressors, Screen Rule Implementation, and Problematic Media Use During the COVID-19 Pandemic (N = 1000)

Family CharacteristicsAge 6–10Age 11–17
B (95% CI) Pβ (SE) PB (95% CI) Pβ (SE) P
Child age 0.82 (0.23 to 1.40) .007 1.14 (0.42) .007 −0.09 (−0.50 to 0.33) .675 −0.18 (0.42) 0.675 
Child gender     
 Male (ref) (ref) (ref) (ref) 
 Female −1.71 (−3.30 to −0.12) .036 −0.85 (0.40) .035 −1.14 (−2.77 to 0.48) .170 −0.57 (0.42) .169 
Parent employment     
 All parents unemployed (ref) (ref) (ref) (ref) 
 1 or more parents employed part-time 1.10 (−1.73 to 3.94) .446 0.55 (0.72) .446 3.16 (0.16 to 6.15) .040 1.58 (0.76) .040 
 2 parents employed full-time 2.95 (0.01, 5.88) 0.051 1.41 (0.72) 0.050 5.17 (2.25 to 8.09) .001 2.51 (0.72) .001 
Parent home presence     
 Low (ref) (ref) (ref) (ref) 
 Moderate 0.032 (−2.27 to 3.34) .979 0.02 (0.55) .978 0.68 (−1.58 to 2.94) .556 0.33 (0.55) .555 
 High 1.57 (−0.91 to 4.04) .216 0.78 (0.63) .215 3.02 (0.60 to 5.44) 1.48 (0.61) .015 
 Public insurance 1.38 (−0.51 to 3.26) .154 0.67 (0.47) .153 −1.10 (−3.12 to 0.92) .288 −0.53 (0.49) .287 
Parent education     
 ≤ High school (ref) (ref) (ref) (ref) 
 Some college or 2 y degree 1.38 (−0.69 to 3.45) .192 0.64 (0.49) .191 −4.05 (−6.23 to −1.88) <.001 −1.88 (0.52) <.001 
 4 y degree 0.93 (−1.47 to 3.34) .449 0.40 (0.53) .449 −2.93 (−5.28 to −0.58) .015 −1.22 (0.50) .015 
 Graduate degree 1.43 (−1.49 to 4.35) .338 0.48 (0.50) .338 −3.01 (−5.82 to −0.20) .037 −1.10 (0.53) 0.037 
Parent PHQ-4 score 0.459 (0.19 to 0.72) <.001 1.52 (0.45) .001 1.27 (1.02 to 1.53) <.001 4.25 (0.43) <.001 
Impact of COVID-19 on parent self-care 0.71 (0.36 to 1.06) <.001 1.79 (0.45) <.001 −0.02 (−0.37 to 0.34) 0.927 −0.04 (0.44) .927 
School modality     
 Remote (ref) (ref) (ref) (ref) 
 Hybrid −0.55 (−2.51 to 1.42) .587 −0.24 (0.44) .586 2.14 (0.35 to 3.93) .020 0.99 (0.42) .020 
 In-person −0.36 (−2.43 to 1.71) .736 −0.15 (0.44) .735 −1.00 (−3.48 to 1.48) .429 −0.37 (0.47) .43 
 During pandemic media rules −0.24 (−0.71 to 0.24) .332 −0.45 (0.46) 0.332 0.43 (−0.08 to 0.934) .097 0.73 (0.44) .096 
 Change in screen rules from prepandemic a 0.99 (0.33 to 1.66) .004 1.31 (0.45) .004 0.71 (−0.09 to 1.52) .085 0.79 (0.46) .084 
Family CharacteristicsAge 6–10Age 11–17
B (95% CI) Pβ (SE) PB (95% CI) Pβ (SE) P
Child age 0.82 (0.23 to 1.40) .007 1.14 (0.42) .007 −0.09 (−0.50 to 0.33) .675 −0.18 (0.42) 0.675 
Child gender     
 Male (ref) (ref) (ref) (ref) 
 Female −1.71 (−3.30 to −0.12) .036 −0.85 (0.40) .035 −1.14 (−2.77 to 0.48) .170 −0.57 (0.42) .169 
Parent employment     
 All parents unemployed (ref) (ref) (ref) (ref) 
 1 or more parents employed part-time 1.10 (−1.73 to 3.94) .446 0.55 (0.72) .446 3.16 (0.16 to 6.15) .040 1.58 (0.76) .040 
 2 parents employed full-time 2.95 (0.01, 5.88) 0.051 1.41 (0.72) 0.050 5.17 (2.25 to 8.09) .001 2.51 (0.72) .001 
Parent home presence     
 Low (ref) (ref) (ref) (ref) 
 Moderate 0.032 (−2.27 to 3.34) .979 0.02 (0.55) .978 0.68 (−1.58 to 2.94) .556 0.33 (0.55) .555 
 High 1.57 (−0.91 to 4.04) .216 0.78 (0.63) .215 3.02 (0.60 to 5.44) 1.48 (0.61) .015 
 Public insurance 1.38 (−0.51 to 3.26) .154 0.67 (0.47) .153 −1.10 (−3.12 to 0.92) .288 −0.53 (0.49) .287 
Parent education     
 ≤ High school (ref) (ref) (ref) (ref) 
 Some college or 2 y degree 1.38 (−0.69 to 3.45) .192 0.64 (0.49) .191 −4.05 (−6.23 to −1.88) <.001 −1.88 (0.52) <.001 
 4 y degree 0.93 (−1.47 to 3.34) .449 0.40 (0.53) .449 −2.93 (−5.28 to −0.58) .015 −1.22 (0.50) .015 
 Graduate degree 1.43 (−1.49 to 4.35) .338 0.48 (0.50) .338 −3.01 (−5.82 to −0.20) .037 −1.10 (0.53) 0.037 
Parent PHQ-4 score 0.459 (0.19 to 0.72) <.001 1.52 (0.45) .001 1.27 (1.02 to 1.53) <.001 4.25 (0.43) <.001 
Impact of COVID-19 on parent self-care 0.71 (0.36 to 1.06) <.001 1.79 (0.45) <.001 −0.02 (−0.37 to 0.34) 0.927 −0.04 (0.44) .927 
School modality     
 Remote (ref) (ref) (ref) (ref) 
 Hybrid −0.55 (−2.51 to 1.42) .587 −0.24 (0.44) .586 2.14 (0.35 to 3.93) .020 0.99 (0.42) .020 
 In-person −0.36 (−2.43 to 1.71) .736 −0.15 (0.44) .735 −1.00 (−3.48 to 1.48) .429 −0.37 (0.47) .43 
 During pandemic media rules −0.24 (−0.71 to 0.24) .332 −0.45 (0.46) 0.332 0.43 (−0.08 to 0.934) .097 0.73 (0.44) .096 
 Change in screen rules from prepandemic a 0.99 (0.33 to 1.66) .004 1.31 (0.45) .004 0.71 (−0.09 to 1.52) .085 0.79 (0.46) .084 

B, unstandardized beta; CI, confidence intervals; β, standardized beta; SE, standard error

a

Prepandemic rule score minus during pandemic rule score

In this sample of parents of school-aged children in the United States, around one-third of children were engaging in media use classified as problematic. Consistent with the premise of the Interactional Theory of Childhood Problematic Media Use,13 problematic use was greater in families experiencing structural stressors and worse parent wellbeing and was unrelated to the number of media-related rules they implemented. Among younger children a greater decline in rules implemented during the pandemic as compared with earlier periods was associated with more problematic use, however this estimate was small and imprecise. Although fewer media rules were implemented during the pandemic, this change was explained almost entirely by prepandemic rules, and not by the structural and family-level stressors that were associated with problematic use.

Although others have documented benefits of having media rules for limiting screen time, at least at younger age,1618  results of this study raise questions about the sufficiency of such an approach to media-related parenting if the goal is limiting problematic media use. The Interactional Theory of Childhood Problematic Media Use13 emphasizes the importance of focusing on how media functions for a family and child, rather than focusing on the absolute level of use. Across both age groups, children whose parents were experiencing more psychological distress had notably higher problematic media use scores, and among younger children there was an additional association between parents experiencing a greater decline in self-care behaviors and problematic media use. Prepandemic data finds that among young children there is an association between greater parenting stress and less parent mediation of child media use,20 and more child screen exposure. Further research is needed to understand how media functions in families when parents are experiencing challenges to their own wellbeing.

Among older children only, problematic media use was higher when parents were employed, and when they were present in the home (eg, working from home). This association raises questions about how media use functioned for families in home environments with competing parental demands. It is possible that among younger children, when parents had competing demands (eg, work), someone else was providing childcare, or parents were more closely involved in monitoring child activities (eg, assisting with logging into remote schooling or supervising leisure activities). Parents of older children may have been more likely to leave them to their own devices when faced with competing demands. As remote work seems likely to continue for many families, learning more about how families manage child media use when children are in the home and parents are working can help inform approaches to supporting families use of media in a way that is functional and not problematic.

There are many reasons why families may have changed their media use practices during the pandemic, and all need to be understood as occurring in structural, social, and family contexts that reinforce and constrain use. Nonetheless, problematic media use is something that many families will be dealing with as the pandemic resolves. Pediatricians and others counseling families about media use or designing behavioral interventions related to media use must balance addressing problematic use with the reality that media use may be helping families function in a range of ways and may be influenced by structural constraints outside of direct parenting control. A pragmatic approach to addressing problematic media use may be viewing it as 1 of many potential indicators of family functioning and parent wellbeing. A family’s change in media use practices could be used as an entry point for checking in about parenting and familial stress and connecting parents to available social services and resources that support their wellbeing and their family’s functioning.

A primary limitation of this study is that is it cross-sectional, with parents recalling prepandemic media practices. Recall may have been inaccurate in unbiased ways, making measurement imprecise. It is also possible recall was biased. Because of social desirability bias, parents may have systematically reported less problematic media use and more media-related rules. It is also possible that families with children with more problematic media use at the time of the study may have been more likely than families with less problematic use to favorably recall prepandemic media use. There were no prepandemic measures of parenting stress or problematic media use, further limiting any inferences related to causality. Second, 1 parent responded about 1 reference child. However, families are complex systems, often with more than 1 parent and child, or blended families across 2 households. Such dynamics (eg, number and age of children in the family or discordant parent perspectives on media use28) undoubtedly impact how families approach rule implementation, how media use functions, and child risk of problematic use. Qualitative research and network-based survey research is needed to explore the complexities of media rule implementation across diverse family structures. Third, we did not include a measure of screen time in these analyses given problems with reliability and validity of parent-report of child screen use. Future research using a reliable, objective, means of measuring child media use would be useful to understand how changes in implementation of media use practices relate to amount of screen use. Additional variables that were unmeasured but are potentially important in explaining problematic media use include child-level mental health, behavior or functioning, social norms related to screen use, parent stress, more nuanced measurement of family employment-related stressors (eg, parent remote work), and more detail on family socioeconomic status, including a direct measure of family income.

Family stressors, but not media rules, were associated with more problematic media use among school-aged children during the COVID-19 pandemic. Harm reduction efforts related to problematic media use should consider the inequitable stressors to which families are exposed and how these impact the ways in which media is used by families to support functioning.

Dr Kroshus conceptualized and designed the study, designed the data collection instruments, and drafted the initial manuscript; Dr Tandon conceptualized and designed the study, designed the data collection instruments, and contributed to data collection; Dr Zhou conducted analyses; Dr Johnson contributed to analyses; Ms Steiner coordinated data collection; Dr Christakis contributed to the design of data collection instruments; and all authors reviewed and revised the manuscript, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.

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Competing Interests

CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no conflicts of interest to disclose.

Supplementary data