social media influence research paper

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• v.12(6); 2020 Jun

Social Media Use and Its Connection to Mental Health: A Systematic Review

Fazida karim.

1 Psychology, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

2 Business & Management, University Sultan Zainal Abidin, Terengganu, MYS

Azeezat A Oyewande

3 Family Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

4 Family Medicine, Lagos State Health Service Commission/Alimosho General Hospital, Lagos, NGA

Lamis F Abdalla

5 Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Reem Chaudhry Ehsanullah

Safeera khan.

Social media are responsible for aggravating mental health problems. This systematic study summarizes the effects of social network usage on mental health. Fifty papers were shortlisted from google scholar databases, and after the application of various inclusion and exclusion criteria, 16 papers were chosen and all papers were evaluated for quality. Eight papers were cross-sectional studies, three were longitudinal studies, two were qualitative studies, and others were systematic reviews. Findings were classified into two outcomes of mental health: anxiety and depression. Social media activity such as time spent to have a positive effect on the mental health domain. However, due to the cross-sectional design and methodological limitations of sampling, there are considerable differences. The structure of social media influences on mental health needs to be further analyzed through qualitative research and vertical cohort studies.

Introduction and background

Human beings are social creatures that require the companionship of others to make progress in life. Thus, being socially connected with other people can relieve stress, anxiety, and sadness, but lack of social connection can pose serious risks to mental health [ 1 ].

Social media

Social media has recently become part of people's daily activities; many of them spend hours each day on Messenger, Instagram, Facebook, and other popular social media. Thus, many researchers and scholars study the impact of social media and applications on various aspects of people’s lives [ 2 ]. Moreover, the number of social media users worldwide in 2019 is 3.484 billion, up 9% year-on-year [ 3 - 5 ]. A statistic in Figure  1  shows the gender distribution of social media audiences worldwide as of January 2020, sorted by platform. It was found that only 38% of Twitter users were male but 61% were using Snapchat. In contrast, females were more likely to use LinkedIn and Facebook. There is no denying that social media has now become an important part of many people's lives. Social media has many positive and enjoyable benefits, but it can also lead to mental health problems. Previous research found that age did not have an effect but gender did; females were much more likely to experience mental health than males [ 6 , 7 ].

Impact on mental health

Mental health is defined as a state of well-being in which people understand their abilities, solve everyday life problems, work well, and make a significant contribution to the lives of their communities [ 8 ]. There is debated presently going on regarding the benefits and negative impacts of social media on mental health [ 9 , 10 ]. Social networking is a crucial element in protecting our mental health. Both the quantity and quality of social relationships affect mental health, health behavior, physical health, and mortality risk [ 9 ]. The Displaced Behavior Theory may help explain why social media shows a connection with mental health. According to the theory, people who spend more time in sedentary behaviors such as social media use have less time for face-to-face social interaction, both of which have been proven to be protective against mental disorders [ 11 , 12 ]. On the other hand, social theories found how social media use affects mental health by influencing how people view, maintain, and interact with their social network [ 13 ]. A number of studies have been conducted on the impacts of social media, and it has been indicated that the prolonged use of social media platforms such as Facebook may be related to negative signs and symptoms of depression, anxiety, and stress [ 10 - 15 ]. Furthermore, social media can create a lot of pressure to create the stereotype that others want to see and also being as popular as others.

The need for a systematic review

Systematic studies can quantitatively and qualitatively identify, aggregate, and evaluate all accessible data to generate a warm and accurate response to the research questions involved [ 4 ]. In addition, many existing systematic studies related to mental health studies have been conducted worldwide. However, only a limited number of studies are integrated with social media and conducted in the context of social science because the available literature heavily focused on medical science [ 6 ]. Because social media is a relatively new phenomenon, the potential links between their use and mental health have not been widely investigated.

This paper attempt to systematically review all the relevant literature with the aim of filling the gap by examining social media impact on mental health, which is sedentary behavior, which, if in excess, raises the risk of health problems [ 7 , 9 , 12 ]. This study is important because it provides information on the extent of the focus of peer review literature, which can assist the researchers in delivering a prospect with the aim of understanding the future attention related to climate change strategies that require scholarly attention. This study is very useful because it provides information on the extent to which peer review literature can assist researchers in presenting prospects with a view to understanding future concerns related to mental health strategies that require scientific attention. The development of the current systematic review is based on the main research question: how does social media affect mental health?

Research strategy

The research was conducted to identify studies analyzing the role of social media on mental health. Google Scholar was used as our main database to find the relevant articles. Keywords that were used for the search were: (1) “social media”, (2) “mental health”, (3) “social media” AND “mental health”, (4) “social networking” AND “mental health”, and (5) “social networking” OR “social media” AND “mental health” (Table  1 ).

Out of the results in Table  1 , a total of 50 articles relevant to the research question were selected. After applying the inclusion and exclusion criteria, duplicate papers were removed, and, finally, a total of 28 articles were selected for review (Figure  2 ).

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Inclusion and exclusion criteria

Peer-reviewed, full-text research papers from the past five years were included in the review. All selected articles were in English language and any non-peer-reviewed and duplicate papers were excluded from finally selected articles.

Of the 16 selected research papers, there were a research focus on adults, gender, and preadolescents [ 10 - 19 ]. In the design, there were qualitative and quantitative studies [ 15 , 16 ]. There were three systematic reviews and one thematic analysis that explored the better or worse of using social media among adolescents [ 20 - 23 ]. In addition, eight were cross-sectional studies and only three were longitudinal studies [ 24 - 29 ].The meta-analyses included studies published beyond the last five years in this population. Table  2  presents a selection of studies from the review.

IGU, internet gaming disorder; PSMU, problematic social media use

This study has attempted to systematically analyze the existing literature on the effect of social media use on mental health. Although the results of the study were not completely consistent, this review found a general association between social media use and mental health issues. Although there is positive evidence for a link between social media and mental health, the opposite has been reported.

For example, a previous study found no relationship between the amount of time spent on social media and depression or between social media-related activities, such as the number of online friends and the number of “selfies”, and depression [ 29 ]. Similarly, Neira and Barber found that while higher investment in social media (e.g. active social media use) predicted adolescents’ depressive symptoms, no relationship was found between the frequency of social media use and depressed mood [ 28 ].

In the 16 studies, anxiety and depression were the most commonly measured outcome. The prominent risk factors for anxiety and depression emerging from this study comprised time spent, activity, and addiction to social media. In today's world, anxiety is one of the basic mental health problems. People liked and commented on their uploaded photos and videos. In today's age, everyone is immune to the social media context. Some teens experience anxiety from social media related to fear of loss, which causes teens to try to respond and check all their friends' messages and messages on a regular basis.

On the contrary, depression is one of the unintended significances of unnecessary use of social media. In detail, depression is limited not only to Facebooks but also to other social networking sites, which causes psychological problems. A new study found that individuals who are involved in social media, games, texts, mobile phones, etc. are more likely to experience depression.

The previous study found a 70% increase in self-reported depressive symptoms among the group using social media. The other social media influence that causes depression is sexual fun [ 12 ]. The intimacy fun happens when social media promotes putting on a facade that highlights the fun and excitement but does not tell us much about where we are struggling in our daily lives at a deeper level [ 28 ]. Another study revealed that depression and time spent on Facebook by adolescents are positively correlated [ 22 ]. More importantly, symptoms of major depression have been found among the individuals who spent most of their time in online activities and performing image management on social networking sites [ 14 ].

Another study assessed gender differences in associations between social media use and mental health. Females were found to be more addicted to social media as compared with males [ 26 ]. Passive activity in social media use such as reading posts is more strongly associated with depression than doing active use like making posts [ 23 ]. Other important findings of this review suggest that other factors such as interpersonal trust and family functioning may have a greater influence on the symptoms of depression than the frequency of social media use [ 28 , 29 ].

Limitation and suggestion

The limitations and suggestions were identified by the evidence involved in the study and review process. Previously, 7 of the 16 studies were cross-sectional and slightly failed to determine the causal relationship between the variables of interest. Given the evidence from cross-sectional studies, it is not possible to conclude that the use of social networks causes mental health problems. Only three longitudinal studies examined the causal relationship between social media and mental health, which is hard to examine if the mental health problem appeared more pronounced in those who use social media more compared with those who use it less or do not use at all [ 19 , 20 , 24 ]. Next, despite the fact that the proposed relationship between social media and mental health is complex, a few studies investigated mediating factors that may contribute or exacerbate this relationship. Further investigations are required to clarify the underlying factors that help examine why social media has a negative impact on some peoples’ mental health, whereas it has no or positive effect on others’ mental health.

Conclusions

Social media is a new study that is rapidly growing and gaining popularity. Thus, there are many unexplored and unexpected constructive answers associated with it. Lately, studies have found that using social media platforms can have a detrimental effect on the psychological health of its users. However, the extent to which the use of social media impacts the public is yet to be determined. This systematic review has found that social media envy can affect the level of anxiety and depression in individuals. In addition, other potential causes of anxiety and depression have been identified, which require further exploration.

The importance of such findings is to facilitate further research on social media and mental health. In addition, the information obtained from this study can be helpful not only to medical professionals but also to social science research. The findings of this study suggest that potential causal factors from social media can be considered when cooperating with patients who have been diagnosed with anxiety or depression. Also, if the results from this study were used to explore more relationships with another construct, this could potentially enhance the findings to reduce anxiety and depression rates and prevent suicide rates from occurring.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

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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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Ine Beyens, J. Loes Pouwels, Irene I. van Driel & Patti M. Valkenburg

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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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The effect of social media influencers' on teenagers Behavior: an empirical study using cognitive map technique

• Published: 31 January 2023
• Volume 42 , pages 19364–19377, ( 2023 )

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• Karima Lajnef   ORCID: orcid.org/0000-0003-1084-6248 1  

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The increase in the use of social media in recent years has enabled users to obtain vast amounts of information from different sources. Unprecedented technological developments are currently enabling social media influencers to build powerful interactivity with their followers. These interactions have, in one way or another, influenced young people's behaviors, attitudes, and choices. Thus, this study contributes to the psychological literature by proposing a new approach for constructing collective cognitive maps to explain the effect of social media influencers' distinctive features on teenagers' behavior. More in depth, this work is an attempt to use cognitive methods to identify adolescents' mental models in the Tunisian context. The findings reveal that the influencers' distinctive features are interconnected. As a result, the influencer's distinctive features are confirmed in one way or another, to the teenagers' behavior. These findings provide important insights and recommendations for different users, including psychologists and academics.

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Introduction

The number of social media users has increased rapidly in the last few years. According to the global ‘State of Digital’ report (2021), the number of social media users reached 4.20 billion, which represents 53% of the world’s total population. This number has risen by more than 13% compared to the last year (2020). In Tunisia, until January 2021 the number of social media users has increased to 8.20 million, which represents 69 percent of the total population, while 97%, are accessed via mobile phones. According to the ALEXA report ( 2021 ), Google.com, Facebook are the most used networks by Tunisian people. Most importantly, 18, 5% of Facebook users are under 13 years old.

In fact, the emphasis on social media has created a consensus among tech companies, leading to the creation of more platforms. Today, the diversity of such platforms has created a new horizon of social media in terms of usage and ideas.

Many people whose careers’ are largely reliant on social media are known as "influencers". More than a profession, for some people, it is even considered as a way of life. Influencers use social media every day to express their opinions and critiques on many topics (like lifestyle, health, beauty) and objects (e.g. brands, services, and products). Accordingly, one of the most important marketing strategies in the market is relying on influencers, which has known as influencer marketing (Audrezet et al., 2020 ; Boerman, 2020 ; Lou & Yuan, 2019 ). In 2017, influencer marketing was considered as the most widespread and trendiest’ communication strategy used by the companies. Therefore, influencers have been considered by many marketing experts as opinion leaders because of their important role in persuading and influencing their followers (De Veirman et al., 2017 ). According to the two-step flow of communication theory, the influencer, as a representative of an organization, is inviting to filter, decode and create messages to match with his particular follower base (Lazarsfeld et al., 1944 ). An influencer is a mediator between consumers and organizations. According to Tarsakoo and Charoensukmongkol ( 2019 ), social media marketing implementation capabilities have a positive effect on customer relationship sustainability. In line with the premise of observational learning theory, influence occurs when the consumers use precedent information and observations shared with them gradually to extend their decision-making by evolving their beliefs, attitudes, and behaviors, (Bandura & Adams, 1977 ). In fact, the consumers are sizeable social networks of followers. In their turn, consumers, especially youth and adolescents, consider influencers as a source of transparency, credibility, and source of personal information from what helps the offered brands to be enlarged through the large social media network (e.g. Jin and Phua, 2014).

Social media influencers play a greater role in controlling and influencing the behavior of the consumer especially young people and teenagers (e.g. Marwick, 2015 ; Sokolova & Kefi, 2020 ). Actually, the use of Smartphone's has become an integral part of the lives of both young people and adolescents. According to Anderson ( 2018 ), 95% of teenagers aged between 13 and 17 own a Smartphone. For young people, the pre-social media era has become something of a blur. This generation has known as Generation Z where its members were born between the nineties and the 2000s. What distinguishes this generation is its extensive use of the Internet at an early age. For them, the social media presents an important part of their social life and since then many thinkers set out to explore the effects of using social media platforms at an early age on adolescents' lives. The excessive use of social media may have an effect on teens' mental health. In fact, adolescence is the interval period between childhood and adulthood. A teenager is not a child to act arbitrarily and is not an adult to make critical decisions. Therefore, young people and teenagers have considered as the most sensitive class of consumers. Teenagers' brain creates many changes that make them more sensitive to the impressions of others, especially the view of their peers (e.g. Elkind, 1967 ; Dacey & Kenny, 1994 ; Arnett, 2000 ). Adolescents' mental changes cause many psychological and cognitive problems. According to Social identity theory, teens appreciate the positive reinforcement they get by being included in a group and dislike the feeling of social rejection (Tajfel, 1972 ). To reinforce their sense of belonging, teens are following influencers on social media (e.g., Loureiro & Sarmento, 2019 ). In line with psychological theories, the attachment theory helps to clarify interpersonal relationships between humans. This theory provides the framework to explain the relationship between adolescents and influencers. Several studies have confirmed that the distinctive feature of social media influencers, including relatedness, autonomy and competence affects the behavior, the psychological situation and the emotional side of the consumers (Deci & Ryan, 2000 ). Does the distinctive feature of social media influencers affect teens' behavior? This kind of questions have become among the most controversial ones (e.g. Djafarova & Rushworth, 2017 ). This problem is still inconclusive, even not addressed in some developing countries like Tunisia. Indeed, it is clear that there are considerable gaps in terms of the academic understanding of what characteristics of social media influencers and their effect on teen behaviors. This problem still arises because the lack of empirical works is investigating in this area.

Therefore, this study contributes to the literature by different ways. First, this paper presents a review of the social media influencers' distinctive features in Tunisian context. This is important because social influencers have been considered as credible and trustworthy sources of information (e.g. Sokolova & Kefi, 2020 ). On the others hand, this study identifies the motivations that teens have for following social influencers. MICS6 Survey (2020) shows a gradual increase in suicide rates among Tunisian children (0–19 years). According to the general delegate for child protection, the phenomenon is in part linked to the intensive use of online games. Understanding the main drivers of social media influence among young Tunisians can help professionals and families guide them. Empirically, this study provides the first investigation of teens’ mental models using the cognitive approach.

The rest of this paper is organized as the following: The second part presents thetheoretical background and research hypotheses. The third part introduces the research methodology. The forth part is reserved to application and results. In the last part, both the conclusion and recommendations are highlighted.

Theoretical background and research hypotheses

Social media influencers' distinctive features.

"Informational social influence" is a concept that has been used in literature by Deutsch & Gerard, 1955 ), and defined as the change in behavior or opinions that happened when people (consumers) are conformed to other people (influencers) because they believe that they have precise and true information (e.g. Djafarova & Rushworth, 2017 , Alotaibi et al., 2019 ). According to (Chahal, 2016 ), there are two kinds of "influencers". The classic ones are the scientists, reporters, lawyers, and all others examples of people who have expert-level knowledge and the new ones are the Social media influencers. Accordingly, social media influencers have many followers that trust them especially on the topics related to their domain of knowledge (e.g. Moore et al., 2018 ). According to the Psychology of Influence perspective, people, often, do not realize that they are influenced because the effect occurs mainly in their subconscious (Pligt & Vliek, 2016 ). When influencers advocate an idea, a service, or a product, they can make a psychological conformity effect on followers through their distinctive features (Colliander, 2019 ; Jahoda, 1959 ).

Vollenbroek et al. ( 2014 ) investigated a study about social media influencers and the impact of these actors on the corporate reputation. To create their model, the authors use the Delphi method. The experts have exposed to a questionnaire that included the characteristics of influential actors, interactions, and networks. The first round of research indicates that a bulk of experts has highlighted the importance of intrinsic characteristics of influencers such as knowledge, commitment, and trust etcetera. While others believe that, the size of the network or the reach of a message determines the influence. The results of the second round indicate that the most agreed-upon distinctive characteristics to be a great influencer are being an active mind, being credible, having expertise, being authoritative, being a trendsetter, and having a substantive influence in discussions and conversations. According to previous literature, among the characteristics that distinguish the influencers is the ability to be creative, original, and unique. Recently, Casaló et al. ( 2020 ) indicated that originality and uniqueness positively influence opinion leadership on Instagram. For the rest of this section, we are going to base on the last two studies to draw on the most important distinctive features of social media influencers.

Credibility (expertise and trustworthiness)

According to Lou and Yuan ( 2019 ), one of the most distinctive characteristics that attract the audience is the influencer's credibility specifically the expertise and trustworthiness. In fact, source credibility is a good way of persuasion because it has related to many conceptualizations. Following Hovland et al. ( 1953 ), credibility has subdivided into expertise and trustworthiness. The expertise has reflected the knowledge and competence of the source (influencer) in a specific area (Ki & Kim, 2019 ; McCroskey, 1966 ). While trustworthiness is represented in influencer honesty and sincerity (Giffin, 1967 ). Such characteristics help the source (influencer) to be more convincing. According to the source credibility theory, consumers (social media audience) give more importance to the source of information to take advantage of the expertise and knowledge of influencers (e.g. Ohanian, 1990 ; Teng et al., 2014 ). Spry et al., ( 2011 ) pointed out that a trusted influencer's positive perception of a product and/or service positively affects consumers' attitudes towards recommended brandsHowever, if the product does not meet the required specifications, consumers lose trust in the product and the influencer (Cheung et al., 2009 ). Based on source credibility theory, this work tested one of the research goals: the effect of expertise and credibility on adolescent behavior.

Originality and creativity

Originality in social media represents the ability of an influencer to provide periodically new and differentiate content that attracts the attention of the audience. The content has perceived as innovative, sophisticated, and unusual. Social media influencers look for creating an authentic image in order to construct their own online identity. Marwick ( 2013 ) defined authenticity as "the way in which individuals distinguish themselves, not only from each other but from other types of media". Most of the time, an authentic and different content attracts attention, and sometimes the unusual topics make surprising (Derbaix & Vanhamme, 2003 ). According to Khamis et al. ( 2017 ), social media influencers attract the consumers' attention by posting authentic content. In fact, the audience often appreciates the originality and the creativity of the ideas (Djafarova & Rushworth, 2017 ).The originality of the content posted by an influencer has considered as a way to resonate with their public (Hashoff, 2017 ). When a company seeks to promote its products and services through social media, it is looking for an influential representative who excels at presenting original and different content. The brand needs to be presented by credible and believable influencers that create authentic content (Sireni, 2020 ). One of the aims of this work is to identify the effect of the authentic content on teen’s behaviors.

Trendsetter and uniqueness

According to Maslach et al. ( 1985 ), uniqueness is the case in which the individual feels distinguished compared to others. Tian et al. ( 2001 ) admitted that individuals attempt to be radically different from others to enhance their selves and social images. The uniqueness in content represents the ability of the influencer to provide an uncirculated content specific to him. Gentina et al. ( 2014 ) proved that male adolescents take into account the uniqueness of the content when they evaluated the influencer role particularly in evaluating the role of an opinion leader. Casaló et al. ( 2020 ) indicated that uniqueness positively influences the leadership opinion. Thus, the uniqueness of influencers’ contents may affect audiences’ attitude. Therefore, we aim to test the effect of the influencers’ contents uniqueness and trendsetter on teenagers’ behaviors.

Persuasion has a substantive influence in discussions and conversations. According to the Psychology of Persuasion, the psychological tactic that revolves around harnessing the principles of persuasion supports in one way or another the influencer’s marketing. The objective is to persuade people to make purchase decisions. Persuasion aims commonly to change others attitudes and behavior in a context of relative freedom (e.g. Perloff, 2008 ; Crano & Prislin, 2011 ; Shen & Bigsb, 2013 ). According to Scheer and Stern ( 1992 ), the dynamic effect of marketing occurs when an influencer persuades consumers to participate in a specific business. Influencers' goal is to convince the audiences of their own ideas, products, or services. There are six principles of persuasion, which are consensus, consistency, scarcity, reciprocity, authority, and liking. Thus, among the objectives of this study is to set the effect of influencers' persuasion on teens' behavior.

To sum up, our hypothesis is as the following:

H1: Social media influencers' distinctive features affect teenagers’ behavior.

Social media influencers' and teenagers’ behavior

Young people and adolescents are increasingly using social media, consequently, they receive a lot of information from different sources that may influence in one way or another their behavior and decisions. Accordingly, the Digital report (2021) (published in partnership with Hootsuite and we Are Social) indicated that connected technologies became an integral part of people's lives, and it has seen great development in the last twelve months especially with regard to social media, e-commerce, video games, and streaming content. According to the statistics raised in the global State of Digital (2021), the number of social media users has increased by 490 million users around the world compared to last year to attain 4.20 billion. In Tunisia, until January 2021 the number of social media users has increased to attain 8.20 million, which represents 69 percent of the total population while 97% accessing via mobile phone. According to the ALEXA report ( 2021 ), Google.com, Facebook and YouTube are the networks most used by Tunisian people. In addition, 18, 5% of Facebook users are under 13 years old.The use of social media by young people has recently increased, which led us to ask about the influence of such an alternative on their psychological and mental conditions, their identity formation, and their self-estimation. One of this study aims is also to answer the question: why teens follow Social media influencers?

Identity formation

Identity formation relates to the complex way in which human beings institute a continued unique view of the self (Erikson, 1950 ). Consequently, this concept has largely attached to terms like self-concept, personality development, and value. Identity, in a simplified way, is an aggregation of the “self-concept, who we are” and “self-awareness” (Aronson et al., 2005 ). In line with communication theory, Scott ( 1987 ) indicated that interpersonal connection is a key factor in identity formation. Most importantly, the individual's identity formation is the cornerstone of building a personality. A stream of research indicates that consumers accept influence from others they identify with and refuse influence when they desire to disconnect (Berger & Heath, 2007 ; White & Dahl, 2006 ).

Adolescence is a transitional stage in individuals' lives that represents the interval between childhood and adulthood (e.g. Hogan & Astone, 1986 ; Sawyer et al., 2018 ). From here begins teens' psychological conflicts that call into question-related to themselves and about their role in society (e.g. Hill et al., 2018 ). In fact, teens go through many experiences because of the physical and psychological changes during the self-establishment phase, which influences not only their identity formation but also their own personality. At this stage, radical changes occur in their lives, which may affect the course of their future life. The family (precisely parents' behaviors) represents the first influencer on their kids' view of themselves, but this is not the main side. In the era of globalization and technological development, social media has become an important role in shaping the identity of adolescents (see Gajaria et al., 2011 ). In the adolescent stage, individuals start to use the flood of information received from various sources (especially from social media) to find out a sense of self and personal identity. Davis ( 2013 ) affirmed that students who communicated online with their peers express better visibility of self-concept. In its turn, self-concept visibility has related to friendship quality. According to Arnett and Hughes ( 2014 ), identity formation is the result of "thinking about the type of person you want to be” (p. 340). Due to the intense appearance of social media in the lives of teenagers, identity formation is highly affected by social media influencers' personalities. Kunkel et al. ( 2004 ) affirmed that targeted advertisements in social media affect the identity molding of teens by encouraging them to espouse new habits of appearance and consumption. Identification is easier when there is a previous model to mimic.

This work aims to explore the effect of social media influencers' distinctive features on the healthy identity development of teens.

Mimetic bias

Investigating mimicry in the psychological literature is not a recent subject. Kendon ( 1970 ) and LaFrance ( 1982 ) were the first researchers that introduce the mimicry concept in literature. Nevertheless, exploring mimicry effect on peoples’ behavior presents a new area of research. Many researchers like Chartrand and Dalton ( 2009 ) and Stel & Vonk ( 2010 ) presented mimicry as the interaction of an individual with others through observing and mirroring their behaviors, attitudes, expressions, and postures. Chartrand and Dalton ( 2009 ) indicated that social surroundings are easily contagious and confirmed the high ability of individuals to mimic what they see in their social environment. Individuals resort to mimicry to fulfill their desire to belong to a group and be active members of society. Therefore, Lakin et al. ( 2003 ) affirmed that mimicry could be used to enhance social links with others. Such behavior aims to bring people closer to each other and create intimacy. White and Argo ( 2011 ) classified mimicry as conscious and unconscious. According to the Neuroscience literature, unconscious mimicry occurs due to the activation of individual mirror neurons that lead to mimic others (e.g. Hatfield et al., 1994 ). Thus, mimickers “automatically” imitate others in many situations like facial expressions (e.g., smiling), behavioral expressions (e.g., laughing), and postural expressions (e.g., hand positioning) (Meltzoff & Moore, 1983 ; LaFrance & Broadbent, 1976 ; Simner, 1971 ). On the other hand, a recent stream of research has advocated conscious mimicry (White & Argo, 2011 ; Ruvio et al., 2013 ). Ruvio et al. ( 2013 ) have presented the "Consumer’s Doppelganger Effect" theory. According to the authors, when consumers have the intention to look like their role models, they imitate them.

One of the paradoxical challenges in the adolescence period is the teens' simultaneous need for "mimic" and "differentiation ".Among the most common questions asked between adolescents is "Who we are?”. The identification of themselves based commonly on a comparison between them and members of the group to which they aim to belong. The feeling of being normal is an obsession that haunts the majority of teenagers. Their sense of being within the norm and not being alienated or disagreed with others prompts teenagers to do anything even if this poses a danger to them just to be accepted by others. Today, with the development of social media, family, peers and friends are no longer the only influencers that teens mimic, but this environment has expanded to include social media influencers. Teens give more attention to their online image and mimic social media influencers to achieve a sense of belonging. According to Cabourg and Manenti ( 2017 ), the content shared by adolescents with each other about their lives on their own social networks helps them understand and discover each other, and create their identity away from their parents. This phenomenon turns into a problem when adolescents mimic each other only not to be excluded or rejected, even if these actions do not represent them.

Another important aim of this study is to explore the effect of social media influencers' distinctive features on teen’s mimicry behavior.

Confirmation bias

Cabourg and Manenti ( 2017 ) pointed out that it is a necessity for a teenager to be a part of a peer group. Belonging to the group for a teenager reinforces his/her sense of existence away from family restrictions. As we have mentioned before and in line with Hernandez et al. ( 2014 ), teens need to create peer relationships, whether to contribute positively or negatively to their psychosocial side and undoubtedly play a crucial role in the development of identity. Araman and Brambilla ( 2016 ) argued that: "Teenage is an important stage in life, full of physical and psychological transformation, awakening in love and professional concerns. Identifying yourself with a group makes you feel stronger, to say that you exist, and even to distinguish yourself from society”. The development of social media platforms promotes the desire of teens to a group belonging. Social media platforms, such as tick-tock, Facebook, and Instagram, motivate their users to interact with likes and comments on others people’s posts. In fact, according to Davis ( 2012 ), casual communication between teens through social networking using text and instant messages enhances their sense of belonging. Furthermore, the author indicates that social media helps teens to compare their ideas and experiences with their peers, which support their sense of belonging. According to Zeng et al. ( 2017 ), social media interactions aim to create strong social bonds and raise emotional belonging to a community. Confirmation bias occurs when an individual cannot think and create outside the herd. Equally important, due to the confirmation bias, teens cannot identify themselves, except by flying inside the swarm. Teens may identify themselves as fans of a famous influencer just to feel the sense of belonging. This work tests the effect of social media influencers' distinctive features on teens’ sense of belonging.

Self-esteem

Psychological literature defines Self-esteem as the individual’s evaluation of himself or herself that can be positive or negative (Smith et al., 2014 ). Coopersmith ( 1965 ) affirmed that the self-esteem is the extent to which an individual views his self as competent and worthwhile. A stream of past works highlighted the effects of social media on self-esteem (Błachnio et al., 2016 ; Denti et al., 2012 ; Gonzales & Hancock, 2011 ). The majority of them found that audiences with low self-esteem use more social networks’ to reinforce their self-esteem. Due to technological developments, social media networks offer a self-comparison between users. According to Festinger ( 1954 ), social media users focus more on self-evaluations by making social comparisons with others concerning many issues like beauty, popularity, social classes or roles, wealth accumulation, etc. Social comparison is a part of building a teen's personal identity (Weinstein, 2017 ). Among adolescents, there are two types of comparisons on social media, which are upward comparison, and downward comparison (Steers et al., 2014 ). The first one has related to weakened levels of self-esteem and high depressive symptoms. The second one is characterized by expanding levels of self-esteem and low levels of anxiety (Burrow & Rainone, 2017 ). According to Wright et al. ( 2018 ), self-presentation on social media is related to the extent to which others accept and the determined level of belonging that based on the number of likes and comments.

This study aims to test the effect of social media influencers' distinctive features on teens’ self-esteem.

Digital distraction

Social media has taken over most of the spare time. It has displaced the time spent on other activities like reading, watching TV, make sports etc.… (Twenge et al., 2019 ). Consequently, the phenomenon of digital distraction has widely spread, especially with the rise of smartphones use. The results of a study established by Luna ( 2018 ) indicated that the use of smartphones during a meal leads to minimize the levels of connectedness and enjoyment and increase the levels of distraction comparing to those who set devices off. Martiz ( 2015 ) found that students with Internet addiction often feel lonely and depressed. Recently, Emerick et al. ( 2019 ) affirmed that the students themselves agree that spending a lot of time using social media leads to distraction. Many studies have proven that most teens spend a lot of time online (e.g., Anderson & Jiang, 2018 ; Twenge et al., 2018 ). Thus, they are the most vulnerable to digital distraction. We believe that whenever distinctive features of influencers are good, the most important impact they have on young people, leads to distraction.

At this level, our second hypothesis is as the following:

H2. The behavior and cognitive biases of teens are affected by social media influence.

Research methods

The cognitive maps.

The cognitive map is relatively an old technique (Huff, 1990 ). However, the use of cognitive maps in scientific research has increased in recent years. According to Axelrod ( 1976 ), a cognitive map is a mathematical model that reflects a belief system of a person. In another words, a cognitive map is a representation of causal assertion way of a person on a limited area. At the beginning of the 1970s, it was intellectually popular amongst behavioral geographers to investigate the significance of cognitive maps, and their impacts on people’s spatial behavior. A cognitive map is a type of mental representation, which serves an individual to acquire, store, recall, code, and decode information about the relative locations and attributes of phenomena in their everyday or metaphorical spatial environment. It is usually defined as the graphical representation of a person belief about a particular field. A map is not a scientific model based on objective reality, but a graphical representation of an individual's specific beliefs and ideas about complex local situations and issues. It is relatively easy for humans to look at maps (cognitive maps in our case) and understand connections, between different concepts. Cognitive maps can therefore also be thought of as graphs. Graphs can be used to represent many interesting things about our world. It can also be used to solve various problems. According to Bueno & Salmeron ( 2009 ), Cognitive Maps are a powerful technique that helps to study human cognitive phenomena and specific topics in the world. This study uses cognitive maps as a tool to investigate the mental schema of teenagers in Tunisian Scouts. In fact, cognitive mapping helps to explore the impact of social media on teenage behavior in the Tunisian context. In other words, we focus on the effect of influencers' distinctive features on teen behavior.

Data collection and sample selection

The aim of this work is to explore the effect of social media influencers' distinctive features on teenagers' behavior in Tunisian context. On the other hand, this work investigates if the psychological health of teens is affected by social media influence. To analyze mentally processing multifactor-interdependencies by the human mind or a scenario with highly complex problems, we need more complex analysis methods like the cognitive map technique.

The questionnaire is one of the appropriate methods used to construct a collective cognitive map (Özesmi & Özesmi, 2004 ). Following Eden and Ackermann ( 1998 ), this study uses face-to-face interviews because it is the most flexible method for data collection and it is the appropriate way to minimize the questionnaire mistiness. The questionnaire contains two parts: the first part is reserved to identify the interviewees. The second part provides the list of concepts for each approach via cross-matrix. The questionnaire takes the form of an adjacency matrix (see Table 1 ). The data collection technique appropriate to build a cognitive map is the adjacent matrix. The adjacency matrix of a graph is an (n × n) matrix:

The variables used in the matrix can be pre-defined (by the interviewer using the previous literature) or it can be identified in the interview by the interviewees. This paper uses the first method to restrict the large number of variables related to both influencers’ distinctive features and teenagers' behavioral biases (see Table 2 ). This work identified two types of social media influencers that are Facebook bloggers and Instagrammers for two reasons. Facebook is the most coveted social network for Tunisians. It has more than 6.9 million active users in 2020 or 75% of the population (+ 13 years) of which 44.9% were female users and 55.1% male. On the other hand, Instagram is the second popular social media platform. It has more than 1.9 million, namely 21% of the Tunisian population (+ 13 years).

In this work, we deal with (10 × 10) adjacency matrix.

Experts (psychologists, academics, etc.) often analyze the relationships between social media and young people’s behavior. The contribution of this work is that we rely on the adolescents' point of view in order to test this problem using the cognitive maps method. To our knowledge, no similar research has been done before.

This work is in parallel to the framework of the Tunisian State project "Strengthening the partnership between the university and the economic and social environment". It aims to merge the scientific track with the association work. We have organized an intellectual symposium in conjunction with the Citizen Journalism Club of youth home and the Mohamed-Jlaiel Scouts Group of Mahres entitled "Social Influencers and Their Role in Changing Youth Behaviors”.This conference took place on April 3, 2021, in the hall of the municipality, under the supervision of an inspector of youth and childhood”. In fact, Scouts is a voluntary educational movement that aims to contribute to the development of young people to reach the full benefit of their physical and social capabilities to make them responsible individuals. Scouts offer children and adolescents an educational space complementary to that of the family and the school. The association emphasizes community life, taking responsibility, and learning resourcefulness.Scouting contributes to enhancing the individual's self-confidence and sense of belonging and keeps them away from digital distraction. Therefore, our sample has based on a questionnaire answered by young people belonging to the Tunisian Scoutsaged between 14 and 17 and, who belong to the Mohamed-Jlaiel Scouts Group of Mahres. In fact, scouting strengthens the willpower of young people and allows them to expand their possibilities for self-discipline. In addition, Scout youth are integrated into the community and spend more time in physical and mental activities than their peers who spend most of their free time on social media. Unfortunately, because of the epidemiological situation that Tunisia experienced during this period due to the spread of the Coronavirus, we could not summon more than 35 people, and the first sample was limited only to 25 young people. Thus, a second study with another data collection is needed. Over two successive months (November and December 2021), we make a few small workshops (due to the pandemic situation) with scouts’ young people. The second sample contains 38 teens. Therefore, our total data hold 63young people (26 female and 37 male). It should be noted that the surveys were carried out after parental consent.

We start our interviews with presenting the pros and cons of social mediaand its effect on audiences’ behavior. After forming an idea with the topic, we asked young people to answer the questionnaire presented to them after we defined and explained all the variables. We have directly supervised the questionnaire. Teens are invited to fulfill the questionnaire (in the form of a matrix) using four possibilities:

If variable i has no influence on variable j, the index (i, j) takes a value of zero

1 if variable I has a weak influence on variable j.

2 if variable I has a strong influence on variable j.

3 if variable I has a very strong influence on variable j.

To sumup, the final data contains 63 individual matrices. The aim of the questionnaire is then to build the perception maps (Lajnef et al., 2017 ).

Collective cognitive map method

This work is of qualitative investigation. The research instrument used in this study is the cognitive approach. This work aims to create a collective cognitive map using an interviewing process. Young peopleare invited to fill the adjacencymatrices by giving their opinion about the effect of social media influencers' distinctive features on teenagers' behavior. To draw up an overall view, individual maps (creating based on adjacency matrices) aggregated to create a collective cognitive map. Since individual maps denote individual thinking, collective map is used to understand the group thinking. The aggregation map aimed to show the point of similarities and differences between individuals (Lajnef et al., 2017 ). The cognitive map has formed essentially by two elements: concepts (variables) and links (relations between variables). The importance of a concept is mainly related to its link with other variables.

This technique helps to better understand the individual and collective cognitive universe. A cognitive map became a mathematical model that reflects a belief system of individuals since the pioneering work of Tolman ( 1948 ). Axelrod ( 1976 ) investigated the political and economic field and considered "cognitive maps" as graphs, reflecting a mental model to predict, understand and improve people's decisions. Recently, Garoui & Jarboui ( 2012 ) have defined the cognitive map as a tool aimed to view certain ideas and beliefs of an individual in a complex area. This work aims to explore a collective cognitive map to set the complex relationships between teenagers and social media influencers. For this reason, we investigate the effect of social media influencers' distinctive features on teenagers' behavior using an aggregated cognitive map.

Results and discussion

In this study, we report all measures, manipulations and exclusions.

Structural analysis and collective cognitive map

This paper uses the structural analysis method to test the relationship between the concepts and to construct a collective cognitive map. According to Godet et al. ( 2008 ), the structural analysis is “A systematic, matrix form, analysis of relations between the constituent variables of the studied system and those of its explanatory environment”. The structural analysis purpose is aimed to distinguish the key factors that identify the evolution of the system based on a matrix that determines the relationships among them (Villacorta et al., 2012 ). To deal with our problem, Micmac software allows us to treat the collected information in the form of plans and graphs in order to configure the mental representation of interviewees.

The influence × dependence chart

This work uses the factor analysis of the influence-dependence chart in which factors have categorized due to their clustered position. The influence × dependence plan depends on four categories of factors, which are the determinants variables, the result variables the relay variables, and the excluded variables. The chart has formed by four zones presented as the following (Fig.  1 ):

Influence-dependence chart, according to MICMAC method

Zone 1: Influent or determinant variables

Influent variables are located in the top left of the chart. According to Arcade et al. ( 1999 ) this category of variables represents a high influence and low dependence. These kinds of variables play and affect the dynamics of the whole system, depending on how much we can control them as key factors. The obtained results identify uniqueness, trustworthiness, and Mimetic as determinant variables. The ability of influencers’ is to provide personalized and unique content that influence Tunisian teens’ behavior. This finding is in line with Casaló et al. ( 2020 ) work. On the other hand, the results indicate that teens mimic social media influencers to feel their belonging. Such an act allows them to discover each other, and create their identity away from their parents (Cabourg & Manenti, 2017 ). The most Influential variable of the system is trustworthiness.The more trustworthiness influencers via social media are, the higher their influence on young people will be. This finding is conformed to previous studies (Giffin, 1967 ; Spry et al., 2011 ).

Zone 2: Relay variables

The intermediate or relay variables are situated at the top right of the chart. These concepts have characterized by high influence and sensitivity. They are also named “stake factors” because they are unstable. Relay variables influence the system depending on the other variables. Any effect of these factors will influence themselves and other external factors to adjust the system. In this study, most of influencers' distinctive features (persuasion, originality, and expertise) play the role of relay variables. The results indicate that the influence of persuasion affects young people's convictions, depending on other variables. The results are in line with previous studies (e.g. Perloff, 2008 ; Shen et al., 2013 ). Furthermore, the findings indicate that the more expertise social media influencers' are, the higher their influence on young people will be. The study of Ki and Kim ( 2019 ) supported our findings. Additionally, the originality of the content presented on social media attracts the audience more than the standard content. The results are in line with those of Khamis et al., ( 2017 ) and Djafarova & Rushworth ( 2017 ).

Based on the results of zone 1 and zone 2, we can sum up that Social media influencers' distinctive features tested on this work affect teenagers’ behavior. Therefore, H1 is accepted.

Zone 3: Excluded or autonomous variables

The excluded variables are positioned in the bottom left of the chart. This category of variables is characterized by a low level of influence and dependence. Such variables have no impact on the overall dynamic changes of the system because their distribution is very close to the origin. This work did not obtain this class of variables.

Zone 4: Dependent variables

The dependent variables are located at the bottom right of the chart. These variables have characterized by a low degree of influence and a high degree of dependence. These variables are less influential and highly sensitive to the rest of variables (influential and relay variables). According to our results, the dependent variables are those related to teens' behavior and cognitive biases. Social media influencers affect the identity development of teens. These findings are in line with those of Kunkel et al. ( 2004 ).The results show also that young people often identify themselves as fans of a famous influencer just to feel the belonging. These results are in line with previous studies like those of Davis ( 2012 ) and Zeng et al. ( 2017 ). Furthermore, the findings indicate that young people use more social networks’ to reinforce their self-esteem.The results confirm with those of Denti et al. ( 2012 ) and Błachnio et al. ( 2016 ).Influencers via social media play a role in digital distraction. Thus, the result found by Emerick et al. ( 2019 ) supports our findings.

Based on the results of zone 3, we can sum up that the behavior and cognitive biases of teens are affected by social media influencers. Therefore, H2 is accepted.

Collective cognitive maps

During this study, we have gathered the individuals’ matrices to create a collective cognitive mind map. The direct influence graph (Figs.  2 and 3 ) present many interesting findings. First, the high experience of influencers via social media enhances the production of original content. Furthermore, the more expertise the influencers' are, the higher their degree of persuasion on young people will be. As similar to this work, Kirmani et al. ( 2004 ) found that the influencers' experience with persuasion emerges as factors that affect customers. Beside the experience, the more an influencer provides unique and uncirculated content specific to him, the higher the originality of the content will be. Previous studies hypothesized that unique ideas are the most stringent method for producing original ideas (e.g., Wallach & Kogan,  1965 ; Wallach & Wing, 1969 ).Generally; influencers that produce different contents have a great popularity because they produce new trends. Therefore, our results indicate that young people want to be one of their fans just to feel their belonging. Furthermore, our findings indicate that the originality of content can be a source of digital distraction. Teenagers spend a lot of time on social media to keep up with new trends (e.g. Chassiakos & Stager, 2020 ).

The collective cognitive maps (25% of links)

The collective cognitive map (100% of links)

The influencers' experience and their degree of trustworthiness, besides the originality of the content, enhance their abilities to persuade adolescents. During adolescence, young people look for a model to follow. According to our results, it can be a social media influencer with a great ability to persuade.

In recent years, the increasing use of social media has enabled users to obtain a large amount of information from different sources. This evolution has affected in one way or another audience's behavior, attitudes, and decisions, especially the young people. Therefore, this study contributes to the literature in many ways. On the first hand, this paper presents the most distinctive features of social media influencers' and tests their effect on teenagers' behavior using a non-clinical sample of young Tunisians. On the other hand, this paper identifies teens' motivations for following social media influencers. This study exercises a new methodology. In fact, it uses the cognitive approach based on structural analysis. According to Benjumea-Arias et al. ( 2016 ), the aim of structural analysis is to determine the key factors of a system by identifying their dependency or influence, thus playing a role in decreasing system complexity. The present study successfully provides a collective cognitive map for a sample of Tunisian young people. This map helps to understand the impact of Facebook bloggers and Instagrammers on Tunisian teen behavior.

This study presents many important findings. First, the results find that influencers' distinctive features tested on this work affect teenagers’ behavior. In fact, influencers with a high level of honesty and sincerity prove trustworthiness among teens. This result is in line with those of Giffin ( 1967 ). Furthermore, the influencer’s ability to provide original and unique content affects the behavior of teens. These findings confirm those of Casaló et al. ( 2020 ). In addition, the ability to influence is related with the ability to persuade and expertise.

The findings related to the direct influence graph reveal that the influencers' distinctive features are interconnected. The experience, the degree of trustworthiness, and the originality of the submitted content influence the ability of an influencer to persuade among adolescents. In return, the high degree of persuasion impresses the behavior, attitudes, and decisions of teens with influences in their identity formation. The high experience and uniqueness help the influencer to make content that is more original. Young people spend more time watching original content (e.g. Chassiakos & Stager, 2020 ). Thus, the originality of content can be a source of digital distraction.

The rise in psychological problems among adolescents in Tunisia carries troubling risks. According to MICS6 Survey (2020), 18.7% of children aged 15–17 years suffer from anxiety, and 5.2% are depressed. The incidence of suicide among children (0–19 years old) was 2.07 cases per 100,000 in 2016, against 1.4 per 100,000 in 2015. Most child suicides concern 15–19-year-olds. They are in part linked to intensive use of online games, according to the general delegate of child protection. However, scientific studies rarely test the link between social media use and psychological disorders for young people in the Tunisian context. In fact, our result emphasized the important role of influencers' distinctive features and their effect on teens' behavior.

Thus, it is necessary and critical to go deeper into those factors that influence the psychological health of teens. We promote researchers to explore further this topic. They can uncover ways to help teens avoid various psychological and cognitive problems, or at least realize them and know the danger they can cause to themselves and others.

These results have many implications for different actors like researchers and experts who were interested in the psychological field.

This work suffers from some methodological and contextual limitations that call recommendations for future research. Fist, the sample size used is relatively small because of the epidemiological situation that Tunisia experienced at the time of completing this work. On the other hand, this work was limited only to study the direct relationship between variables. Therefore, we suggest expanding the questionnaire circle. We can develop this research by interviewing specialists in the psychological field. From an empirical point of view, we can go deeper into this topic by testing the indirect relationship among variables.

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Lajnef, K. The effect of social media influencers' on teenagers Behavior: an empirical study using cognitive map technique. Curr Psychol 42 , 19364–19377 (2023). https://doi.org/10.1007/s12144-023-04273-1

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