Skip to main content
NCBI home page
Springer Nature - PMC COVID-19 Collection logoLink to Springer Nature - PMC COVID-19 Collection
. 2022 Aug 17;32(1):81–92. doi: 10.1007/s10826-022-02399-7

Mothers’ Perceptions of Children’s Screen Use During the COVID-19 Lockdown in Israel

Yaakov Ophir 1,✉, Hananel Rosenberg 2, Yaniv Efrati 3, Refael Tikochinski 1
PMCID: PMC9382602  PMID: 35991343

Abstract

The contemporary parenting challenge of regulating children’s screen time became even more difficult during the coronavirus pandemic (COVID-19). The current research addresses the characteristics of this challenge and explores mothers’ perceptions regarding their children’s screen use, through two consecutive studies. Study 1 included 299 mothers of elementary school children, who were asked to complete questionnaires regarding their children’s screen habits. Mothers were also asked about their own attitudes towards screens, as parents, and about their personal feelings of frustration and guilt. Study 2 replicated this procedure among a new sample of 283 mothers who also completed validated scales assessing their sense of parental competence and authority style. Retrospective reports of mothers indicated that, during the lockdown, entertainment use of screens increased by 73% among 4th–6th graders and by 108% among 1st–3rd graders. Educational use increased by 86% in both age groups. Mothers’ guilt increased as well and was predicted by children’s entertainment use (but not educational use), after accounting for demographic variables and mothers’ attitudes. Other factors, such as parenting style and having at-least one child with a diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD), were associated with entertainment use (regardless of the COVID-19 lockdown). Factors that were found to moderate the lockdown effect were mothers’ attitudes towards screens and parental confidence. The findings are discussed in the context of parents’ efforts to regulate their children’s screen use.

Keywords: Screen use, COVID-19, Parenting style, Parental competence, ADHD

Highlights

  • Children’s screen time is a major parenting challenge today.

  • Children’s screen use for entertainment and educational purposes increased during the COVID-19 pandemic.

  • Mothers’ guilt also increased but was associated only with entertainment use of screens.

  • The increase in entertainment use was moderated by mothers’ attitudes and parental confidence.

  • Parents may derive insights from this study regarding their own parental approach.

A major concern of parents in our modern society is the amount of time children spend engaging with screen-based content. Twenty-first century children are the first generation to grow up with smartphone devices from very young ages, and many parents are worried that this unprecedented exposure to screen technologies could impair their children’s psychological development (Ophir, Rosenberg, et al., 2020). Naturally, this parental concern is not unfounded. An increasing number of studies have documented links between children’s screen use and a range of unwanted developmental outcomes, including, for example, cognitive delays (Hutton et al., 2020; Madigan et al., 2020), addictive behaviors (King et al., 2010; Van Deursen et al., 2015) and emotional dysregulation (Elhai et al., 2017). Considering these potential adverse outcomes, parents are typically advised by health officials to limit their children’s screen time, especially at young ages (WHO, 2019).

However, limiting children’s screen time is not always an easy task for parents. There are multiple factors that are known to facilitate (or to moderate) children’s screen time, some of which are very difficult to control. Previous studies have shown that children’s screen time is associated with the socio-demographic and educational background of parents and with specific characteristics of children (Rideout et al., 2011). For example, multiple studies investigated screen use in children with Attention-Deficit/Hyperactivity Disorder (ADHD), with the assumption that the restlessness that characterizes the disorder would lead children with ADHD to favor the stimulating and highly rewarding activities associated with screen use (Beyens et al., 2018). Additional, perhaps less concrete, factors that can influence children’s screen use are their parent’s general competence, confidence, and parenting styles (Bjelland et al., 2015; Livingstone et al., 2015; Valcke et al., 2010). Finally, parental attitudes towards children’s screen use seem to play a significant role in children’s actual screen use (Cingel & Krcmar, 2013; Lauricella et al., 2015). These attitudes include parents’ beliefs regarding the benefits and risks of screen use, alongside their perceptions regarding their own parental role in limiting their children’s screen time.

Notably, parental attitudes towards children’s screen use predict children’s actual screen time, even in cases where the parents’ own patterns of screen use are not consistent with their attitudes (e.g., parents that spend excessive time on screen technologies despite their negative attitudes towards children’s use) (Lauricella et al., 2015). In addition, mundane “functional parental motives” may also prove to be useful in predicting children’s screen time (Cingel & Krcmar, 2013). Parents who work long hours, for example, may allow their children more screen time than they would like (according to their personal attitudes towards screens). Correspondingly, many parents struggle to meet the strict screen time guidelines of medical officials and allow their children more screen time than is recommended (Götz et al., 2020; Trinh et al., 2020). Inevitably, modern lifestyles and working habits, along with the glut of scientific warnings regarding the effects of screens on children’s development, lead many parents to experience considerable guilt and frustration (Carson et al., 2014).

Unfortunately, this complex parental struggle became even more difficult with the COVID-19 pandemic. The pandemic led many countries to shut schools and enforce partial or complete lockdowns, which left millions of children at home, relatively isolated, without productive programs or activities. In order to cope with this challenging and unfamiliar situation, many parents turned to screen technologies as a fast and immediate solution, and the overall screen time of children soared dramatically (Götz et al., 2020; Schmidt et al., 2020). This rise in children’s screen use became a further source of anxiety in these already difficult pandemic times (Nagata et al., 2020; Sultana et al., 2021). The present research aims to investigate the characteristics of this parental concern and to explore mothers’ perspectives regarding their children’s screen use.

Specifically, this research consists of two consecutive studies which were conducted in Israel, a world leader in the use of smartphones and other screen technologies (Ministry of Education, 2018; Pew Research Center, 2019). In fact, most children in Israel receive their first smartphone as soon as they reach the 4th grade (National Council for the Child, 2020). Study 1 explored the following research questions: To what extent did children’s screen time increase during the COVID-19 lockdown? Did mothers experience negative emotions regarding their own parenting following their children’s use of screens, and, if so, did they differentiate between educational use and entertainment use of screens? Study 2 furthered this investigation and targeted the following questions: What were the factors that augmented or moderated children’s screen use during the COVID-19 lockdown? Did certain parenting capabilities and certain traits in children predict children’s screen use during the lockdown? A detailed description of the hypotheses, methodologies, and results of both studies is provided below.

Study 1

The goal of the first study was to investigate the extent to which children’s screen time increased during the COVID-19 lockdown and to evaluate mothers’ consequent negative emotional reactions (i.e., frustration and guilt). Based on recent evidence that children’s screen time did in fact increase during the COVID-19 pandemic (Götz et al., 2020; Schmidt et al., 2020) and based on prior work that documented increased parental guilt when official guidelines on screen time were not met (Carson et al., 2014), we hypothesized that a significant increase would be observed in both variables. We were also interested to see if these variables are positively correlated beyond the expected effects of other potential variables that are known to affect screen use, such as the demographic background of the mothers and their individual attitudes towards children’s screen use (see the introduction above).

Additionally, this study aims to examine a unique aspect of screen use that is less discussed in the literature—the distinction between general use of screens, mainly for entertainment, and a more targeted use of screens for educational purposes (e.g., Skvarc et al., 2021). In this study, we predicted that not all types of screen use would be associated with parental guilt and frustration. We hypothesized that mothers would experience negative feelings regarding their children’s use of screens for entertainment and would not necessarily experience these feelings with regard to their children’s educational use of screens (e.g., lessons using video communication tools, educational TV programs, etc.).

Method

Participants and procedure

The procedures of Study 1 and Study 2 were approved by the Institutional Review Board (IRB) of Beit Berl College. The recruitment of participants was conducted on April 16, 2020, using a large and well-established survey company in Israel, approximately three weeks after the beginning of the first COVID-related lockdown. On account of the lockdown, all data-collection procedures were conducted online using the popular application Qualtrics. After signing a consent form, participants were asked to answer a set of close-ended questions, which were developed for the purpose of this study (all questions were presented to the participants in Hebrew). To minimize poor-quality responses, we applied a strict data-quality protocol (Ophir, Sisso, et al., 2020). First, we measured the response time for each participant. Participants who provided answers within an improbable response time (i.e., over ten words in one second) were omitted from the final sample. Second, we administered an “honesty item” at the end of the study in which participants could declare if they had been “attentive,” “not so attentive,” or “completely inattentive” during the study. In this item, we shared our concern with the participants that poor-quality responses might impair the scientific process, and we assured them that honest responses would not harm them in any way. Participants who admitted they had been not so attentive or completely inattentive were excluded from the final sample.

Altogether, the initial sample consisted of 326 mothers. Twenty-seven (8.2%) mothers, however, failed the attention checks. The final sample included 299 mothers aged 27 to 67 (M = 40.88, SD = 5.45), of which 100 mothers had children in the 1st to 3rd grades, 82 had children in 4th to 6th grades, and 117 had children in both age groups. The demographic characteristics of the sample (age of the mothers, number of children, education years, and economic status) are described in Table 1. What follows is a detailed description of the study’s material.

Table 1.

Descriptive statistics of all variables (study one)

Variable N Mean (SD) [Min/Max]
Age 292 40.88 (5.45) [27/67]
No. of children 291 3.02 (1.15) [1/7]
Education years 292 15.27 (2.76) [4/25]
Religion status
Not religious 176 (24%)
Traditional 68 (9.3%)
Orthodox 45 (6.1%)
Ultra-orthodox 6 (0.8%)
Economic status 292 2.91 (0.82) [1/5]
Screen-time (in hours) before the COVID
Entertainment use (1st to 3rd grade) 206 1.74 (1.01) [0/6]
Entertainment use (4th to 6th grade) 188 2.48 (1.21) [0/6]
Education use (1st to 3rd grade) 202 0.71 (1.13) [0/6]
Education use (4th to 6th grade) 186 0.82 (1.03) [0/6]
Screen-time (in hours) during the COVID
Entertainment use (1st to 3rd grade) 200 3.62 (1.68) [0/6]
Entertainment use (4th to 6th grade) 185 4.29 (1.69) [0/6]
Education use (1st to 3rd grade) 199 1.33 (1.25) [0/6]
Education use (4th to 6th grade) 181 1.53 (1.43) [0/6]
Attitudes towards screens
Positive attitudes 299 3.04 (0.83) [1/5]
Negative attitudes 299 3.61 (0.80) [1/5]
Frustration and guilt–before the COVID 273 2.86 (1.07) [1/5]
Frustration and guilt–during the COVID 273 3.35 (1.25) [1/5]
Open in a new tab

Mean scores, Standard Deviations, and Min-max scores are presented for continuous variables. Percentage of participants in each class is presented for categorical variables (i.e., nominal scales)

Attitudes towards screen use

We formulated six items to measure parent attitudes towards children’s screen use. Participants’ levels of agreement with each item were rated on a 5-point scale (1 = completely disagree, 5 = fully agree). The items were: (1) screen use can lead to cognitive problems, such as delays in brain development or impairments in attention capabilities; (2) screen use can lead to emotional and social problems, such as impairments in emotion regulation and poor interpersonal capabilities; (3) screen use may contribute to children’s cognitive functioning, for example, through online education; (4) screen use may contribute to emotional and social functioning, for example through online communications with friends; (5) it is important to limit screen time among children in the 1st to 3rd grades; (6) it is important to limit screen time among children in the 4th to 6th grades.

All six attitude items significantly correlated with each other (0.2 ≤ r ≤ 0.5, p < 0.05). A factor analysis revealed two principal factors with eigenvalue >1, which together explained 69.67% of the original variance. The loadings of the items on each factor suggested that one factor represents the mother’s negative attitudes towards screens, whereas the other represents her positive attitudes. Based on this analysis, two average scores were computed, one for negative attitudes and one for positive attitudes (Table 2).

Table 2.

Factor loadings of screen-use attitudes questionnaire (study one)

Item Principal components
Negative attitudes Positive attitudes
Cognitive problems 0.760 0.141
Emotional and social problems 0.704 0.241
Screen-time limits are needed (1st to 3rd grades) 0.850 0.194
Screen-time limits are needed (4th to 6th grades) 0.828 0.246
Cognitive benefits −0.354 0.813
Emotional and social benefits −0.485 0.712
Open in a new tab

Note: The loading scores of the items that were classified to each factor are presented in bold

Screen time

Upon completion of the attitudes questionnaire, participants were asked to report their children’s daily screen time separately for both entertainment and educational use, and for their young (1st to 3rd grades) and older children (4th to 6th grades). Mothers were asked to address these four items twice – once in relation to their children’s use of screens before the COVID-19 lockdown and once during the lockdown. Under each item, mothers could choose from the following time options per day: “several minutes or even less”; “half an hour”; “one hour”; “two hours”; “three hours”; “four hours”; “five hours,” and “six hours and more.” Prior to the statistical analyses, these categorical options were transformed into a continuous “screen time” variable, such that the verbal answers (e.g., three hours) were replaced by their corresponding numerical value (e.g., 3). The first option of “several minutes or even less” was coded 0.1 and the last option of “6 hours and more” was coded 6.1.

Parental guilt and frustration

Finally, mothers were asked to rate on a 5-point scale (1 = not at all, 5 = very much) the extent to which they experienced negative feelings concerning their parenting, such as guilt or frustration, in relation to their children’s screen use. Mothers completed this item twice, once in the section that addressed their children’s screen use before the COVID-19 lockdown, and once in the section that addressed their children’s screen use during the lockdown.

Results

The descriptive statistics of all the variables in the study, including the average screen time of the children before and during the COVID-19 lockdown are presented in Table 1. To examine our first hypothesis regarding the expected increase in screen time, we conducted paired-samples t-tests. The first main finding was that children’s screen time increased significantly during the COVID-19 lockdown across all ages and usages [entertainment use in the 1st to 3rd grades: Mdiff = 1.87, t(199) = 17.01, p < 0.01; entertainment use in the 4th to 6th grades: Mdiff = 1.80, t(182 = 16.20, p < 0.01; educational use in the 1st to 3rd grades: Mdiff = 0.65, t(198) = 7.15, p < 0.01; educational use in the 4th to 6th grades: Mdiff = 0.72, t(180) = 6.75, p < 0.01)]. The results indicated that during the COVID-19 lockdown, entertainment use of screens increased by 73% among 4th–6th graders and by 108% among 1st–3rd graders. Educational use increased by 86% in both age groups. The second main finding was that mothers’ guilt and frustration regarding their children’s screen use had also increased significantly during the COVID-19 lockdown (Mdiff = 0.49, t(291) = 7.70, p < 0.01), although the magnitude of this increase was smaller than the rise in children’s screen use. Here, the levels of frustration and guilt increased by 17% only.

To examine the specific relationships between the mothers’ guilt and frustration and their children’s screen use during the lockdown, and to explore what other factors may have contributed to mothers’ increased sense of guilt and frustration, we conducted a two-step hierarchical regression. Step 1 included the following predictors: demographic variables (age, number of children, education years, economic status); mothers’ attitudes towards screen use (average positive attitudes and average negative attitudes), and baseline-levels of mothers’ guilt and frustration before COVID-19. Step 2 included the actual increase in screen time before and during the COVID-19 lockdown (calculated as the duration during the lockdown minus the duration before the lockdown). This increase included two predictors: increase in entertainment use and increase in educational use. The regression analysis was conducted twice, once for mothers of children in the 1st to 3rd grades (Table 3) and once for mothers of children in the 4th to 6th grades (Table 4).

Table 3.

Negative feelings among mothers of children in the 1st to 3rd grades – a regression analysis (study one)

Model B S β t p R2 R2 changed F p
1 Age −0.023 0.016 −0.099 −1.404 0.162 0.218 0.218 5.550 0.000
Number of Children 0.002 0.071 0.002 0.029 0.977
Education years −0.002 0.028 −0.004 −0.063 0.950
Economic status 0.105 0.098 0.075 1.073 0.285
Religious
 Orthodox 0.014 0.198 0.005 0.070 0.944
 Ultra-orthodox −1.21 0.237 −0.41 −0.509 0.611
Positive attitudes −0.061 0.093 −0.049 −0.657 0.512
Negative attitudes 0.349 0.104 0.247 3.367 0.001
Pre-COVID negative feelings −0.446 0.073 −0.449 −6.143 0.000
2 Age −0.025 0.015 −0.112 −1.662 0.098 0.299 0.081 10.25 0.000
Number of Children 0.036 0.068 0.038 0.523 0.601
Education years −0.006 0.027 =0.015 −0.219 0.827
Economic status 0.098 0.093 0.070 1.054 0.293
Religious
 Orthodox 0.106 0.189 0.039 0.559 0.577
 Ultra-orthodox −0.119 0.225 −0.041 −0.528 0.598
Positive attitudes −0.087 0.089 −0.069 −0.947 0.331
Negative attitudes 0.297 0.099 0.210 2.986 0.003
Pre-COVID negative feelings −0.424 0.069 −0.427 −6.113 0.000
Change in screen-time (Entertainment) 0.212 0.047 0.291 4.51 0.000
Change in screen-time (Educational) 0.012 0.056 0.013 0.211 0.833
Open in a new tab

Table 4.

Negative feelings among mothers of children in the 4th to 6th grades–a regression analysis (study one)

Model B S β t p R2 R2 changed F p
1 Age 0.012 0.014 0.059 0.837 0.404 0.240 0.240 5.582 0.000
Number of Children 0.049 0.059 0.060 0.834 0.406
Education years 0.074 0.027 0.201 2.790 0.006
Economic status 0.238 0.083 0.208 2.854 0.005
Religious
 orthodox −0.001 0.164 0.000 −0.005 0.996
 Ultra-orthodox −0.185 0.218 −0.066 −0.847 0.398
Positive attitudes −0.284 0.092 −0.230 −3.081 0.002
Negative attitudes 0.257 0.105 0.203 2.448 0.015
Pre-COVID negative feelings −0.459 0.078 −0.463 −5.879 0.000
2 Age 0.005 0.014 0.027 0.387 0.699 0.297 0.057 6.680 0.002
Number of Children 0.057 0.058 0.069 0.991 0.323
Education years 0.068 0.026 0.185 2.634 0.009
Economic status 0.240 0.081 0.209 2.972 0.003
Religious
 Orthodox 0.085 0.161 0.037 0.526 0.600
 Ultra-orthodox −0.192 0.211 −0.069 −0.909 0.364
Positive attitudes −0.278 0.089 −0.225 −3.113 0.002
Negative attitudes 0.283 0.102 0.223 2.776 0.006
Pre-COVID negative feelings −0.475 0.076 −0.479 −6.276 0.000
Change in screen-time (Entertainment) 0.167 0.046 0.246 3.638 0.000
Change in screen-time (Educational) 0.005 0.047 0.007 0.103 0.918
Open in a new tab

For mothers of children in the 1st to 3rd grades, the first step revealed two significant predictors: the mothers’ negative attitudes (B = 0.349, SE = 0.104, t(180) = 3.367, p < 0.005) and the baseline level of guilt and frustration (B = −0.446, SE = 0.073, t(180) = −6.143, p < 0.001). The second step revealed an additional significant predictor: an increase in entertainment use (B = 0.212, SE = 0.05, t(180) = 4.51, p < 0.001). Importantly, the second step, which included the increase in entertainment use, contributed to the prediction of increased guilt and frustration among the mothers, above and beyond the first step that included the demographic predictors and the mothers’ attitudes towards screens and baseline levels of frustration and guilt, R2change = 0.081, Fchange(2,178) = 10.248, p < 0.001.

For mothers of children in the 4th to 6th grades, the first step revealed five significant predictors: years of education (B = 0.07, SE = 0.03, t(168) = 2.79, p < 0.01), economic status (B = 0.238, SE = 0.083, t(168) = 2.854, p < 0.05), positive attitudes (B = −0.284, SE = 0.09, t(168) = −3.081, p < 0.05), negative attitudes (B = 0.257, SE = 0.105, t(168) = 2.448, p < 0.05), and the baseline-level of guilt and frustration (B = −0.459, SE = 0.078, t(168) = −5.879, p < 0.001). The second step revealed the same additional significant predictor from the previous analysis, that is, an increase in entertainment use (B = 0.167, SE = 0.05, t(168) = 3.638, p < 0.005). Like the previous analysis, this regression showed that the second step, which included an increase in entertainment use contributed to the prediction of increased guilt and frustration among the mothers, above and beyond the first step that included the demographic predictors and the mothers’ attitudes towards screens and base-line levels of frustration and guilt, R2change = 0.057, Fchange(2,168) = 6.680, p < 0.005. Altogether, these findings suggest that a main factor that contributes to the prediction of mothers’ guilt and frustration regarding screen use is the actual increase in their children use of screens for entertainment. A further discussion of this study’s findings is provided below, after the presentation of the results of Study 2.

Study 2

The goal of Study 2 was to further our understanding of the increase in children’s use of screens for entertainment (which, as seen in Study 1 correlated with mothers’ guilt and frustration). In this study, we explored what could be contributing to this increase in entertainment use, besides the straightforward explanation that children were seeking recreational activities while schools were closed during the COVID-19 lockdown. Following previous studies on this topic, we extracted three clusters of potential predictors of children’s screen use: (1) the socio-demographic background of the mothers (Rideout et al., 2011), (2) their negative/positive attitudes towards children’s screen use (Cingel & Krcmar, 2013; Lauricella et al., 2015), and (3) their general approach to parenting (Bjelland et al., 2015; Livingstone et al., 2015; Valcke et al., 2010). Although this study was mostly explorative, we speculated that mothers who hold positive attitudes towards screens and/or have a permissive parenting style, would allow their children more screen time than mothers with different attitudes towards screens and/or a different parenting style.

Following studies that emphasized the characteristics of the child as a central predictor of actual screen use (Beyens et al., 2018), we also asked the mothers whether one (or more) of their children has Attention-Deficit/Hyperactivity Disorder (ADHD). We hypothesized that these children, who often feel “uncomfortable being still for extended time” and who are “often unable to play or engage in leisure activities quietly” (American Psychiatric Association, 2013), would be granted more screen time by their parents, during the COVID-19 lockdown.

Method

Participants and Procedure

The recruitment of participants for this study was conducted by research assistants from a large Israeli college. The recruitment process started about a week after the first study, a full month into the first COVID-19 lockdown. As in Study 1, the data-collection procedure was conducted online using Qualtrics. To minimize poor quality responses, we applied the same data quality protocol that was used in Study 1, including time measurements and an “honesty item”. The initial sample consisted of 308 mothers, of whom 25 (8.1%) failed the attention checks. The final sample included 283 mothers aged from 26 to 54 (M = 36.91, SD = 6.26), of whom 106 had children in the 1st to 3rd grades; 28 had children in the 4th to 6th grades, and 149 had children in both age groups. The demographic characteristics of the sample are described in Table 5.

Table 5.

Descriptive statistics (study two)

N Mean (SD) [Min/Max]
Age 258 36.97 (6.26) [26/54]
No. of children 261 4.51 (1.96) [1/13]
Education years 259 16.97 (1.99) [11/25]
At least one child with ADHD 55 (17.1%)
Religion status
 Not religious 23 (7.2%)
 Traditional 13 (4%)
 Orthodox 150 (46.7%)
 Ultra-orthodox 78 (24.3%)
 missing 57 (17.8%)
 Economic status 263 2.93 (0.60) [1/5]
Screen-time (in hours) before the COVID
 Entertainment use (1st to 3rd grade) 245 1.11 (1.01) [0/6]
 Entertainment use (4th to 6th grade) 164 1.48 (1.17) [0/6]
 Education use (1st to 3rd grade) 242 0.27 (0.41) [0/6]
 Education use (4th to 6th grade) 160 0.44 (0.64) [0/6]
Screen-time (in hours) during the COVID
 Entertainment use (1st to 3rd grade) 243 2.55 (1.60) [0/6]
 Entertainment use (4th to 6th grade) 161 3.00 (1.81) [0/6]
 Education use (1st to 3rd grade) 242 1.01 (0.94) [0/6]
 Education use (4th to 6th grade) 160 1.36 (1.15) [0/6]
 Attitudes towards screens
 Positive attitudes 283 2.68 (0.77) [1/5]
 Negative attitudes 283 4.10 (0.63) [1/5]
Parental competence
 Confidence 267 4.42 (0.72) [1/6]
 Efficacy 267 4.56 (0.55) [1/6]
Parental authority style
 Authoritarian 260 3.65 (0.74) [1/6]
 Authoritative 260 4.76 (0.49) [1/6]
 Permissive 260 2.82 (0.70) [1/6]
Open in a new tab

Mean scores, Standard Deviations, and Min-max scores are presented for continuous variables. Percentage of participants in each class is presented for categorical variables (i.e., nominal scales)

After signing a consent form, participants were asked to answer the same set of questions that were used in Study 1. Factor analysis of the screen attitudes questionnaire revealed the same pattern that was found in Study 1, explaining 65.21% of the questionnaire variance (Table 6). Based on this analysis, two average scores were calculated, one for negative attitudes and one for positive attitudes. In addition, this study included a single item regarding children with ADHD and two well-established questionnaires that addressed the mothers’ parenting authority style and sense of competence. What follows is a detailed description of the additional measurements of Study 2.

Table 6.

Factor loadings of screen-use attitudes questionnaire (study two)

Item Principal components
Negative attitudes Positive attitudes
Cognitive problems 0.686 0.150
Emotional and social problems 0.708 0.106
Screen-time limits are needed (1st to 3rd grades) 0.811 0.329
Screen-time limits are needed (4th to 6th grades) 0.766 0.310
Cognitive benefits −0.505 0.695
Emotional and social benefits −0.493 0.687
Open in a new tab

Note: The loading scores of the items that were classified to each factor are presented in bold

Children with ADHD

Mothers were presented with a single multiple-choice item in which they were asked whether one (or more) of their children has ADHD. In this item, mothers could choose one of the following responses: “I do not have children with ADHD”; “one/two/three/four or more of my children of elementary school age has received a diagnosis of ADHD”; “I have at least one child with a diagnosis of ADHD but not of elementary school age,” and “I have children with ADHD but none of them has been formally diagnosed by an authorized clinician”. For the purpose of this study, the scores of this item were recoded to form a binary (yes/no) variable. ADHD-positive (yes) was indicated when mothers reported of having at least one child with a formal diagnosis of ADHD and ADHD-negative (no) was indicated for all other cases.

Parenting Sense of Competence

Mothers were then asked to complete the Hebrew version (Goldstein-Farber, 1988) of the Parenting Sense of Competence Scale (PSOC; Gibaud-Wallston & Wandersman, 1978). The PSOC is a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree) that addresses two sub-factors of parenting competence: a sense of efficacy and a sense of confidence. The sense of efficacy is measured by eight items (e.g., “I honestly believe I have all the skills necessary to be a good parent to my child”), and the sense of confidence is measured by nine items (e.g., “Being a parent makes me tense and anxious”). The reliability of the Hebrew version of the PSOC is well-documented (e.g., Efrati & Gola, 2019; Waldman-Levi et al., 2015) and this study evidenced good internal consistency of the items in terms of both sub-factors (Cronbach’s α = 0.7 and 0.74, for efficacy and confidence, respectively).

Parental Authority Questionnaire

Finally, the mothers’ parenting style was rated using the Hebrew version (Sholet, 1997) of the Parental Authority Questionnaire (PAQ; Buri, 1991). This questionnaire, which is well-established in the scholarly literature (e.g., Efrati & Boniel-Nissim, 2021; Gong et al., 2015), consists of 30 items that are rated on a 5-point scale (1 = strongly disagree, 5 = strongly agree). The PAQ addresses three types of parenting style: permissive (e.g., “children need to be free to make up their own mind”), authoritarian (e.g., “children should be forced to conform to what the parent thinks is right”), and authoritative (e.g., “the parent discusses the reasoning behind rules”). The psychometric validity of the PAQ is well-documented in the literature (e.g., Buri, 1991; Yaffe, 2018), and the current study evidenced good internal consistency in all sub-factors (Cronbach’s α = 0.7, 0.74, and 0.614, for permissive, authoritarian, and authoritative, respectively).

Results

The descriptive statistics of this study’s variables are provided in Table 5. To examine the relative effect of each variable on entertainment screen use, two repeated measures ANCOVAs were conducted, one for children in the 1st to 3rd grades and one for children in the 4th to 6th grades. The categorical predictors in each analysis were the COVID-19 lockdown and ADHD. The COVID-19 lockdown was defined as a within-subjects binary predictor that includes two levels (before and during the lockdown). The ADHD variable was defined as a between-subjects binary predictor with two levels (with and without ADHD) as mentioned in the method section. The continuous predictors were the two types of attitudes towards screens (positive attitudes and negative attitudes); the two sub-factors of the Parenting Sense Of Competence Scale (PSOC-efficacy and PSOC-confidence); the three parenting styles according to the PAQ (PAQ-permissive, PAQ-authoritarian, and PAQ-authoritative), and the demographic variables of the study (age, religious affiliation, number of children, and economics status).

Entertainment use among children in the 1st to 3rd grades

Table 7 presents the results from the repeated measures ANCOVA for children in the 1st to 3rd grades. The following predictors were found to be significant in this analysis: the COVID-19 lockdown [the estimated means of screen time before and during the lockdown were 1.27 and 2.75, respectively, F(1,210) = 6.45, p < 0.05, partial η2 = 0.03]; ADHD [estimated means for mothers of children without and with ADHD were 1.68 and 2.34 respectively, F(1,210) = 12.41, p < 0.005, partial η2 = 0.06]; the mothers’ positive attitudes towards screens [F(1,210) = 13.86, p < 0.001, partial η2 = 0.06]; the mothers’ negative attitudes towards screens [F(1,210) = 6.91, p < 0.01, partial η2 = 0.03]; the PAQ-authoritarian sub-factor [F(1,210) = 4.84, p < 0.05, partial η2 = 0.02]; the age of the mother [F(1,210) = 10.32, p < 0.001, partial η2 = 0.047], and the number of children [F(1,210) = 5.06, p < 0.01, partial η2 = 0.024].

Table 7.

Repeated Measures ANCOVA for entertainment screen use among children in the 1st to 3rd grades

Source df MSE F p η2
Between subjects
 ADHD 1 26.650 12.413 0.001 0.056
 Religious 3 6.220 2.897 0.036 0.040
 Age 1 22.157 10.320 0.002 0.047
 No. of children 1 10.872 5.064 0.025 0.024
 Economic status 1 0.804 0.375 0.541 0.002
 PSOC–Confidence 1 6.649 3.097 0.080 0.015
 PSOC–Efficacy 1 1.145 0.533 0.466 0.003
 PAQ–Authoritarian 1 10.386 4.838 0.029 0.023
 PAQ–Permissive 1 0.003 0.002 0.968 0.000
 PAQ–Authoritative 1 2.600 1.211 0.272 0.006
 Positive attitudes 1 29.762 13.862 0.000 0.062
 Negative attitudes 1 14.833 6.909 0.009 0.032
 Error 210 2.147
Within subjects
 COVID -19 1 3.812 6.455 0.012 0.030
Interactions with COVID-19
 COVID * ADHD 1 0.313 0.530 0.467 0.003
 COVID * Religious 3 0.998 1.690 0.170 0.024
 COVID * Age 1 1.650 2.794 0.096 0.013
 COVID * No. of children 1 0.074 0.125 0.724 0.001
 COVID * Economic status 1 1.156 1.957 0.163 0.009
 COVID * PSOC Confidence 1 3.987 6.753 0.010 0.031
 COVID * PSOC Efficacy 1 0.189 0.320 0.572 0.002
 COVID * PAQ Authoritarian 1 0.787 1.332 0.250 0.006
 COVID * PAQ Permissiv 1 2.287 3.872 0.050 0.018
 COVID * PAQ Authoritativ 1 0.611 1.035 0.310 0.005
 COVID * Positive attitudes 1 1.310 2.219 0.138 0.010
 COVID * Negative attitudes 1 3.595 6.088 0.014 0.028
Error 210 0.591
Open in a new tab

In addition, the following interactions were found to be significant: the COVID-19 lockdown with negative attitudes towards screens [F(1,210) = 6.08, p < 0.05, partial η2 = 0.029] and the COVID-19 lockdown with the PSOC-confidence sub-factor [F(1,210) = 6.75, p < 0.05, partial η2 = 0.03]. To interpret these interactions, we calculated the correlations between each of these covariates and the change in screen time that occurred during the COVID-19 lockdown. The two covariates were negatively correlated with the change in screen-use duration (r = −0.185, and −0.138, for negative attitudes towards screens and PSOC-confidence respectively). These negative correlations suggest that the greater the score of one of these three continuous variables, the less pronounced the effect of the COVID-19 lockdown on the entertainment use of screens (see the discussion section for further interpretation of these interactions).

Entertainment use among children in 4th to 6th grades

Table 8 presents the results from the repeated-measures ANCOVA for children in the 4th to 6th grades. The following predictors were found to be significant in this analysis: the COVID-19 lockdown [estimated means before and during the lockdown were 1.59 and 3.26, respectively, F(1,136) = 4.37, p < 0.05, partial η2 = 0.03); the presence of ADHD [estimated means for mothers of children without and with ADHD were 2.17 and 2.68 respectively, F(1,136) = 4.38, p < 0.05, partial η2 = 0.03]; positive attitudes towards screens [F(1,136) = 8.57, p < 0.05, partial η2 = 0.059]; negative attitudes towards screens [F(1,136) = 5.33, p < 0.05, partial η2 = 0.038]; the PAQ-authoritarian sub-factor [F(1,136) = 4.19, p < 0.05, partial η2 = 0.03]; the age of the mother [F(1,136) = 5.19, p < 0.05, partial η2 = 0.037], and the number of her children [F(1,136) = 4.41, p < 0.05, partial η2 = 0.031].

Table 8.

Repeated Measures ANCOVA for entertainment screen use among children in the 4th to 6th grades

Source df MSE F p η2
Between subjects
 ADHD 1 13.321 4.378 0.038 0.031
 Religious 3 6.802 2.236 0.087 0.047
 Age 1 15.787 5.189 0.024 0.037
 No. of children 1 13.406 4.406 0.038 0.031
 Economic status 1 2.495 0.820 0.367 0.006
 PSOC–Confidence 1 0.372 0.122 0.727 0.001
 PSOC–Efficacy 1 6.995 2.299 0.132 0.017
 PAQ–Authoritarian 1 12.740 4.187 0.043 0.030
 PAQ–Permissive 1 0.278 0.091 0.763 0.001
 PAQ–Authoritative 1 0.526 0.173 0.678 0.001
 Positive attitudes 1 26.088 8.575 0.004 0.059
 Negative attitudes 1 16.224 5.333 0.022 0.038
 Error 136 3.043
Within subjects
 COVID -19 1 2.427 4.370 0.038 0.031
Interactions with COVID-19
 COVID * ADHD 1 1.901 3.423 0.066 0.025
 COVID * Religious 3 0.467 0.840 0.474 0.018
 COVID * Age 1 0.430 0.774 0.381 0.006
 COVID * No. of childre 1 0.049 0.089 0.766 0.001
 COVID * Economic status 1 0.132 0.237 0.627 0.002
 COVID * PSOC Confidence 1 0.010 0.018 0.895 0.000
 COVID * PSOC Efficacy 1 1.163 2.093 0.150 0.015
 COVID * PAQ Authoritarian 1 0.647 1.166 0.282 0.008
 COVID * PAQ Permissive 1 1.622 2.919 0.090 0.021
 COVID * PAQ Authoritative 1 0.041 0.074 0.786 0.001
 COVID * Positive attitudes 1 2.810 5.059 0.026 0.036
 COVID * Negative attitudes 1 4.900 8.821 0.004 0.061
Error 136 0.555
Open in a new tab

In this analysis, two continuous variables interacted with the COVID-19 lockdown variable: positive attitudes towards screens [F(1,136) = 5.05, p < 0.05, partial η2 = 0.036], and negative attitudes towards screens [F(1,136) = 8.82, p < 0.005, partial η2 = 0.06]. The positive attitudes scores were positively correlated with the increase in entertainment use of screens (r = 0.256), and the negative attitudes were negatively correlated with this increase (r = −0.202). These results suggest that the mothers’ relative attitudes towards screen use, either moderated, or augmented, the effect of the COVID-19 lockdown on children’s use of screens for entertainment.

Discussion

The two studies presented in this article aimed to investigate the increase in children’s screen use during the COVID-19 lockdown, from the point of view of mothers. Unsurprisingly, mothers in both studies reported a significant increase in their children’s screen use during the COVID-19 lockdown. During the lockdown, children used screen technologies for approximately twice the time they used them before the onset of the pandemic. According to the mothers, the highest increase (108%) was in the use of screens for entertainment among young children (the 1st to 3rd grades). This finding corroborates recent studies that were conducted on this topic (Götz et al., 2020; Schmidt et al., 2020).

Importantly, study one revealed that the reported increase in screen time was accompanied by an increase in guilt and frustration among the mothers. These disturbing parental feelings are understandable, and to be expected, considering the multiple studies (and their subsequent, often sensationalist, divulgation in the press) that found associations between screen use and adverse developmental outcomes (e.g., Elhai et al., 2017; Hutton et al., 2020; King et al., 2010; Madigan et al., 2020; Van Deursen et al., 2015). Indeed, in many cases, there is a gap between the alarming headlines in popular media and the actual scientific evidence regarding the developmental risk of screen use (Ophir, Lipshits-Braziler, et al., 2019; Ophir, Tikochinski, et al., 2019, 2020); however, there seems to be consensus among scholars that excessive and problematic use of screens is dangerous to children’s healthy psychological development. From this point of view, the parental fear from secondary negative outcomes of the COVID-19 lockdown (i.e., the increase in screen use), is highly reasonable (Nagata et al., 2020; Sultana et al., 2021).

Parental guilt and frustration, however, are not always a direct product of the child’s screen use. Study 1 showed that mothers make a clear distinction between the use of screens for educational purposes and for entertainment purposes. It seems that mothers believe that the risk to their children’s development does not lie in the duration of use per se, as implied, for example, in the WHO guidelines for sedentary behaviors (WHO, 2019), but in the specific type of use, that is, the use of screens for entertainment rather than for educational purposes. In other words, they are less worried about the physical health consequences of sedentary behavior (e.g., gaining weight, decreased physical activity) and more about its psychological consequences. Study 1 also showed that this factor of children’s use of screens for entertainment contributes to the prediction of the mothers’ guilt and frustration, above and beyond other significant factors, such as the mothers’ age, educational background, economic status, and even the mothers’ personal attitudes towards screen use.

A further exploration of this specific type of screen use conducted in Study 2 revealed that the COVID-19 lockdown was not the only factor that contributed to children’s entertainment use of screens. Other factors, such as the mothers’ characteristics (attitudes towards screens, parenting style, age, and number of children) and whether they had one or more children with a diagnosis of ADHD, played a role in the children’s entertainment use of screens. These findings corroborate with pre-COVID literature that singled out socio-demographic variables (Rideout et al., 2011) and ADHD diagnosis (Beyens et al., 2018) as potential predictors of children’s screen use. It is noted however, that despite this presumed link between ADHD characteristics and screen use (probably due to the inherent need of ADHD-type children for stimulating and exciting activities), the reported increase in screen use during the lockdown did not differ between mothers of children with and without this diagnosis.

Other factors that did interact with the COVID-19 factor concerned specific characteristics of the mothers. In the younger group of children (1st to 3rd grades), the effect of the COVID-19 lockdown on entertainment use of screens was moderated by two characteristics: the mothers’ negative attitudes towards screens and their perceived confidence in their parenting capabilities. These moderating effects may suggest that mothers who have strong beliefs that screen use can impair their children’s development and/or mothers that are confident in their parenting, managed (to a certain extent) to regulate their children’s excessive use of screens during the COVID-19 lockdown.

Somewhat different results were documented in the older group of children (those in the 4th to 6th grades). In this age group, both types of the mothers’ attitudes towards screens (positive and negative) interacted with the COVID-19 lockdown factor, suggesting that the increase in screen use during COVID-19 was dependent on the mothers’ attitudes. Children of mothers with positive attitudes towards screens demonstrated a large increase in screen use, whereas children of mothers with strong negative attitudes towards screens demonstrated a small increase in screen use, during COVID-19. These findings correspond with the existing pre-COVID studies that demonstrated significant links between parental attitudes and actual screen use of their children (Cingel & Krcmar, 2013; Lauricella et al., 2015).

This research has limitations. Firstly, all the results are based on self-report measures. For this reason, despite the strict data-quality protocol, they may not reflect the actual rise in screen use during the pandemic. Secondly, the measures were scored using common Likert scales while the statistical analyses related to the raw values of these measures as if they were real-world quantities (for more information, see in: Morris et al., 2017). Although this limitation characterizes considerable portions of modern psychological research, it is important to acknowledge it here as well, because of its potential implications for real-life practices. Thirdly, the research did not address fathers, and, more importantly, it did not address the children themselves. The focus on mothers only may have yielded a somewhat biased and incomplete picture of children’s screen use. Further studies are recommended to deepen our understanding of the factors associated with this major contemporary parenting challenge. It is our hope that the pandemic will be over soon but, in case additional lockdowns are enforced, and in case other crisis situations will require prolonged lockdowns, we encourage researchers to continue investigating children’s screen use, preferably through experimental designs, as well as more objective and more comprehensive methods, such as digital tracking, questionnaires for both parents, and designated scales for children.

In conclusion, the current research turned the spotlight on the increase in children’s screen use following the outbreak of the COVID-19, and more specifically, on the increase in entertainment use of screens (rather than educational), which seemed to have triggered negative motherly feelings of guilt and frustration. On the bright side, the research also marked potential protective factors, such as perceived parental confidence and attitudes towards screens, which can be utilized for designing practical guiding tools for parents. Previous research showed that psychoeducational programs for parents, which bring forth the risks of screen use may contribute to concrete reduction in children’s screen use as well as other unwanted socio-emotional consequences, such as aggressive behaviors (Yilmaz et al., 2015). Inspired by the findings of the current study, we recommend that such parenting programs will also address the potential educational benefits of screen use, and that they will emphasize the more general parental role of helping children construct longstanding, positive, and safe habits of screen use.

Aside from common restrictive mediation strategies (i.e., limiting screen time), parents are encouraged to (1) dedicate time for joint usage of screens with their children, (2) actively search for stimulating educational contents online, (3) make sure that healthy, non-screen-related activities, such as outdoor sports, sleep, and social relationships are not overridden by screens, and (4) adopt an instructive screen mediation strategy that maintains an open and continued discourse with the child regarding her/his screen habits (Modecki et al., 2022; Valkenburg et al., 1999). Such strategies may help parents better understand the psychological needs of their children, especially during times of crisis, when screen use may compensate over broken routines, uncertainties, and isolations.

Acknowledgments

Funding

The funding of both studies was provided by the Israeli education institution of MOFET.

Compliance with Ethical Standards

Conflict of Interest

The authors declare no competing interests.

Ethical Approval

The procedures of the current studies were approved by the institutional ethical review board (IRB) of Beit Berl College.

Informed Consent

Informed consent was obtained from all the participants of this research.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). American Psychiatric Pub.
  2. Beyens I, Valkenburg PM, Piotrowski JT. Screen media use and ADHD-related behaviors: Four decades of research. Proceedings of the National Academy of Sciences. 2018;115(40):9875–9881. doi: 10.1073/pnas.1611611114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bjelland M, Soenens B, Bere E, Kovács É, Lien N, Maes L, Te Velde SJ. Associations between parental rules, style of communication and children’s screen time. BMC Public Health. 2015;15(1):1–13. doi: 10.1186/s12889-015-2337-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Buri JR. Parental authority questionnaire. Journal of Personality Assessment. 1991;57(1):110–119. doi: 10.1207/s15327752jpa5701_13. [DOI] [PubMed] [Google Scholar]
  5. Carson V, Clark M, Berry T, Holt NL, Latimer-Cheung AE. A qualitative examination of the perceptions of parents on the Canadian Sedentary Behaviour Guidelines for the early years. International Journal of Behavioral Nutrition and Physical Activity. 2014;11(1):65. doi: 10.1186/1479-5868-11-65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cingel DP, Krcmar M. Predicting media use in very young children: The role of demographics and parent attitudes. Communication Studies. 2013;64(4):374–394. doi: 10.1080/10510974.2013.770408. [DOI] [Google Scholar]
  7. Van Deursen AJAM, Bolle CL, Hegner SM, Kommers PAM. Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Computers in human behavior. 2015;45:411–420. doi: 10.1016/j.chb.2014.12.039. [DOI] [Google Scholar]
  8. Efrati Y, Gola M. Adolescents’ compulsive sexual behavior: The role of parental competence, parents’ psychopathology, and quality of parent–child communication about sex. Journal of Behavioral Addictions. 2019;8(3):420–431. doi: 10.1556/2006.8.2019.33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Efrati Y, Boniel-Nissim M. Parents’ Psychopathology Promotes the Adoption of Ineffective Pornography-Related Parenting Mediation Strategies. Journal of Sex & Marital Therapy. 2021;47(2):117–129. doi: 10.1080/0092623X.2020.1835759. [DOI] [PubMed] [Google Scholar]
  10. Elhai JD, Dvorak RD, Levine JC, Hall BJ. Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders. 2017;207:251–259. doi: 10.1016/j.jad.2016.08.030. [DOI] [PubMed] [Google Scholar]
  11. Gibaud-Wallston, J., & Wandersman, L. P. (1978, August). Development and utility of the Parenting Sense of Competence scale. Paper presented at the meeting of the American Psychological Association Toronto, Canada.
  12. Goldstein-Farber, S. (1988). First interaction between the mother and her premature infant. Unpublished Doctoral Dissertation). Bar Ilan University, Ramat-Gan (Hebrew).
  13. Gong X, Fletcher KL, Bolin JH. Dimensions of perfectionism mediate the relationship between parenting styles and coping. Journal of Counseling & Development. 2015;93(3):259–268. doi: 10.1002/jcad.12024. [DOI] [Google Scholar]
  14. Götz M, Mendel C, Lemish D, Jennings N, Hains R, Abdul F, Blaya C. Children, COVID-19 and the media: A Study On The Challenges Children Are Facing In The 2020 Coronavirus. Crisis. Televizion. 2020;33(2020/E):4–9. [Google Scholar]
  15. Hutton JS, Dudley J, Horowitz-Kraus T, DeWitt T, Holland SK. Associations between screen-based media use and brain white matter integrity in preschool-aged children. JAMA Pediatrics. 2020;174(1):e193869–e193869. doi: 10.1001/jamapediatrics.2019.3869. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. King ALS, Valença AM, Nardi AE. Nomophobia: the mobile phone in panic disorder with agoraphobia: reducing phobias or worsening of dependence? Cognitive and Behavioral Neurology. 2010;23(1):52–54. doi: 10.1097/WNN.0b013e3181b7eabc. [DOI] [PubMed] [Google Scholar]
  17. Lauricella AR, Wartella E, Rideout VJ. Young children’s screen time: The complex role of parent and child factors. Journal of Applied Developmental Psychology. 2015;36:11–17. doi: 10.1016/j.appdev.2014.12.001. [DOI] [Google Scholar]
  18. Livingstone, S., Mascheroni, G., Dreier, M., Chaudron, S., & Lagae, K. (2015). How Parents of Young Children Manage Digital Devices at Home: The Role of Income, Education and Parental Style. London: EU Kids Online, LSE.
  19. Madigan, S., McArthur, B. A., Anhorn, C., Eirich, R., & Christakis, D. A. (2020). Associations Between Screen Use and Child Language Skills: A Systematic Review and Meta-analysis. JAMA Pediatrics. 10.1001/jamapediatrics.2020.0327. [DOI] [PMC free article] [PubMed]
  20. Ministry, & of Education. (2018). Students and Computers: Data from the Pisa Study (in Hebrew). In: Israel Ministry of Education. Last retrieved on March 8, 2021, from https://meyda.education.gov.il/files/Rama/ICT_PISA_2015_Report.pdf.
  21. Modecki, K. L., Goldberg, R. E., Wisniewski, P., & Orben, A. (2022). What is digital parenting? A systematic review of past measurement and blueprint for the future. Perspectives on Psychological Science, 17456916211072458. 10.1177/17456916211072458. [DOI] [PMC free article] [PubMed]
  22. Morris SD, Grice JW, Cox RA. Scale imposition as quantitative alchemy: Studies on the transitivity of neuroticism ratings. Basic and Applied Social Psychology. 2017;39(1):1–18. doi: 10.1080/01973533.2016.1256288. [DOI] [Google Scholar]
  23. Nagata JM, Abdel Magid HS, Pettee Gabriel K. Screen time for children and adolescents during the coronavirus disease 2019 pandemic. Obesity. 2020;28(9):1582–1583. doi: 10.1002/oby.22917. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. National Council for the Child. (2020). The statistical yearbook “Children in Israel” (in Hebrew) In: National Council for the Child. Last retrieved on March 19, 2021, from https://www.children.org.il/%D7%94%D7%A9%D7%A0%D7%AA%D7%95%D7%9F-%D7%94%D7%A1%D7%98%D7%98%D7%99%D7%A1%D7%98%D7%99-%D7%99%D7%9C%D7%93%D7%99%D7%9D-%D7%91%D7%99%D7%A9%D7%A8%D7%90%D7%9C/.
  25. Ophir Y, Tikochinski R, Rosenberg H. Challenging the Association Between Screen Time and Cognitive Development. JAMA Pediatrics. 2019;173(9):890–890. doi: 10.1001/jamapediatrics.2019.2246. [DOI] [PubMed] [Google Scholar]
  26. Ophir Y, Tikochinski R, Rosenberg H. Science Has Not Proven That Screen Use Impacts Children’s Brain Development. JAMA Pediatrics. 2020;174(8):805–805. doi: 10.1001/jamapediatrics.2020.0635. [DOI] [PubMed] [Google Scholar]
  27. Ophir Y, Sisso I, Asterhan CSC, Tikochinski R, Reichart R. The turker blues: Hidden factors behind increased depression rates among Amazon’s Mechanical Turkers. Clinical Psychological Science. 2020;8(1):65–83. doi: 10.1177/2167702619865973. [DOI] [Google Scholar]
  28. Ophir, Y., Lipshits-Braziler, Y., & Rosenberg, H. (2019). New-Media Screen Time is Not (Necessarily) Linked to Depression: Comments on Twenge, Joiner, Rogers, and Martin (2018). Clinical Psychological Science, 2167702619849412.10.1177/2167702619849412.
  29. Ophir, Y., Rosenberg, H., Lipshits-Braziler, Y., & Amichai-Hamburger, Y. (2020). “Digital adolescence”: The effects of smartphones and social networking technologies on adolescents’ well-being. In Online Peer Engagement in Adolescence (pp. 122–139). Routledge.
  30. Pew Research Center. (2019). Smartphone ownership is growing rapidly around the world, but not always equally. In: Pew Research Center Internet & Technology. Last retrieved on March 19, 2021, from https://www.pewresearch.org/global/2019/02/05/smartphone-ownership-is-growing-rapidly-around-the-world-but-not-always-equally/.
  31. Rideout, V., Lauricella, A., & Wartella, E. (2011). Children, media, and race: Media use among White, Black, Hispanic, and Asian American children. Evanston, IL: Center on Media and Human Development, School of Communication, Northwestern University.
  32. Schmidt SCE, Anedda B, Burchartz A, Eichsteller A, Kolb S, Nigg C, Woll A. Physical activity and screen time of children and adolescents before and during the COVID-19 lockdown in Germany: a natural experiment. Scientific Reports. 2020;10(1):1–12. doi: 10.1038/s41598-020-78438-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Sholet, M. (1997). The relationship between parenting styles and the child's initial adaptation to a military framework. master’s thesis. Haifa (IS): University of Haifa.
  34. Skvarc DR, Penny A, Harries T, Wilson C, Joshua N, Byrne LK. Type of screen time and academic achievement in children from Australia and New Zealand: interactions with socioeconomic status. Journal of Children and Media. 2021;15(4):509–525. doi: 10.1080/17482798.2021.1878045. [DOI] [Google Scholar]
  35. Sultana A, Tasnim S, Hossain MM, Bhattacharya S, Purohit N. Digital screen time during the COVID-19 pandemic: a public health concern. F1000Research. 2021;10(81):81. doi: 10.12688/f1000research.50880.1. [DOI] [Google Scholar]
  36. Trinh M-H, Sundaram R, Robinson SL, Lin T-C, Bell EM, Ghassabian A, Yeung EH. Association of trajectory and covariates of children’s screen media time. JAMA Pediatrics. 2020;174(1):71–78. doi: 10.1001/jamapediatrics.2019.4488. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Valcke M, Bonte S, De Wever B, Rots I. Internet parenting styles and the impact on Internet use of primary school children. Computers & Education. 2010;55(2):454–464. doi: 10.1016/j.compedu.2010.02.009. [DOI] [Google Scholar]
  38. Valkenburg PM, Krcmar M, Peeters AL, Marseille NM. Developing a scale to assess three styles of television mediation: “Instructive mediation”, “restrictive mediation,” and “social coviewing”. Journal of Broadcasting & Electronic Media. 1999;43(1):52–66. doi: 10.1080/08838159909364474. [DOI] [Google Scholar]
  39. Waldman-Levi A, Finzi-Dottan R, Weintraub N. Attachment security and parental perception of competency among abused women in the shadow of PTSD and childhood exposure to domestic violence. Journal of Child and Family Studies. 2015;24(1):57–65. doi: 10.1007/s10826-013-9813-3. [DOI] [Google Scholar]
  40. WHO. (2019). Guidelines on physical activity, sedentary behaviour and sleep for children under 5 years of age. World Health Organization. https://apps.who.int/iris/rest/bitstreams/1213838/retrieve. [PubMed]
  41. Yaffe Y. Convergent validity and reliability of the Hebrew version of the Parenting Styles and Dimensions Questionnaire (PSDQ) in Hebrew-speaking Israeli-Arab families. Interpersona: An International Journal on Personal Relationships. 2018;12(2):133–144. doi: 10.5964/ijpr.v12i2.303. [DOI] [Google Scholar]
  42. Yilmaz G, Demirli Caylan N, Karacan CD. An intervention to preschool children for reducing screen time: a randomized controlled trial. Child: Care, Health and Development. 2015;41(3):443–449. doi: 10.1111/cch.12133. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Child and Family Studies are provided here courtesy of Nature Publishing Group

RESOURCES