SYSTEMATIC REVIEW article
Sec. Public Mental Health
Volume 9 - 2021 | https://doi.org/10.3389/fpubh.2021.793868
Digital Media Use and Adolescents' Mental Health During the Covid-19 Pandemic: A Systematic Review and Meta-Analysis
- 1Faculty of Communication, Culture and Society, USI Università della Svizzera italiana, Lugano, Switzerland
- 2Institute of Public Health, USI Università della Svizzera italiana, Lugano, Switzerland
The Covid-19 physical distancing measures had a detrimental effect on adolescents' mental health. Adolescents worldwide alleviated the negative experiences of social distancing by spending more time on digital devices. Through a systematic literature search in eight academic databases (including Eric, Proquest Sociology, Communication & Mass Media Complete, Psychology and Behavioral Sciences Collection, PsycINFO, CINAHL, Pubmed, and Web of Science), the present systematic review and meta-analysis first summarized the existing evidence from 30 studies, published up to September 2021, on the link between mental health and digital media use in adolescents during Covid-19. Digital media use measures included social media, screen time, and digital media addiction. Mental health measures were grouped into conceptually similar dimensions, such as well-being, ill-being, social well-being, lifestyle habits, and Covid-19-related stress. Results showed that, although most studies reported a positive association between ill-being and social media use (r = 0.171, p = 0.011) and ill-being and media addiction (r = 0.434, p = 0.024), not all types of digital media use had adverse consequences on adolescents' mental health. In particular, one-to-one communication, self-disclosure in the context of mutual online friendship, as well as positive and funny online experiences mitigated feelings of loneliness and stress. Hence, these positive aspects of online activities should be promoted. At the same time, awareness of the detrimental effects of addictive digital media use should be raised: That would include making adolescents more aware of adverse mechanisms such as social comparison, fear of missing out, and exposure to negative contents, which were more likely to happen during social isolation and confinement due to the pandemic.
The Covid-19 pandemic and its related containment measures unavoidably affected mental health, which can be defined as “a state of well-being in which an individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and is able to make a contribution to his or her community” (1). Mental health is most affected during adolescence, when individuals enlarge their social sphere, establish a sense of autonomy, and make crucial decisions to achieve long-term goals (2). The concomitant maturation of social and cognitive control areas of the brain supports the progress of these skills, together with the exposure to and experience of appropriate contextual and social stimuli (3). Indeed, for adolescents, the social environment is important for developing essential brain functions, self-concept, and mental health in general (4). Hence, physical distancing measures introduced during the Covid-19 pandemic may have had a detrimental effect on youth development. Several studies already showed that adolescent age is a risk factor for diverse mental health problems, especially during epidemic outbreaks [e.g., (4–10)]. Particularly, social deprivation during a developmental period characterized by a high need for peer interaction likely augments negative consequences on mental health.
During the early months of the pandemic, many countries worldwide went into complete lockdown. Mental health of youth was threatened due to the shift toward distant learning, the closure of leisure environments, the decrease in outdoor activities, the impossibility to organize social events, and the increase of distress related to the pandemic. As measures were taken across the globe, their long-term effects on adolescents' mental health were unknown. To date, several reviews have summarized the immediate impact of the Covid-19 pandemic on the younger population. According to a review of ten studies (11), school closure contributed to anxiety, loneliness, stress, depressive symptoms, frustration in young people, together with higher indiscipline and hyperactive conduct. Similarly, also an increase in Body Mass Index and overweight was reported. A rapid narrative review of 15 articles (12) highlighted that pandemic and lockdown measures impacted young persons' mental health in particular, leading to a general decrease in psychological well-being followed by changes in sleep habits. Stressors were mainly linked to academic, economic, and social issues. Another review of six studies reported a general decrement in adolescents' quality of life during Covid-19, including the perception of physical, psychological, and social well-being (8). Overall, these reviews showed that young people were more vulnerable to psychological distress, highlighting the need for targeted interventions and psychological support.
Adolescents around the world alleviated the negative experiences of social distancing by spending more time online. A general increment in the use of digital technologies has been reported, especially of social media (13), with applications such as TikTok, Pinterest, Reddit, Facebook, Snapchat, Instagram, LinkedIn, and Twitter showing growth in active users ranging from 8 to 38% (14). Notably, teens reported staying connected with others via text messages (83%), phone calls (72%), social media and video chats (66%), instant messaging apps (48%), and, to a lesser extent, e-mails (37%) (15).
In line with this increment, a study on 5114 high school students from five countries (16) showed that more than 40% increased their social media time to stay connected with others since they could not meet in person. Similarly, Munasinghe et al. (17) reported augmented screen time – including social media, Internet, and smartphone use – together with diminished time for physical activity, decreased happiness, and more fast-food consumption. Focusing on the use of digital technology in 1,860 adolescents aged 12–18 years, Salzano et al. (18) reported that participants spent more than six hours a day on screens for educational purposes and from four-to-six hours a day for recreational activities. To note, adolescents reported that, on average, they sent and received over 100 messages per day. Not surprisingly, more frequent symptoms of smartphone dependency have been observed, especially among young females (19). The augmented time spent on digital technologies, particularly social media, might have alleviated feelings of loneliness and enhanced social connection. However, social media platforms also provided an overload of Covid-19 related information, where one-third of Covid-19 updates have been classified as fake (20), thus adding additional stress to the already worrisome situation. Accordingly, social media use has been identified as both a protective and risk factor for mental well-being during Covid-19 (21). This evidence should be interpreted in a larger, pre-pandemic context, where past reviews concluded that screen media use has negative but small effects on adolescents' health [e.g., (22, 23)] through various mechanisms such as upward social comparison and time displaced for other activities. This poses the question of whether the augmented use of screen media due to the pandemic may have exacerbated adverse outcomes by increasing social comparison and envy, displacing time for health-promoting activities such as sleep and exercising, and fostering cognitive distraction. Yet, screen media use could have also acted as a buffer, e.g., by initiating and maintaining social connections in times of limited face-to-face interactions or providing a way to get entertained. Additionally, adolescents may have used digital media as a coping tool to deal with the stress generated by the Covid-19 confinement by self-regulating their emotions using, for example, social media to escape ongoing worries and boost their mood (24).
To the best of our knowledge, no systematic synthesis on the link between digital media use, including social media and smartphone use, and adolescents' mental health during Covid-19 exists. Hence, the present systematic review and meta-analysis aims to fill this gap by focusing on the adolescent age, mental health, and digital media use during the Covid-19 pandemic.
On 16th April 2021, a systematic search was carried out in the titles and abstracts of scientific publications listed in eight academic databases, including Eric and Proquest Sociology (via Proquest), Communication & Mass Media Complete, Psychology and Behavioral Sciences Collection, PsycINFO, and CINAHL (via Ebscohost), Pubmed (via Medline and Proquest), Web of Science (via Clarivate Analytics). Key terms covered the population (e.g., “adolescent*”, “teen*”, “young*”), intervention/activity (e.g., “social media*, “screen time*”), outcome (e.g., “well-being*”, “psych*”, “mental*”), and context (e.g., “covid*”). They were combined using Boolean operators. The complete list of keywords and their combination is reported in Table 1.
To exclude any duplicates, all entries were imported in Zotero, a reference management software. After duplicates were excluded, the remaining titles and abstracts were screened by two coders according to the predefined eligibility criteria. Cohen's kappa statistic (25) was calculated and used to measure inter-coder reliability. Discrepancies that emerged after full-text screening were resolved through a consensus meeting. Two additional hand searches were carried out on 15th June 2021 and 15th September 2021 to update the initial search due to the rapid rate of published works on the topic.
According to the PICO [Population, Intervention, Comparison, and Outcome; (26)] definition of pre-specified eligibility criteria, we included articles with original data on a population aged 10 to 24 years (P) (27), including measures of (problematic) digital media as intervention (I), and mental health as the outcome (O), in the context of the Covid-19 pandemic. We did not include any comparison. Additionally, only studies published in peer-reviewed journals, written in English, and using a quantitative methodology with a cross-sectional or a longitudinal design were retained.
Articles were excluded if they were book chapters, pre-prints, conference papers, experimental studies, intervention studies, qualitative studies, studies focusing on gaming or cyberbullying, studies with no reference to Covid-19, as well as studies focusing on education, information-seeking behaviors, contact tracing, and clinical populations. Publications were also excluded if they reported only descriptive information of digital media use and mental health without linking the two concepts.
The following information was collected for each study: First author, year, and title of the paper, the country where the research was conducted, study design (cross-sectional or longitudinal), sample size, type of recruitment (online vs. other), type of sampling (random vs. convenience), % of male participants, age of participants, theoretical background, construct and measure of digital media use, construct and measure of mental health (including its different facets as well-being and ill-being), a brief description of the results, and raw data convertible into effect sizes.
Quality Assessment of the Included Studies
The quality assessment of the included studies was carried out using the Strobe-checklist (28). In particular, for each study, we evaluated the quality of the information regarding the background/rationale, objectives, setting, participants, included variables, data sources/measurement, statistical methods, descriptive results, outcome data, key results, and limitations. The assessment of each study resulted in a total score from 0 to 11. A summary of the studies' quality can be found in Tables 2, 3. We also considered if the included studies used reliable measures for digital media use and well-being.
Due to the high heterogeneity of the included studies, meta-analytic syntheses were carried out only for studies including raw data convertible into effects sizes and similar investigated concepts. The “meta” (29) package in R statistical software was used for the meta-analysis. A Fisher's r-to-z transformation was calculated as a measure of effect size, and results were converted back to r correlation coefficients for interpretation. Conversion formulas (30, 31) were used when necessary to convert raw data to correlations. Several meta-analyses were carried out linking (i) social media use, (ii) screen-time, and (iii) media addiction to diverse mental health outcomes grouped into comparable categories. We interpreted pooled effect sizes of r = 0.10, r = 0.30, and r = 0.50 as small, medium, and large, respectively (32). An inverse-variance method with a random-effects model and Hartung-Knapp-Sidik-Jonkman adjustment (33) was used to adjust for study variability in sample sizes. Heterogeneity of results was calculated with the between-study-variance τ2, the restricted maximum-likelihood estimator (REML), and reported as I2 statistic (31, 34, 35). When possible (k = 10), additional meta-regression analyses were carried out to investigate the role of moderators, such as the age and gender of participants.
From the initial database search, 378 records were obtained. After duplicates removal, the title and abstract of 217 records were screened independently by two coders based on the predefined eligibility criteria. Cohen's kappa as a measure of intercoder reliability was 0.80, indicating substantial agreement. After title and abstract screening, 45 articles were retained. Another 31 articles were identified through the two additional hand searches, adding up to 76 articles for full-text screening. Of these, 30 articles were retained in the systematic review and a subset of 23 in the meta-analysis (see PRISMA flowchart in Figure 1).
The included studies were mainly conducted in Asia (n = 12) and Europe (n = 11). Few were conducted in Oceania (n = 3), America (n = 2), and Middle East (n = 1). One study (36) collected data from Italy, Argentina, and United Kingdom. Six studies adopted a longitudinal design, ranging from 14 days (37) to twelve months (38). In all the studies, data were collected through online questionnaires, and three studies made use of a random sampling procedure. The median sample size was 760, ranging from 102 to 13,525, with one longitudinal study including 1,64,101 participants at the first time point of data collection (39). In general, females were slightly over-represented (mean = 60%). Participants' mean age was 17.75 years (ranging from 9.50 to 25.5).
Included studies mainly assessed social media use (n = 16), screen time (n = 10; including time spent on different devices, change in screen time, and type of usage), and media addiction (n = 9; including measures of Internet and social media addiction). Mental health was measured in terms of ill-being (n = 17, i.e., psychopathological problems such as symptoms of depression, anxiety, mood disorder, ruminative thoughts), well-being (n = 6, including life satisfaction, optimism, happiness), social well-being (n = 12, covering the quality of social relationships, social support, interpersonal conflict, and loneliness), lifestyle habits (n = 15, including physical activity, sleep, smoking, nutrition, and everyday health routines), and Covid-19-related stress (n = 10, covering distress, fear, and worries due to the Covid-19 pandemic). For a summary of the investigated concepts, see Figures 2, 3.
A summary of the study characteristics can be found in Tables 4–6. Applying the Strobe checklist, all studies were of very good quality, except for three studies lacking detailed information on data sources and measurement (55, 58, 66) and two studies with insufficient recognition of their study limitations (48, 64).
In the following subchapters, the studies are summarized qualitatively and - when possible - quantitatively by grouping them according to the type of media use and its association with mental health, i.e. social media use and mental health, screen time (excluding social media use) and mental health, and media addiction and mental health. A separate subchapter focuses on longitudinal studies investigating the different types of media use and their causal relationships with mental health outcomes.
Social Media Use and Mental Health During Covid-19
In general, studies reported that social media use increased during the Covid-19 pandemic (36, 47, 56, 60, 62), including the usage of a variety of social media platforms (e.g., Instagram, Snapchat, TikTok). In particular, three studies reported that about one-third of the participants used social media for more than 5 h per day (40, 50, 56), with some participants reporting time spent on social platforms up to 10 h per day (40).
Overall, meta-analytic results showed that time spent on social media was positively correlated with ill-being (k = 11, r = 0.171, 95%CI [0.050–0.286], p = 0.011, I2 = 96%, Figure 4), indicating that using social platforms was related to higher psychopatological symptoms. To note, meta-regression analyses showed that the strength of correlation slightly augmented with age (β = 0.008, p = 0.027) and percentage of males in the sample (β = 0.333, p = 0.034). No significant association was found for measures of well-being (k = 6, r = −0.051, 95%CI [−0.194–0.0947], p = 0.411, I2 = 89%).
Looking at single studies examining ill-being, social media use was associated with higher levels of depression, anxiety, mental health problems in general, and lower self-esteem, especially among girls (38). Furthermore, girls reported having had negative online experiences more often (55). One study found that exposure to Covid-19 information likely increased levels of anxiety and depression, especially when participants had already reported psychopathological symptoms before the pandemic (50). Also, adolescents who - under normal circumstances - did not use social media so often reported a steeper increment in mental problems: Indeed, a three-fold increase in distress was reported in young people who augmented social media time up to 3 hours more than before the pandemic (56). Symptoms were also exacerbated through the mediating role of rumination - which refers to the persistent act of thinking about something bad, hurtful, or uncertain for an extended period (67). That was probably due to the greater exposure to Covid-19 related information online, although mindfulness skills buffered this adverse effect (49). A lack of cognitive control over the time spent on social media platforms likely exacerbated psychopathological symptoms and augmented a sense of isolation from social reality, fueling an obsessive cycle of social media usage patterns (59). Conversely, anxious participants reported using social media more often as a strategy to adapt to the current emergency and – to a lower extent – as a way to keep in touch with family and friends (60). Interestingly, individuals who reported more frequent experiences of Fear of Missing Out (FoMO) tended to use social media more frequently to seek and share information, thus fueling a vicious cycle and leading to an even higher engagement with these platforms (64). The higher engagement in social media content was carried out also if the information received were perceived as overwhelming (42). Furthermore, the use of Instagram and, in particular, following appearance-focused accounts was related to higher body dissatisfaction, drive for thinness and lower self-esteem in female adolescents. However, the effect sizes were small (47).
To note, conflicting results were found when social media use was considered in relation to social well-being (k = 5, r = −0.002, 95%CI [−0.181–0.176], p = 0.972, I2 = 94%), since studies reported both positive and negative associations. In particular, although depressive symptoms augmented – social media use mitigated the feeling of loneliness (40). However, the way through which this positive effect acted is complex. For example, disclosing oneself to a small group of people, i.e. reciprocal online friendship, was found to relieve stress more than one-to-many online communication (45). Similarly, a study found that messaging and the use of VoIP apps (e.g., Skype, Viber, WhatsApp) were associated with lower levels of loneliness. In contrast, general social media use increased feelings of loneliness via the mediating role of FoMO (36). A study of thirteen-year-old participants found that positive online experiences (e.g., feeling valued, receiving advice) decreased loneliness, whereas negative experiences (e.g., being cut-off and mistreated) augmented it (55). At the same time, one study showed that lonely participants were more inclined to use social media as a coping tool, but social media did not influence their happiness feelings (60). However, in the same study, humorous coping - e.g., watching or sharing funny videos - was positively related to feelings of happiness, although it was not influenced by loneliness or anxiety. These results underlined the positive associations between social media use and mental health in a developmental period during which connecting with peers is crucial for social well-being and showed that the quality and the quantity of social connections play a pivotal role.
Social media use was positively associated with Covid-19 related stress (k = 6, r = 0.253, 95%CI [0.049–0.437], p = 0.025, I2 = 93%). In particular, Covid-19 information shared through social platforms have been perceived as excessively complex and overwhelming, thus augmenting both social media fatigue and fear of Covid-19 (42), with the risk to further bias information-processing capacities for the assessment of Covid-19 information. Conversely, young people reporting more Covid-19-related stress fostered active use of social media as a coping tool [e.g., (40, 43)].
Lifestyle behaviors closely linked to mental health were also associated with time spent on social media. More precisely, higher levels of social media use were associated with lower levels of physical activity, more frequent sleep problems, as well as higher levels of substance use. In the meta-analysis, including two studies (40, 41), a non-significant relationship between lifestyle behaviors and social media use during the pandemic was found.
Screen Time and Mental Health During Covid-19
Screen time included any screen-based media use except for video gaming and social media use (excluded, unless studied alongside other screen-based activities). The majority of the included studies looking at screen time found that it augmented during the pandemic, especially for online leisure activities, watching television, news consumption, and overall Internet usage through smartphones, computers, and tablets (37, 46, 50, 51, 54, 62, 65). In one study, participants reported spending up to 11 h and more per day in front of screens (65). Also, young people living in urban areas reported an additional increase in their time spent in front of screens compared to those living in the countryside (51).
Two studies reported comparable effect sizes for screen time and well-being, the latter measured as general well-being and happiness (41, 54). The meta-analytic results revealed a negative yet marginally significant pooled correlation (k = 2, r = −0.196, 95%CI [−0.429–0.061], p = 0.065). The same studies also reported comparable effect sizes on screen time and ill-being. However, meta-analytic results were not significant.
Looking at the individual studies, the frequency and duration of recreational screen media use, as well as nighttime use, augmented, and this increment was related to increased psychopathology (46). Particularly, leisure screen time was negatively associated with mood problems, even after considering covariates such as physical activity and body mass index (57). In addition, young people showed less increment in Internet-related activities and lower psychological distress when involved in structured activities (37) or spent more time reading, studying or exercising (62).
Screen time that was not used for social interactions was negatively related to social well-being (k = 2, r = −0.115, 95%CI [−0.178–−0.051], p = 0.028). Meta-analytic results linking screen time and lifestyle behaviors were not significant. However, increased sitting and screen time was followed by a precipitous decline in physical activity, which led to lower mood levels (57). To note, the increment in screen and sedentary time was reported irrespectively of the initial time dedicated to both activities (51). Participants with previous mental health problems were also at higher risk of an unhealthy lifestyle, including lower levels of physical activity, higher levels of screen time, and poorer sleep quality (41). On the contrary, when adolescents used digital platforms promoting physical activities, they were more likely to meet the recommended movement guidelines (53). Also, lower television and mobile phone use levels were related to greater adherence to a Mediterranean diet, which was, in turn, related to less perceived adversity and more happiness and quality of life during the lockdown (54).
Finally, although a meta-analysis was not possible due to the paucity of studies, participants reported that increased screen time, including news consumption, helped them stay up-to-date and cope with Covid-19 uncertainty, although news consumption also augmented fear of infection (37).
Media Addiction and Mental Health During Covid-19
Across the studies included in this review, prevalence rates of media addiction ranged from about 20 to 70% (44, 48, 52, 63, 65). Two studies revealed that media addiction levels grew during the pandemic (46, 48). A study found that media addiction was more prevalent among youth who had difficulties organizing their daily schedules (59).
During the Covid-19 pandemic, media addiction showed a medium-to-large positive relation to ill-being (k = 6, r = 0.434. 95% CI [0.092–0.685], p = 0.024, I2 = 98%, Figure 5) including internalizing and externalizing problems [e.g., (65)]. Looking at the different types of addiction, Fung et al. (63) found a positive association between social media addiction and ill-being, likely caused by rumors and alarming news on Covid-19 circulating on social media platforms. Nevertheless, the same authors reported a decrease in the strength of the association between depression and anxiety with smartphone addiction over time, possibly due to the recently designed mental health apps (63). Also, according to Siste et al. (65), adolescents were more susceptible to Internet addiction than young adults during Covid-19. The authors explained these findings with the fact that adolescents' cognitive control system is still underdeveloped. On top of that, the pandemic has limited physical peer contacts essential for adolescents' growth and social connection, pushing adolescents to alternative, online means to stay in contact with peers and friends. Media addiction also deteriorated psychological adjustment via college belongingness: Students with higher levels of college belongingness reported better psychological adjustment. However, when social media addiction was high, it likely interfered with the sense of belonging to the school (44).
Concerning the association between media addiction and lifestyle behaviors, the former was related to irregular physical exercise or physical inactivity, lower engagement with studying, ignoring earning activities and household chores, poor or heavy sleep, and alcohol or cigarettes consumption (52, 66). Yet, the meta-analytic results based on the comparable effect sizes of the two studies were not significant.
Six studies included in this review used a longitudinal design (36–38, 50, 55, 63), thus providing insights into the causal mechanisms between (addictive) media use and mental health. In particular, using Ecological Momentary Assessments (EMAs) for 14 days, Arend et al. (37) found that more than 40% of participants augmented daily time spent watching TV and using social media. Participants who reported frequent experiences of structured daily activities also engaged in less intense sessions of screen-based activities, like video gaming, Internet surfing, and television watching. Fumagalli et al. (36) obtained screen-time usage data for a 4-week period from diverse countries. They found that only social media use augmented at the beginning of the lockdown in spring 2020. Furthermore, higher levels of social media use predicted higher levels of loneliness through the mediating role of FoMO. On the contrary, messaging and VoIP apps usage reduced loneliness and was not influenced by individuals' FoMO levels. Also, VoIP apps consumption varied greatly among countries, but time spent using these apps was still lower with respect to time spent using social media apps. Magis-Weinberg et al. (55) studied levels of loneliness and reported that they remained unchanged between weeks 6 and 11 of the lockdown in Spring 2020 in Perù. Yet, loneliness was consistently more prevalent among females. Social media use, including positive experiences, such as feeling valued and receiving advice, predicted lower levels of loneliness over three months, whereas negative experiences on social media as well as overall screen time predicted the opposite. Furthermore, one study (38) reported an increment in depressive and anxiety symptoms and a decrease in life satisfaction from the pre-pandemic to the intra-pandemic period. However, exposure to Covid-19 information on social media did not significantly affect these changes in mental health. Fung et al. (63) collected data from 11-years-old participants during the pre-, ongoing-, and post- Covid-19 lockdown, finding that the positive association between smartphone addiction and ill-being decreased across the three waves. The opposite happened for social media addiction, for which the association with depression and anxiety increased across the three waves. Finally, the study by Li et al. (50), including 1,64,101 Chinese college students at the onset of the Covid-19 in February 2020 and 68,685 participants at the follow-up assessment - about 2.5 months later - highlighted that acute stress diminished. However, depressive and anxiety symptoms augmented, and social media exposure was a risk factor, especially when participants spent more than 3 h per day with these platforms.
During the Covid-19 pandemic, especially during the lockdown, social distancing measures and the associated disruption of everyday activities and social contacts threatened the mental health of adolescents (6, 68). To alleviate the negative experiences of social distancing measures, young people spent more time online. Lockdown and distancing measures began not long ago, but researchers have studied whether and how the time spent in front of screens affected mental health. However, a comprehensive synthesis of the literature published so far was still missing. Based on a systematic search and screening process, the present review qualitatively and quantitively summarized the existing evidence on the association between (addictive) screen media use and mental health in adolescents during the Covid-19 pandemic.
The key message of the present review is that not all uses of digital media had negative consequences on adolescents' mental health during the pandemic. In particular, our results suggested that social media use was helpful in mitigating the feeling of loneliness during Covid-19, but only when a one-to-one or one-to-few communication (e.g., use of VoIP apps), rather than a general social media use, was promoted. Likewise, online disclosure in the context of reciprocal friendship was found to relieve stress rather than a one-to-all peripheral disclosure on social media. In addition, good online experiences like receiving positive feedback augmented social connection and reduced loneliness during the lockdown, and using social media as a humorous coping tool (i.e., using humor to cope with the pandemic) increased happiness. These findings align with the Theory of Compensatory Internet Use, according to which “negative life situations can give rise to a motivation to go online to alleviate negative feelings” [(69), p. 352], although time online can have both positive and negative outcomes. In the present review, positive outcomes included better self-reported (social) well-being and less ill-being in terms of loneliness and stress.
Although some studies underlined the positive side of social media use, the majority reported that digital media use was associated with diminished well-being. Firstly, detrimental effects of social media may derive from the overload of Covid-19-related information, which was frequently negatively valenced and included much misinformation augmenting feelings of worry, fear of the pandemic, and FoMO, thus diminishing well-being [e.g., (42)]. It is likely that, when dealing with high levels of stress and uncertainty, online communication and posts' sharing among adolescents fostered rumination on negative feelings and involuntarily intensified these concerns. Not surprisingly, older participants, who better understood the pandemic's severity, were more affected by the negative consequences of social media contents' exposure.
Secondly, young people used social media as a coping tool to disconnect from negativity, avoid boredom, displace time for homework, get entertained and follow social media content without getting directly involved. However, as reported by previous literature reviews, passive and compensatory social media use led to increased ill-being (59), including feelings of depression, anxiety, loneliness, and low self-esteem due to social comparison as well as body-related concerns (47). The latter result is in line with a general risk of increased eating disorders during the pandemic (70). Although many of the studies included in this review used a correlational design, the results indicated a detrimental effect of social media use during the Covid-19 pandemic, especially in adolescents who were less involved in online activities and those who already experienced mental health problems before the pandemic.
While mechanisms such as social comparison, FoMO or exposure to negative Covid-19-related information are one possible explanation for the detrimental effect of social media, another mechanism is that social media, and screen time in general, replaced lifestyle activities promoting mental health. For example, more time in front of screens was associated with sleep problems, leading to even more screen time during night hours and determining irritability and anxiety. Likewise, physical activity was reduced, and a more sedentary lifestyle was adopted, including a poorer diet and greater use of substances like alcohol and cigarettes, which were subsequently associated with more screen time [e.g. (54)] and a more frequent engagement in alcohol-related social media usage [e.g., (66)].
Additionally, youth who spent more time in front of screens to deal with Covid-19 stressful situations also tended to fall into “an immersed pleasant state through repeated use”, which eventually led to the development of media addiction symptoms (43). Yet, the prevalence of these addictive symptoms varied considerably across the included studies, ranging from 20 to 70 per cent. In particular, during home quarantine, social media use was the only way to meet and socialize, thus contributing to longer time spent online and more frequently reported symptoms of social media addiction, especially when adolescents experienced FoMO, thus diminishing well-being (64) - in particular, FoMO proneness was higher at the early stage of the pandemic (64). Given that adolescents' self-control skills are still underdeveloped due to the immaturity of the prefrontal cortex, younger age groups were even more at risk of developing symptoms of media addiction during the pandemic, which was further facilitated by the instantaneous and easy-to-access gratifying contents that (social) media platforms convey (65, 71). According to the Interaction of Person-Affect-Cognition-Execution Model (72), the experience of psychological distress, such as the one created by the Covid-19 lockdown, likely contributed to the development of addictive Internet use. As previously stated, social media, and screen media in general, could be used as a coping tool for self-regulating negative emotions deriving from stress, fear, uncertainty, and lifestyle changes due to the pandemic. That would end up in the experience of negative emotions due to the loss of control over online activities and the search for more frequent gratifications online (62). This would explain the sizeable meta-analytic correlation found between media addiction measures and ill-being.
To conclude, although overall digital media use was related to lower adolescents' well-being during Covid-19, some kind of social media use (i.e., one-to-one communication and online mutual relationships, the experience of funny and positive contents) improved social and mental well-being and helped adolescents to deal with the lack of in-person social experiences during the pandemic. That said, our findings contribute to a growing body of evidence highlighting that the quality rather than the quantity of online interactions and experiences are crucial in determining potential influences on young people's mental health. Thus, the positive aspects of online activities should be promoted. At the same time, awareness should be raised about the detrimental effects of addictive media use and adverse mechanisms such as social comparison, FoMO, and the exposure to negative content during online activities, which can happen more frequently in times of pandemic, social isolation, and confinement.
Limitations and Future Directions
This review does not come without limitations. We included only peer-reviewed articles; hence, pre-prints and gray literature were left out, which may have introduced some biases. Also, in some cases, we did not have enough effect sizes to conduct a meta-analysis on all of the associations of interest or to run meta-regression and sub-group analyses. Additionally, heterogeneity levels of the effect sizes varied largely, suggesting a significant variance that other factors should likely explain. Also, more studies are needed to conclude on more reliable results. Eventually, the findings of our systematic review may be biased because the included studies looked mainly at detrimental effects of screen time and social media use, including addictive use, with only a few focusing on a positive conceptualization of mental well-being. Likewise, causality claims, i.e., whether screen time and social media use impact mental health or whether the latter is a driver of certain usage behaviors, could only be made with caution since most reviewed studies relied on a cross-sectional design.
We encourage researchers to focus on the positive side of mental health for future research, including hedonic and eudaimonic well-being measures. Furthermore, given the strong focus and predominance of studies measuring the quantity of (social) media use in terms of duration and frequency, future studies should move beyond these holistic measures and disentangle the type and quality of (social) media use. Furthermore, researchers should invest time and effort in longitudinal studies, although we are confident that more longitudinal findings will be published in the upcoming months. Researchers should include longer time ranges when conducting longitudinal studies and use a rigorous statistical procedure to differentiate between- and between-person effects.
To conclude, the present systematic review and meta-analysis first summarizes the existing evidence from 30 studies on the link between mental health and digital media use in adolescents during Covid-19. Results showed that adolescents augmented their social media use, including general screen time. Also, higher levels of digital media addiction were reported during the pandemic. In general, higher social media use and media addiction were related to higher ill-being. Hence, adolescents are particularly at risk of experiencing mental health problems due to the augmented exposure to screen time and social media during the pandemic. However, not all types of digital media use had a negative consequence. In particular, one-to-one communication, mutual online friendship, and positive and funny online experiences mitigated feelings of loneliness and stress during Covid-19. These positive aspects of online activities should be promoted. Youth's access to psychological support services to provide measures for and promote healthy coping mechanisms during the ongoing Covid-19 pandemic should be facilitated (68).
Data Availability Statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.
LM and MO contributed to developing the main research question, carrying out the literature search, collecting the included studies' information, and describing the results. LM performed the meta-analysis and wrote the first draft of the manuscript. A-LC contributed to developing the main research question and revised the manuscript. PS revised the manuscript. All authors contributed to the article and approved the submitted version.
This research was in part funded by the Swiss National Science Foundation (Grant No. 175874).
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
1. World Health Organization. (2004). Promoting Mental Health. World Health Organization. Available online at: https://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=4978588
2. Steinberg L. Adolescence (11th ed.). McGraw-Hill Education. (2016).
3. Larsen B, Luna B. Adolescence as a neurobiological critical period for the development of higher-order cognition. Neurosci Biobehav Rev. (2018) 94:179–95. doi: 10.1016/j.neubiorev.2018.09.005
4. Orben A, Tomova L, Blakemore S-J. The effects of social deprivation on adolescent development and mental health. Lancet Child Adolesc Health. (2020) 4:634–40. doi: 10.1016/S2352-4642(20)30186-3
5. Caffo E, Scandroglio F, Asta L. Debate: COVID-19 and psychological well-being of children and adolescents in Italy. Child Adolesc Ment Health. (2020) 25:167–8. doi: 10.1111/camh.12405
6. Guessoum SB, Lachal J, Radjack R, Carretier E, Minassian S, Benoit L, et al. Adolescent psychiatric disorders during the COVID-19 pandemic and lockdown. Psychiatry Res. (2020) 291:113264. doi: 10.1016/j.psychres.2020.113264
7. Mazza C, Ricci E, Biondi S, Colasanti M, Ferracuti S, Napoli C, et al. A nationwide survey of psychological distress among italian people during the COVID-19 pandemic: immediate psychological responses and associated factors. Int J Environ Res Public Health. (2020) 17:3165. doi: 10.3390/ijerph17093165
8. Nobari H, Fashi M, Eskandari A, Villafaina S, Murillo-Garcia Á, Pérez-Gómez J. Effect of COVID-19 on health-related quality of life in adolescents and children: a systematic review. Int J Environ Res Public Health. (2021) 18:4563. doi: 10.3390/ijerph18094563
9. Taylor MR, Agho KE, Stevens GJ, Raphael B. Factors influencing psychological distress during a disease epidemic: Data from Australia's first outbreak of equine influenza. BMC Public Health. (2008) 8:347. doi: 10.1186/1471-2458-8-347
10. Viner R., Russell, S., Saulle, R., Croker, H., Stansfeld, C., Packer, J., et al. (2021). Impacts of school closures on physical and mental health of children and young people: a systematic review. Available online at: https://www.medrxiv.org/content/10.1101/2021.02.10.21251526v1
11. Chaabane S, Doraiswamy S, Chaabna K, Mamtani R, Cheema S. The impact of COVID-19 school closure on child and adolescent health: a rapid systematic review. Children. (2021) 8:415. doi: 10.3390/children8050415
12. Cielo F, Ulberg R, Di Giacomo D. Psychological impact of the COVID-19 outbreak on mental health outcomes among youth: a rapid narrative review. Int J Environ Res Public Health. (2021) 18:6067. doi: 10.3390/ijerph18116067
13. MediaBriefAdmin. (2020). KalaGato Report: COVID 19 Digital Impact: A Boon for Social Media? MediaBrief. https://mediabrief.com/kalagato-vocid-19-digital-impact-report-part-1/. (accessed April 6, 2020)
14. Statista. (2021). Growth of monthly active users of selected social media platforms worldwide from 2019 to 2021. Available online at: https://www.statista.com/statistics/1219318/social-media-platforms-growth-of-mau-worldwide/
15. Statista. (2020). Technologies used by teens in the United States to stay connected to friends and family the no longer see in-person during the coronavirus pandemic in April 2020. Available online at: Statista. https://www.statista.com/statistics/1115305/technology-used-by-teens-stay-connected-during-coronavirus-pandemic-usa/
16. Kerekes N, Bador K, Sfendla A, Belaatar M, Mzadi AE, Jovic V, et al. Changes in Adolescents' Psychosocial Functioning and Well-Being as a Consequence of Long-Term COVID-19 Restrictions. Int J Environ Res Public Health. (2021) 18:8755. doi: 10.3390/ijerph18168755
17. Munasinghe S, Sperandei S, Freebairn L, Conroy E, Jani H, Marjanovic S, et al. The impact of physical distancing policies during the COVID-19 pandemic on health and well-being among Australian adolescents. J Adolesc Health. (2020) 67:653–61. doi: 10.1016/j.jadohealth.2020.08.008
18. Salzano G, Passanisi S, Pira F, Sorrenti L, La Monica G, Pajno GB, et al. Quarantine due to the COVID-19 pandemic from the perspective of adolescents: the crucial role of technology. Ital J Pediatr. (2021) 47:40. doi: 10.1186/s13052-021-00997-7
19. Caponnetto P, Inguscio L, Valeri S, Maglia M, Polosa R, Lai C, et al. Smartphone addiction across the lifetime during Italian lockdown for COVID-19. J Addict Dis. (2021) 1–11. doi: 10.3390/ECERPH-3-09027
20. Tsao S-F, Chen H, Tisseverasinghe T, Yang Y, Li L, Butt ZA. What social media told us in the time of COVID-19: A scoping review. Lancet Digital Health. (2021) 3:e175–94. doi: 10.1016/S2589-7500(20)30315-0
21. Okabe-Miyamoto K, Lyubomirsky S. Social Connection and Well-Being during COVID-19.22. (2021).
22. Odgers CL, Schueller SM, Ito M. Screen time, social media use, and adolescent development. Ann Rev Develop Psychol. (2020) 2:485–502. doi: 10.1146/annurev-devpsych-121318-084815
23. Orben A, Przybylski AK. The association between adolescent well-being and digital technology use. Nat Human Behav. (2019) 3:173–82. doi: 10.1038/s41562-018-0506-1
24. Wolfers LN, Schneider FM. Using media for coping: a scoping review. Communic Res. (2020) 25:0093650220939778. doi: 10.1177/0093650220939778
25. McHugh ML. Interrater reliability: the kappa statistic. Biochemia Medica. (2012) 22:276–82. doi: 10.11613/BM.2012.031
26. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: Elaboration and explanation. BMJ. (2015) 349. doi: 10.1136/bmj.g7647
27. Sawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. The age of adolescence. Lancet Child Adolesc Health. (2018) 2:223–8. doi: 10.1016/S2352-4642(18)30022-1
28. Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. The Lancet. (2007) 370:1453–7. doi: 10.1016/S0140-6736(07)61602-X
29. Schwarzer G, Carpenter JR, Rücker G. Meta-Analysis with R. Springer International Publishing. (2015). doi: 10.1007/978-3-319-21416-0
30. Lüdecke D. Esc: Effect Size Computation For Meta Analysis. Zenodo. (2018).
31. Peterson RA, Brown SP. On the use of beta coefficients in meta-analysis. J Appl Psychol. (2005) 90:175–81. doi: 10.1037/0021-9010.90.1.175
32. Cohen J. Statistical Power Analysis for the Behavioral Sciences. Academic Press. (2013). doi: 10.4324/9780203771587
33. IntHout J, Ioannidis JP, Borm GF. The hartung-knapp-sidik-jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard dersimonian-laird method. BMC Med Res Methodol. (2014) 14:25. doi: 10.1186/1471-2288-14-25
34. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ (Clinical Research Ed). (2003) 327:557–60. doi: 10.1136/bmj.327.7414.557
35. Ried K. Interpreting and understanding meta-analysis graphs—a practical guide. Aust Fam Physician. (2006) 35:635–8.
36. Fumagalli E, Dolmatzian MB, Shrum LJ. Centennials, FOMO, and loneliness: an investigation of the impact of social networking and messaging/voip apps usage during the initial stage of the coronavirus pandemic. Front Psychol. (2021) 12:211. doi: 10.3389/fpsyg.2021.620739
37. Arend A-K, Blechert J, Pannicke B, Reichenberger J. Increased screen use on days with increased perceived COVID-19-related confinements—a day level ecological momentary assessment study. Frontiers in Public Health. (2021) 8:1062. doi: 10.3389/fpubh.2020.623205
38. Magson NR, Freeman JYA, Rapee RM, Richardson CE, Oar EL, Fardouly J. Risk and protective factors for prospective changes in adolescent mental health during the COVID-19 pandemic. J Youth Adolesc. (2021) 50:44–57. doi: 10.1007/s10964-020-01332-9
39. Yang B-Y, Zeng X-W, Markevych I, Bloom MS, Heinrich J, Knibbs LD, et al. Association between greenness surrounding schools and kindergartens and attention-deficit/hyperactivity disorder in children in China. JAMA Network Open. (2019) 2:e1917862–e1917862. doi: 10.1001/jamanetworkopen.2019.17862
40. Ellis WE, Dumas TM, Forbes LM. Physically isolated but socially connected: Psychological adjustment and stress among adolescents during the initial COVID-19 crisis. Canad J Behav Sci. (2020) 52:177–87. doi: 10.1037/cbs0000215
41. Li SH, Beames JR, Newby JM, Maston K, Christensen H, Werner-Seidler A. The impact of COVID-19 on the lives and mental health of Australian adolescents. Eur Child Adolesc Psychiatry. (2021) 1–13. doi: 10.1007/s00787-021-01790-x
42. Liu H, Liu W, Yoganathan V, Osburg V-S. COVID-19 information overload and generation Z's social media discontinuance intention during the pandemic lockdown. Technol Forecast Soc Change. (2021) 166:120600. doi: 10.1016/j.techfore.2021.120600
43. Zhao N, Zhou G. COVID-19 stress and addictive social media use (SMU): mediating role of active use and social media flow. Front Psychiatry. (2021) 12:635546. doi: 10.3389/fpsyt.2021.635546
44. Arslan G, Yılırım M, Zangeneh M. Coronavirus anxiety and psychological adjustment in college students: exploring the role of college belongingness and social media addiction. Int J Ment Health Addict. (2021) 1–14. doi: 10.1007/s11469-020-00460-4
45. Zhen L, Nan Y, Pham B. College students coping with COVID-19: Stress-buffering effects of self-disclosure on social media and parental support. Communic Res Rep. (2021) 38:23–31. doi: 10.1080/08824096.2020.1870445
46. Dong H, Yang F, Lu X, Hao W. Internet addiction and related psychological factors among children and adolescents in china during the coronavirus disease 2019 (COVID-19) epidemic. Front Psychiatry. (2020) 11:751. doi: 10.3389/fpsyt.2020.00751
47. Vall-Roqué H, Andrés A, Saldaña C. The impact of COVID-19 lockdown on social network sites use, body image disturbances and self-esteem among adolescent and young women. Progress Neuro-Psychopharmacol Biol Psychiat. (2021) 110:110293. doi: 10.1016/j.pnpbp.2021.110293
48. Sheoran P. Prevalence of Psychological Distress Among Adolescents in Relation to Internet Addiction During COVID-19 Times. (2021). p. 8.
49. Hong W, Liu R-D, Ding Y, Fu X, Zhen R, Sheng X. Social media exposure and college students' mental health during the outbreak of COVID-19: the mediating role of rumination and the moderating role of mindfulness. Cyberpsychol Behav Soc Netw. (2021) 24:282–7. doi: 10.1089/cyber.2020.0387
50. Li Y, Zhao J, Ma Z, McReynolds LS, Lin D, Chen Z, et al. Mental health among college students during the COVID-19 pandemic in China: a 2-wave longitudinal survey. J Affect Disord. (2021) 281:597–604. doi: 10.1016/j.jad.2020.11.109
51. Chambonniere C, Lambert C, Fearnbach N, Tardieu M, Fillon A, Genin P, et al. Effect of the COVID-19 lockdown on physical activity and sedentary behaviors in French children and adolescents: New results from the ONAPS national survey. Eur J Integr Med. (2021) 43:101308. doi: 10.1016/j.eujim.2021.101308
52. Islam MS, Sujan MS, Tasnim R, Mohona RA, Ferdous MZ, Kamruzzaman S, et al. Problematic smartphone and social media use among bangladeshi college and university students amid COVID-19: the role of psychological well-being and pandemic related factors. Front Psychiat. (2021) 12:386. doi: 10.3389/fpsyt.2021.647386
53. Parker K, Uddin R, Ridgers ND, Brown H, Veitch J, Salmon J, et al. The use of digital platforms for adults' and adolescents' physical activity during the COVID-19 pandemic (Our Life at Home): survey study. J Med Internet Res. (2021) 23:e23389. doi: 10.2196/23389
54. Dragun R, Veček NN, Marendić M, Pribisalić A, Đivić G, Cena H, et al. Have lifestyle habits and psychological well-being changed among adolescents and medical students due to COVID-19 lockdown in Croatia? Nutrients. (2020) 13:97. doi: 10.3390/nu13010097
55. Magis-Weinberg L, Gys CL, Berger EL, Domoff SE, Dahl RE. Positive and negative online experiences and loneliness in peruvian adolescents during the COVID-19 lockdown. J Res Adolesc. (2021) 31:717–33. doi: 10.1111/jora.12666
56. Rens E, Smith P, Nicaise P, Lorant V, Van den Broeck K. Mental distress and its contributing factors among young people during the first wave of COVID-19: a belgian survey study. Front Psychiatry. (2021) 12:35. doi: 10.3389/fpsyt.2021.575553
57. Xiao S, Yan Z, Zhao L. Physical activity, screen time, and mood disturbance among chinese adolescents during COVID-19. J Psychosoc Nurs Ment Health Serv. (2021) 59:14–20. doi: 10.3928/02793695-20201104-04
58. Nomura K, Minamizono S, Maeda E, Kim R, Iwata T, Hirayama J, et al. Cross-sectional survey of depressive symptoms and suicide-related ideation at a Japanese national university during the COVID-19 stay-home order. Environ Health Prev Med. (2021) 26:30. doi: 10.1186/s12199-021-00953-1
59. Hudimova A, Popovych I, Baidyk V, Buriak O, Kechyk O. The impact of social media on young web users' psychological well-being during the COVID-19 pandemic progression. Amazonia Investiga. (2021) 10:50–61. doi: 10.34069/AI/2021.39.03.5
60. Cauberghe V, Van Wesenbeeck I, De Jans S, Hudders L, Ponnet K. How adolescents use social media to cope with feelings of loneliness and anxiety during COVID-19 lockdown. Cyberpsychol Behav Soc Netw. (2021) 24:250–7. doi: 10.1089/cyber.2020.0478
61. Pigaiani Y Zoccante L Zocca A Arzenton A Menegolli M Fadel S Adolescent lifestyle behaviors coping strategies and subjective wellbeing during the COVID-19 pandemic: an online student survey. Healthcare. (2020) 8:E472. doi: 10.3390/healthcare8040472
62. Chen CY, Chen IH, Pakpour AH, Lin CY, Griffiths MD. Internet-related behaviors and psychological distress among schoolchildren during the COVID-19 school hiatus. Cyberpsychol Behav Soc Netw. (2021) 24:654–63. doi: 10.1089/cyber.2020.0497
63. Fung XCC, Siu AMH, Potenza MN, O'Brien KS, Latner JD, Chen C-Y, et al. Problematic use of internet-related activities and perceived weight stigma in schoolchildren: a longitudinal study across different epidemic periods of COVID-19 in China. Front Psychiatry. (2021) 12:675839. doi: 10.3389/fpsyt.2021.675839
64. Hayran C, Anik L. Well-being and fear of missing out (FOMO) on digital content in the time of COVID-19: a correlational analysis among university students. Int J Environ Res Public Health. (2021) 18:1974. doi: 10.3390/ijerph18041974
65. Siste K, Hanafi E, Sen LT, Murtani BJ, Christian H, Limawan AP, et al. Implications of COVID-19 and lockdown on internet addiction among adolescents: data from a developing country. Front Psychiatry. (2021) 12:665675. doi: 10.3389/fpsyt.2021.665675
66. Islam MS, Sujan MSH, Tasnim R, Ferdous MZ, Masud JHB, Kundu S, et al. Problematic internet use among young and adult population in Bangladesh: correlates with lifestyle and online activities during the COVID-19 pandemic. Addict Behav Rep. (2020) 12:100311. doi: 10.1016/j.abrep.2020.100311
67. Ito T, Takenaka K, Tomita T, Agari I. Comparison of ruminative responses with negative rumination as a vulnerability factor for depression. Psychol Rep. (2006) 99:763–72. doi: 10.2466/PR0.99.3.763-772
68. Singh S, Roy D, Sinha K, Parveen S, Sharma G, Joshi G. Impact of COVID-19 and lockdown on mental health of children and adolescents: a narrative review with recommendations. Psychiatry Res. (2020) 293:113429. doi: 10.1016/j.psychres.2020.113429
69. Kardefelt-Winther D. A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Comput Human Behav. (2014) 31:351–4. doi: 10.1016/j.chb.2013.10.059
70. Rodgers RF, Lombardo C, Cerolini S, Franko DL, Omori M, Fuller-Tyszkiewicz M, et al. The impact of the COVID-19 pandemic on eating disorder risk and symptoms. Int J Eat Diso. (2020) 53:1166–70. doi: 10.1002/eat.23318
71. Marciano L, Camerini A-L, Morese R. The developing brain in the digital era: a scoping review of structural and functional correlates of screen time in adolescence. In press. (2021). doi: 10.3389/fpsyg.2021.671817
72. Brand M, Wegmann E, Stark R, Müller A, Wölfling K, Robbins TW, et al. The interaction of person-affect-cognition-execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neurosci Biobehav Rev. (2019) 104:1–10. doi: 10.1016/j.neubiorev.2019.06.032
Keywords: adolescence, social media, mental health, media addiction, well-being, review, Covid-19 pandemic
Citation: Marciano L, Ostroumova M, Schulz PJ and Camerini A-L (2022) Digital Media Use and Adolescents' Mental Health During the Covid-19 Pandemic: A Systematic Review and Meta-Analysis. Front. Public Health 9:793868. doi: 10.3389/fpubh.2021.793868
Received: 12 October 2021; Accepted: 08 December 2021;
Published: 01 February 2022.
Edited by:Giorgio Di Lorenzo, University of Rome Tor Vergata, Italy
Reviewed by:Chidiebere Emmanuel Okechukwu, Sapienza University of Rome, Italy
Maria Signorelli, University of Catania, Italy
Copyright © 2022 Marciano, Ostroumova, Schulz and Camerini. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Laura Marciano, email@example.com