Digital media use by adolescents is both widespread and frequent. In the United Kingdom (UK), 99% of 12- to 15-year-olds go online, for an average of 20 h a week, double the frequency of ten years ago (Ofcom, 2019). Over the same years that digital media use grew (primarily after 2010), the prevalence of emotional problems and depression (Fink et al., 2015; Patalay & Gage, 2019), non-fatal self-harm (Morgan et al., 2017) increased among adolescents in the UK, especially among girls. Given the parallel increases in social media use and mental health problems, several researchers have speculated that these troubling trends in mental health may be connected to the increasingly frequent use of digital media (Keyes et al., 2019; Luby & Kertz, 2019; Spiller et al., 2019; Twenge, 2019).

The public health and economic consequences of depression and self-harm are considerable, with negative effects including functional impairment, reduced quality of life, disability, low work productivity, premature mortality, and increased health care utilization (Cooper et al., 2005; Evans-Lacko & Knapp, 2016; Mangnall & Yurkovich, 2008; Mrazek et al., 2014). Given these substantial consequences and the co-occurring increases in screen media use, depression, and self-harm, this study focused on links between screen media use and rates of depression and self-harm. Note that the current study is unable to parse whether self-harm occurred with or without suicidal intent; this study and broadly defines self-harm as an intentional act of hurting oneself regardless of suicidal intention, though it is important to recognize that self-harm with vs. without suicidal intent can have drastically different antecedents and outcomes (Mangnall & Yurkovich, 2008).

Numerous cross-sectional studies, as well as several longitudinal studies, find that heavy users of digital media are more likely to have mental health issues (e.g., Kelly et al., 2019; Lin et al., 2016; Madhav et al., 2017; Twenge and Campbell, 2018; for a review, see Twenge, 2019). However, several recent studies have concluded that the associations are too small to be meaningful (Barryman et al., 2017; Ferguson, 2017; Orben & Przybylski, 2019a, 2019b; Przybylski & Weinstein, 2017), suggesting more research is needed to determine the size and importance of effects in this area. Longitudinal studies examining associations between digital media use and depressive symptoms have revealed both positive and some null associations (Coyne et al., 2020; Khouja et al., 2019; Marino et al., 2018). Similarly, systematic reviews have found potential for both detrimental and protective effects of screen media use on self-harm (Biernesser et al., 2020; Marchant et al., 2017).

Thus far, most research has examined technology use through retrospective self-report surveys, which may be subject to recall biases and other issues (Wonneberger & Irazoqui, 2017). Thus, retrospective reports may not accurately represent the actual amount of time spent on screen activities (Scharkow, 2016), with heavy users underestimating their time and light users overestimating (Araujo et al., 2017). In contrast, time diaries, which ask participants to contemporaneously report their activities on a given day (Iida et al., 2012), may provide a more accurate picture of participants’ time use (Booker et al., 2015; Stone & Shiffman, 2002; Walentynowicz et al., 2018). In this paper, we examine associations between depressive symptoms and self-harm behaviors (irrespective of suicidal and non-suicidal intent) and contemporaneous reports of screen technology use based on time diaries. We undertake this analysis with a nationally representative sample of adolescents in the UK larger than those employed in most time diary studies.

We also advance the literature by examining two important aspects of media use and mental health: Type of screen time and gender. First, we examine digital media use (including social media, gaming, and internet use) separately from TV/video watching, as well as examine each digital media activity separately. Several recent studies examining associations with well-being treated screen time monolithically (Orben & Przybylski, 2019a, b). Combining all screen time together may obscure meaningful associations, as some activities may be more strongly associated with mental health issues than others. For example, given the potential mental health impacts of cyberbullying, upward social comparison, and body image pressures (John et al., 2018; Steers et al., 2014), spending 3 h/day on social media may be more strongly associated with mental health issues than spending 3 h/day watching TV/videos (Twenge & Farley, 2021). In other words, all screen time may not be created equal, and it is imperative to take a more granular approach to examining associations between screen time and mental health (Christakis, 2019), especially given key differences among activities (McFarland & Ployhart, 2015).

Second, we examine associations for boys and girls separately, as most large studies have not taken this step. When data for boys and girls are analyzed together, it may obscure potentially meaningful associations that may appear only for one gender or the other. Girls are more frequent users of social media (Twenge & Martin, 2020), and their mental health tends to be more influenced by interpersonal events than boys’ (Flook, 2011), including online events (Nesi & Prinstein, 2015; Yau & Reich, 2019). Girls may also be more susceptible to social contagion aspects of self-harm behaviors (Prinstein et al., 2010), which increasingly occurs online (Spiller et al., 2019). Adolescent females in the UK also report engaging in self-harm behaviors more often than adolescent males (Hawton et al., 2002, 2007; Ohlis et al., 2020). These factors, as well as the more pronounced increases in mental health issues among girls since 2010, suggest associations will be larger for girls than for boys. Thus, we hypothesize that the associations between digital media use and mental health will be larger and more robust for social media compared to other activities, and larger and more robust for girls than for boys.

Methods

Participants

The Millennium Cohort Study (MCS) is a nationally representative sample of the cohort of children born in the UK between September 2000 and January 2002. Human subjects review board approval was obtained by the study administrators, the Centre for Longitudinal Studies at the University of London (https://cls.ucl.ac.uk/wp-content/uploads/2017/07/MCS-Ethical-review-and-consent-Shepherd-P-November-2012.pdf). Families were found using a list generated from the Child Benefit register provided by the UK Department for Work and Pensions (DWP), and consent was obtained via an opt out procedure after the DWP wrote to all families. Of the families identified and selected at the birth of their children, 61% continued to participate by the sixth wave of data collection in 2015 when participants were approximately 14 years old. During this wave, some adolescents were asked to keep time diaries (Centre for Longitudinal Studies, 2018). We included only the first child surveyed in the household, excluding the small number of multiple and close births, consistent with other research using the MCS (Kelly et al., 2019). After completing the main portion of the survey with demographic questions and the mental health measures, a randomly selected subsample of participants in the main survey were sent text messages asking them to complete a time diary on one weekday and one weekend day randomly-selected within 10 days of completing the rest of the questionnaire. The time diary specified activities occurring from 4:00am one day to 4:00am the next day. Participants could complete the time diaries online, via an app, or on paper. Total n was 4,243 for weekdays and 4,252 for weekend days (for boys, n = 1,928 for weekdays and n = 1,944 for weekend days; for girls, n = 2,315 for weekdays and n = 2,308 for weekend days). Average age was 13.75 (SD = 0.46; range 13 to 15); participants were 45% male.

Measures

Screen media use. Adolescents selected one of 37 activity codes for each 10-min time slot. This “light” closed-ended format reduces participant burden (Chatzitheochari et al., 2018). The activities included a comprehensive list of ways adolescents might spend their time, including choices such as homework, pet care, eating, personal care, doing chores, and specific types of exercise. We examined the 5 activities on the list that involved screen media: “answering emails, instant messaging, texting” (texting/e-mailing), “browsing and updating social networking sites” (social media), “general internet browsing, programming” (internet use), “playing electronic games and apps” (gaming) and “watching TV, DVDs, downloaded videos” (TV/videos). We added together time spent e-mailing and texting, social media, internet use, and gaming to examine digital media use separately from TV/videos (as TV is an older technology and not digital media per se). We also examined each type of digital media to examine differences in specific types of screen use (i.e., social media use versus gaming). Additionally, recommendations for limiting screen media use in children to two hours were used to make informed dichotomous variables to demonstrate clinical significance of associations (American Heart Association, 2018; Council on Communications & Media, 2013, Tremblay et al., 2011).

Specifically, we began by comparing those spending 2 or more hrs/day on screen activities with those spending less than 2 h/day. Because heavy use may be more problematic than moderate use (Twenge & Campbell, 2018), we also examined levels of use up to 5 or more hours a day.

Depression and self-harm. MCS included a question on self-harm behaviors: “In the past year have you hurt yourself on purpose in any way?” with response choices of “yes” or “no.” Thus, both suicidal and non-suicidal behaviors are included in this question. Participants also completed the short version of the Mood and Feelings Questionnaire (SMFQ) (Angold et al., 1995), a 13-item measure of depressive symptoms in the last two weeks (Cronbach alpha = 0.93). Because depression scores were highly skewed, we dichotomized the depression data based upon the established score of 12 or over which indicates clinically relevant depressive symptoms (Thabrew et al., 2018). This sixth wave is the first time these measures were included.

Control variables. We included demographic control variables used in previous research with this dataset (Kelly et al., 2019; Orben & Przybylski, 2019a): Child’s age, yearly family income (equivalized fifths for the UK), natural father present in the household, child’s ethnicity (White vs. non-White), the age the primary caregiver left formal education, the primary caregiver’s employment (yes or no), number of siblings of the child in the household, whether the child has a long-standing illness (yes or no), and the primary caregiver’s vocabulary word score (a measure of verbal intelligence).

Data analysis plan

First, we examined sex differences in the amount of time spent on the screen time activities. Due to large sample size and the robustness of one-way ANOVAs to normality concerns, we considered the normality assumption met. To address the unequal variances, we utilized Welch’s test for significance testing in Table 1. Next, we tested whether associations between digital media time and self-harm/depression were moderated by sex. All subsequent analyses were conducted separately for boys and girls. For all analyses, missing data was not imputed. Given current (American Heart Association, 2018) and past (Council on Communications & Media, 2013) recommendations for screen media use, we began by comparing those spending 2 or more hrs/day on screen activities with those spending less than 2 h/day, including all digital media use combined (including social media, gaming, texting/e-mailing, and internet use) as well as on each specific activity. We then examined the exposure–response curves for total digital media use (comparing up to 5 + hrs/day of use, with categories based on Kelly et al., 2019 and the verification of sufficient n within each cell) and the three screen activities with the highest levels of engagement (there were not a sufficient number of adolescents who engaged in specific activities for 4 + hrs/day, leading to insufficient n at higher levels of use, so we used 3 + hrs/day as the maximum category). We determined exposure–response curve cutoffs by balancing specificity with having sufficient n to make comparisons (> 50, and preferably > 100). We rely primarily on relative risk (RR) and adjusted relative risk (ARR) using the control variables.

Table 1 Hours per day spent on screen media in time diaries and mental health variables, boys vs. girls
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Results

Table 1 presents gender differences in media activities and the percentage of youth engaging in two hours or more of media use activities. There were significant gender differences in the amount of time adolescents spent on screen media activities in time diary reports. Boys spent more time on digital media overall (social media, gaming, texting/e-mailing, and internet use combined, Mdiff = 1.26 h, p < 0.001), more time on gaming (Mdiff = 1.57 h, p < 0.001) and slightly more time on the internet (Mdiff = 0.10 h, p < 0.001), while girls spent more time on social media (Mdiff = -0.37 h, p < 0.001). However, there were no significant gender differences in time spent texting/emailing or TV/video watching. Of note, twice as many boys as girls used digital media more than 2 h a day (boys 49% vs. girls 21%, p < 0.001). The majority of girls used social media for about 1 h per day, with a minority (~10%) using social media for 2 h or more. Overall, 20% of girls met criteria for clinically-significant depressive symptoms or engaged in self-harm, compared to approximately 7–8% of boys.

Total time spent on digital media activities was positively correlated with self-harm and depression, and these correlations were moderated by sex, with significant interaction terms (see Table 2). Probing these interactions revealed that when predicting depression, slopes for both girls and boys were significant (girls B = 0.61, p < 0.001, boys B = 0.11, p < 0.05); however, slopes for girls were significantly greater than slopes for boys (see Fig. 1). Probing these interactions also revealed that when predicting self-harm, the slope for girls was significant (B = 0.03, p < 0.001); results were not significant for the slope for boys in this case (see Fig. 2). Below, we detail the associations between screen time and mental health issues separately for girls and boys.

Table 2 Standardized betas in regression equations including digital media time (hours per day), sex, and their interaction term to predict self-harm and depressive symptoms
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Fig. 1
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Interaction effects for percent with clinically relevant symptoms of depression and low or high digital media usage, by gender

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Fig. 2
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Interaction effects for percent who have self-harmed in the last year and low or high digital media usage, by gender

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Associations for girls

Girls who used digital media more than 2 h/day were significantly more likely to self-harm or have clinically significant symptoms of depression compared to those using digital media less than 2 h/day (see Table 3). For specific digital media activities, significant associations appeared for use of social media and internet use of < 2 h/day compared to 2 + hrs/day. Gaming, texting/emailing, or TV/video watching < 2 h/day vs. 2 + hrs/day were not significantly associated with depressive symptoms or self-harm among girls (see Table 3). Thus, associations between digital media use and mental health among girls were driven primarily by social media and internet use.

Table 3 Percent and n, unadjusted and adjusted relative risk (RR), and 95% CI for use < 2 h/day and 2 + hrs/day, girls
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Next, we examined the exposure–response curves capturing the range of hrs/day of screen time as measured by time diaries. We began by examining total digital media use (social media, gaming, texting/e-mailing, and internet use combined). Consistent with previous research, associations were curvilinear (Przybylski & Weinstein, 2017; Twenge & Campbell, 2018), with depression and self-harm least prevalent at light use rather than no use. After use of an hour a day, associations between digital media use and depression and self-harm for girls followed a fairly linear exposure–response curve (e.g., see Fig. 3 for self-harm and Fig. 4 for depression).

Fig. 3
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Percent who have self-harmed in the last year, by hours a day of digital media use in time diaries, by gender. NOTES: Numbers are adjusted for child’s age, yearly family income, Natural father presence in household, child’s ethnicity, parent’s education level, parent’s employment status, number of siblings, long standing illness status, and primary caregiver’s vocabulary (verbal intelligence). Sample size information for each Digital Media Use group can be found in table S1

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Fig. 4
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Percent with clinically relevant symptoms of depression by hours a day of digital media use in time diaries, by gender. NOTES: Numbers are adjusted for child’s age, yearly family income, Natural father presence in household, child’s ethnicity, parent’s education level, parent’s employment status, number of siblings, long standing illness status, and primary caregiver’s vocabulary (verbal intelligence). Sample size information for each Digital Media Use group can be found in table S2

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Girls who spent 5 + hrs/day on digital media (heavy users, n = 71) were the most likely to be depressed (31%) and those who spent < 1 h/day (light users, n = 768) were the least likely (19%), ARR = 1.65 (1.13, 2.41). Results were not significant for self-harm.

Next, we examined the exposure–response curves for social media, gaming, and TV, the three screen media activities with the highest levels of engagement. Associations with mental health were strongest for social media (see Figs. 5 and 6).

Fig. 5
figure 5

Percent who have self-harmed in the last year, by hours a day of types of screen media use, by gender. NOTES: Numbers are adjusted for child’s age, yearly family income, Natural father presence in household, child’s ethnicity, parent’s education level, parent’s employment status, number of siblings, long standing illness status, and primary caregiver’s vocabulary (verbal intelligence). Standard error and sample size information for each group can be found in table S3

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Fig. 6
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Percent with clinically relevant symptoms of depression by hours a day of types of screen media use, by gender. NOTES: Numbers are adjusted for child’s age, yearly family income, Natural father presence in household, child’s ethnicity, parent’s education level, parent’s employment status, number of siblings, long standing illness status, and primary caregiver’s vocabulary (verbal intelligence). Standard error and sample size information for each group can be found in table S4

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Girls who spent 3 + hrs/day on social media (n = 92) were the most likely to self-harm (29%) and those who spent < 1 h/day (n = 852) were the least likely (19%), ARR = 1.56 (1.10, 2.21). Results were similar for depressive symptoms, 31% vs. 19%, ARR = 1.66 (1.18, 2.32).

Comparisons of mental health at both light and heavy levels of gaming and light and heavy levels of TV/video watching among girls were not significant.

Associations for boys

In contrast to the results for girls, boys demonstrated few consistent associations between spending 2 + hrs/day on digital media vs. 2 h/day or less and self-harm or depressive symptoms (see Table 4 and Figs. 3 and 4). Comparisons of light (1 h/day, n = 301) and heavy digital media users (5 + hrs/day, n = 296) were not significant.

Table 4 Percent and n, unadjusted and adjusted relative risk (RR), and 95% CI for use < 2 h/day and 2 + hrs/day, boys
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Comparisons of mental health issues among light vs. heavy users of social media, gaming, and TV/video use were also not significant among boys, where there was not an evident exposure–response curve as there was among girls (see Figs. 5 and 6).

Discussion

In a nationally representative sample of UK adolescents who completed contemporaneous time diaries of their activities, digital media use was consistently associated with (suicidal and non-suicidal) self-harm and depressive symptoms among girls, but only rarely among boys. Associations for girls were most consistent for social media use and internet use, with some role for texting/e-mailing. With a few exceptions, TV/video use and gaming were not associated with depressive symptoms or self-harm.

Thus, not all screen time is created equal, and not all screen time has equal associations with mental health issues for boys and girls. The bulk of the association with depression and self-harm appears for social media and internet use among girls. These activities may have a negative impact on mental health via mechanisms such as cyberbullying, body image, or displacement of face-to-face social interaction, to which girls may be more susceptible (Nesi & Prinstein, 2015). In contrast, few significant associations with depression and self-harm appeared for boys, even though boys spend a considerable amount of time on gaming in particular. That may have occurred because gaming is more often conducted in real time with voice communication among players (McFarland & Ployhart, 2015). It is also possible that gaming is more associated with externalizing issues rather than the internalizing issues explored in the current research (e.g., Prescott et al., 2018). However, smaller sample sizes and less precise estimates at higher screen usage could affect the significance of associations and comparisons.

These results provide valuable information towards understanding inconsistent results in associations between screen time and well-being in prior research. When all screen time is combined together and data are not divided by gender, significant effects may be obscured. Yet when social media, texting, and internet use are isolated and the data are examined separately by gender, larger associations between social media use and mental health emerge, especially among girls.

A key limitation of this study is that data are cross-sectional and directionality of the association cannot be ascertained. Digital media use could cause depression or self-harm, or depression or self-harm could cause more digital media use. Reciprocal relationships may also exist, in which girls who self-harm use more social media, which then further exacerbates their self-harm. Although the current study cannot disentangle the directionality, two random-controlled experimental trials found that limiting social media use lowered depression (Hunt et al., 2018; Tromholt, 2016) and a third found that using social media for just 20 min resulted in lower positive mood (Yuen et al., 2019). A recent, large longitudinal study found that social media use predicted later internalizing symptoms even when previous symptoms were controlled (Riehm et al., 2019). Even if reverse causation is occurring, caregivers and physicians should be aware that heavy users of social media and the internet – particularly girls – are more likely to self-harm and have clinically relevant symptoms of depression. It is important to note that the majority of adolescent girls did not use social media for 2 h or more per day, suggesting that those who do may represent a clinically-significant minority.

Another limitation is that adolescents only kept time diaries for one weekday and one weekend day. Time diary measurements are generally more reliable when kept for more days (Iida et al., 2012), as any one day might not be typical of adolescents’ overall use and introduces error variance. Thus, future research should explore associations between mental health and screen media use measured with a larger number of time-diary days. In addition, this limitation suggests caution in interpreting findings inconsistent with studies based on retrospective reports of screen media use, which usually ask about use on a typical day; these studies have, for example, identified significant associations between mental health issues and TV/video watching and electronic gaming as well as associations among boys (Primack et al., 2009; Przybylski & Weinstein, 2017; Twenge & Farley, 2021). Future research should use smartphone tracking apps that objectively record how much time participants spend on certain digital media activities (particularly if the apps can be employed across all devices used by the participants).

In addition, we did not examine associations with other facets of well-being that may be linked to digital media use among both girls and boys, including shortened sleep, anger issues, aggressive behavior, or compromised academic performance. Further, our study did not examine the device used for media activities (i.e., smartphone, tablet, game console, television), so it is not possible to know whether similar devices were used for various screen time activities. As mentioned earlier, another limitation is that self-harm with vs. without suicidal intent can have drastically different antecedents and outcomes (Mangnall & Yurkovich, 2008). Future studies should also have more comprehensive measures of self-harm to identify the type, severity, and intent (i.e., non-suicidal self-injury vs suicidal behavior) of self-harm among adolescents. These aspects of self-harm may provide more insight into potential mechanisms underlying the association between social media and self-harm in girls. Also, the survey assessed sex/gender only as male and female, which does not allow the examination of gender queer or nonbinary individuals. Another limitation is in the differing time scales of the mental health measures; depressive symptoms were measured within the last two weeks, but self-harm was measured within the last year.

The sharp increases in depression and self-harm among adolescents since 2012 in the UK have been most pronounced among girls (Morgan et al., 2017). If these mental health trends are associated with increased technology use, particularly with social media use (Luby & Kertz, 2019), the increase in social media use over this time may have a larger impact on girls’ mental health. The current study furthers our understanding of these relationships by demonstrating a unique association between social media use and depression and self-harm among adolescent girls. Future research is needed to examine the directionality of this relationship to inform public policy, intervention, and prevention programs and bend the curve on increasing rates of depression, self-harm, and suicide among adolescent girls.