research report on social media

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• Published: 01 July 2020

The effect of social media on well-being differs from adolescent to adolescent

• Ine Beyens   ORCID: orcid.org/0000-0001-7023-867X 1 ,
• J. Loes Pouwels   ORCID: orcid.org/0000-0002-9586-392X 1 ,
• Irene I. van Driel   ORCID: orcid.org/0000-0002-7810-9677 1 ,
• Loes Keijsers   ORCID: orcid.org/0000-0001-8580-6000 2 &
• Patti M. Valkenburg   ORCID: orcid.org/0000-0003-0477-8429 1  

Scientific Reports volume  10 , Article number:  10763 ( 2020 ) Cite this article

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The question whether social media use benefits or undermines adolescents’ well-being is an important societal concern. Previous empirical studies have mostly established across-the-board effects among (sub)populations of adolescents. As a result, it is still an open question whether the effects are unique for each individual adolescent. We sampled adolescents’ experiences six times per day for one week to quantify differences in their susceptibility to the effects of social media on their momentary affective well-being. Rigorous analyses of 2,155 real-time assessments showed that the association between social media use and affective well-being differs strongly across adolescents: While 44% did not feel better or worse after passive social media use, 46% felt better, and 10% felt worse. Our results imply that person-specific effects can no longer be ignored in research, as well as in prevention and intervention programs.

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Introduction.

Ever since the introduction of social media, such as Facebook and Instagram, researchers have been studying whether the use of such media may affect adolescents’ well-being. These studies have typically reported mixed findings, yielding either small negative, small positive, or no effects of the time spent using social media on different indicators of well-being, such as life satisfaction and depressive symptoms (for recent reviews, see for example 1 , 2 , 3 , 4 , 5 ). Most of these studies have focused on between-person associations, examining whether adolescents who use social media more (or less) often than their peers experience lower (or higher) levels of well-being than these peers. While such between-person studies are valuable in their own right, several scholars 6 , 7 have recently called for studies that investigate within-person associations to understand whether an increase in an adolescent’s social media use is associated with an increase or decrease in that adolescent’s well-being. The current study aims to respond to this call by investigating associations between social media use and well-being within single adolescents across multiple points in time 8 , 9 , 10 .

Person-specific effects

To our knowledge, four recent studies have investigated within-person associations of social media use with different indicators of adolescent well-being (i.e., life satisfaction, depression), again with mixed results 6 , 11 , 12 , 13 . Orben and colleagues 6 found a small negative reciprocal within-person association between the time spent using social media and life satisfaction. Likewise, Boers and colleagues 12 found a small within-person association between social media use and increased depressive symptoms. Finally, Coyne and colleagues 11 and Jensen and colleagues 13 did not find any evidence for within-person associations between social media use and depression.

Earlier studies that investigated within-person associations of social media use with indicators of well-being have all only reported average effect sizes. However, it is possible, or even plausible, that these average within-person effects may have been small and nonsignificant because they result from sizeable heterogeneity in adolescents’ susceptibility to the effects of social media use on well-being (see 14 , 15 ). After all, an average within-person effect size can be considered an aggregate of numerous individual within-person effect sizes that range from highly positive to highly negative.

Some within-person studies have sought to understand adolescents’ differential susceptibility to the effects of social media by investigating differences between subgroups. For instance, they have investigated the moderating role of sex to compare the effects of social media on boys versus girls 6 , 11 . However, such a group-differential approach, in which potential differences in susceptibility are conceptualized by group-level moderators (e.g., gender, age) does not provide insights into more fine-grained differences at the level of the single individual 16 . After all, while girls and boys each represent a homogenous group in terms of sex, they may each differ on a wide array of other factors.

As such, although worthwhile, the average within-person effects of social media on well-being obtained in previous studies may have been small or non-significant because they are diluted across a highly heterogeneous population (or sub-population) of adolescents 14 , 15 . In line with the proposition of media effects theories that each adolescent may have a unique susceptibility to the effects of social media 17 , a viable explanation for the small and inconsistent findings in earlier studies may be that the effect of social media differs from adolescent to adolescent. The aim of the current study is to investigate this hypothesis and to obtain a better understanding of adolescents’ unique susceptibility to the effects of social media on their affective well-being.

Social media and affective well-being

Within-person studies have provided important insights into the associations of social media use with cognitive well-being (e.g., life satisfaction 6 ), which refers to adolescents’ cognitive judgment of how satisfied they are with their life 18 . However, the associations of social media use with adolescents’ affective well-being (i.e., adolescents’ affective evaluations of their moods and emotions 18 ) are still unknown. In addition, while earlier within-person studies have focused on associations with trait-like conceptualizations of well-being 11 , 12 , 13 , that is, adolescents’ average well-being across specific time periods 18 , there is a lack of studies that focus on well-being as a momentary affective state. Therefore, we extend previous research by examining the association between adolescents’ social media use and their momentary affective well-being. Like earlier experience sampling (ESM) studies among adults 19 , 20 , we measured adolescents’ momentary affective well-being with a single item. Adolescents’ momentary affective well-being was defined as their current feelings of happiness, a commonly used question to measure well-being 21 , 22 , which has high convergent validity, as evidenced by the strong correlations with the presence of positive affect and absence of negative affect.

To assess adolescents’ momentary affective well-being (henceforth referred to as well-being), we conducted a week-long ESM study among 63 middle adolescents ages 14 and 15. Six times a day, adolescents were asked to complete a survey using their own mobile phone, covering 42 assessments per adolescent, assessing their affective well-being and social media use. In total, adolescents completed 2,155 assessments (83.2% average compliance).

We focused on middle adolescence, since this is the period in life characterized by most significant fluctuations in well-being 23 , 24 . Also, in comparison to early and late adolescents, middle adolescents are more sensitive to reactions from peers and have a strong tendency to compare themselves with others on social media and beyond. Because middle adolescents typically use different social media platforms, in a complementary way 25 , 26 , 27 , each adolescent reported on his/her use of the three social media platforms that s/he used most frequently out of the five most popular social media platforms among adolescents: WhatsApp, followed by Instagram, Snapchat, YouTube, and, finally, the chat function of games 28 . In addition to investigating the association between overall social media use and well-being (i.e., the summed use of adolescents’ three most frequently used platforms), we examined the unique associations of the two most popular platforms, WhatsApp and Instagram 28 .

Like previous studies on social media use and well-being, we distinguished between active social media use (i.e., “activities that facilitate direct exchanges with others” 29 ) and passive social media use (i.e., “consuming information without direct exchanges” 29 ). Within-person studies among young adults have shown that passive but not active social media use predicts decreases in well-being 29 . Therefore, we examined the unique associations of adolescents’ overall active and passive social media use with their well-being, as well as active and passive use of Instagram and WhatsApp, specifically. We investigated categorical associations, that is, whether adolescents would feel better or worse if they had actively or passively used social media. And we investigated dose–response associations to understand whether adolescents’ well-being would change as a function of the time they had spent actively or passively using social media.

The hypotheses and the design, sampling and analysis plan were preregistered prior to data collection and are available on the Open Science Framework, along with the code used in the analyses ( https://osf.io/nhks2 ). For details about the design of the study and analysis approach, see Methods.

In more than half of all assessments (68.17%), adolescents had used social media (i.e., one or more of their three favorite social media platforms), either in an active or passive way. Instagram (50.90%) and WhatsApp (53.52%) were used in half of all assessments. Passive use of social media (66.21% of all assessments) was more common than active use (50.86%), both on Instagram (48.48% vs. 20.79%) and WhatsApp (51.25% vs. 40.07%).

Strong positive between-person correlations were found between the duration of active and passive social media use (overall: r  = 0.69, p  < 0.001; Instagram: r  = 0.38, p  < 0.01; WhatsApp: r  = 0.85, p  < 0.001): Adolescents who had spent more time actively using social media than their peers, had also spent more time passively using social media than their peers. Likewise, strong positive within-person correlations were found between the duration of active and passive social media use (overall: r  = 0.63, p  < 0.001; Instagram: r  = 0.37, p  < 0.001; WhatsApp: r  = 0.57, p  < 0.001): The more time an adolescent had spent actively using social media at a certain moment, the more time s/he had also spent passively using social media at that moment.

Table 1 displays the average number of minutes that adolescents had spent using social media in the past hour at each assessment, and the zero-order between- and within-person correlations between the duration of social media use and well-being. At the between-person level, the duration of active and passive social media use was not associated with well-being: Adolescents who had spent more time actively or passively using social media than their peers did not report significantly higher or lower levels of well-being than their peers. At the within-person level, significant but weak positive correlations were found between the duration of active and passive overall social media use and well-being. This indicates that adolescents felt somewhat better at moments when they had spent more time actively or passively using social media (overall), compared to moments when they had spent less time actively or passively using social media. When looking at specific platforms, a positive correlation was only found for passive WhatsApp use, but not for active WhatsApp use, and not for active and passive Instagram use.

Average and person-specific effects

The within-person associations of social media use with well-being and differences in these associations were tested in a series of multilevel models. We ran separate models for overall social media use (i.e., active use and passive use of adolescents’ three favorite social media platforms, see Table 2 ), Instagram use (see Table 3 ), and WhatsApp use (see Table 4 ). In a first step we examined the average categorical associations for each of these three social media uses using fixed effects models (Models 1A, 3A, and 5A) to investigate whether, on average, adolescents would feel better or worse at moments when they had used social media compared to moments when they had not (i.e., categorical predictors: active use versus no active use, and passive use versus no passive use). In a second step, we examined heterogeneity in the within-person categorical associations by adding random slopes to the fixed effects models (Models 1B, 3B, and 5B). Next, we examined the average dose–response associations using fixed effects models (Models 2A, 4A, and 6A), to investigate whether, on average, adolescents would feel better or worse when they had spent more time using social media (i.e., continuous predictors: duration of active use and duration of passive use). Finally, we examined heterogeneity in the within-person dose–response associations by adding random slopes to the fixed effects models (Models 2B, 4B, and 6B).

Overall social media use.

The model with the categorical predictors (see Table 2 ; Model 1A) showed that, on average, there was no association between overall use and well-being: Adolescents’ well-being did not increase or decrease at moments when they had used social media, either in a passive or active way. However, evidence was found that the association of passive (but not active) social media use with well-being differed from adolescent to adolescent (Model 1B), with effect sizes ranging from − 0.24 to 0.68. For 44.26% of the adolescents the association was non-existent to small (− 0.10 <  r  < 0.10). However, for 45.90% of the adolescents there was a weak (0.10 <  r  < 0.20; 8.20%), moderate (0.20 <  r  < 0.30; 22.95%) or even strong positive ( r  ≥ 0.30; 14.75%) association between overall passive social media use and well-being, and for almost one in ten (9.84%) adolescents there was a weak (− 0.20 <  r  < − 0.10; 6.56%) or moderate negative (− 0.30 <  r  < − 0.20; 3.28%) association.

The model with continuous predictors (Model 2A) showed that, on average, there was a significant dose–response association for active use. At moments when adolescents had used social media, the time they spent actively (but not passively) using social media was positively associated with well-being: Adolescents felt better at moments when they had spent more time sending messages, posting, or sharing something on social media. The associations of the time spent actively and passively using social media with well-being did not differ across adolescents (Model 2B).

Instagram use

As shown in Model 3A in Table 3 , on average, there was a significant categorical association between passive (but not active) Instagram use and well-being: Adolescents experienced an increase in well-being at moments when they had passively used Instagram (i.e., viewing posts/stories of others). Adolescents did not experience an increase or decrease in well-being when they had actively used Instagram. The associations of passive and active Instagram use with well-being did not differ across adolescents (Model 3B).

On average, no significant dose–response association was found for Instagram use (Model 4A): At moments when adolescents had used Instagram, the time adolescents spent using Instagram (either actively or passively) was not associated with their well-being. However, evidence was found that the association of the time spent passively using Instagram differed from adolescent to adolescent (Model 4B), with effect sizes ranging from − 0.48 to 0.27. For most adolescents (73.91%) the association was non-existent to small (− 0.10 <  r  < 0.10), but for almost one in five adolescents (17.39%) there was a weak (0.10 <  r  < 0.20; 10.87%) or moderate (0.20 <  r  < 0.30; 6.52%) positive association, and for almost one in ten adolescents (8.70%) there was a weak (− 0.20 <  r  < − 0.10; 2.17%), moderate (− 0.30 <  r  < − 0.20; 4.35%), or strong ( r  ≤ − 0.30; 2.17%) negative association. Figure  1 illustrates these differences in the dose–response associations.

The dose–response association between passive Instagram use (in minutes per hour) and affective well-being for each individual adolescent (n = 46). Red lines represent significant negative within-person associations, green lines represent significant positive within-person associations, and gray lines represent non-significant within-person associations. A graph was created for each participant who had completed at least 10 assessments. A total of 13 participants were excluded because they had completed less than 10 assessments of passive Instagram use. In addition, one participant was excluded because no graph could be computed, since this participant's passive Instagram use was constant across assessments.

WhatsApp use

As shown in Model 5A in Table 4 , just as for Instagram, we found that, on average, there was a significant categorical association between passive (but not active) WhatsApp use and well-being: Adolescents reported that they felt better at moments when they had passively used WhatsApp (i.e., read WhatsApp messages). For active WhatsApp use, no significant association was found. Also, in line with the results for Instagram use, no differences were found regarding the associations of active and passive WhatsApp use (Model 5B).

In addition, a significant dose–response association was found for passive (but not active) use (Model 6A). At moments when adolescents had used WhatsApp, we found that, on average, the time adolescents spent passively using WhatsApp was positively associated with well-being: Adolescents felt better at moments when they had spent more time reading WhatsApp messages. The time spent actively using WhatsApp was not associated with well-being. No differences were found in the dose–response associations of active and passive WhatsApp use (Model 6B).

This preregistered study investigated adolescents’ unique susceptibility to the effects of social media. We found that the associations of passive (but not active) social media use with well-being differed substantially from adolescent to adolescent, with effect sizes ranging from moderately negative (− 0.24) to strongly positive (0.68). While 44.26% of adolescents did not feel better or worse if they had passively used social media, 45.90% felt better, and a small group felt worse (9.84%). In addition, for Instagram the majority of adolescents (73.91%) did not feel better or worse when they had spent more time viewing post or stories of others, whereas some felt better (17.39%), and others (8.70%) felt worse.

These findings have important implications for social media effects research, and media effects research more generally. For decades, researchers have argued that people differ in their susceptibility to the effects of media 17 , leading to numerous investigations of such differential susceptibility. These investigations have typically focused on moderators, based on variables such as sex, age, or personality. Yet, over the years, studies have shown that such moderators appear to have little power to explain how individuals differ in their susceptibility to media effects, probably because a group-differential approach does not account for the possibility that media users may differ across a range of factors, that are not captured by only one (or a few) investigated moderator variables.

By providing insights into each individual’s unique susceptibility, the findings of this study provide an explanation as to why, up until now, most media effects research has only found small effects. We found that the majority of adolescents do not experience any short-term changes in well-being related to their social media use. And if they do experience any changes, these are more often positive than negative. Because only small subsets of adolescents experience small to moderate changes in well-being, the true effects of social media reported in previous studies have probably been diluted across heterogeneous samples of individuals that differ in their susceptibility to media effects (also see 30 ). Several scholars have noted that overall effect sizes may mask more subtle individual differences 14 , 15 , which may explain why previous studies have typically reported small or no effects of social media on well-being or indicators of well-being 6 , 11 , 12 , 13 . The current study seems to confirm this assumption, by showing that while the overall effect sizes are small at best, the person-specific effect sizes vary considerably, from tiny and small to moderate and strong.

As called upon by other scholars 5 , 31 , we disentangled the associations of active and passive use of social media. Research among young adults found that passive (but not active) social media use is associated with lower levels of affective well-being 29 . In line with these findings, the current study shows that active and passive use yielded different associations with adolescents’ affective well-being. Interestingly though, in contrast to previous findings among adults, our study showed that, on average, passive use of Instagram and WhatsApp seemed to enhance rather than decrease adolescents’ well-being. This discrepancy in findings may be attributed to the fact that different mechanisms might be involved. Verduyn and colleagues 29 found that passive use of Facebook undermines adults’ well-being by enhancing envy, which may also explain the decreases in well-being found in our study among a small group of adolescents. Yet, adolescents who felt better by passively using Instagram and WhatsApp, might have felt so because they experienced enjoyment. After all, adolescents often seek positive content on social media, such as humorous posts or memes 32 . Also, research has shown that adolescents mainly receive positive feedback on social media 33 . Hence, their passive Instagram and WhatsApp use may involve the reading of positive feedback, which may explain the increases in well-being.

Overall, the time spent passively using WhatsApp improved adolescents’ well-being. This did not differ from adolescent to adolescent. However, the associations of the time spent passively using Instagram with well-being did differ from adolescent to adolescent. This discrepancy suggests that not all social media uses yield person-specific effects on well-being. A possible explanation may be that adolescents’ responses to WhatsApp are more homogenous than those to Instagram. WhatsApp is a more private platform, which is mostly used for one-to-one communication with friends and acquaintances 26 . Instagram, in contrast, is a more public platform, which allows its users to follow a diverse set of people, ranging from best friends to singers, actors, and influencers 28 , and to engage in intimate communication as well as self-presentation and social comparison. Such diverse uses could lead to more varied, or even opposing responses, such as envy versus inspiration.

Limitations and directions for future research

The current study extends our understanding of differential susceptibility to media effects, by revealing that the effect of social media use on well-being differs from adolescent to adolescent. The findings confirm our assumption that among the great majority of adolescents, social media use is unrelated to well-being, but that among a small subset, social media use is either related to decreases or increases in well-being. It must be noted, however, that participants in this study felt relatively happy, overall. Studies with more vulnerable samples, consisting of clinical samples or youth with lower social-emotional well-being may elicit different patterns of effects 27 . Also, the current study focused on affective well-being, operationalized as happiness. It is plausible that social media use relates differently with other types of well-being, such as cognitive well-being. An important next step is to identify which adolescents are particularly susceptible to experience declines in well-being. It is conceivable, for instance, that the few adolescents who feel worse when they use social media are the ones who receive negative feedback on social media 33 .

In addition, future ESM studies into the effects of social media should attempt to include one or more follow-up measures to improve our knowledge of the longer-term influence of social media use on affective well-being. While a week-long ESM is very common and applied in most earlier ESM studies 34 , a week is only a snapshot of adolescent development. Research is needed that investigates whether the associations of social media use with adolescents’ momentary affective well-being may cumulate into long-lasting consequences. Such investigations could help clarify whether adolescents who feel bad in the short term would experience more negative consequences in the long term, and whether adolescents who feel better would be more resistant to developing long-term negative consequences. And while most adolescents do not seem to experience any short-term increases or decreases in well-being, more research is needed to investigate whether these adolescents may experience a longer-term impact of social media.

While the use of different platforms may be differently associated with well-being, different types of use may also yield different effects. Although the current study distinguished between active and passive use of social media, future research should further differentiate between different activities. For instance, because passive use entails many different activities, from reading private messages (e.g., WhatsApp messages, direct messages on Instagram) to browsing a public feed (e.g., scrolling through posts on Instagram), research is needed that explores the unique effects of passive public use and passive private use. Research that seeks to explore the nuances in adolescents’ susceptibility as well as the nuances in their social media use may truly improve our understanding of the effects of social media use.

Participants

Participants were recruited via a secondary school in the south of the Netherlands. Our preregistered sampling plan set a target sample size of 100 adolescents. We invited adolescents from six classrooms to participate in the study. The final sample consisted of 63 adolescents (i.e., 42% consent rate, which is comparable to other ESM studies among adolescents; see, for instance 35 , 36 ). Informed consent was obtained from all participants and their parents. On average, participants were 15 years old ( M  = 15.12 years, SD  = 0.51) and 54% were girls. All participants self-identified as Dutch, and 41.3% were enrolled in the prevocational secondary education track, 25.4% in the intermediate general secondary education track, and 33.3% in the academic preparatory education track.

The study was approved by the Ethics Review Board of the Faculty of Social and Behavioral Sciences at the University of Amsterdam and was performed in accordance with the guidelines formulated by the Ethics Review Board. The study consisted of two phases: A baseline survey and a personalized week-long experience sampling (ESM) study. In phase 1, researchers visited the school during school hours. Researchers informed the participants of the objective and procedure of the study and assured them that their responses would be treated confidentially. Participants were asked to sign the consent form. Next, participants completed a 15-min baseline survey. The baseline survey included questions about demographics and assessed which social media each adolescent used most frequently, allowing to personalize the social media questions presented during the ESM study in phase 2. After completing the baseline survey, participants were provided detailed instructions about phase 2.

In phase 2, which took place two and a half weeks after the baseline survey, a 7-day ESM study was conducted, following the guidelines for ESM studies provided by van Roekel and colleagues 34 . Aiming for at least 30 assessments per participant and based on an average compliance rate of 70 to 80% reported in earlier ESM studies among adolescents 34 , we asked each participant to complete a total of 42 ESM surveys (i.e., six 2-min surveys per day). Participants completed the surveys using their own mobile phone, on which the ESM software application Ethica Data was installed during the instruction session with the researchers (phase 1). Each 2-min survey consisted of 22 questions, which assessed adolescents’ well-being and social media use. Two open-ended questions were added to the final survey of the day, which asked about adolescents’ most pleasant and most unpleasant events of the day.

The ESM sampling scheme was semi-random, to allow for randomization and avoid structural patterns in well-being, while taking into account that adolescents were not allowed to use their phone during school time. The Ethica Data app was programmed to generate six beep notifications per day at random time points within a fixed time interval that was tailored to the school’s schedule: before school time (1 beep), during school breaks (2 beeps), and after school time (3 beeps). During the weekend, the beeps were generated during the morning (1 beep), afternoon (3 beeps), and evening (2 beeps). To maximize compliance, a 30-min time window was provided to complete each survey. This time window was extended to one hour for the first survey (morning) and two hours for the final survey (evening) to account for travel time to school and time spent on evening activities. The average compliance rate was 83.2%. A total of 2,155 ESM assessments were collected: Participants completed an average of 34.83 surveys ( SD  = 4.91) on a total of 42 surveys, which is high compared to previous ESM studies among adolescents 34 .

The questions of the ESM study were personalized based on the responses to the baseline survey. During the ESM study, each participant reported on his/her use of three different social media platforms: WhatsApp and either Instagram, Snapchat, YouTube, and/or the chat function of games (i.e., the most popular social media platforms among adolescents 28 ). Questions about Instagram and WhatsApp use were only included if the participant had indicated in the baseline survey that s/he used these platforms at least once a week. If a participant had indicated that s/he used Instagram or WhatsApp (or both) less than once a week, s/he was asked to report on the use of Snapchat, YouTube, or the chat function of games, depending on what platform s/he used at least once a week. In addition to Instagram and WhatsApp, questions were asked about a third platform, that was selected based on how frequently the participant used Snapchat, YouTube, or the chat function of games (i.e., at least once a week). This resulted in five different combinations of three platforms: Instagram, WhatsApp, and Snapchat (47 participants); Instagram, WhatsApp, and YouTube (11 participants); Instagram, WhatsApp, and chatting via games (2 participants); WhatsApp, Snapchat, and YouTube (1 participant); and WhatsApp, YouTube, and chatting via games (2 participants).

Frequency of social media use

In the baseline survey, participants were asked to indicate how often they used and checked Instagram, WhatsApp, Snapchat, YouTube, and the chat function of games, using response options ranging from 1 ( never ) to 7 ( more than 12 times per day ). These platforms are the five most popular platforms among Dutch 14- and 15-year-olds 28 . Participants’ responses were used to select the three social media platforms that were assessed in the personalized ESM study.

Duration of social media use

In the ESM study, duration of active and passive social media use was measured by asking participants how much time in the past hour they had spent actively and passively using each of the three platforms that were included in the personalized ESM surveys. Response options ranged from 0 to 60 min , with 5-min intervals. To measure active Instagram use, participants indicated how much time in the past hour they had spent (a) “posting on your feed or sharing something in your story on Instagram” and (b) “sending direct messages/chatting on Instagram.” These two items were summed to create the variable duration of active Instagram use. Sum scores exceeding 60 min (only 0.52% of all assessments) were recoded to 60 min. To measure duration of passive Instagram use, participants indicated how much time in the past hour they had spent “viewing posts/stories of others on Instagram.” To measure the use of WhatsApp, Snapchat, YouTube and game-based chatting, we asked participants how much time they had spent “sending WhatsApp messages” (active use) and “reading WhatsApp messages” (passive use); “sending snaps/messages or sharing something in your story on Snapchat” (active use) and “viewing snaps/stories/messages from others on Snapchat” (passive use); “posting YouTube clips” (active use) and “watching YouTube clips” (passive use); “sending messages via the chat function of a game/games” (active use) and “reading messages via the chat function of a game/games” (passive use). Duration of active and passive overall social media use were created by summing the responses across the three social media platforms for active and passive use, respectively. Sum scores exceeding 60 min (2.13% of all assessments for active overall use; 2.90% for passive overall use) were recoded to 60 min. The duration variables were used to investigate whether the time spent actively or passively using social media was associated with well-being (dose–response associations).

Use/no use of social media

Based on the duration variables, we created six dummy variables, one for active and one for passive overall social media use, one for active and one for passive Instagram use, and one for active and one for passive WhatsApp use (0 =  no active use and 1 =  active use , and 0 =  no passive use and 1 =  passive use , respectively). These dummy variables were used to investigate whether the use of social media, irrespective of the duration of use, was associated with well-being (categorical associations).

Consistent with previous ESM studies 19 , 20 , we measured affective well-being using one item, asking “How happy do you feel right now?” at each assessment. Adolescents indicated their response to the question using a 7-point scale ranging from 1 ( not at all ) to 7 ( completely ), with 4 ( a little ) as the midpoint. Convergent validity of this item was established in a separate pilot ESM study among 30 adolescents conducted by the research team of the fourth author: The affective well-being item was strongly correlated with the presence of positive affect and absence of negative affect (assessed by a 10-item positive and negative affect schedule for children; PANAS-C) at both the between-person (positive affect: r  = 0.88, p < 0.001; negative affect: r  = − 0.62, p < 0.001) and within-person level (positive affect: r  = 0.74, p < 0.001; negative affect: r  = − 0.58, p < 0.001).

Statistical analyses

Before conducting the analyses, several validation checks were performed (see 34 ). First, we aimed to only include participants in the analyses who had completed more than 33% of all ESM assessments (i.e., at least 14 assessments). Next, we screened participants’ responses to the open questions for unserious responses (e.g., gross comments, jokes). And finally, we inspected time series plots for patterns in answering tendencies. Since all participants completed more than 33% of all ESM assessments, and no inappropriate responses or low-quality data patterns were detected, all participants were included in the analyses.

Following our preregistered analysis plan, we tested the proposed associations in a series of multilevel models. Before doing so, we tested the homoscedasticity and linearity assumptions for multilevel analyses 37 . Inspection of standardized residual plots indicated that the data met these assumptions (plots are available on OSF at  https://osf.io/nhks2 ). We specified separate models for overall social media use, use of Instagram, and use of WhatsApp. To investigate to what extent adolescents’ well-being would vary depending on whether they had actively or passively used social media/Instagram/WhatsApp or not during the past hour (categorical associations), we tested models including the dummy variables as predictors (active use versus no active use, and passive use versus no passive use; models 1, 3, and 5). To investigate whether, at moments when adolescents had used social media/Instagram/WhatsApp during the past hour, their well-being would vary depending on the duration of social media/Instagram/WhatsApp use (dose–response associations), we tested models including the duration variables as predictors (duration of active use and duration of passive use; models 2, 4, and 6). In order to avoid negative skew in the duration variables, we only included assessments during which adolescents had used social media in the past hour (overall, Instagram, or WhatsApp, respectively), either actively or passively. All models included well-being as outcome variable. Since multilevel analyses allow to include all available data for each individual, no missing data were imputed and no data points were excluded.

We used a model building approach that involved three steps. In the first step, we estimated an intercept-only model to assess the relative amount of between- and within-person variance in affective well-being. We estimated a three-level model in which repeated momentary assessments (level 1) were nested within adolescents (level 2), who, in turn, were nested within classrooms (level 3). However, because the between-classroom variance in affective well-being was small (i.e., 0.4% of the variance was explained by differences between classes), we proceeded with estimating two-level (instead of three-level) models, with repeated momentary assessments (level 1) nested within adolescents (level 2).

In the second step, we assessed the within-person associations of well-being with (a) overall active and passive social media use (i.e., the total of the three platforms), (b) active and passive use of Instagram, and (c) active and passive use of WhatsApp, by adding fixed effects to the model (Models 1A-6A). To facilitate the interpretation of the associations and control for the effects of time, a covariate was added that controlled for the n th assessment of the study week (instead of the n th assessment of the day, as preregistered). This so-called detrending is helpful to interpret within-person associations as correlated fluctuations beyond other changes in social media use and well-being 38 . In order to obtain within-person estimates, we person-mean centered all predictors 38 . Significance of the fixed effects was determined using the Wald test.

In the third and final step, we assessed heterogeneity in the within-person associations by adding random slopes to the models (Models 1B-6B). Significance of the random slopes was determined by comparing the fit of the fixed effects model with the fit of the random effects model, by performing the Satorra-Bentler scaled chi-square test 39 and by comparing the Bayesian information criterion (BIC 40 ) and Akaike information criterion (AIC 41 ) of the models. When the random effects model had a significantly better fit than the fixed effects model (i.e., pointing at significant heterogeneity), variance components were inspected to investigate whether heterogeneity existed in the association of either active or passive use. Next, when evidence was found for significant heterogeneity, we computed person-specific effect sizes, based on the random effect models, to investigate what percentages of adolescents experienced better well-being, worse well-being, and no changes in well-being. In line with Keijsers and colleagues 42 we only included participants who had completed at least 10 assessments. In addition, for the dose–response associations, we constructed graphical representations of the person-specific slopes, based on the person-specific effect sizes, using the xyplot function from the lattice package in R 43 .

Three improvements were made to our original preregistered plan. First, rather than estimating the models with multilevel modelling in R 43 , we ran the preregistered models in Mplus 44 . Mplus provides standardized estimates for the fixed effects models, which offers insight into the effect sizes. This allowed us to compare the relative strength of the associations of passive versus active use with well-being. Second, instead of using the maximum likelihood estimator, we used the maximum likelihood estimator with robust standard errors (MLR), which are robust to non-normality. Sensitivity tests, uploaded on OSF ( https://osf.io/nhks2 ), indicated that the results were almost identical across the two software packages and estimation approaches. Third, to improve the interpretation of the results and make the scales of the duration measures of social media use and well-being more comparable, we transformed the social media duration scores (0 to 60 min) into scales running from 0 to 6, so that an increase of 1 unit reflects 10 min of social media use. The model estimates were unaffected by this transformation.

Reporting summary

Further information on the research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The dataset generated and analysed during the current study is available in Figshare 45 . The preregistration of the design, sampling and analysis plan, and the analysis scripts used to analyse the data for this paper are available online on the Open Science Framework website ( https://osf.io/nhks2 ).

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Acknowledgements

This study was funded by the NWO Spinoza Prize and the Gravitation grant (NWO Grant 024.001.003; Consortium on Individual Development) awarded to P.M.V. by the Dutch Research Council (NWO). Additional funding was received from the VIDI grant (NWO VIDI Grant 452.17.011) awarded to L.K. by the Dutch Research Council (NWO). The authors would like to thank Savannah Boele (Tilburg University) for providing her pilot ESM results.

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I.B., J.L.P., I.I.v.D., L.K., and P.M.V. designed the study; I.B., J.L.P., and I.I.v.D. collected the data; I.B., J.L.P., and L.K. analyzed the data; and I.B., J.L.P., I.I.v.D., L.K., and P.M.V. contributed to writing and reviewing the manuscript.

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Beyens, I., Pouwels, J.L., van Driel, I.I. et al. The effect of social media on well-being differs from adolescent to adolescent. Sci Rep 10 , 10763 (2020). https://doi.org/10.1038/s41598-020-67727-7

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Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice

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Introduction

Social media has become a prominent fixture in the lives of many individuals facing the challenges of mental illness. Social media refers broadly to web and mobile platforms that allow individuals to connect with others within a virtual network (such as Facebook, Twitter, Instagram, Snapchat, or LinkedIn), where they can share, co-create, or exchange various forms of digital content, including information, messages, photos, or videos (Ahmed et al. 2019 ). Studies have reported that individuals living with a range of mental disorders, including depression, psychotic disorders, or other severe mental illnesses, use social media platforms at comparable rates as the general population, with use ranging from about 70% among middle-age and older individuals to upwards of 97% among younger individuals (Aschbrenner et al. 2018b ; Birnbaum et al. 2017b ; Brunette et al. 2019 ; Naslund et al. 2016 ). Other exploratory studies have found that many of these individuals with mental illness appear to turn to social media to share their personal experiences, seek information about their mental health and treatment options, and give and receive support from others facing similar mental health challenges (Bucci et al. 2019 ; Naslund et al. 2016b ).

Across the USA and globally, very few people living with mental illness have access to adequate mental health services (Patel et al. 2018 ). The wide reach and near ubiquitous use of social media platforms may afford novel opportunities to address these shortfalls in existing mental health care, by enhancing the quality, availability, and reach of services. Recent studies have explored patterns of social media use, impact of social media use on mental health and wellbeing, and the potential to leverage the popularity and interactive features of social media to enhance the delivery of interventions. However, there remains uncertainty regarding the risks and potential harms of social media for mental health (Orben and Przybylski 2019 ) and how best to weigh these concerns against potential benefits.

In this commentary, we summarized current research on the use of social media among individuals with mental illness, with consideration of the impact of social media on mental wellbeing, as well as early efforts using social media for delivery of evidence-based programs for addressing mental health problems. We searched for recent peer reviewed publications in Medline and Google Scholar using the search terms “mental health” or “mental illness” and “social media,” and searched the reference lists of recent reviews and other relevant studies. We reviewed the risks, potential harms, and necessary safety precautions with using social media for mental health. Overall, our goal was to consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services, while balancing the need for safety. Given this broad objective, we did not perform a systematic search of the literature and we did not apply specific inclusion criteria based on study design or type of mental disorder.

Social Media Use and Mental Health

In 2020, there are an estimated 3.8 billion social media users worldwide, representing half the global population (We Are Social 2020 ). Recent studies have shown that individuals with mental disorders are increasingly gaining access to and using mobile devices, such as smartphones (Firth et al. 2015 ; Glick et al. 2016 ; Torous et al. 2014a , b ). Similarly, there is mounting evidence showing high rates of social media use among individuals with mental disorders, including studies looking at engagement with these popular platforms across diverse settings and disorder types. Initial studies from 2015 found that nearly half of a sample of psychiatric patients were social media users, with greater use among younger individuals (Trefflich et al. 2015 ), while 47% of inpatients and outpatients with schizophrenia reported using social media, of which 79% reported at least once-a-week usage of social media websites (Miller et al. 2015 ). Rates of social media use among psychiatric populations have increased in recent years, as reflected in a study with data from 2017 showing comparable rates of social media use (approximately 70%) among individuals with serious mental illness in treatment as compared with low-income groups from the general population (Brunette et al. 2019 ).

Similarly, among individuals with serious mental illness receiving community-based mental health services, a recent study found equivalent rates of social media use as the general population, even exceeding 70% of participants (Naslund et al. 2016 ). Comparable findings were demonstrated among middle-age and older individuals with mental illness accessing services at peer support agencies, where 72% of respondents reported using social media (Aschbrenner et al. 2018b ). Similar results, with 68% of those with first episode psychosis using social media daily were reported in another study (Abdel-Baki et al. 2017 ).

Individuals who self-identified as having a schizophrenia spectrum disorder responded to a survey shared through the National Alliance of Mental Illness (NAMI) and reported that visiting social media sites was one of their most common activities when using digital devices, taking up roughly 2 h each day (Gay et al. 2016 ). For adolescents and young adults ages 12 to 21 with psychotic disorders and mood disorders, over 97% reported using social media, with average use exceeding 2.5 h per day (Birnbaum et al. 2017b ). Similarly, in a sample of adolescents ages 13–18 recruited from community mental health centers, 98% reported using social media, with YouTube as the most popular platform, followed by Instagram and Snapchat (Aschbrenner et al. 2019 ).

Research has also explored the motivations for using social media as well as the perceived benefits of interacting on these platforms among individuals with mental illness. In the sections that follow (see Table 1 for a summary), we consider three potentially unique features of interacting and connecting with others on social media that may offer benefits for individuals living with mental illness. These include: (1) Facilitate social interaction; (2) Access to a peer support network; and (3) Promote engagement and retention in services.

Facilitate Social Interaction

Social media platforms offer near continuous opportunities to connect and interact with others, regardless of time of day or geographic location. This on demand ease of communication may be especially important for facilitating social interaction among individuals with mental disorders experiencing difficulties interacting in face-to-face settings. For example, impaired social functioning is a common deficit in schizophrenia spectrum disorders, and social media may facilitate communication and interacting with others for these individuals (Torous and Keshavan 2016 ). This was suggested in one study where participants with schizophrenia indicated that social media helped them to interact and socialize more easily (Miller et al. 2015 ). Like other online communication, the ability to connect with others anonymously may be an important feature of social media, especially for individuals living with highly stigmatizing health conditions (Berger et al. 2005 ), such as serious mental disorders (Highton-Williamson et al. 2015 ).

Studies have found that individuals with serious mental disorders (Spinzy et al. 2012 ) as well as young adults with mental illness (Gowen et al. 2012 ) appear to form online relationships and connect with others on social media as often as social media users from the general population. This is an important observation because individuals living with serious mental disorders typically have few social contacts in the offline world and also experience high rates of loneliness (Badcock et al. 2015 ; Giacco et al. 2016 ). Among individuals receiving publicly funded mental health services who use social media, nearly half (47%) reported using these platforms at least weekly to feel less alone (Brusilovskiy et al. 2016 ). In another study of young adults with serious mental illness, most indicated that they used social media to help feel less isolated (Gowen et al. 2012 ). Interestingly, more frequent use of social media among a sample of individuals with serious mental illness was associated with greater community participation, measured as participation in shopping, work, religious activities, or visiting friends and family, as well as greater civic engagement, reflected as voting in local elections (Brusilovskiy et al. 2016 ).

Emerging research also shows that young people with moderate to severe depressive symptoms appear to prefer communicating on social media rather than in-person (Rideout and Fox 2018 ), while other studies have found that some individuals may prefer to seek help for mental health concerns online rather than through in-person encounters (Batterham and Calear 2017 ). In a qualitative study, participants with schizophrenia described greater anonymity, the ability to discover that other people have experienced similar health challenges and reducing fears through greater access to information as important motivations for using the Internet to seek mental health information (Schrank et al. 2010 ). Because social media does not require the immediate responses necessary in face-to-face communication, it may overcome deficits with social interaction due to psychotic symptoms that typically adversely affect face-to-face conversations (Docherty et al. 1996 ). Online social interactions may not require the use of non-verbal cues, particularly in the initial stages of interaction (Kiesler et al. 1984 ), with interactions being more fluid and within the control of users, thereby overcoming possible social anxieties linked to in-person interaction (Indian and Grieve 2014 ). Furthermore, many individuals with serious mental disorders can experience symptoms including passive social withdrawal, blunted affect, and attentional impairment, as well as active social avoidance due to hallucinations or other concerns (Hansen et al. 2009 ), thus potentially reinforcing the relative advantage, as perceived by users, of using social media over in person conversations.

Access to a Peer Support Network

There is growing recognition about the role that social media channels could play in enabling peer support (Bucci et al. 2019 ; Naslund et al. 2016b ), referred to as a system of mutual giving and receiving where individuals who have endured the difficulties of mental illness can offer hope, friendship, and support to others facing similar challenges (Davidson et al. 2006 ; Mead et al. 2001 ). Initial studies exploring use of online self-help forums among individuals with serious mental illnesses have found that individuals with schizophrenia appeared to use these forums for self-disclosure and sharing personal experiences, in addition to providing or requesting information, describing symptoms, or discussing medication (Haker et al. 2005 ), while users with bipolar disorder reported using these forums to ask for help from others about their illness (Vayreda and Antaki 2009 ). More recently, in a review of online social networking in people with psychosis, Highton-Williamson et al. ( 2015 ) highlight that an important purpose of such online connections was to establish new friendships, pursue romantic relationships, maintain existing relationships or reconnect with people, and seek online peer support from others with lived experience (Highton-Williamson et al. 2015 ).

Online peer support among individuals with mental illness has been further elaborated in various studies. In a content analysis of comments posted to YouTube by individuals who self-identified as having a serious mental illness, there appeared to be opportunities to feel less alone, provide hope, find support and learn through mutual reciprocity, and share coping strategies for day-to-day challenges of living with a mental illness (Naslund et al. 2014 ). In another study, Chang ( 2009 ) delineated various communication patterns in an online psychosis peer-support group (Chang 2009 ). Specifically, different forms of support emerged, including “informational support” about medication use or contacting mental health providers, “esteem support” involving positive comments for encouragement, “network support” for sharing similar experiences, and “emotional support” to express understanding of a peer’s situation and offer hope or confidence (Chang 2009 ). Bauer et al. ( 2013 ) reported that the main interest in online self-help forums for patients with bipolar disorder was to share emotions with others, allow exchange of information, and benefit by being part of an online social group (Bauer et al. 2013 ).

For individuals who openly discuss mental health problems on Twitter, a study by Berry et al. ( 2017 ) found that this served as an important opportunity to seek support and to hear about the experiences of others (Berry et al. 2017 ). In a survey of social media users with mental illness, respondents reported that sharing personal experiences about living with mental illness and opportunities to learn about strategies for coping with mental illness from others were important reasons for using social media (Naslund et al. 2017 ). A computational study of mental health awareness campaigns on Twitter provides further support with inspirational posts and tips being the most shared (Saha et al. 2019 ). Taken together, these studies offer insights about the potential for social media to facilitate access to an informal peer support network, though more research is necessary to examine how these online interactions may impact intentions to seek care, illness self-management, and clinically meaningful outcomes in offline contexts.

Promote Engagement and Retention in Services

Many individuals living with mental disorders have expressed interest in using social media platforms for seeking mental health information (Lal et al. 2018 ), connecting with mental health providers (Birnbaum et al. 2017b ), and accessing evidence-based mental health services delivered over social media specifically for coping with mental health symptoms or for promoting overall health and wellbeing (Naslund et al. 2017 ). With the widespread use of social media among individuals living with mental illness combined with the potential to facilitate social interaction and connect with supportive peers, as summarized above, it may be possible to leverage the popular features of social media to enhance existing mental health programs and services. A recent review by Biagianti et al. ( 2018 ) found that peer-to-peer support appeared to offer feasible and acceptable ways to augment digital mental health interventions for individuals with psychotic disorders by specifically improving engagement, compliance, and adherence to the interventions and may also improve perceived social support (Biagianti et al. 2018 ).

Among digital programs that have incorporated peer-to-peer social networking consistent with popular features on social media platforms, a pilot study of the HORYZONS online psychosocial intervention demonstrated significant reductions in depression among patients with first episode psychosis (Alvarez-Jimenez et al. 2013 ). Importantly, the majority of participants (95%) in this study engaged with the peer-to-peer networking feature of the program, with many reporting increases in perceived social connectedness and empowerment in their recovery process (Alvarez-Jimenez et al. 2013 ). This moderated online social therapy program is now being evaluated as part of a large randomized controlled trial for maintaining treatment effects from first episode psychosis services (Alvarez-Jimenez et al. 2019 ).

Other early efforts have demonstrated that use of digital environments with the interactive peer-to-peer features of social media can enhance social functioning and wellbeing in young people at high risk of psychosis (Alvarez-Jimenez et al. 2018 ). There has also been a recent emergence of several mobile apps to support symptom monitoring and relapse prevention in psychotic disorders. Among these apps, the development of PRIME (Personalized Real-time Intervention for Motivational Enhancement) has involved working closely with young people with schizophrenia to ensure that the design of the app has the look and feel of mainstream social media platforms, as opposed to existing clinical tools (Schlosser et al. 2016 ). This unique approach to the design of the app is aimed at promoting engagement and ensuring that the app can effectively improve motivation and functioning through goal setting and promoting better quality of life of users with schizophrenia (Schlosser et al. 2018 ).

Social media platforms could also be used to promote engagement and participation in in-person services delivered through community mental health settings. For example, the peer-based lifestyle intervention called PeerFIT targets weight loss and improved fitness among individuals living with serious mental illness through a combination of in-person lifestyle classes, exercise groups, and use of digital technologies (Aschbrenner et al. 2016b , c ). The intervention holds tremendous promise as lack of support is one of the largest barriers towards exercise in patients with serious mental illness (Firth et al. 2016 ), and it is now possible to use social media to counter such. Specifically, in PeerFIT, a private Facebook group is closely integrated into the program to offer a closed platform where participants can connect with the lifestyle coaches, access intervention content, and support or encourage each other as they work towards their lifestyle goals (Aschbrenner et al. 2016a ; Naslund et al. 2016a ). To date, this program has demonstrated preliminary effectiveness for meaningfully reducing cardiovascular risk factors that contribute to early mortality in this patient group (Aschbrenner, Naslund, Shevenell, Kinney, et al., 2016), while the Facebook component appears to have increased engagement in the program, while allowing participants who were unable to attend in-person sessions due to other health concerns or competing demands to remain connected with the program (Naslund et al. 2018 ). This lifestyle intervention is currently being evaluated in a randomized controlled trial enrolling young adults with serious mental illness from real world community mental health services settings (Aschbrenner et al. 2018a ).

These examples highlight the promise of incorporating the features of popular social media into existing programs, which may offer opportunities to safely promote engagement and program retention, while achieving improved clinical outcomes. This is an emerging area of research, as evidenced by several important effectiveness trials underway (Alvarez-Jimenez et al. 2019 ; Aschbrenner et al. 2018a ), including efforts to leverage online social networking to support family caregivers of individuals receiving first episode psychosis services (Gleeson et al. 2017 ).

Challenges with Social Media for Mental Health

The science on the role of social media for engaging persons with mental disorders needs a cautionary note on the effects of social media usage on mental health and wellbeing, particularly in adolescents and young adults. While the risks and harms of social media are frequently covered in the popular press and mainstream news reports, careful consideration of the research in this area is necessary. In a review of 43 studies in young people, many benefits of social media were cited, including increased self-esteem and opportunities for self-disclosure (Best et al. 2014 ). Yet, reported negative effects were an increased exposure to harm, social isolation, depressive symptoms, and bullying (Best et al. 2014 ). In the sections that follow (see Table 1 for a summary), we consider three major categories of risk related to use of social media and mental health. These include: (1) Impact on symptoms; (2) Facing hostile interactions; and (3) Consequences for daily life.

Impact on Symptoms

Studies consistently highlight that use of social media, especially heavy use and prolonged time spent on social media platforms, appears to contribute to increased risk for a variety of mental health symptoms and poor wellbeing, especially among young people (Andreassen et al. 2016 ; Kross et al. 2013 ; Woods and Scott 2016 ). This may partly be driven by the detrimental effects of screen time on mental health, including increased severity of anxiety and depressive symptoms, which have been well documented (Stiglic and Viner 2019 ). Recent studies have reported negative effects of social media use on mental health of young people, including social comparison pressure with others and greater feeling of social isolation after being rejected by others on social media (Rideout and Fox 2018 ). In a study of young adults, it was found that negative comparisons with others on Facebook contributed to risk of rumination and subsequent increases in depression symptoms (Feinstein et al. 2013 ). Still, the cross-sectional nature of many screen time and mental health studies makes it challenging to reach causal inferences (Orben and Przybylski 2019 ).

Quantity of social media use is also an important factor, as highlighted in a survey of young adults ages 19 to 32, where more frequent visits to social media platforms each week were correlated with greater depressive symptoms (Lin et al. 2016 ). More time spent using social media is also associated with greater symptoms of anxiety (Vannucci et al. 2017 ). The actual number of platforms accessed also appears to contribute to risk as reflected in another national survey of young adults where use of a large number of social media platforms was associated with negative impact on mental health (Primack et al. 2017 ). Among survey respondents using between 7 and 11 different social media platforms compared with respondents using only 2 or fewer platforms, there were 3 times greater odds of having high levels of depressive symptoms and a 3.2 times greater odds of having high levels of anxiety symptoms (Primack et al. 2017 ).

Many researchers have postulated that worsening mental health attributed to social media use may be because social media replaces face-to-face interactions for young people (Twenge and Campbell 2018 ) and may contribute to greater loneliness (Bucci et al. 2019 ) and negative effects on other aspects of health and wellbeing (Woods and Scott 2016 ). One nationally representative survey of US adolescents found that among respondents who reported more time accessing media such as social media platforms or smartphone devices, there were significantly greater depressive symptoms and increased risk of suicide when compared with adolescents who reported spending more time on non-screen activities, such as in-person social interaction or sports and recreation activities (Twenge et al. 2018 ). For individuals living with more severe mental illnesses, the effects of social media on psychiatric symptoms have received less attention. One study found that participation in chat rooms may contribute to worsening symptoms in young people with psychotic disorders (Mittal et al. 2007 ), while another study of patients with psychosis found that social media use appeared to predict low mood (Berry et al. 2018 ). These studies highlight a clear relationship between social media use and mental health that may not be present in general population studies (Orben and Przybylski 2019 ) and emphasize the need to explore how social media may contribute to symptom severity and whether protective factors may be identified to mitigate these risks.

Facing Hostile Interactions

Popular social media platforms can create potential situations where individuals may be victimized by negative comments or posts. Cyberbullying represents a form of online aggression directed towards specific individuals, such as peers or acquaintances, which is perceived to be most harmful when compared with random hostile comments posted online (Hamm et al. 2015 ). Importantly, cyberbullying on social media consistently shows harmful impact on mental health in the form of increased depressive symptoms as well as worsening of anxiety symptoms, as evidenced in a review of 36 studies among children and young people (Hamm et al. 2015 ). Furthermore, cyberbullying disproportionately impacts females as reflected in a national survey of adolescents in the USA, where females were twice as likely to be victims of cyberbullying compared with males (Alhajji et al. 2019 ). Most studies report cross-sectional associations between cyberbullying and symptoms of depression or anxiety (Hamm et al. 2015 ), though one longitudinal study in Switzerland found that cyberbullying contributed to significantly greater depression over time (Machmutow et al. 2012 ).

For youth ages 10 to 17 who reported major depressive symptomatology, there were over 3 times greater odds of facing online harassment in the last year compared with youth who reported mild or no depressive symptoms (Ybarra 2004 ). Similarly, in a 2018 national survey of young people, respondents ages 14 to 22 with moderate to severe depressive symptoms were more likely to have had negative experiences when using social media and, in particular, were more likely to report having faced hostile comments or being “trolled” from others when compared with respondents without depressive symptoms (31% vs. 14%) (Rideout and Fox 2018 ). As these studies depict risks for victimization on social media and the correlation with poor mental health, it is possible that individuals living with mental illness may also experience greater hostility online compared to individuals without mental illness. This would be consistent with research showing greater risk of hostility, including increased violence and discrimination, directed towards individuals living with mental illness in in-person contexts, especially targeted at those with severe mental illnesses (Goodman et al. 1999 ).

A computational study of mental health awareness campaigns on Twitter reported that while stigmatizing content was rare, it was actually the most spread (re-tweeted) demonstrating that harmful content can travel quickly on social media (Saha et al. 2019 ). Another study was able to map the spread of social media posts about the Blue Whale Challenge, an alleged game promoting suicide, over Twitter, YouTube, Reddit, Tumblr, and other forums across 127 countries (Sumner et al. 2019 ). These findings show that it is critical to monitor the actual content of social media posts, such as determining whether content is hostile or promotes harm to self or others. This is pertinent because existing research looking at duration of exposure cannot account for the impact of specific types of content on mental health and is insufficient to fully understand the effects of using these platforms on mental health.

Consequences for Daily Life

The ways in which individuals use social media can also impact their offline relationships and everyday activities. To date, reports have described risks of social media use pertaining to privacy, confidentiality, and unintended consequences of disclosing personal health information online (Torous and Keshavan 2016 ). Additionally, concerns have been raised about poor quality or misleading health information shared on social media and that social media users may not be aware of misleading information or conflicts of interest especially when the platforms promote popular content regardless of whether it is from a trustworthy source (Moorhead et al. 2013 ; Ventola 2014 ). For persons living with mental illness, there may be additional risks from using social media. A recent study that specifically explored the perspectives of social media users with serious mental illnesses, including participants with schizophrenia spectrum disorders, bipolar disorder, or major depression, found that over one third of participants expressed concerns about privacy when using social media (Naslund and Aschbrenner 2019 ). The reported risks of social media use were directly related to many aspects of everyday life, including concerns about threats to employment, fear of stigma and being judged, impact on personal relationships, and facing hostility or being hurt (Naslund and Aschbrenner 2019 ). While few studies have specifically explored the dangers of social media use from the perspectives of individuals living with mental illness, it is important to recognize that use of these platforms may contribute to risks that extend beyond worsening symptoms and that can affect different aspects of daily life.

In this commentary, we considered ways in which social media may yield benefits for individuals living with mental illness, while contrasting these with the possible harms. Studies reporting on the threats of social media for individuals with mental illness are mostly cross-sectional, making it difficult to draw conclusions about direction of causation. However, the risks are potentially serious. These risks should be carefully considered in discussions pertaining to use of social media and the broader use of digital mental health technologies, as avenues for mental health promotion or for supporting access to evidence-based programs or mental health services. At this point, it would be premature to view the benefits of social media as outweighing the possible harms, when it is clear from the studies summarized here that social media use can have negative effects on mental health symptoms, can potentially expose individuals to hurtful content and hostile interactions, and can result in serious consequences for daily life, including threats to employment and personal relationships. Despite these risks, it is also necessary to recognize that individuals with mental illness will continue to use social media given the ease of accessing these platforms and the immense popularity of online social networking. With this in mind, it may be ideal to raise awareness about these possible risks so that individuals can implement necessary safeguards, while highlighting that there could also be benefits. Being aware of the risks is an essential first step, before then recognizing that use of these popular platforms could contribute to some benefits like finding meaningful interactions with others, engaging with peer support networks, and accessing information and services.

To capitalize on the widespread use of social media and to achieve the promise that these platforms may hold for supporting the delivery of targeted mental health interventions, there is need for continued research to better understand how individuals living with mental illness use social media. Such efforts could inform safety measures and also encourage use of social media in ways that maximize potential benefits while minimizing risk of harm. It will be important to recognize how gender and race contribute to differences in use of social media for seeking mental health information or accessing interventions, as well as differences in how social media might impact mental wellbeing. For example, a national survey of 14- to 22-year olds in the USA found that female respondents were more likely to search online for information about depression or anxiety and to try to connect with other people online who share similar mental health concerns when compared with male respondents (Rideout and Fox 2018 ). In the same survey, there did not appear to be any differences between racial or ethnic groups in social media use for seeking mental health information (Rideout and Fox 2018 ). Social media use also appears to have a differential impact on mental health and emotional wellbeing between females and males (Booker et al. 2018 ), highlighting the need to explore unique experiences between gender groups to inform tailored programs and services. Research shows that lesbian, gay, bisexual, or transgender individuals frequently use social media for searching for health information and may be more likely compared with heterosexual individuals to share their own personal health experiences with others online (Rideout and Fox 2018 ). Less is known about use of social media for seeking support for mental health concerns among gender minorities, though this is an important area for further investigation as these individuals are more likely to experience mental health problems and online victimization when compared with heterosexual individuals (Mereish et al. 2019 ).

Similarly, efforts are needed to explore the relationship between social media use and mental health among ethnic and racial minorities. A recent study found that exposure to traumatic online content on social media showing violence or hateful posts directed at racial minorities contributed to increases in psychological distress, PTSD symptoms, and depression among African American and Latinx adolescents in the USA (Tynes et al. 2019 ). These concerns are contrasted by growing interest in the potential for new technologies including social media to expand the reach of services to underrepresented minority groups (Schueller et al. 2019 ). Therefore, greater attention is needed to understanding the perspectives of ethnic and racial minorities to inform effective and safe use of social media for mental health promotion efforts.

Research has found that individuals living with mental illness have expressed interest in accessing mental health services through social media platforms. A survey of social media users with mental illness found that most respondents were interested in accessing programs for mental health on social media targeting symptom management, health promotion, and support for communicating with health care providers and interacting with the health system (Naslund et al. 2017 ). Importantly, individuals with serious mental illness have also emphasized that any mental health intervention on social media would need to be moderated by someone with adequate training and credentials, would need to have ground rules and ways to promote safety and minimize risks, and importantly, would need to be free and easy to access.

An important strength with this commentary is that it combines a range of studies broadly covering the topic of social media and mental health. We have provided a summary of recent evidence in a rapidly advancing field with the goal of presenting unique ways that social media could offer benefits for individuals with mental illness, while also acknowledging the potentially serious risks and the need for further investigation. There are also several limitations with this commentary that warrant consideration. Importantly, as we aimed to address this broad objective, we did not conduct a systematic review of the literature. Therefore, the studies reported here are not exhaustive, and there may be additional relevant studies that were not included. Additionally, we only summarized published studies, and as a result, any reports from the private sector or websites from different organizations using social media or other apps containing social media–like features would have been omitted. Although, it is difficult to rigorously summarize work from the private sector, sometimes referred to as “gray literature,” because many of these projects are unpublished and are likely selective in their reporting of findings given the target audience may be shareholders or consumers.

Another notable limitation is that we did not assess risk of bias in the studies summarized in this commentary. We found many studies that highlighted risks associated with social media use for individuals living with mental illness; however, few studies of programs or interventions reported negative findings, suggesting the possibility that negative findings may go unpublished. This concern highlights the need for a future more rigorous review of the literature with careful consideration of bias and an accompanying quality assessment. Most of the studies that we described were from the USA, as well as from other higher income settings such as Australia or the UK. Despite the global reach of social media platforms, there is a dearth of research on the impact of these platforms on the mental health of individuals in diverse settings, as well as the ways in which social media could support mental health services in lower income countries where there is virtually no access to mental health providers. Future research is necessary to explore the opportunities and risks for social media to support mental health promotion in low-income and middle-income countries, especially as these countries face a disproportionate share of the global burden of mental disorders, yet account for the majority of social media users worldwide (Naslund et al. 2019 ).

Future Directions for Social Media and Mental Health

As we consider future research directions, the near ubiquitous social media use also yields new opportunities to study the onset and manifestation of mental health symptoms and illness severity earlier than traditional clinical assessments. There is an emerging field of research referred to as “digital phenotyping” aimed at capturing how individuals interact with their digital devices, including social media platforms, in order to study patterns of illness and identify optimal time points for intervention (Jain et al. 2015 ; Onnela and Rauch 2016 ). Given that most people access social media via mobile devices, digital phenotyping and social media are closely related (Torous et al. 2019 ). To date, the emergence of machine learning, a powerful computational method involving statistical and mathematical algorithms (Shatte et al. 2019 ), has made it possible to study large quantities of data captured from popular social media platforms such as Twitter or Instagram to illuminate various features of mental health (Manikonda and De Choudhury 2017 ; Reece et al. 2017 ). Specifically, conversations on Twitter have been analyzed to characterize the onset of depression (De Choudhury et al. 2013 ) as well as detecting users’ mood and affective states (De Choudhury et al. 2012 ), while photos posted to Instagram can yield insights for predicting depression (Reece and Danforth 2017 ). The intersection of social media and digital phenotyping will likely add new levels of context to social media use in the near future.

Several studies have also demonstrated that when compared with a control group, Twitter users with a self-disclosed diagnosis of schizophrenia show unique online communication patterns (Birnbaum et al. 2017a ), including more frequent discussion of tobacco use (Hswen et al. 2017 ), symptoms of depression and anxiety (Hswen et al. 2018b ), and suicide (Hswen et al. 2018a ). Another study found that online disclosures about mental illness appeared beneficial as reflected by fewer posts about symptoms following self-disclosure (Ernala et al. 2017 ). Each of these examples offers early insights into the potential to leverage widely available online data for better understanding the onset and course of mental illness. It is possible that social media data could be used to supplement additional digital data, such as continuous monitoring using smartphone apps or smart watches, to generate a more comprehensive “digital phenotype” to predict relapse and identify high-risk health behaviors among individuals living with mental illness (Torous et al. 2019 ).

With research increasingly showing the valuable insights that social media data can yield about mental health states, greater attention to the ethical concerns with using individual data in this way is necessary (Chancellor et al. 2019 ). For instance, data is typically captured from social media platforms without the consent or awareness of users (Bidargaddi et al. 2017 ), which is especially crucial when the data relates to a socially stigmatizing health condition such as mental illness (Guntuku et al. 2017 ). Precautions are needed to ensure that data is not made identifiable in ways that were not originally intended by the user who posted the content as this could place an individual at risk of harm or divulge sensitive health information (Webb et al. 2017 ; Williams et al. 2017 ). Promising approaches for minimizing these risks include supporting the participation of individuals with expertise in privacy, clinicians, and the target individuals with mental illness throughout the collection of data, development of predictive algorithms, and interpretation of findings (Chancellor et al. 2019 ).

In recognizing that many individuals living with mental illness use social media to search for information about their mental health, it is possible that they may also want to ask their clinicians about what they find online to check if the information is reliable and trustworthy. Alternatively, many individuals may feel embarrassed or reluctant to talk to their clinicians about using social media to find mental health information out of concerns of being judged or dismissed. Therefore, mental health clinicians may be ideally positioned to talk with their patients about using social media and offer recommendations to promote safe use of these sites while also respecting their patients’ autonomy and personal motivations for using these popular platforms. Given the gap in clinical knowledge about the impact of social media on mental health, clinicians should be aware of the many potential risks so that they can inform their patients while remaining open to the possibility that their patients may also experience benefits through use of these platforms. As awareness of these risks grows, it may be possible that new protections will be put in place by industry or through new policies that will make the social media environment safer. It is hard to estimate a number needed to treat or harm today given the nascent state of research, which means the patient and clinician need to weigh the choice on a personal level. Thus, offering education and information is an important first step in that process. As patients increasingly show interest in accessing mental health information or services through social media, it will be necessary for health systems to recognize social media as a potential avenue for reaching or offering support to patients. This aligns with growing emphasis on the need for greater integration of digital psychiatry, including apps, smartphones, or wearable devices, into patient care and clinical services through institution-wide initiatives and training clinical providers (Hilty et al. 2019 ). Within a learning healthcare environment where research and care are tightly intertwined and feedback between both is rapid, the integration of digital technologies into services may create new opportunities for advancing use of social media for mental health.

As highlighted in this commentary, social media has become an important part of the lives of many individuals living with mental disorders. Many of these individuals use social media to share their lived experiences with mental illness, to seek support from others, and to search for information about treatment recommendations, accessing mental health services and coping with symptoms (Bucci et al. 2019 ; Highton-Williamson et al. 2015 ; Naslund et al. 2016b ). As the field of digital mental health advances, the wide reach, ease of access, and popularity of social media platforms could be used to allow individuals in need of mental health services or facing challenges of mental illness to access evidence-based treatment and support. To achieve this end and to explore whether social media platforms can advance efforts to close the gap in available mental health services in the USA and globally, it will be essential for researchers to work closely with clinicians and with those affected by mental illness to ensure that possible benefits of using social media are carefully weighed against anticipated risks.

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Dr. Naslund is supported by a grant from the National Institute of Mental Health (U19MH113211). Dr. Aschbrenner is supported by a grant from the National Institute of Mental Health (1R01MH110965-01).

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Naslund, J.A., Bondre, A., Torous, J. et al. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. J. technol. behav. sci. 5 , 245–257 (2020). https://doi.org/10.1007/s41347-020-00134-x

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Received : 19 October 2019

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Published : 20 April 2020

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DOI : https://doi.org/10.1007/s41347-020-00134-x

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Social media's growing impact on our lives

Media psychology researchers are beginning to tease apart the ways in which time spent on social media is, and is not, impacting our day-to-day lives.

Social media use has skyrocketed over the past decade and a half. Whereas only five percent of adults in the United States reported using a social media platform in 2005, that number is now around 70 percent .

Growth in the number of people who use Facebook, Instagram, Twitter, and Snapchat and other social media platforms — and the time spent on them—has garnered interest and concern among policymakers, teachers, parents, and clinicians about social media's impacts on our lives and psychological well-being.

While the research is still in its early years — Facebook itself only celebrated its 15 th birthday this year — media psychology researchers are beginning to tease apart the ways in which time spent on these platforms is, and is not, impacting our day-to-day lives.

Social media and relationships

One particularly pernicious concern is whether time spent on social media sites is eating away at face-to-face time, a phenomenon known as social displacement .

Fears about social displacement are longstanding, as old as the telephone and probably older. “This issue of displacement has gone on for more than 100 years,” says Jeffrey Hall, PhD, director of the Relationships and Technology Lab at the University of Kansas. “No matter what the technology is,” says Hall, there is always a “cultural belief that it's replacing face-to-face time with our close friends and family.”

Hall's research interrogates that cultural belief. In one study , participants kept a daily log of time spent doing 19 different activities during weeks when they were and were not asked to abstain from using social media. In the weeks when people abstained from social media, they spent more time browsing the internet, working, cleaning, and doing household chores. However, during these same abstention periods, there was no difference in people's time spent socializing with their strongest social ties.

The upshot? “I tend to believe, given my own work and then reading the work of others, that there's very little evidence that social media directly displaces meaningful interaction with close relational partners,” says Hall. One possible reason for this is because we tend to interact with our close loved ones through several different modalities—such as texts, emails, phone calls, and in-person time.

What about teens?

When it comes to teens, a recent study by Jean Twenge , PhD, professor of psychology at San Diego State University, and colleagues found that, as a cohort, high school seniors heading to college in 2016 spent an “ hour less a day engaging in in-person social interaction” — such as going to parties, movies, or riding in cars together — compared with high school seniors in the late 1980s. As a group, this decline was associated with increased digital media use. However, at the individual level, more social media use was positively associated with more in-person social interaction. The study also found that adolescents who spent the most time on social media and the least time in face-to-face social interactions reported the most loneliness.

While Twenge and colleagues posit that overall face-to-face interactions among teens may be down due to increased time spent on digital media, Hall says there's a possibility that the relationship goes the other way.

Hall cites the work of danah boyd, PhD, principal researcher at Microsoft Research  and the founder of Data & Society . “She [boyd] says that it's not the case that teens are displacing their social face-to-face time through social media. Instead, she argues we got the causality reversed,” says Hall. “We are increasingly restricting teens' ability to spend time with their peers . . . and they're turning to social media to augment it.”

According to Hall, both phenomena could be happening in tandem — restrictive parenting could drive social media use and social media use could reduce the time teens spend together in person — but focusing on the latter places the culpability more on teens while ignoring the societal forces that are also at play.

The evidence is clear about one thing: Social media is popular among teens. A 2018 Common Sense Media report found that 81 percent of teens use social media, and more than a third report using social media sites multiple times an hour. These statistics have risen dramatically over the past six years, likely driven by increased access to mobile devices. Rising along with these stats is a growing interest in the impact that social media is having on teen cognitive development and psychological well-being.

“What we have found, in general, is that social media presents both risks and opportunities for adolescents,” says Kaveri Subrahmanyam, PhD, a developmental psychologist, professor at Cal State LA, and associate director of the Children's Digital Media Center, Los Angeles .

Risks of expanding social networks

Social media benefits teens by expanding their social networks and keeping them in touch with their peers and far-away friends and family. It is also a creativity outlet. In the Common Sense Media report, more than a quarter of teens said that “social media is ‘extremely' or ‘very' important for them for expressing themselves creatively.”

But there are also risks. The Common Sense Media survey found that 13 percent of teens reported being cyberbullied at least once. And social media can be a conduit for accessing inappropriate content like violent images or pornography. Nearly two-thirds of teens who use social media said they “'often' or ‘sometimes' come across racist, sexist, homophobic, or religious-based hate content in social media.”

With all of these benefits and risks, how is social media affecting cognitive development? “What we have found at the Children's Digital Media Center is that a lot of digital communication use and, in particular, social media use seems to be connected to offline developmental concerns,” says Subrahmanyam. “If you look at the adolescent developmental literature, the core issues facing youth are sexuality, identity, and intimacy,” says Subrahmanyam.

Her research suggests that different types of digital communication may involve different developmental issues. For example, she has found that teens frequently talked about sex in chat rooms , whereas their use of blogs and social media appears to be more concerned with self-presentation and identity construction.

In particular, exploring one's identity appears to be a crucial use of visually focused social media sites for adolescents. “Whether it's Facebook, whether it's Instagram, there's a lot of strategic self presentation, and it does seem to be in the service of identity,” says Subrahmanyam. “I think where it gets gray is that we don't know if this is necessarily beneficial or if it harms.”

Remaining questions

“It's important to develop a coherent identity,” she says. “But within the context of social media — when it's not clear that people are necessarily engaging in real self presentation and there's a lot of ideal-self or false-self presentation — is that good?”

There are also more questions than answers when it comes to how social media affects the development of intimate relationships during adolescence. Does having a wide network of contacts — as is common in social media—lead to more superficial interactions and hinder intimacy? Or, perhaps more important, “Is the support that you get online as effective as the support that you get offline?” ponders Subrahmanyam. “We don't know that necessarily.”

Based on her own research comparing text messages and face-to-face interactions, she says: “My hypothesis is that maybe digital interactions may be a little more ephemeral, they're a little more fleeting, and you feel good, but that the feeling is lost quickly versus face-to-face interaction.”

However, she notes that today's teens — being tech natives — may get less hung up on the online/offline dichotomy. “ We tend to think about online and offline as disconnected, but we have to recognize that for youth . . . there's so much more fluidity and connectedness between the real and the physical and the offline and the online,” she says.

In fact, growing up with digital technology may be changing teen brain development in ways we don't yet know — and these changes may, in turn, change how teens relate to technology. “Because the exposure to technology is happening so early, we have to be mindful of the possibility that perhaps there are changes happening at a neural level with early exposure,” says Subrahmanyam. “How youths interact with technology could just be qualitatively different from how we do it.”

In part two of this article , we will look at how social media affects psychological well-being and ways of using social media that are likely to amplify its benefits and decrease its harms.

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New report says restricting social media access can help kids ... but only sometimes

A new report from the National Academies of Sciences, Engineering and Medicine released Wednesday grapples with the questions: Is social media harming teenagers? And what can parents, and the government, do about it? 

The answers are murky.

The authors surveyed hundreds of studies across more than a decade and came to complicated, occasionally contradictory, conclusions. 

On one hand, they found there isn’t enough population data to specifically blame social media for changes in adolescent health. On the other hand, as shown in study after study cited by the report, social media has the clear potential to hurt the health of teenagers, and in situations where a teenager is already experiencing difficulties like a mental health crisis, social media tends to make it worse. 

What is needed: more research and more coordination.

“There is much we still don’t know, but our report lays out a clear path forward for both pursuing the biggest unanswered questions about youth health and social media, and taking steps that can minimize the risk to young people using social media now,” Sandro Galea, dean of the Boston University School of Public Health and chair of the committee behind the report, said in a news release.

In adolescents, overly restrictive and controlling parental rules, like confiscating a phone for punishment, are often associated with that teenager taking more risks online.

“Our recommendations call on social media companies, Congress, federal agencies, and others to make changes that will protect and benefit young people who use social media,” he added.

Parents hoping for clear guidelines will have to keep waiting.

“The committee sympathizes with some parents’ desire for authoritative prescription on teenagers’ social media use but is also mindful of overreaching the data,” the report concludes. “Venturing hard and fast rules regarding teenagers’ use of social media, rules that the data cannot support, is not something this committee can do.”

The National Academies of Sciences, Engineering and Medicine is an advisory group tasked by Congress with providing guidance on science-related issues.

But its report suggests that parents are closer than ever to arriving at effective strategies for navigating their families through the social media landscape. In the future, calculating the harms and potential benefits of social media will have to take place on a case-by-case basis, it suggests, taking into account factors that will vary widely from teenager to teenager and family to family. 

For instance, the report says that while middle school girls have been found to experience social anxiety, body dissatisfaction and depression when they compared themselves with others on social media, factors such as media literacy, supportive parents and a positive school environment lessened those negative effects.  

The ways social media is used seem to make a difference. When a teenager passively scrolls, as opposed to actively posting, that’s connected by many studies to low life satisfaction and feelings of sadness. It may be that showcasing a hobby or an interest on social media doesn’t produce the same harms. 

But those rates differ by demographic group: Black, non-Hispanic participants in one study reported more negative moods during active social media use, suggesting that the potential benefits of posting on social media are not the same for teenagers of all backgrounds.

And age affects how well certain strategies work. In younger children (12 and under), a family policy that restricts social media except when it’s actively guided by a parent seems to reduce the risk of problematic use and inappropriate behavior online. But in adolescents (13 and older), overly restrictive and controlling parental rules, like confiscating a phone for punishment, are often associated with that teenager taking more risks online. 

“Restrictions on media use are useful for young children,” the authors write, “while increased communication and awareness are more suitable and helpful for teenagers.”

Faced with an urgent need to “create a more transparent industry and a better-informed consumer of social media,” the report calls on companies and regulators to establish international standards, such as clear ways for companies to share data with researchers and accepted best practices to avoid proven harms where possible. 

It recommends that the International Organization for Standardization — a body that sets global rules in areas such as manufacturing and food safety — be tasked with creating a new system, one that could be used by federal and international agencies to track and evaluate social media companies and the algorithms they build. And it asks for funding from the National Institutes of Health, the National Science Foundation and other agencies to pay for the sort of large, long-term studies that have in the past identified major public health crises. 

This story was first published on NBCNews.com.

Jacob Ward, a technology correspondent for NBC News, is a 2018-19 Berggruen Fellow at Stanford University’s Center for Advanced Study in the Behavioral Sciences, where he is writing a book about how artificial intelligence will shape human behavior. 

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Media Tone: The Role of News and Social Media on Heterogeneous Inflation Expectations

Bank of Finland Research Discussion Paper No. 8/2024

67 Pages Posted: 5 Sep 2024

Joni Heikkinen

Bank of Finland - Research

Kari Heimonen

University of Jyväskylä - Jyväskylä International Macro & Finance Research Group (JyIMaF)

Date Written: September 04, 2024

This study investigates the role of media tone on inflation expectations. Examining the relationships between news and the inflation expectations of various U.S demographic groupings, we find that traditional news influences older cohorts, while social media news align more closely with the expectations of younger and more educated groups. Interestingly, social media correspond more closely than traditional news with the expectations of professional forecasters. Our analysis shows that media influences can persist for longer than a year, highlighting the importance of historical inflation data and the gradual adaptation of new information. Additionally, we find that separate media tones for specific news topics such as “Inflation & Fed” and “Healthcare Costs” resonate differently across demographic groups. These insights highlight the nuanced role of media in shaping inflation expectations across demographic segments. 

Keywords: Inflation Expectations, Household Heterogeneity, Media Tone, Local Projection, Language Model, Forecasting

JEL Classification: E3, E31, E32, E52, E58

Suggested Citation: Suggested Citation

Joni Heikkinen (Contact Author)

Bank of finland - research ( email ), university of jyväskylä - jyväskylä international macro & finance research group (jyimaf) ( email ).

PO Box 35 Jyväskylä Finland

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The Impact of Social Media on the Mental Health of Adolescents and Young Adults: A Systematic Review

Abderrahman m khalaf.

1 Psychiatry Department, Saudi Commission for Health Specialties, Ministry of Health, Riyadh, SAU

Abdullah A Alubied

Ahmed m khalaf.

2 College of Medicine, Imam Mohammad Ibn Saud Islamic University, Riyadh, SAU

Abdallah A Rifaey

3 College of Medicine, Almaarefa University, Riyadh, SAU

Adolescents increasingly find it difficult to picture their lives without social media. Practitioners need to be able to assess risk, and social media may be a new component to consider. Although there is limited empirical evidence to support the claim, the perception of the link between social media and mental health is heavily influenced by teenage and professional perspectives. Privacy concerns, cyberbullying, and bad effects on schooling and mental health are all risks associated with this population's usage of social media. However, ethical social media use can expand opportunities for connection and conversation, as well as boost self-esteem, promote health, and gain access to critical medical information. Despite mounting evidence of social media's negative effects on adolescent mental health, there is still a scarcity of empirical research on how teens comprehend social media, particularly as a body of wisdom, or how they might employ wider modern media discourses to express themselves. Youth use cell phones and other forms of media in large numbers, resulting in chronic sleep loss, which has a negative influence on cognitive ability, school performance, and socio-emotional functioning. According to data from several cross-sectional, longitudinal, and empirical research, smartphone and social media use among teenagers relates to an increase in mental distress, self-harming behaviors, and suicidality. Clinicians can work with young people and their families to reduce the hazards of social media and smartphone usage by using open, nonjudgmental, and developmentally appropriate tactics, including education and practical problem-solving.

Introduction and background

Humans are naturally social species that depend on the companionship of others to thrive in life. Thus, while being socially linked with others helps alleviate stress, worry, and melancholy, a lack of social connection can pose major threats to one's mental health [ 1 ]. Over the past 10 years, the rapid emergence of social networking sites like Facebook, Twitter, Instagram, and others has led to some significant changes in how people connect and communicate (Table 1 ). Over one billion people are currently active users of Facebook, the largest social networking website, and it is anticipated that this number will grow significantly over time, especially in developing countries. Facebook is used for both personal and professional interaction, and its deployment has had a number of positive effects on connectivity, idea sharing, and online learning [ 2 ]. Furthermore, the number of social media users globally in 2019 was 3.484 billion, a 9% increase year on year [ 3 ].

Mental health is represented as a state of well-being in which individuals recognize their potential, successfully navigate daily challenges, perform effectively at work, and make a substantial difference in the lives of others [ 4 ]. There is currently debate over the benefits and drawbacks of social media on mental health [ 5 ]. Social networking is an important part of safeguarding our mental health. Mental health, health behavior, physical health, and mortality risk are all affected by the quantity and quality of social contacts [ 5 ].

Social media use and mental health may be related, and the displaced behavior theory could assist in clarifying why. The displaced behavior hypothesis is a psychology theory that suggests people have limited self-control and, when confronted with a challenging or stressful situation, may engage in behaviors that bring instant gratification but are not in accordance with their long-term objectives [ 6 ]. In addition, when people are unable to deal with stress in a healthy way, they may act out in ways that temporarily make them feel better but ultimately harm their long-term goals and wellness [ 7 , 8 ]. In the 1990s, social psychologist Roy Baumeister initially suggested the displaced behavior theory [ 9 ]. Baumeister suggested that self-control is a limited resource that can be drained over time and that when self-control resources are low, people are more likely to engage in impulsive or self-destructive conduct [ 9 ]. This can lead to a cycle of bad behaviors and outcomes, as individuals may engage in behaviors that bring short respite but eventually add to their stress and difficulties [ 9 ]. According to the hypothetical terms, those who participate in sedentary behaviors, including social media, engage in fewer opportunities for in-person social interaction, both of which have been demonstrated to be protective against mental illnesses [ 10 ]. Social theories, on the other hand, discovered that social media use influences mental health by affecting how people interpret, maintain, and interact with their social network [ 4 ].

Numerous studies on social media's effects have been conducted, and it has been proposed that prolonged use of social media sites like Facebook may be linked to negative manifestations and symptoms of depression, anxiety, and stress [ 11 ]. A distinct and important time in a person's life is adolescence. Additionally, risk factors such as family issues, bullying, and social isolation are readily available at this period, and it is crucial to preserve social and emotional growth. The growth of digital technology has affected numerous areas of adolescent lives. Nowadays, teenagers' use of social media is one of their most apparent characteristics. Being socially connected with other people is a typical phenomenon, whether at home, school, or a social gathering, and adolescents are constantly in touch with their classmates via social media accounts. Adolescents are drawn to social networking sites because they allow them to publish pictures, images, and videos on their platforms. It also allows teens to establish friends, discuss ideas, discover new interests, and try out new kinds of self-expression. Users of these platforms can freely like and comment on posts as well as share them without any restrictions. Teenagers now frequently post insulting remarks on social media platforms. Adolescents frequently engage in trolling for amusement without recognizing the potentially harmful consequences. Trolling on these platforms focuses on body shaming, individual abilities, language, and lifestyle, among other things. The effects that result from trolling might cause anxiety, depressive symptoms, stress, feelings of isolation, and suicidal thoughts. The authors explain the influence of social media on teenage well-being through a review of existing literature and provide intervention and preventative measures at the individual, family, and community levels [ 12 ].

Although there is a "generally correlated" link between teen social media use and depression, certain outcomes have been inconsistent (such as the association between time spent on social media and mental health issues), and the data quality is frequently poor [ 13 ]. Browsing social media could increase your risk of self-harm, loneliness, and empathy loss, according to a number of research studies. Other studies either concluded that there is no harm or that some people, such as those who are socially isolated or marginalized, may benefit from using social media [ 10 ]. Because of the rapid expansion of the technological landscape in recent years, social media has become increasingly important in the lives of young people. Social networking has created both enormous new challenges and interesting new opportunities. Research is beginning to indicate how specific social media interactions may impair young people's mental health [ 14 ]. Teenagers could communicate with one another on social media platforms, as well as produce, like, and share content. In most cases, these individuals are categorized as active users. On the other hand, teens can also use social media in a passive manner by "lurking" and focusing entirely on the content that is posted by others. The difference between active and passive social media usage is sometimes criticized as a false dichotomy because it does not necessarily reveal whether a certain activity is goal-oriented or indicative of procrastination [ 15 ]. However, the text provides no justification for why this distinction is wrong [ 16 ]. For instance, one definition of procrastination is engaging in conversation with other people to put off working on a task that is more important. The goal of seeing the information created by other people, as opposed to participating with those same individuals, may be to keep up with the lives of friends. One of the most important distinctions that can be made between the various sorts is whether the usage is social. When it comes to understanding and evaluating all these different applications of digital technology, there are a lot of obstacles to overcome. Combining all digital acts into a single predictor of pleasure would, from both a philosophical and an empirical one, invariably results in a reduction in accuracy [ 17 ].

Methodology

This systematic review was carried out and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and standard practices in the field. The purpose of this study was to identify studies on the influence of technology, primarily social media, on the psychosocial functioning, health, and well-being of adolescents and young adults.

The MEDLINE bibliographical database, PubMed, Google Scholar, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Scopus were searched between 1 January 2000 and 30 May 2023. Social media AND mental health AND adolescents AND young adults were included in the search strategy (impact or relation or effect or influence).

Two researchers (AK and AR) separately conducted a literature search utilizing the search method and evaluated the inclusion eligibility of the discovered papers based on their titles and abstracts. Then, the full texts of possibly admissible publications were retrieved and evaluated for inclusion. Disagreements among the researchers were resolved by debate and consensus.

The researchers included studies that examined the impact of technology, primarily social media, on the psychosocial functioning, health, and well-being of adolescents and young adults. We only considered English publications, reviews, longitudinal surveys, and cross-sectional studies. We excluded studies that were not written in English, were not comparative, were case reports, did not report the results of interest, or did not list the authors' names. We also found additional articles by looking at the reference lists of the retrieved articles.

Using a uniform form, the two researchers (AK and AA) extracted the data individually and independently. The extracted data include the author, publication year, study design, sample size and age range, outcome measures, and the most important findings or conclusions.

A narrative synthesis of the findings was used to analyze the data, which required summarizing and presenting the results of the included research in a logical and intelligible manner. Each study's key findings or conclusions were summarized in a table.

Study Selection

A thorough search of electronic databases, including PubMed, Embase, and Cochrane Library, was done from 1 January 2000 to 20 May 2023. Initial research revealed 326 potentially relevant studies. After deleting duplicates and screening titles and abstracts, the eligibility of 34 full-text publications was evaluated. A total of 23 papers were removed for a variety of reasons, including non-comparative studies, case reports, and studies that did not report results of interest (Figure ​ (Figure1 1 ).

PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

This systematic review identified 11 studies that examined the connection between social media use and depression symptoms in children and adolescents. The research demonstrated a modest but statistically significant association between social media use and depression symptoms. However, this relationship's causality is unclear, and additional study is required to construct explanatory models and hypotheses for inferential studies [ 18 ].

Additional research studied the effects of technology on the psychosocial functioning, health, and well-being of adolescents and young adults. Higher levels of social media usage were connected with worse mental health outcomes [ 19 ], and higher levels of social media use were associated with an increased risk of internalizing and externalizing difficulties among adolescents, especially females [ 20 ]. The use of social media was also connected with body image problems and disordered eating, especially among young women [ 21 ], and social media may be a risk factor for alcohol consumption and associated consequences among adolescents and young adults [ 22 ].

It was discovered that cyberbullying victimization is connected with poorer mental health outcomes in teenagers, including an increased risk of sadness and anxiety [ 23 ]. The use of social media was also connected with more depressive symptoms and excessive reassurance-seeking, but also with greater popularity and perceived social support [ 24 ], as well as appearance comparisons and body image worries, especially among young women [ 25 ]. Children and adolescents' bedtime media device use was substantially related to inadequate sleep quantity, poor sleep quality, and excessive daytime drowsiness [ 26 ].

Online friends can be a significant source of social support, but in-person social support appears to provide greater protection against persecution [ 27 ]. Digital and social media use offers both benefits and risks to the health of children and adolescents, and an individualized family media use plan can help strike a balance between screen time/online time and other activities, set boundaries for accessing content, promote digital literacy, and support open family communication and consistent media use rules (Tables ​ (Tables2, 2 , ​ ,3) 3 ) [ 28 ].

Does Social Media Have a Positive or Negative Impact on Adolescents and Young Adults?

Adults frequently blame the media for the problems that younger generations face, conceptually bundling different behaviors and patterns of use under a single term when it comes to using media to increase acceptance or a feeling of community [ 29 , 30 ]. The effects of social media on mental health are complex, as different goals are served by different behaviors and different outcomes are produced by distinct patterns of use [ 31 ]. The numerous ways that people use digital technology are often disregarded by policymakers and the general public, as they are seen as "generic activities" that do not have any specific impact [ 32 ]. Given this, it is crucial to acknowledge the complex nature of the effects that digital technology has on adolescents' mental health [ 19 ]. This empirical uncertainty is made worse by the fact that there are not many documented metrics of how technology is used. Self-reports are the most commonly used method for measuring technology use, but they can be prone to inaccuracy. This is because self-reports are based on people's own perceptions of their behavior, and these perceptions can be inaccurate [ 33 ]. At best, there is simply a weak correlation between self-reported smartphone usage patterns and levels that have been objectively verified [ 34 , 35 ].

When all different kinds of technological use are lumped together into a single behavioral category, not only does the measurement of that category contribute to a loss of precision, but the category also contributes to a loss of precision. To obtain precision, we need to investigate the repercussions of a wide variety of applications, ideally guided by the findings of scientific research [ 36 ]. The findings of this research have frequently been difficult to interpret, with many of them suggesting that using social media may have a somewhat negative but significantly damaging impact on one's mental health [ 36 ]. There is a growing corpus of research that is attempting to provide a more in-depth understanding of the elements that influence the development of mental health, social interaction, and emotional growth in adolescents [ 20 ].

It is challenging to provide a succinct explanation of the effects that social media has on young people because it makes use of a range of different digital approaches [ 37 , 38 ]. To utilize and respond to social media in either an adaptive or maladaptive manner, it is crucial to first have a solid understanding of personal qualities that some children may be more likely to exhibit than others [ 39 ]. In addition to this, the specific behaviors or experiences on social media that put teenagers in danger need to be recognized.

When a previous study particularly questioned teenagers in the United States, the authors found that 31% of them believe the consequences are predominantly good, 45% believe they are neither positive nor harmful, and 24% believe they are unfavorable [ 21 ]. Teens who considered social media beneficial reported that they were able to interact with friends, learn new things, and meet individuals who shared similar interests because of it. Social media is said to enhance the possibility of (i) bullying, (ii) ignoring face-to-face contact, and (iii) obtaining incorrect beliefs about the lives of other people, according to those who believe the ramifications are serious [ 21 ]. In addition, there is the possibility of avoiding depression and suicide by recognizing the warning signs and making use of the information [ 40 ]. A common topic that comes up in this area of research is the connection that should be made between traditional risks and those that can be encountered online. The concept that the digital age and its effects are too sophisticated, rapidly shifting, or nuanced for us to fully comprehend or properly shepherd young people through is being questioned, which challenges the traditional narrative that is sent to parents [ 41 ]. The last thing that needs to be looked at is potential mediators of the link between social factors and teenage depression and suicidality (for example, gender, age, and the participation of parents) [ 22 ].

The Dangers That Come With Young Adults Utilizing Social Media

The experiences that adolescents have with their peers have a substantial impact on the onset and maintenance of psychopathology in those teenagers. Peer relationships in the world of social media can be more frequent, intense, and rapid than in real life [ 42 ]. Previous research [ 22 ] has identified a few distinct types of peer interactions that can take place online as potential risk factors for mental health. Being the target of cyberbullying, also known as cyber victimization, has been shown to relate to greater rates of self-inflicted damage, suicidal ideation, and a variety of other internalizing and externalizing issues [ 43 ]. Additionally, young people may be put in danger by the peer pressure that can be found on social networking platforms [ 44 ]. This can take the form of being rejected by peers, engaging in online fights, or being involved in drama or conflict [ 45 ]. Peer influence processes may also be amplified among teenagers who spend time online, where they have access to a wider diversity of their peers as well as content that could be damaging to them [ 46 ]. If young people are exposed to information on social media that depicts risky behavior, their likelihood of engaging in such behavior themselves (such as drinking or using other drugs) may increase [ 22 ]. It may be simple to gain access to online materials that deal with self-harm and suicide, which may result in an increase in the risk of self-harm among adolescents who are already at risk [ 22 ]. A recent study found that 14.8% of young people who were admitted to mental hospitals because they posed a risk to others or themselves had viewed internet sites that encouraged suicide in the two weeks leading up to their admission [ 24 ]. The research was conducted on young people who were referred to mental hospitals because they constituted a risk to others or themselves [ 24 ]. They prefer to publish pictures of themselves on social networking sites, which results in a steady flow of messages and pictures that are often and painstakingly modified to present people in a favorable light [ 24 ]. This influences certain young individuals, leading them to begin making unfavorable comparisons between themselves and others, whether about their achievements, their abilities, or their appearance [ 47 , 48 ].

There is a correlation between higher levels of social networking in comparison and depressed symptoms in adolescents, according to studies [ 25 ]. When determining how the use of technology impacts the mental health of adolescents, it is essential to consider the issue of displacement. This refers to the question of what other important activities are being replaced by time spent on social media [ 49 ]. It is a well-established fact that the circadian rhythms of children and adolescents have a substantial bearing on both their physical and mental development.

However, past studies have shown a consistent connection between using a mobile device before bed and poorer sleep quality results [ 50 ]. These results include shorter sleep lengths, decreased sleep quality, and daytime tiredness [ 50 ]. Notably, 36% of adolescents claim they wake up at least once over the course of the night to check their electronic devices, and 40% of adolescents say they use a mobile device within five minutes of going to bed [ 25 ]. Because of this, the impact of social media on the quality of sleep continues to be a substantial risk factor for subsequent mental health disorders in young people, making it an essential topic for the continuation of research in this area [ 44 ].

Most studies that have been conducted to investigate the link between using social media and experiencing depression symptoms have concentrated on how frequently and problematically people use social media [ 4 ]. Most of the research that was taken into consideration for this study found a positive and reciprocal link between the use of social media and feelings of depression and, on occasion, suicidal ideation [ 51 , 52 ]. Additionally, it is unknown to what extent the vulnerability of teenagers and the characteristics of substance use affect this connection [ 52 ]. It is also unknown whether other aspects of the environment, such as differences in cultural norms or the advice and support provided by parents, have any bearing on this connection [ 25 ]. Even if it is probable that moderate use relates to improved self-regulation, it is not apparent whether this is the result of intermediate users having naturally greater self-regulation [ 25 ].

Gains From Social Media

Even though most of the debate on young people and new media has centered on potential issues, the unique features of the social media ecosystem have made it feasible to support adolescent mental health in more ways than ever before [ 39 ]. Among other benefits, using social media may present opportunities for humor and entertainment, identity formation, and creative expression [ 53 ]. More mobile devices than ever before are in the hands of teenagers, and they are using social media at never-before-seen levels [ 27 ]. This may not come as a surprise given how strongly young people are drawn to digital devices and the affordances they offer, as well as their heightened craving for novelty, social acceptance, and affinity [ 27 ]. Teenagers are interacting with digital technology for longer periods of time, so it is critical to comprehend the effects of this usage and use new technologies to promote teens' mental health and well-being rather than hurt it [ 53 ]. Considering the ongoing public discussion, we should instead emphasize that digital technology is neither good nor bad in and of itself [ 27 ].

One of the most well-known benefits of social media is social connection; 81% of students say it boosts their sense of connectedness to others. Connecting with friends and family is usually cited by teenagers as the main benefit of social media, and prior research typically supports the notion that doing so improves people's well-being. Social media can be used to increase acceptance or a feeling of community by providing adolescents with opportunities to connect with others who share their interests, beliefs, and experiences [ 29 ]. Digital media has the potential to improve adolescent mental health in a variety of ways, including cutting-edge applications in medical screening, treatment, and prevention [ 28 ]. In terms of screening, past research has suggested that perusing social media pages for signs of melancholy or drug abuse may be viable. More advanced machine-learning approaches have been created to identify mental disease signs on social media, such as depression, post-traumatic stress disorder, and suicidality. Self-report measures are used in most studies currently conducted on adolescent media intake. It is impossible to draw firm conclusions on whether media use precedes and predicts negative effects on mental health because research has only been conducted once. Adults frequently blame the media for the problems that younger generations face [ 30 ]. Because they are cyclical, media panics should not just be attributed to the novel and the unknown. Teenagers' time management, worldview, and social interactions have quickly and dramatically changed as a result of technology. Social media offers a previously unheard-of opportunity to spread awareness of mental health difficulties, and social media-based health promotion programs have been tested for a range of cognitive and behavioral health conditions. Thanks to social media's instant accessibility, extensive possibilities, and ability to reach remote areas, young people with mental health issues have exciting therapy options [ 54 ]. Preliminary data indicate that youth-focused mental health mobile applications are acceptable, but further research is needed to assess their usefulness and effectiveness. Youth now face new opportunities and problems as a result of the growing significance of digital media in their life. An expanding corpus of research suggests that teenagers' use of social media may have an impact on their mental health. But more research is needed [ 18 ] considering how swiftly the digital media landscape is changing.

Conclusions

In the digital era, people efficiently employ technology; it does not "happen" to them. Studies show that the average kid will not be harmed by using digital technology, but that does not mean there are no situations where it could. In this study, we discovered a connection between social media use and adolescent depression. Since cross-sectional research represents the majority, longitudinal studies are required. The social and personal life of young people is heavily influenced by social media. Based on incomplete and contradictory knowledge on young people and digital technology, professional organizations provide guidance to parents, educators, and institutions. If new technologies are necessary to promote social interaction or develop digital and relational (digitally mediated) skills for growing economies, policies restricting teen access to them may be ineffective. The research on the impact of social media on mental health is still in its early stages, and more research is needed before we can make definitive recommendations for parents, educators, or institutions. Reaching young people during times of need and when assistance is required is crucial for their health. The availability of various friendships and services may improve the well-being of teenagers.

The authors have declared that no competing interests exist.

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Social Media Content Plan: What You Need to Succeed

Craft a winning social media content plan that boosts engagement, enhances brand visibility, and aligns with your marketing goals. This guide covers all you need to succeed.

If your brand has an online presence, having an effective social media content plan should be the core of your digital marketing strategy.

So, why is it worth putting time and effort into a content plan for social media?

In short, a social media content plan acts to foster engagement between you and your audience. Paired with a social media content calendar, it can guide you to deliver the right messages to the right people.

After all, a thought-out plan can spotlight your brand and turn potential customers into loyal clients. Content planning has never been so valuable.

The best plans for social media content begin with setting clear goals and conducting some investigation into what makes your audience tick. After that, you'll be on a path to creating content that both resonates with your audience and showcases your brand.

Once your content plan is in action, we'll look at how to analyze whether it's doing its job properly, and leave you with a few tips for changing course if required.

In this article we cover:

Understanding the social media landscape

Developing a social media strategy, crafting a content strategy, operations and management tools, building an actionable content calendar, implementing your social media content plan, measuring success and optimization, maintaining a dynamic social media approach.

• Final notes on creating a content plan

First, let's cover some basics.

Before you get started on drafting a content plan for social media, it's important to have a wider understanding of the social media landscape. Consider the social media platforms available for you to use, and then think about which of these your target audience tend to gravitate towards. Which communities can you tap into? And which apps have the largest number of your target audience on them?

This groundwork will help you focus your efforts, so let's look at those steps in more detail.

Defining social media marketing

Social media marketing is essentially just using social media to tell people about your brand, products, or services.

It involves lots of different types of content – anything from straightforward text (for example, in a tweet) to carefully edited video or images.

As you develop your social media strategy, you'll be thinking about things like:

• Which platforms your audience uses
• What type of content your brand should be using to convey it's message
• How often you plan to post on social media
• How to encourage user engagement

The role of different social platforms

Different social media platforms cater to specific purposes and audiences. Unless you have a big social media team, you'll probably be focusing your efforts on creating content for a few social media channels, rather than every single one. Think quality over quantity.

For example, you might choose to build a presence on Instagram in the first instance, then add content for TikTok later as your brand grows.

If your brand does a lot of business-to-business marketing, you might decide that more LinkedIn activity would be useful. Alternatively, you might decided that Facebook has a place in your strategy.

Next up in the quest to develop your social media strategy, let's look at some factors like your current activity on social media, your audience, and your social media marketing goals.

This is also a good opportunity to have a closer look at what your competitors are getting up to on social media, too.

Assessing your social media presence

Before diving into a new social media content plan, take a moment to think about your current social media activity. A social media audit, of sorts.

Look at which platforms are performing the best in terms of engagement, followers, and conversions.

Cast a critical eye over the content you've published in the past to determine if it resonates with your audience. It's important to be honest here. If you spent months on a social media campaign that didn't work, then admit it didn't and learn from those mistakes.

Check, too, that you've been posting consistently across all platforms you have a presence on. This initial assessment will give you a better idea of where your current social media efforts stand.

Once you have these answers in mind, you can identify areas that need improvement.

Setting social media marketing goals

It's also good to have some clear and measurable social media marketing goals to guide your strategy.

You might decide to focus on things like increasing brand awareness, lead generation, driving website traffic, or getting more engagement.

Remember, your social media goals should match up with your overall marketing objectives.

Want to know more? Read our blog on social media management tips.

Identifying your target audience

Knowing your audience will help you create social media content that resonates and inspires people to click like, share, comment, or follow.

When thinking about your target audience, first consider their demographics (age, gender, or income), then consider things like geographic location, interests, and challenges or pain points.

By knowing your audience, you can learn how to create content that appeals to their interests, which in turn, will result in higher engagement and conversions.

Conducting a competitive analysis

A bit of competitive analysis can tell you all you need to know about your competitors’ strengths and weaknesses.

Start by listing your top competitors. This part is usually pretty easy, as you've probably been bumping into them online as they offer similar products or services in your market.

Next up, gather data that gives you information about your competitors’ social media accounts. Look at the types of content they are publishing, and how many people are engaging with them.

After that, draw a few comparisons between your social media performance and theirs. Look for patterns, trends, and opportunities for improvement.

With this information, you can brainstorm ways to differentiate your social media activity from your competitors and capitalize on the unique aspects of your brand.

Read our extensive Competitor Analysis guide for more info.

So, you should now have an understanding of the current social media landscape, have a few goals in mind, and know what your competitors are doing.

Now it's time to use all of this to create an amazing social media strategy.

There are a few techniques to cover here, so we'll dive right in.

Audience engagement techniques

Engagement is a really important part of a successful social media strategy.

If people don't engage with your social media content, then your posts will be hidden by algorithms that prioritize high engagement rates. So you want people to like, comment, save, or share your posts.

On the flip side, high levels of engagement will increase brand awareness, attract more followers, and boost conversions.

So, it's a good idea to include some specific techniques for increasing engagement in your content plan.

This might look like asking questions that encourage people to share their opinions, experiences, or suggestions in the comments. You could also try polls and quizzes. These can to be quite irresistible to audiences – a lot of people will click just to see the results. Of course, the results also double up as data about your audience for you to use elsewhere in your strategy.

Video content and livestreams are another way to drive higher engagement rates, as they often bring more views than still images.

Finally, educational content can bring more eyes to your posts as your audience will look to you as a knowledgeable source and come back to learn more.

Remember, if you're not seeing engagement rates go up after putting your strategy into action, you can always change course when needed.

Incorporating user generated content

Sharing user generated content (UGC) is another smart way to boost your social media content strategy.

For example, a clothing brand could share a reel from a style influencer featuring products that were gifted from their brand.

We love UGC. Not only does it save time and money by making the most of existing content, it's also exciting for your customers to see their content on your social media account.

You could try contests and giveaways to encourage UGC. Give users who share content related to your brand a chance to win prizes or recognition.

Testimonials and reviews can also count as UGC, endorsing your brand's authenticity.

Finally, if you share your audience's experiences or stories related to your brand, this will help to build a sense of community and trust.

Remember to always ask for permission before using someone's content, and give proper credit when sharing it.

Planning for diverse content types

A well-rounded content strategy includes a mix of evergreen content, engaging content, and educational content. By mixing things up with different content types, you keep your social media channels fresh and provide opportunities for users to find something that resonates.

A carefully curated social media content calendar can help you plan for a variety of content, and analytics will help you understand which which content types perform best.

Keep an eye on trends too, in case you want to tap into them yourself!

Part of planning your social media content is knowing how you will be able to put it into action.

Here's our top tip: the easiest way to action your plan is to use a social media planning tool, or management tool.

In this section we'll take a look at the options available, and we'll also share some advice about choosing the right tool to oversee all your social media campaigns.

Choosing social media management tools

A social media management tool is the perfect partner for your social content strategy.

Some popular options include Brandwatch , Buffer, and Sprout Social. Remember though, it's a good idea to research and compare a few tools to find one that suits your needs.

Think about factors such as the platforms supported, ease of use, team collaboration features, and pricing.

Want to know more about Brandwatch? Learn how to master social media management with us!

Scheduling and automation

A consistent posting schedule is vital to keep your audience engaged and maintain your brand's presence on social media.

This can help you plan and prepare your content ahead of time, and ensure that content is shared automatically according to your plan.

Most social media management tools offer automation features that enable you to schedule posts across multiple platforms from a single dashboard, which can be super useful for social media marketers.

Tracking performance with analytics

To check if your content plan is bringing in results, it's a good idea to keep an eye on performance using social media analytics.

By monitoring engagement metrics and assessing things like follower growth and reach, you can check how your content is playing with both existing followers and new audiences.

A good social media management tool will come with built-in analytics, allowing you to easily measure the success of your posting efforts and make data-driven decisions.

Creating a social media posting schedule will involve categorizing your content and strategizing the timing and frequency of posts to bring maximum eyes to your content.

Here's a bit more detail to help guide you through these tasks.

Structuring your social media calendar

An organized social media content calendar is a must-have in any social media content strategy. There are many digital tools available to help transform your social media calendar dreams into a reality.

We suggest using a management tool like Brandwatch with a built-in social media calendar to keep everything in one place.

Simply categorize your content and tag accordingly, then make sure that different content types are spread across multiple posts.

Timing and frequency of social posts

Social media algorithms tend to favor accounts that post consistently.

For this reason, it's important to consider the timing and frequency of your social posts.

In order to increase post visibility, you should find out when your audience are most active on social platforms and use this information in your social media content calendar.

Aim for a steady flow of content to keep your followers engaged, but avoid flooding their feeds. Balance is crucial.

If you need help with this, your tool may offer you AI-led optimization. This means you can post at a time when your audience is most engaged. AI is now used is most top social media calendar tools, so look out for it!

Now that you have a content plan and a social media content calendar to guide your publishing schedule, you can start to push your content out into the world.

Here are three areas you need to focus on:

Content publishing best practices

When rolling out your content plan, there are a few best practices to keep in mind.

First, stick to a consistent posting schedule to maintain your appearance on social media and keep your audience engaged. Remember, your content calendar can help guide you through this.

Secondly, prioritize creating quality content over the quantity of content. Great social media posts published in a steady flow will always win over substandard content that's posted in a rush.

Finally, don't forget to optimize your social media content for each platform by using the appropriate image sizes, character limits, hashtags, and keywords. Your all-in-one software might have a tool that resizes posts to fit each platform, making the content creation process a whole lot easier.

Employee advocacy and involvement

You could also use your own employees as brand ambassadors – this is called employee advocacy.

To do this, simply encourage your team members to share your company's content on their personal social media channels. This will expand your reach and create a more robust, authentic social media presence.

A few guidelines can help employees feel more confident in this area, as they can access to a content library with ready-to-share posts, images, and articles.

You could also try recognition and rewards for employees who consistently demonstrate brand advocacy.

Learn how to leverage employee advocacy for social media success here!

Responding and adapting to feedback

As your audience interacts with your social media content, you'll want to monitor their feedback and adapt your plan accordingly.

The most important thing here is to respond to comments, messages, and inquiries in a timely manner. This will build trust and establish a positive relationship with your audience.

Adjust your content planning habits, posting schedule, or social media strategy as needed.

Once you've polished up your social media plan and put it into action, it's time to check that it's bringing the results you hoped for. This is where social analytics come into play.

Understanding analytics and KPIs

To measure the success of your content plan, it's essential to look at analytics and set relevant Key Performance Indicators (KPIs).

Your social media metrics will give you an idea of how well your content is performing.

Pay attention to KPIs like engagement, reach, impressions, and conversions. Of course, there are more KPIs worth tracking than just these three.

The KPIs you choose should align with your social strategy and overall goals, such as increasing brand awareness or driving website traffic.

Continuous improvement process

Once you've gathered and analyzed your data, it's time to tweak your social strategy to make it even better. This is known as a continuous improvement mindset.

Start by pinpointing top-performing content – in other words, the posts that received the most engagement. If you understand why it performed well, you can create more content with similar qualities.

You could also test various content formats such as images, videos, polls, or links to articles to see which ones resonate the most with your audience.

If nothing is sticking, you could try adjusting your posting schedule to different times of the day.

Be prepared to make changes and test new ideas to see what works best for your brand.

A brand's social media presence can quickly sour if the company doesn't appear to be evolving or doing anything new or exciting.

In order to maintain a dynamic social media approach, you should keep a close eye on your audience's preferences and the latest social media trends.

Keep things fresh by trying a new social media platform where your audience may be active.

You should also take advantage of new product features in your existing social media accounts.

Four actions to create a social media plan with meaning

But how do you do all this in practice? Below are four actionable steps you can take to broaden your content and create a social media plan that meets your audience's interests:

1. Plan content on a channel-by-channel basis

Remember that not all stories will work on every social media channel, so adapt and customize content accordingly.

Some careful reading of your analytics will also reveal which of your posts are working well and which aren't.

You might find that your LinkedIn posts fails to match the audience interests found on your Facebook channel. Use this information to plan future content that really strikes a chord with your audience.

2. Stay creative with visual content

A picture is worth a thousand words, so make sure your visual content is compelling and eye-catching. Even better – a video that keeps viewers hooked until the final second will play well for the algorithm.

This is particularly important for TikTok and Instagram, while Facebook and X favor content on how much engagement it receives.

Experiment with different formats such as images, infographics, and videos, and tap into your social media team for fresh ideas.

3. Optimize your content with relevant hashtags

Depending on the platform, relevant hashtags or keywords in your posts can increase their visibility and reach.

LinkedIn, for example, is a surprisingly useful platform for industry leaders. You can easily create your own unique hashtags and make an impact in a space that not all businesses are aware of.

So, be sure to research popular hashtags and maybe have a few industry-specific ones in your back pocket, too. Tread carefully here, though – too many hashtags or irrelevant tags could be seen as spammy.

4. Engage with your audience

A dynamic social media approach involves more than just posting content.

Take time to interact with your followers by acknowledging their comments, questions, and reactions. This not only strengthens your relationship with your audience but can also tell you a little more about their needs and preferences.

It can also help you with your overall social media goals by driving more interest to your brand, when other users see their friends interacting with you.

And there you go – you did it! You created a content plan to boost your brand's social media activity. Don't forget to check that content plan regularly. In particular, keep an eye out for any new social platforms or trends that you might want to add to your publishing rota.

Perhaps your brand has pivoted, and the social marketing strategy needs some adjustment, too? Remember to update your content ideas and social media content calendar as the brand naturally evolves.

Keep it fresh and you'll stay ahead of the competition.

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News consumption on social media, who consumes news on each social media site, find out more, social media and news fact sheet.

Digital news has become an important part of Americans’ news media diets , with social media playing a crucial role in news consumption. Today, half of U.S. adults get news at least sometimes from social media.

When it comes to where Americans regularly get news on social media, Facebook outpaces all other social media sites. Three-in-ten U.S. adults say they regularly get news there. Slightly fewer (26%) regularly get news on YouTube.

Smaller shares regularly get news on Instagram (16%), TikTok (14%), X (12%) or Reddit (8%). Even fewer Americans regularly get news on Nextdoor (5%), LinkedIn (5%), Snapchat (4%), WhatsApp (3%) or Twitch (1%).

(Seven-in-ten U.S. adults say they have seen or heard something about the renaming of Twitter as X. The platform’s name change took place in July 2023 .)

Some social media sites – despite having relatively small overall audiences – stand out for having high shares of users who regularly go to the site for news. For example, roughly half of users on X (53%) get news there. On the other hand, only 15% of Snapchat users regularly get news on the app.

There are demographic differences, such as by gender, in who turns to each social media site regularly for news. Women make up a greater portion of regular news consumers on Nextdoor (66%), Facebook (62%), Instagram (59%) and TikTok (58%), while men make up a greater share on sites like Reddit (67%), X (62%) and YouTube (58%).

Some partisan differences also arise when it comes to who regularly gets news on some social media sites. The majority of regular news consumers on many sites are Democrats or lean Democratic. No social media site included here has regular news consumers who are more likely to be Republicans or lean Republican, though there is no significant partisan difference among news consumers on Facebook, X or Nextdoor. ( Read the Appendix for data on U.S. adults in each demographic group and party who regularly get news from each social media site.)

This fact sheet was compiled by Research Analyst Jacob Liedke and Research Associate Luxuan Wang .

Read the  methodology and the topline .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. This is the latest report in Pew Research Center’s ongoing investigation of the state of news, information and journalism in the digital age, a research program funded by The Pew Charitable Trusts, with generous support from the John S. and James L. Knight Foundation.

Follow these links for more in-depth analysis of news consumption:

News Platform Fact Sheet , Nov. 15, 2023

More Americans are getting news on TikTok, bucking the trend on most other social media sites , Nov. 15, 2023

Americans are following the news less closely than they used to , Oct. 24, 2023

Black Americans’ Experiences With News , Sept. 26, 2023

U.S. adults under 30 now trust information from social media almost as much as from national news outlets , Oct. 27, 2022

More Americans are getting news on TikTok, bucking the trend on other social media sites , Oct. 21, 2022

The Role of Alternative Social Media in the News and Information Environment , Oct. 6, 2022

Twitter is the go-to social media site for U.S. journalists, but not for the public , June 27, 2022

News on Twitter: Consumed by Most Users and Trusted by Many , Nov. 15, 2021

More than eight-in-ten Americans get news from digital devices , Jan. 12, 2021

Measuring News Consumption in a Digital Era , Dec. 8, 2020

Many Americans Get News on YouTube, Where News Organizations and Independent Producers Thrive Side by Side , Sept. 28, 2020

Americans Who Mainly Get Their News on Social Media Are Less Engaged, Less Knowledgeable , July 30, 2020

Read all reports and short reads related to news platforms and sources .

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