DOI: https://doi.org/10.21203/rs.3.rs-1784639/v1
Several studies indicated that the COVID-19 pandemic and the containment measures it required (including social distancing, quarantine and school closure) had a significant impact on children’s mental health. The present study aimed to examine executive function difficulties at behavioural level in school children during the COVID-19 lockdown, and to analyze potential associations with home literacy environment, current reading and screen times. Data were collected from mothers of 210 children (9–12 years old) through an online survey. Significant increases in children screen times were observed, while most of them did not read for pleasure on a daily basis. Parents’ literacy beliefs and children’s current leisure reading times were negative predictors of executive function difficulties, which increased with videogame and internet exposure. Nevertheless, perceived changes on screen or reading times with respect to pre-pandemic levels were not associated with executive function scores. The results might indicate: 1) opposite effects of literacy and screen times over children’s executive functioning; 2) a preference for reading or screen recreational use according to their executive function profiles; or 3) a combination of both. Our findings highlight the relation of reading and screen times with children’s cognitive development, and the importance of following their trajectory during post-pandemic times.
The term “executive functions'' (hereinafter, “EF”) refers to a set of cognitive processes involved in planning, executing, monitoring and adapting goal-directed behaviors (Miyake & Friedman, 2012). It includes the skills to: manipulate and update contents within working memory, suppress irrelevant information and/or contextually inadequate responses and shift between behaviors, strategies and cognitive processes to flexibly adapt behavior to situational demands (Lezak et al., 2012). Children’s EF can be assessed through cognitive performance-based instruments (such as neuropsychological tests) or behavioral rating scales (either self or heteroreport formats, according to the child’s age) (most notably, BRIEF; Gioia, et al., 2000). It has been argued that these measures capture different types of information, with the former representing performance efficiency in optimal settings and the latter indicating the frequency of goal achievement in typical settings (Toplak et al., 2013). Behavioral scales reflect expected EF patterns in clinical populations, correlate with physiological markers, and predict behavior (Isquith et al., 2013). In addition, both cognitive performance (see Pascual et al., 2019 for a meta-analysis) and behavioral scale (Thorell et al, 2012) measures of EF predict children’s academic achievement (see Gerst et al., 2017 for a study combining both assessments), as well as their emotional regulation skills (Li et al., 2020; Rhoades et al., 2009). Therefore, EF constitutes a relevant construct to examine when considering the potential impact of the COVID-19 pandemic, and the consequent changes in schooling and daily activities that took place during its first two years, on children.
In their efforts to reduce COVID-19 spread, several governments implemented containment measures that included social distancing, school closures and quarantine at home (Loades et al., 2020). Confinement alters routine dramatically, leading to social and physical isolation, loneliness, frustration, and boredom; thus posing a challenge to coping and self-regulation skills (Rodríguez-Rey, 2020; Urbina-García, 2020). In Argentina, school closure was effective from march throughout the whole 2020, while recreational, social and cultural outdoor activities for children were also restricted or completely suspended. During this period, several studies examined different aspects of the children’s behavior, mental health, cognitive and emotional functioning; as well as the changes on their daily routines and their potential impact on them. We briefly review this evidence in the following sections.
Children executive functioning during the COVID-19 pandemic
While many studies addressed children’s mental health during the pandemic (Andrés et al., 2022; see Bussieres et al. 2021, Loades et al., 2020; Theberath et al., 2022 for reviews), only a few focused on EF. These studies showed a considerable incidence of EF deficits on children’s behavioral functioning (Hanno et al., 2022; Lavigne-Cerván et al., 2021a,b; Polizzi et al., 2021; Shuai et al, 2021). Some of them found worse EF ratings associated with remote schooling (Hanno et al., 2022), or confinement (Lavigne-Cerván et al., 2021a). Children’s anxiety (Lavigne-Cerván et al., 2021b) and parental distress (Polizzi et al., 2021) were additional predictors of EF issues. Only one study conducted in pre-school children did not find significant differences with pre-pandemic EF levels (Abufhele et al., 2021), but it did observe worse outcomes in language, socioemotional behavior and general development measures. In Argentina, children’s EF in the pandemic has not been addressed specifically, but several psychopathology indicators were found to have increased significantly during this period (Andrés et al., 2022). Considering these findings, it would be relevant to examine the incidence of difficulties on different EF domains among Argentinean children. Moreover, it is of interest to analyze the potential link between these difficulties and the children’s daily habits during the pandemic, particularly, their reading frequency and exposure to screen media.
Children leisure reading during the COVID-19 pandemic
Several studies indicated changes in adults (Salmerón et al., 2020), adolescents and childrens’ reading habits (Clark & Picton, 2020, 2021). Parent-child shared reading (Wheeler & Hill, 2021) and screen-based reading became more frequent (Read et al., 2021). Children’s reading frequency and enjoyment also increased throughout the pandemic (Clark & Picton, 2020, 2021), motivated by relaxation and emotional regulation. Considering reading is a cognitively demanding activity that involves vocabulary, metacognitive processes and EF (Butterfuss & Kendeou, 2018; Follmer, 2018), and that leisure reading has been associated with the executive control brain network connectivity in children (Horowitz-Kraus & Hutton, 2018), it would be expected to find associations between reading times and EF during the pandemic. In the same line, another reading-related variable of interest is the Home Literacy Environment (hereinafter, “EF”). HLE can be defined as a set of“experiences, attitudes and materials pertaining to literacy that a child encounters and interacts with at home” (Roberts et al., 2005). It has been shown that HLE can promote children's cognitive development in general (for a review, see: Head-Zauche et al., 2016), and two recent studies suggest that it might be associated with EF skills in preschool children and toddlers (Altun, 2022; Korucu et al., 2020). Therefore, it might be possible to find additional contributions of HLE to childrens’ EF during the pandemic besides the potential links with leisure reading.
Children screen times during the pandemic
Since the pandemic drastically reduced the possibility for outdoor activities throughout the globe, it is unsurprising that screen media exposure had increased dramatically among 3-17 year olds in (for a review, see Bergmann et al., 2022) and toddlers (Bergmann et al., 2022). In the United States, both total screen media exposure and problematic media use (defined as a dependence that interferes with a child's usual functioning) increased among 2-11 year-olds, compared to pre-pandemic levels (Eales et al., 2021). These findings are preoccupying, considering the American Academy of Pediatrics warning of keeping screen times under two hours a day for children and adolescents (Council of Communications and Media - APA, 2021), and the considerable body of literature indicating detrimental effects of screen times over children’s language (for a recent meta-analysis, see Madigan et al., 2020), cognitive development (Hu et al., 2020) and academic achievement (for a recent meta-analysis, see Adelantado-Renau et al., 2019). Problematic media device use (smartphones, tablets) has been associated with worse behavioral EF outcomes on healthy children (Oh et al., 2021) and ADHD-diagnosed children during the pandemic (Shuai et al., 2021), but the evidence regarding screen media effects on cognitive development is mixed (Taylor et al., 2018; see Fietzer & Chin, 2017 for a review). Therefore, more data are needed to figure out the potential detrimental effect of different types of screen media on children’s EF during the pandemic.
Present study
While there’s plenty of evidence about the changes on children’s screen and reading times during the pandemic, few studies have specifically addressed their potential association with EF difficulties in this period. In addition, no pandemic study considered the potential contribution of HLE to executive functioning. In order to fill this gap in the literature, the present work had the following objectives: 1) to examine the incidence of EF difficulties among Argentinean school-aged children during the COVID-19 lockdown, 2) to examine children’s reading (both leisure and study-related) and screen times during the pandemic, a 3) to analyze the potential associations of EF difficulties with HLE, reading and screen times. Due to lockdown logistic restrictions, data were collected through online surveys. A locally designed and validated behavioral questionnaire was used to assess children’s EF functions through parents’ reports (“Cuestionario de Funciones Ejecutivas”, CuFE - “Executive Functions Questionnaire”; Canet-Juric et al., 2021). Current leisure and study reading times, and TV, internet and video game use frequencies were considered, as well as their perceived changes compared with pre-pandemic times. Moreover, we included specific HLE indicators: number of books at home, parents’ attitudes towards reading and shared reading frequency during pre-school. These measures were based on previous international (D’Apice & von Stumm, 2019) and local (Tabullo & Gago, 2021) studies. We expected to find EF difficulties to decrease with HLE and reading times and to increase with screen exposure.
A cross-sectional correlational study was carried out. Our study sample consisted of 210 Argentinean mothers of 9–12 year-old children (108 of them girls, M = 10.5, SD = 0.903 years), who volunteered to participate on our online survey after being contacted through the children’s schools. All their children attended private management schools and were under the remote online teaching modality at the time of data collection. The children were either 4th (n = 47), 5th (n = 77) or 6th (n = 86) graders. No developmental or learning disorders were reported by the mothers, neither were the children under psychological or psychiatric treatment at the time of the survey. Regarding the mothers, 77% of them had either complete or incomplete university level studies (see Table 1.).
Sociodemographic measures. Close ended questions were used to explore children’s gender and age, and parents’ and caregivers’ educational level, which was classified according to a scale based on the Argentinian education system (Pascual et al., 1993). We chose mother education level as a proxy indicator for SES, considering that it seems to be the SES aspect that is more strongly related to children’s language outcomes (Hoff et al, 2003, 2006).
HLE measures. Based on previous works (D’Apice & von Stumm, 2019; Tabullo & Gago, 2021), we selected the following variables as indicators of Home Literacy Environment: number of books at home and estimated frequency of shared reading with the child before primary school, and attitude towards literacy. Home library size and shared reading frequency were assessed through 5-item multiple choice questions (“how many books are there in your home approximately?”: less than 10; 10–50; 51–100; more than 100; “How often did you read to your child before primary school, approximately?: less than once a week, once a week, 2–3, 4–5, more than 5 times a week”). Literacy beliefs was measured through 6 items of the Parent Belief Reading scale (PRBI; DeBaryshe & Binder, 1994) selected from the aforementioned studies (Cronbach’s α = .825) (see Appendix 1). This scale measures positive affect associated with reading, parents’ intentions to elicit children’s active verbal participation when reading, whether children acquire moral orientation and world knowledge from books and parents’ practical capacity to participate in reading (DeBaryshe,1995).
Reading and screen times. Our participants reported their children’s weekly leisure (defined as reading for non-study purposes) and study reading times, as well as their frequency of TV, internet (for non-study purposes) and video-games use (regardless the device). Responses were made on a 1–7 likert scale (1. does not do it; 2. a couple days a week; 3. less than 1 hour a day; 4. 1–2 hours a day; 5. 2–3 hours a day; 6. 3–4 hours a day; 7. more than 4 hours a day). In addition, they were asked what format their children preferred for leisure and study reading, and the perceived changes in their reading and screen media times with respect to pre-pandemic levels, answering in a 1–5 likert scale (1. much less than before − 5. much more than before) .
EF Questionnaire. The Executive Functions Questionnaire (EFQ, Canet-Juric et al., 2021) was applied to examine behavioral manifestations of children’s EF difficulties. EFQ is a 33-item heteroreport questionnaire (see Appendix 1 for item examples) with 1–5 likert format response and a three factor structure: 1) Working memory (α = .91): examines difficulties for online processing, maintaining and manipulation of information, 2) Inhibition (α = .81): assesses the difficulty to regulate and suppress responses and/or specific behaviors, 3) Flexibility and emotional control (α = .81): assesses difficulties to flexibly adapt behavior to environmental changes and to regulate emotional responses. The instrument has been designed and validated in a local school-aged children population, has shown adequate psychometric properties and significantly predicts children’s reading comprehension, math and language academic achievement.
Data collection took place between October and November of 2020. The instruments were administered through an online Google forms survey that was distributed to children’s parents through local schools. All parents received a document informing them that their participation would be voluntary, anonymous and that they could withdraw from the experiment at any time, without any negative consequences. Contact information of the research group was also provided in order to clarify doubts that may arise in relation to the care of rights in research contexts. Those who chose to take part followed the survey’s link and expressed their consent with a click before moving on the questionnaires. A follow up EF assessment was conducted one year later, but only 22 mothers responded.
This study was performed in accordance with the ethical principles for research with human subjects recommended by the Declaration of Helsinki (World Medical Association, 2013), as well as the ethical guidelines for research with human participants of the American Psychological Association (2010). In addition, this research was conducted following the ethical regulation 5344/99 by the National Scientific and Technical Research Council of Argentina (CONICET) and was approved and supervised by CONICET’s committee.
Statistical analysis were carried out in SPSS v25 and JAMOVI software. EF difficulties were analyzed considering mean scores for each factor and qualitative interpretation (very good, good, bad, very bad) according to normative data (Canet-Juric et al., 2021). Gender and school grade effects were analyzed by a MANOVA, and a repeated measures ANOVA was conducted on the follow up data. Qualitative EF data were analyzed by chi-square tests. Associations between EF and HLE, reading and screen time measures were examined by Pearson correlation coefficients.
In order to identify significant predictors of each EF domain scores, separate hierarchical linear regression models were carried out. The first step of the models included sociodemographics (grade, gender, mother education), HLE (literacy beliefs), reading and screen time measures. Literacy beliefs was selected among HLE variables to avoid collinearity issues. The second step included current reading and screen time interactions with grade. Casewise diagnostics were applied to deal with outliers (standardized residuals above 3 or below − 3) (Cousineau and Cartier, 2010). Since no outliers were detected, no data was removed from the analysis. Assumptions of normality, homoscedasticity and linearity were verified by inspection of: normal quantile plots of residuals, standardized residuals scatter plots and observed versus predicted values, respectively. Independence of error assumption was met for all models (1.95 < Durbin-Watson < 2.1). Variance inflation factors indicated that multicollinearity was not a concern in any of the models (1.07 < VIFs < 3.34). Adjusted R squared values and standardized coefficients (with their corresponding confidence intervals are reported).
Descriptive statistics of HLE, reading and screen times and EF difficulties
A complete summary of descriptive statistics can be found in Table 1. See supplementary materials (Tables 1 and 2) for a detailed description of children’s reading and screen times.
EF difficulties
Mean scores of EF difficulties can be found on Table X. According to the MANOVA, only the effect of sex was significant (Wilk’s λ = 0.936, F(3,189) = 4.277, p = 0.006, µ2p = 0,064). Girls exhibited lower EF difficulties in working memory and inhibition (F’s > 0.035, p’s < 0.003, µ2p < 0,047.
According to EFQ norms, better functioning scores (good and very good) were more frequent in the inhibition domain (74.8%), while approximately half the children exhibited worse (regular and bad) cognitive flexibility (49.5%) and working memory (42,8%). Significant differences were observed in working memory between grades (χ2 = 7.601, p = 0.022): good functioning scores were more frequent among sixth graders (65.1%), while worse functioning was more frequent in fourth graders (59.6%). Finally, a follow-up assessment conducted on a sub-sample (n = 22) one year later did not find significant changes on any EF function, in any of the grades (F’s < 1.403, p’s > 0.270).
Associations between EF difficulties, HLE, reading and screen times
Significant associations were found between EF scores, HLE, screen exposure and reading habits (see Supplementary Table 3). Cognitive flexibility difficulties decreased with parent reading attitudes and leisure reading times, while working memory issues decreased with age, reading attitudes, shared reading before school, and study as well as leisure reading times (-.141 < r < -.285, p’s < .05). In addition, HLE variables (literacy beliefs, number of books at home, shared reading) covaried significantly with each other (r’s > .418, p’s < .001). Regarding the children’s screen use and reading habits, both leisure and study reading times (r = .171, p < .05) and internet and video game (but no TV) times (r = .265, p < .05) were significantly associated. On the other hand, both video game and internet use were inversely associated with leisure (but not study) reading times (r’s < -.167, p’s < .05). More positive parent reading attitudes were associated with more frequent children leisure reading (r = .308, p < .001), and less frequent video game and internet use (r’s < –.149, p’s < .05). Finally, perceived increases in childrens’ reading times and screen use during the pandemic were inversely correlated (r = -.265, p < .001).
HLE, reading and screen times predictors of EF difficulties
We examined HLE, reading and screen times predictors of EF difficulties scores by a series of hierarchical linear regression models, fit for each EF subscale (see methods: data analysis section). Table 2 provides a complete list of regression coefficients for each model.
EF-I scores. The complete model accounted for 10.8% of the variance (F(21,175 = 2.13, p = .004). The inclusion of grade interactions significantly increased the explained variance (∆R2 = .093, p =.032). Inhibition difficulties increased with mother education (𝛽 = .208) but decreased with leisure reading (𝛽 = -.387) (p’s < .049). Omnibus ANOVA tests indicated significant interactions between video game times and grade (F(2,174) = 4.980, p = .008). Video game times were more positively associated with EF-I scores in fourth than in fifth graders (𝛽 = -.637, p = .004).
EF-F scores. The initial accounted for 5.13% of the variance (F(11,183 = 1.95, p = .035), while the inclusion of grade interactions failed to increase explained variance (∆R2 = .082, p =.072). Video game times were the only significant predictor of CF difficulties (𝛽 = .360, p = .047).
EF-WM scores. The full model accounted for a total of 17.1% of the variance (F(11,183 = 3.68, p < .001). The inclusion of grade interactions significantly increased fit (∆R2 = .079, p = .049). Working memory difficulties increased with Mother education (𝛽 =.152) but decreased with literacy beliefs (𝛽 = -.216) and children leisure reading times (𝛽 = -.413) (p’s < .03). Omnibus ANOVA tests indicated significant interactions between video game (F(2,174) = 3.8, p = .024), internet (F(2,174) = 3.608, p = .029), study reading times (F(2,174) = 3.304, p = .039) and grade. Video game times were more positively associated with EF-WM scores in fourth than in fifth graders (𝛽 = -.534), while internet times were better predictors of EF-WM in fifth compared to fourth graders (𝛽 = .607) (p’s = .013). Study reading times, on the other hand, were stronger negative predictors of EF-WM in fifth and sixth (when compared to fourth) graders (𝛽’s < -.413, p’s < .041).
Effects of change in reading and screen times. An additional model including changes in reading times and changes in screen times factor did not contribute to improving fit in any of the EF scores analyses (∆R2 < .0198, p’s > .123).
This study has been the first to examine school-aged childrens’ EF functioning during the COVID-19 lockdown in Argentina, and its potential association with HLE, reading and screen times. Around half our sample exhibited more frequent FE issues in cognitive flexibility and emotional control (49.5%) and working memory domains (42.8%). More prominent increases were observed for screen times, which were also inversely related to reading. While HLE and reading times were associated with lower EF difficulties, worse ratings were observed for specific domains and grades in relation to video games and internet times. These findings are discussed in detail in the following paragraphs.
Children’s EF difficulties during COVID-19 lockdown
We found more frequent cognitive flexibility and working memory issues among our sample, while better scores for inhibition were observed. In addition, the incidence of EF issues was greater in the lower grades. Our results are consistent with several pandemic studies indicating an increase in perceived behavioral indicators of EF deficits in children. In a sample of Spanish children, around 40% exhibited more frequent problems in cognitive flexibility and emotional regulation EF domains (Lavigne-Cerván et al., 2021a), that were best explained by their state anxiety scores. In addition, different studies showed that the incidence of EF difficulties was significantly associated with the school learning format during the pandemic, with the worse outcomes observed for remote vs in-person schooling (Lavigne-Cerván et al., 2021b; Hanno et al., 2022). Another line of evidence showed that parental distress was an additional predictor of childrens’ behavioral EF outcomes (Polizzi et al., 2021). All these results are congruent with a previous study that showed increased psychopathology indicators (anxiety, depression, impulsivity, inattention, aggression) and lesser positive affect on a large sample of Argentinean children and adolescents (Andrés et al, 2021), that was more prominent within the 9-11 age range and in those children under total confinement (as opposed to those under social distancing conditions). This study also showed a link between parents and childrens’ mental health. Overall, these results coincide in indicating that the pandemic and confinement-related distress has taken a toll on the children’s self-regulating capabilities, a process that could be buffered or intensified by their parents’ psychological well being and their home’s emotional climate. It is worth noting that this study was conducted on a sample of mostly high socioeconomic level homes (most parents had completed university education), therefore it is quite possible that EF problems in children had been worse in those homes more vulnerable to social and environmental stressors during the pandemic. On the other hand, cognitive flexibility and working memory issues tended to increase with mother education within our sample. This rather counterintuitive finding might be indicating that more highly educated mothers were more aware of and/or exigent with their children’s behavior, leading to worse perceived behavior ratings. Finally, we should point out that our follow-up assessment one year later did not show evidence of changes in EF ratings with respect to the lockdown period, suggesting that cognitive flexibility and working memory issues may have endured (although the extremely low sample size limits the significance of this particular finding).
Children reading and screen times during COVID-19 lockdown
Most of the parents perceived large increases on their children’s leisure screen times, while only one third of the sample reported the same for leisure reading. Similarly to a previous large scale study in the UK (Clark & Picton, 2020, 2021), we observed higher reading frequencies in approximately one-third of our sample. These studies pointed out that coping and emotional regulation were two of the more frequent reasons for reading among children. Nevertheless, we also found a perceived decrease in the reading frequency of one-third of our sample, and almost 17% of them did not read for pleasure at all. This might be in part due to the increase on screen times, since they were both inversely correlated. This large increment (reported by around 60% of the parents) is consistent with the higher screen times observed during the pandemic among school-aged children in several countries, particularly during lockdown measures (Eales et al., 2021; Werling et al., 2021; see Bergmann et al., 2022 for a review). One of these studies (Eales et al., 2021) found that problematic media use increased particularly for school-aged children, associated with factors such as: family stress, schools-closure and the limitations of lockdown measures as well as parental behaviors and attitudes towards screen media. While we did not assess problematic use specifically, this interpretation can be extended to our sample, since 1) children in Argentina endured a prolonged lockdown without possibility of outdoor activities, favoring more sedentary forms of entertainment 2) exhibited increased distress indicators (Andrés et al., 2022), which may have prompted turning to screen devices as a coping mechanism.
Associations between EF difficulties, HLE and reading times
Our exploratory correlation analysis showed that several HLE variables (literacy beliefs, preschool shared reading) and leisure reading times were negatively associated with cognitive flexibility and working memory issues. Moreover, regression analyses indicated that more frequent leisure reading times were seen in children with fewer inhibition and working memory issues. The latter also decreased with better parents’ reading attitudes and longer reading study times in the higher grades. Two non-mutually exclusive interpretations can be put forward to explain this pattern: 1) reading-stimulating home environments and current reading practices promote EF development, acting as a protective factor against behavioral EF issues and possibly buffering the impact of the pandemic and lockdown-related stress, 2) those children with more working memory and inhibitory control difficulties will be less prone to cognitively demanding activities such as leisure reading, favoring more passive or quickly rewarding forms of entertainment, like screen media. While we cannot infer causality due to the correlational nature of our data, several lines of evidence indicate a positive impact of HLE and reading practices on children’s cognitive development in general (D’Apice & von Stumm, 2019; for a review, see: Head-Zauche et al., 2016) and EF in particular. Two recent studies found a significant association between HLE and EF skills in preschool children and toddlers (Altun, 2022; Korucu et al., 2020). It has been proposed that HLE may provide a context for parents to encourage their child to listen, pay attention, actively manipulate information and practice self-control – all EF-related skills – during structured, language and literacy-related learning activities (Korucu et al., 2020). In particular, during storybook reading, parents may prompt their children to remember details or actively predict possible outcomes for the narrative and characters (Bernier et al., 2010), thus scaffolding the children’s meaning-creation processes. Furthermore, reading comprehension actively engages EF processes such as cognitive flexibility, inhibition and working memory (Nouwens et al, 2021; see Follmer 2018 for a meta-analysis and Butterfuss and Kendeou, 2018 for a review). It is thus expected that better EF functioning scores are associated with more frequent reading times. Quite in fact, a study conducted on Argentinean children applying the same behavioral questionnaire showed that working memory issues were negatively associated with narrative and expository text comprehension (Canet-Juric et al., 2021). Lastly, a neuroimaging study (Kraus & Hutton, 2017) found that more frequent leisure reading was associated with a stronger connectivity between visual and cognitive control regions in school-aged children, a result that was interpreted as an indicator of EF engagement during reading. Summing it up, our results could be interpreted as evidence of a positive impact of HLE and reading practices on EF, which might act as a buffer for the lockdown impact on EF functioning at a behavioral level. It should be noted that we did not observe significant effects of the perceived changes in reading times (compared with pre-pandemic times) on EF issues, which might be indicating a more stable long-term effect of HLE and reading practices on executive functioning.
Associations between EF difficulties and screen times
Longer video game times were associated with more behavioral issues in all EF dimensions, while working memory issues increased with internet use (social networks, media streaming, web surfing) for fifth graders. As was the case with reading-related variables, two compatible explanations can be put forward. Screen media use might have contributed to behavioral EF problems by favoring more passive or instantly gratifying mental activities, while competing with more focused and cognitively demanding activities (such as reading, as we did observe in our sample). Conversely, children exhibiting more distractibility, impulsivity, or self-regulation problems might have been more attracted to screen media. However, unlike the literacy environment and practices, screen media is a much more heterogeneous construct, and the evidence of its impact on cognitive development is more diverse, mixed and even contradictory.
A previous longitudinal study found that both TV and video game times were independent predictors of current and future attention problems during middle childhood (6-12 years old) (Swing et al., 2010). A subsequent study further suggested bidirectional causality between video game times, attention and impulsiveness in children (Gentile et al., 2012). The authors proposed that video games might be deleterious for children’s sustained attention and self-regulation skills, since they provide frequent reinforcement, shifting attentional focuses and salient stimuli. In addition, video games (as well as other screen media) might displace other stimulating activities (reading, physical exercise, homework and study) that might be more demanding in terms of EF engagement (focus, frustration tolerance, delaying gratification, sustaining goal-directed behaviors, emotion regulation). In line with these claims, children who obtained higher scores on a video game addiction scale exhibited worse behavioral ratings of attention, problem solving and memory (Farchakh, et al.,, 2020), and converging evidence points to a link between prefrontal cortex and striatum functional alterations and cognitive control deficits in children diagnosed with internet gaming disorder (Sugaya et al. 2019). On the other hand, it should be noted that evidence regarding video game effects on children is mixed, with some studies pointing to null effects and others indicating positive outcomes on cognitive development, and even EF skills training and improvement (see Fietzer & Chin, 2017; Smirni et al., 2021 for reviews). It has been claimed that potential effects of video games had to be considered in relation to several variables and dimensions, such as content, gaming mechanics, age and (critically) time spent playing (Smirni et al., 2021).
Regarding internet use, children and adolescents diagnosed with ADHD who qualified for problematic media use (criteria for excessive mobile phone times or internet addiction) exhibited worse EF ratings in all dimensions of the behavioral BRIEF scale when compared to less screen-exposed ADHD controls (Shuai et al., 2021). While we did not consider excessive internet use indicators in our sample, our results are also consistent with those from problematic use studies. Internet abuse has been associated with increased impulsivity and impaired self-regulation in children, adolescents and young adults (Ioannidis et al., 2019; Billieux & Van der Linden, 2012). In addition, problematic users exhibited EF deficits in inhibitory control, working memory and decision making, particularly among youth (12-24 years old) (Ioannidis et al., 2019). A theoretical model that explains problematic internet use through the interaction of psychological and neurobiological factors has pointed out the importance of stressful events (in this case, the pandemic and the lockdown measures) as potential triggers; as well the contribution of coping styles and impaired executive functions (particularly, inhibitory controls) in the maintenance of these behaviors (Brand et al., 2016). Moreover, it has been observed that longer daily screen times may affect the inhibitory control network development in children by decreasing fronto-striatal connectivity, as well as increasing reward-seeking tendencies that promote impulsive and/or addictive behaviors (Chen et al., 2022).
To sum up, longer video game and internet times were associated with worse EF behavioral ratings (particularly, working memory). It should be noted that the perceived increase (compared with pre-pandemic times) was not a significant predictor of EF. Therefore, our findings can be interpreted as screen media being: 1) detrimental to EF in children, 2) a preferred source of entertainment (or even a coping mechanism) for those children with more EF issues or 3) a synergic combination of the former. Finally, it is also worth noting that we did not observe significant detrimental effects of TV on EF within our sample, unlike previous studies (Nathanson et al., 2014; Lillard et al, 2015; Swing et al., 2010). This might be explained by the fact that high TV times (more than 3 hours a day) were much less frequent in our sample than high video game or internet times (11.4% vs 27.1% and 22.9%; respectively). Furthermore, it is quite possible that streaming has replaced traditional TV among these children.
Limitations and future directions
We should point out the following limitations in the present study. 1) The relatively low sample size, combined with potential selection bias (since participants were volunteers recruited from social networks) and the fact that our sample was composed mostly by high NSE participants (parents who completed university), might reduce the generalizability of our findings. Future studies should focus on the aftermath of the pandemic in more socially vulnerable populations. 2) The correlational nature of our findings does not allow us to draw conclusions about causality. In addition, a larger scale follow up would have provided more empirical ground to comment on the trajectory of the EF issues one year after the lockdown measures. 3) On a related note, we did not have access to pre-pandemic EF assessments for our sample (but we did have normative data for the EF questionnaire), and we did not specifically ask parents to compare current behavior with pre-lockdown functioning. Therefore, we cannot claim that the incidence of EF issues observed in our sample is due to the pandemic or the lockdown measure. On the other hand, several studies indicate that this was indeed the case, finding that confinement and remote schooling were associated with worse behavioral EF scores in children (Lavigne-Cerván et al., 2021a,b; Hanno et al., 2022). 4) The use of an online heteroreport scale to assess EF instead of direct cognitive performance tests might be questioned, despite the fact that it was the only available assessment instrument due the lockdown measure. However, these measures allow to describe and make predictions about the manifestations of EF on childrens’ daily behavior (Gioia et al., 2017), and they have been shown to provide a useful complement to performance tests (Gerst et al, 2017). Furthermore, EF questionnaires are robusts predictors of childrens’ academic achievement in math or reading skills (Canet-Juric et al., 2021; Gerst et al., 2017). Still, future studies might benefit from including performance-based measures. 5) We did not consider other potentially relevant variables in our study, such as parenting style or stress, psychopathology indicators (such as anxiety or depression tests) or personality traits for children.
We were able to identify high EF functioning difficulties in the domains of cognitive flexibility (and emotional regulation) and working memory in around half our sample during the COVID-19 lockdown, in accordance with other studies of children behavior in the pandemic. In addition, we observed larger increases of screen media than reading times, while most children did not read on a daily basis. We found that both parents’ literacy beliefs and children leisure reading times were associated with fewer EF issues. Conversely, video game and internet times were positive predictors of EF issues. Since we cannot infer causality, our results could be explained as: 1) effects of reading and screen media over EF functioning, 2) a preference for reading or screens, according to the children’s EF profile or 3) a combination of both. At any rate, our findings are consistent with the literature that highlights the toll of the pandemic and the lockdown on the children’s cognitive and emotional self-regulation skills. Considering the relevance of behavioral EF to academic achievement and children’s psychological well being, we recommend (in line with Andrés et al., 2021) that parents and public institutions be mindful of the current trajectory of children behavior and recreational habits, in order to preserve their mental health during the transition to the post-pandemic normality.
Conflict of interest: All authors declare that they have no conflict of interest.
Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the CONICET research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent: Informed consent was obtained from all individual participants included in the study.
Table 1
Descriptive Statistics of Measure Variables
|
Variables |
M (SD) / % |
Minimum |
Maximum |
n |
|
Sociodemographic data |
|
|
|
|
|
Gender |
|
|
|
|
|
boys |
54% |
|
|
|
|
girls |
46% |
|
|
|
|
Age (years) |
10.05 (0.903) |
9 |
12 |
210 |
|
Mother education |
|
|
|
210 |
|
Primary |
4.8% |
|
|
|
|
Secondary |
18.2% |
|
|
|
|
University |
77% |
|
|
|
|
Home Literacy |
|
|
|
210 |
|
Number Books at Home |
3.08(0.930) |
1 |
4 |
|
|
Shared Reading Preschool |
3.4(1.31) |
1 |
5 |
|
|
Literacy beliefs |
26.1(2.89) |
19 |
30 |
|
|
Reading Times |
|
|
|
|
|
Leisure reading |
2.23(1.33) |
1 |
7 |
|
|
Study reading |
3.68(1.42) |
1 |
7 |
|
|
Change pre-pandemic |
2.8(1.21) |
1 |
5 |
|
|
Screen Media Times |
|
|
|
210 |
|
TV |
1.91(1.16) |
1 |
7 |
|
|
Video games |
0.18(0.51) |
1 |
7 |
|
|
Internet |
0.15(0.47) |
1 |
7 |
|
|
Change pre-pandemic |
4.31(1.08) |
1 |
5 |
|
|
Executive function (QEF) |
|
|
|
210 |
|
Inhibition |
2.15(0.718) |
1 |
4 |
|
|
Flexibility |
2.47(0.731) |
1 |
4.7 |
|
|
Working Memory |
2.27(0.665) |
1 |
4.41 |
|
Table 2
|
Linear regression analysis coefficients for EF measures |
|
||||||||||||||||||||||||||
|
95% Confidence Interval |
|
||||||||||||||||||||||||||
|
Predictor |
Estimate |
SE |
t |
p |
Stand. Estimate |
Lower |
Upper |
|
|||||||||||||||||||
|
EF-I: Full model |
|||||||||||||||||||||||||||
|
Grade |
|
|
|
|
|
|
|
||||||||||||||||||||
|
(5 – 4) |
-0.3142 |
0.6941 |
-0.453 |
0.651 |
-0.0694 |
-0.6363 |
0.49754 |
||||||||||||||||||||
|
(6 – 4) |
-0.4993 |
0.7130 |
-0.700 |
0.485 |
-0.4136 |
-1.1694 |
0.34218 |
||||||||||||||||||||
|
age |
0.1373 |
0.1140 |
1.205 |
0.230 |
0.1716 |
-0.1094 |
0.45262 |
||||||||||||||||||||
|
mother ed |
0.1163 |
0.0400 |
2.905 |
0.004 |
0.2089 |
0.0670 |
0.35090 |
||||||||||||||||||||
|
Gender |
0.2684 |
0.1083 |
2.477 |
0.014 |
0.3793 |
0.0771 |
0.68151 |
||||||||||||||||||||
|
litbelief |
-0.0283 |
0.0192 |
-1.475 |
0.142 |
-0.1147 |
-0.2681 |
0.03878 |
||||||||||||||||||||
|
tv |
-0.0804 |
0.0763 |
-1.054 |
0.293 |
-0.1863 |
-0.5353 |
0.16266 |
||||||||||||||||||||
|
vgame |
0.0649 |
0.0675 |
0.961 |
0.338 |
0.1702 |
-0.1791 |
0.51943 |
||||||||||||||||||||
|
internet |
-0.1139 |
0.0765 |
-1.489 |
0.138 |
-0.3058 |
-0.7112 |
0.09952 |
||||||||||||||||||||
|
Lread |
-0.2049 |
0.1033 |
-1.983 |
0.049 |
-0.3871 |
-0.7724 |
-0.00183 |
||||||||||||||||||||
|
Sread |
0.1292 |
0.0798 |
1.618 |
0.108 |
0.2601 |
-0.0572 |
0.57740 |
||||||||||||||||||||
|
TV ×grade: |
|
|
|
|
|
|
|
||||||||||||||||||||
|
(5 – 4) |
0.1381 |
0.0905 |
1.526 |
0.129 |
0.3201 |
-0.0938 |
0.73398 |
||||||||||||||||||||
|
(6 – 4) |
0.0864 |
0.0883 |
0.978 |
0.329 |
0.2003 |
-0.2037 |
0.60420 |
||||||||||||||||||||
|
VideoG ×grade: |
|
|
|
|
|
|
|
||||||||||||||||||||
|
(5 – 4) |
-0.2431 |
0.0842 |
-2.888 |
0.004 |
-0.6372 |
-1.0725 |
-0.20181 |
||||||||||||||||||||
|
(6 – 4) |
-0.0817 |
0.0809 |
-1.010 |
0.314 |
-0.2140 |
-0.6324 |
0.20433 |
||||||||||||||||||||
|
Internet ×grade: |
|
|
|
|
|
|
|
||||||||||||||||||||
|
(5 – 4) |
0.2090 |
0.0930 |
2.247 |
0.026 |
0.5610 |
0.0682 |
1.05374 |
||||||||||||||||||||
|
(6 – 4) |
0.1248 |
0.0859 |
1.453 |
0.148 |
0.3351 |
-0.1202 |
0.79030 |
||||||||||||||||||||
|
Lread × grade |
|
|
|
|
|
|
|
||||||||||||||||||||
|
(5 – 4) |
0.2740 |
0.1293 |
2.118 |
0.036 |
0.5176 |
0.0354 |
0.99991 |
||||||||||||||||||||
|
(6 – 4) |
0.2227 |
0.1164 |
1.914 |
0.057 |
0.4207 |
-0.0131 |
0.85447 |
||||||||||||||||||||
|
Sread ×grade: |
|
|
|
|
|
|
|
||||||||||||||||||||
|
(5 – 4) |
-0.1665 |
0.1028 |
-1.620 |
0.107 |
-0.3353 |
-0.7438 |
0.07316 |
||||||||||||||||||||
|
(6 – 4) |
-0.2010 |
0.0949 |
-2.119 |
0.035 |
-0.4048 |
-0.7818 |
-0.02784 |
||||||||||||||||||||
|
EF-CF: model 1 |
|||||||||||||||||||||||||||
|
Grade |
|
|
|
|
|
|
|
||||||||||||||||||||
|
(5 – 4) |
0.25849 |
0.7213 |
0.358 |
0.721 |
-0.3682 |
-0.94700 |
0.2106 |
||||||||||||||||||||
|
(6 – 4) |
-0.26767 |
0.7413 |
-0.361 |
0.718 |
-0.9148 |
-1.68342 |
-0.1461 |
||||||||||||||||||||
|
age |
0.17731 |
0.1192 |
1.488 |
0.139 |
0.2162 |
-0.07067 |
0.5032 |
||||||||||||||||||||
|
mother ed |
0.01118 |
0.0416 |
0.269 |
0.788 |
0.0196 |
-0.12461 |
0.1639 |
||||||||||||||||||||
|
Gender |
0.07347 |
0.1136 |
0.647 |
0.519 |
0.1010 |
-0.20720 |
0.4092 |
||||||||||||||||||||
|
litbelief |
-0.02845 |
0.0200 |
-1.426 |
0.156 |
-0.1125 |
-0.26826 |
0.0432 |
||||||||||||||||||||
|
tv |
-0.03432 |
0.0793 |
-0.433 |
0.666 |
-0.0768 |
-0.42729 |
0.2736 |
||||||||||||||||||||
|
vgame |
0.14052 |
0.0702 |
2.003 |
0.047 |
0.3599 |
0.00518 |
0.7147 |
||||||||||||||||||||
|
internet |
-0.00826 |
0.0795 |
-0.104 |
0.917 |
-0.0216 |
-0.43313 |
0.3898 |
||||||||||||||||||||
|
Lread |
-0.17234 |
0.1074 |
-1.605 |
0.110 |
-0.3168 |
-0.70644 |
0.0728 |
||||||||||||||||||||
|
Sread |
0.10003 |
0.0830 |
1.206 |
0.230 |
0.1950 |
-0.12426 |
0.5143 |
||||||||||||||||||||
|
FE WM: Full model |
|
|
|
|
|
|
|
||||||||||||||||||||
|
Grade |
0.1149 |
0.6182 |
0.186 |
0.853 |
-0.1059 |
-0.65440 |
0.4427 |
|
|||||||||||||||||||
|
(5 – 4) |
-0.3332 |
0.6350 |
-0.525 |
0.600 |
-0.5518 |
-1.28176 |
0.1782 |
|
|||||||||||||||||||
|
(6 – 4) |
0.0949 |
0.1017 |
0.933 |
0.352 |
0.1286 |
-0.14334 |
0.4006 |
|
|||||||||||||||||||
|
age |
0.0779 |
0.0357 |
2.184 |
0.030 |
0.1519 |
0.01463 |
0.2891 |
|
|||||||||||||||||||
|
mother ed |
|
|
|
|
|
|
|
|
|||||||||||||||||||
|
Gender |
0.1204 |
0.0966 |
1.246 |
0.214 |
0.1842 |
-0.10757 |
0.4760 |
|
|||||||||||||||||||
|
litbelief |
-0.0501 |
0.0173 |
-2.888 |
0.004 |
-0.2164 |
-0.36434 |
-0.0685 |
|
|||||||||||||||||||
|
tv |
-0.0312 |
0.0680 |
-0.459 |
0.647 |
-0.0785 |
-0.41584 |
0.2589 |
|
|||||||||||||||||||
|
vgame |
0.0919 |
0.0602 |
1.527 |
0.129 |
0.2612 |
-0.07641 |
0.5989 |
|
|||||||||||||||||||
|
internet |
-0.0872 |
0.0682 |
-1.280 |
0.202 |
-0.2540 |
-0.64590 |
0.1378 |
|
|||||||||||||||||||
|
Lread |
-0.2021 |
0.0921 |
-2.196 |
0.029 |
-0.4136 |
-0.78530 |
-0.0419 |
|
|||||||||||||||||||
|
Sread |
0.0903 |
0.0711 |
1.270 |
0.206 |
0.1974 |
-0.10929 |
0.5041 |
|
|||||||||||||||||||
|
TV ×grade: |
|
|
|
|
|
|
|
|
|||||||||||||||||||
|
(5 – 4) |
0.0535 |
0.0806 |
0.664 |
0.508 |
0.1346 |
-0.26567 |
0.5348 |
|
|||||||||||||||||||
|
(6 – 4) |
0.0540 |
0.0787 |
0.687 |
0.493 |
0.1358 |
-0.25464 |
0.5263 |
|
|||||||||||||||||||
|
VideoG ×grade: |
|
|
|
|
|
|
|
|
|||||||||||||||||||
|
(5 – 4) |
-0.1878 |
0.0750 |
-2.505 |
0.013 |
-0.5343 |
-0.95513 |
-0.1134 |
|
|||||||||||||||||||
|
(6 – 4) |
-0.0605 |
0.0720 |
-0.840 |
0.402 |
-0.1721 |
-0.57644 |
0.2323 |
|
|||||||||||||||||||
|
Internet ×grade: |
|
|
|
|
|
|
|
|
|||||||||||||||||||
|
(5 – 4) |
0.2083 |
0.0829 |
2.513 |
0.013 |
0.6068 |
0.13028 |
1.0833 |
|
|||||||||||||||||||
|
(6 – 4) |
0.0909 |
0.0765 |
1.188 |
0.236 |
0.2649 |
-0.17517 |
0.7050 |
|
|||||||||||||||||||
|
Lread × grade |
|
|
|
|
|
|
|
|
|||||||||||||||||||
|
(5 – 4) |
0.1368 |
0.1154 |
1.185 |
0.238 |
0.2799 |
-0.18619 |
0.7460 |
|
|||||||||||||||||||
|
(6 – 4) |
0.2071 |
0.1036 |
1.999 |
0.047 |
0.4238 |
0.00531 |
0.8422 |
|
|||||||||||||||||||
|
Sread ×grade: |
|
|
|
|
|
|
|
|
|||||||||||||||||||
|
(5 – 4) |
-0.1889 |
0.0916 |
-2.062 |
0.041 |
-0.4127 |
-0.80780 |
-0.0176 |
|
|||||||||||||||||||
|
(6 – 4) |
-0.2128 |
0.0845 |
-2.519 |
0.013 |
-0.4650 |
-0.82940 |
-0.1006 |
|
|||||||||||||||||||
Notes. Mother ed: mother education; litbelief: literacy beliefs; TV: tv times; vgame: video game times; internet: internet times; Lread: leisure reading times; Sread: study reading times. Significant effects have been highlighted in bold.
Appendix 1 is not available with this version.