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  • Published: 08 May 2024

Exploring the dynamics of consumer engagement in social media influencer marketing: from the self-determination theory perspective

  • Chenyu Gu   ORCID: orcid.org/0000-0001-6059-0573 1 &
  • Qiuting Duan 2  

Humanities and Social Sciences Communications volume  11 , Article number:  587 ( 2024 ) Cite this article

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  • Business and management
  • Cultural and media studies

Influencer advertising has emerged as an integral part of social media marketing. Within this realm, consumer engagement is a critical indicator for gauging the impact of influencer advertisements, as it encompasses the proactive involvement of consumers in spreading advertisements and creating value. Therefore, investigating the mechanisms behind consumer engagement holds significant relevance for formulating effective influencer advertising strategies. The current study, grounded in self-determination theory and employing a stimulus-organism-response framework, constructs a general model to assess the impact of influencer factors, advertisement information, and social factors on consumer engagement. Analyzing data from 522 samples using structural equation modeling, the findings reveal: (1) Social media influencers are effective at generating initial online traffic but have limited influence on deeper levels of consumer engagement, cautioning advertisers against overestimating their impact; (2) The essence of higher-level engagement lies in the ad information factor, affirming that in the new media era, content remains ‘king’; (3) Interpersonal factors should also be given importance, as influencing the surrounding social groups of consumers is one of the effective ways to enhance the impact of advertising. Theoretically, current research broadens the scope of both social media and advertising effectiveness studies, forming a bridge between influencer marketing and consumer engagement. Practically, the findings offer macro-level strategic insights for influencer marketing.

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Introduction.

Recent studies have highlighted an escalating aversion among audiences towards traditional online ads, leading to a diminishing effectiveness of traditional online advertising methods (Lou et al., 2019 ). In an effort to overcome these challenges, an increasing number of brands are turning to influencers as their spokespersons for advertising. Utilizing influencers not only capitalizes on their significant influence over their fan base but also allows for the dissemination of advertising messages in a more native and organic manner. Consequently, influencer-endorsed advertising has become a pivotal component and a growing trend in social media advertising (Gräve & Bartsch, 2022 ). Although the topic of influencer-endorsed advertising has garnered increasing attention from scholars, the field is still in its infancy, offering ample opportunities for in-depth research and exploration (Barta et al., 2023 ).

Presently, social media influencers—individuals with substantial follower bases—have emerged as the new vanguard in advertising (Hudders & Lou, 2023 ). Their tweets and videos possess the remarkable potential to sway the purchasing decisions of thousands if not millions. This influence largely hinges on consumer engagement behaviors, implying that the impact of advertising can proliferate throughout a consumer’s entire social network (Abbasi et al., 2023 ). Consequently, exploring ways to enhance consumer engagement is of paramount theoretical and practical significance for advertising effectiveness research (Xiao et al., 2023 ). This necessitates researchers to delve deeper into the exploration of the stimulating factors and psychological mechanisms influencing consumer engagement behaviors (Vander Schee et al., 2020 ), which is the gap this study seeks to address.

The Stimulus-Organism-Response (S-O-R) framework has been extensively applied in the study of consumer engagement behaviors (Tak & Gupta, 2021 ) and has been shown to integrate effectively with self-determination theory (Yang et al., 2019 ). Therefore, employing the S-O-R framework to investigate consumer engagement behaviors in the context of influencer advertising is considered a rational approach. The current study embarks on an in-depth analysis of the transformation process from three distinct dimensions. In the Stimulus (S) phase, we focus on how influencer factors, advertising message factors, and social influence factors act as external stimuli. This phase scrutinizes the external environment’s role in triggering consumer reactions. During the Organism (O) phase, the research explores the intrinsic psychological motivations affecting individual behavior as posited in self-determination theory. This includes the willingness for self-disclosure, the desire for innovation, and trust in advertising messages. The investigation in this phase aims to understand how these internal motivations shape consumer attitudes and perceptions in the context of influencer marketing. Finally, in the Response (R) phase, the study examines how these psychological factors influence consumer engagement behavior. This part of the research seeks to understand the transition from internal psychological states to actual consumer behavior, particularly how these states drive the consumers’ deep integration and interaction with the influencer content.

Despite the inherent limitations of cross-sectional analysis in capturing the full temporal dynamics of consumer engagement, this study seeks to unveil the dynamic interplay between consumers’ psychological needs—autonomy, competence, and relatedness—and their varying engagement levels in social media influencer marketing, grounded in self-determination theory. Through this lens, by analyzing factors related to influencers, content, and social context, we aim to infer potential dynamic shifts in engagement behaviors as psychological needs evolve. This approach allows us to offer a snapshot of the complex, multi-dimensional nature of consumer engagement dynamics, providing valuable insights for both theoretical exploration and practical application in the constantly evolving domain of social media marketing. Moreover, the current study underscores the significance of adapting to the dynamic digital environment and highlights the evolving nature of consumer engagement in the realm of digital marketing.

Literature review

Stimulus-organism-response (s-o-r) model.

The Stimulus-Response (S-R) model, originating from behaviorist psychology and introduced by psychologist Watson ( 1917 ), posits that individual behaviors are directly induced by external environmental stimuli. However, this model overlooks internal personal factors, complicating the explanation of psychological states. Mehrabian and Russell ( 1974 ) expanded this by incorporating the individual’s cognitive component (organism) into the model, creating the Stimulus-Organism-Response (S-O-R) framework. This model has become a crucial theoretical framework in consumer psychology as it interprets internal psychological cognitions as mediators between stimuli and responses. Integrating with psychological theories, the S-O-R model effectively analyzes and explains the significant impact of internal psychological factors on behavior (Koay et al., 2020 ; Zhang et al., 2021 ), and is extensively applied in investigating user behavior on social media platforms (Hewei & Youngsook, 2022 ). This study combines the S-O-R framework with self-determination theory to examine consumer engagement behaviors in the context of social media influencer advertising, a logic also supported by some studies (Yang et al., 2021 ).

Self-determination theory

Self-determination theory, proposed by Richard and Edward (2000), is a theoretical framework exploring human behavioral motivation and personality. The theory emphasizes motivational processes, positing that individual behaviors are developed based on factors satisfying their psychological needs. It suggests that individual behavioral tendencies are influenced by the needs for competence, relatedness, and autonomy. Furthermore, self-determination theory, along with organic integration theory, indicates that individual behavioral tendencies are also affected by internal psychological motivations and external situational factors.

Self-determination theory has been validated by scholars in the study of online user behaviors. For example, Sweet applied the theory to the investigation of community building in online networks, analyzing knowledge-sharing behaviors among online community members (Sweet et al., 2020 ). Further literature review reveals the applicability of self-determination theory to consumer engagement behaviors, particularly in the context of influencer marketing advertisements. Firstly, self-determination theory is widely applied in studying the psychological motivations behind online behaviors, suggesting that the internal and external motivations outlined within the theory might also apply to exploring consumer behaviors in influencer marketing scenarios (Itani et al., 2022 ). Secondly, although research on consumer engagement in the social media influencer advertising context is still in its early stages, some studies have utilized SDT to explore behaviors such as information sharing and electronic word-of-mouth dissemination (Astuti & Hariyawan, 2021 ). These behaviors, which are part of the content contribution and creation dimensions of consumer engagement, may share similarities in the underlying psychological motivational mechanisms. Thus, this study will build upon these foundations to construct the Organism (O) component of the S-O-R model, integrating insights from SDT to further understand consumer engagement in influencer marketing.

Consumer engagement

Although scholars generally agree at a macro level to define consumer engagement as the creation of additional value by consumers or customers beyond purchasing products, the specific categorization of consumer engagement varies in different studies. For instance, Simon and Tossan interpret consumer engagement as a psychological willingness to interact with influencers (Simon & Tossan, 2018 ). However, such a broad definition lacks precision in describing various levels of engagement. Other scholars directly use tangible metrics on social media platforms, such as likes, saves, comments, and shares, to represent consumer engagement (Lee et al., 2018 ). While this quantitative approach is not flawed and can be highly effective in practical applications, it overlooks the content aspect of engagement, contradicting the “content is king” principle of advertising and marketing. We advocate for combining consumer engagement with the content aspect, as content engagement not only generates more traces of consumer online behavior (Oestreicher-Singer & Zalmanson, 2013 ) but, more importantly, content contribution and creation are central to social media advertising and marketing, going beyond mere content consumption (Qiu & Kumar, 2017 ). Meanwhile, we also need to emphasize that engagement is not a fixed state but a fluctuating process influenced by ongoing interactions between consumers and influencers, mediated by the evolving nature of social media platforms and the shifting sands of consumer preferences (Pradhan et al., 2023 ). Consumer engagement in digital environments undergoes continuous change, reflecting a journey rather than a destination (Viswanathan et al., 2017 ).

The current study adopts a widely accepted definition of consumer engagement from existing research, offering operational feasibility and aligning well with the research objectives of this paper. Consumer engagement behaviors in the context of this study encompass three dimensions: content consumption, content contribution, and content creation (Muntinga et al., 2011 ). These dimensions reflect a spectrum of digital engagement behaviors ranging from low to high levels (Schivinski et al., 2016 ). Specifically, content consumption on social media platforms represents a lower level of engagement, where consumers merely click and read the information but do not actively contribute or create user-generated content. Some studies consider this level of engagement as less significant for in-depth exploration because content consumption, compared to other forms, generates fewer visible traces of consumer behavior (Brodie et al., 2013 ). Even in a study by Qiu and Kumar, it was noted that the conversion rate of content consumption is low, contributing minimally to the success of social media marketing (Qiu & Kumar, 2017 ).

On the other hand, content contribution, especially content creation, is central to social media marketing. When consumers comment on influencer content or share information with their network nodes, it is termed content contribution, representing a medium level of online consumer engagement (Piehler et al., 2019 ). Furthermore, when consumers actively upload and post brand-related content on social media, this higher level of behavior is referred to as content creation. Content creation represents the highest level of consumer engagement (Cheung et al., 2021 ). Although medium and high levels of consumer engagement are more valuable for social media advertising and marketing, this exploratory study still retains the content consumption dimension of consumer engagement behaviors.

Theoretical framework

Internal organism factors: self-disclosure willingness, innovativeness, and information trust.

In existing research based on self-determination theory that focuses on online behavior, competence, relatedness, and autonomy are commonly considered as internal factors influencing users’ online behaviors. However, this approach sometimes strays from the context of online consumption. Therefore, in studies related to online consumption, scholars often use self-disclosure willingness as an overt representation of autonomy, innovativeness as a representation of competence, and trust as a representation of relatedness (Mahmood et al., 2019 ).

The use of these overt variables can be logically explained as follows: According to self-determination theory, individuals with a higher level of self-determination are more likely to adopt compensatory mechanisms to facilitate behavior compared to those with lower self-determination (Wehmeyer, 1999 ). Self-disclosure, a voluntary act of sharing personal information with others, is considered a key behavior in the development of interpersonal relationships. In social environments, self-disclosure can effectively alleviate stress and build social connections, while also seeking societal validation of personal ideas (Altman & Taylor, 1973 ). Social networks, as para-social entities, possess the interactive attributes of real societies and are likely to exhibit similar mechanisms. In consumer contexts, personal disclosures can include voluntary sharing of product interests, consumption experiences, and future purchase intentions (Robertshaw & Marr, 2006 ). While material incentives can prompt personal information disclosure, many consumers disclose personal information online voluntarily, which can be traced back to an intrinsic need for autonomy (Stutzman et al., 2011 ). Thus, in this study, we consider the self-disclosure willingness as a representation of high autonomy.

Innovativeness refers to an individual’s internal level of seeking novelty and represents their personality and tendency for novelty (Okazaki, 2009 ). Often used in consumer research, innovative consumers are inclined to try new technologies and possess an intrinsic motivation to use new products. Previous studies have shown that consumers with high innovativeness are more likely to search for information on new products and share their experiences and expertise with others, reflecting a recognition of their own competence (Kaushik & Rahman, 2014 ). Therefore, in consumer contexts, innovativeness is often regarded as the competence dimension within the intrinsic factors of self-determination (Wang et al., 2016 ), with external motivations like information novelty enhancing this intrinsic motivation (Lee et al., 2015 ).

Trust refers to an individual’s willingness to rely on the opinions of others they believe in. From a social psychological perspective, trust indicates the willingness to assume the risk of being harmed by another party (McAllister, 1995 ). Widely applied in social media contexts for relational marketing, information trust has been proven to positively influence the exchange and dissemination of consumer information, representing a close and advanced relationship between consumers and businesses, brands, or advertising endorsers (Steinhoff et al., 2019 ). Consumers who trust brands or social media influencers are more willing to share information without fear of exploitation (Pop et al., 2022 ), making trust a commonly used representation of the relatedness dimension in self-determination within consumer contexts.

Construction of the path from organism to response: self-determination internal factors and consumer engagement behavior

Following the logic outlined above, the current study represents the internal factors of self-determination theory through three variables: self-disclosure willingness, innovativeness, and information trust. Next, the study explores the association between these self-determination internal factors and consumer engagement behavior, thereby constructing the link between Organism (O) and Response (R).

Self-disclosure willingness and consumer engagement behavior

In the realm of social sciences, the concept of self-disclosure willingness has been thoroughly examined from diverse disciplinary perspectives, encompassing communication studies, sociology, and psychology. Viewing from the lens of social interaction dynamics, self-disclosure is acknowledged as a fundamental precondition for the initiation and development of online social relationships and interactive engagements (Luo & Hancock, 2020 ). It constitutes an indispensable component within the spectrum of interactive behaviors and the evolution of interpersonal connections. Voluntary self-disclosure is characterized by individuals divulging information about themselves, which typically remains unknown to others and is inaccessible through alternative sources. This concept aligns with the tenets of uncertainty reduction theory, which argues that during interpersonal engagements, individuals seek information about their counterparts as a means to mitigate uncertainties inherent in social interactions (Lee et al., 2008 ). Self-disclosure allows others to gain more personal information, thereby helping to reduce the uncertainty in interpersonal relationships. Such disclosure is voluntary rather than coerced, and this sharing of information can facilitate the development of relationships between individuals (Towner et al., 2022 ). Furthermore, individuals who actively engage in social media interactions (such as liking, sharing, and commenting on others’ content) often exhibit higher levels of self-disclosure (Chu et al., 2023 ); additional research indicates a positive correlation between self-disclosure and online engagement behaviors (Lee et al., 2023 ). Taking the context of the current study, the autonomous self-disclosure willingness can incline social media users to read advertising content more attentively and share information with others, and even create evaluative content. Therefore, this paper proposes the following research hypothesis:

H1a: The self-disclosure willingness is positively correlated with content consumption in consumer engagement behavior.

H1b: The self-disclosure willingness is positively correlated with content contribution in consumer engagement behavior.

H1c: The self-disclosure willingness is positively correlated with content creation in consumer engagement behavior.

Innovativeness and consumer engagement behavior

Innovativeness represents an individual’s propensity to favor new technologies and the motivation to use new products, associated with the cognitive perception of one’s self-competence. Individuals with a need for self-competence recognition often exhibit higher innovativeness (Kelley & Alden, 2016 ). Existing research indicates that users with higher levels of innovativeness are more inclined to accept new product information and share their experiences and discoveries with others in their social networks (Yusuf & Busalim, 2018 ). Similarly, in the context of this study, individuals, as followers of influencers, signify an endorsement of the influencer. Driven by innovativeness, they may be more eager to actively receive information from influencers. If they find the information valuable, they are likely to share it and even engage in active content re-creation to meet their expectations of self-image. Therefore, this paper proposes the following research hypotheses:

H2a: The innovativeness of social media users is positively correlated with content consumption in consumer engagement behavior.

H2b: The innovativeness of social media users is positively correlated with content contribution in consumer engagement behavior.

H2c: The innovativeness of social media users is positively correlated with content creation in consumer engagement behavior.

Information trust and consumer engagement

Trust refers to an individual’s willingness to rely on the statements and opinions of a target object (Moorman et al., 1993 ). Extensive research indicates that trust positively impacts information dissemination and content sharing in interpersonal communication environments (Majerczak & Strzelecki, 2022 ); when trust is established, individuals are more willing to share their resources and less suspicious of being exploited. Trust has also been shown to influence consumers’ participation in community building and content sharing on social media, demonstrating cross-cultural universality (Anaya-Sánchez et al., 2020 ).

Trust in influencer advertising information is also a key predictor of consumers’ information exchange online. With many social media users now operating under real-name policies, there is an increased inclination to trust information shared on social media over that posted by corporate accounts or anonymously. Additionally, as users’ social networks partially overlap with their real-life interpersonal networks, extensive research shows that more consumers increasingly rely on information posted and shared on social networks when making purchase decisions (Wang et al., 2016 ). This aligns with the effectiveness goals of influencer marketing advertisements and the characteristics of consumer engagement. Trust in the content posted by influencers is considered a manifestation of a strong relationship between fans and influencers, central to relationship marketing (Kim & Kim, 2021 ). Based on trust in the influencer, which then extends to trust in their content, people are more inclined to browse information posted by influencers, share this information with others, and even create their own content without fear of exploitation or negative consequences. Therefore, this paper proposes the following research hypotheses:

H3a: Information trust is positively correlated with content consumption in consumer engagement behavior.

H3b: Information trust is positively correlated with content contribution in consumer engagement behavior.

H3c: Information trust is positively correlated with content creation in consumer engagement behavior.

Construction of the path from stimulus to organism: influencer factors, advertising information factors, social factors, and self-determination internal factors

Having established the logical connection from Organism (O) to Response (R), we further construct the influence path from Stimulus (S) to Organism (O). Revisiting the definition of influencer advertising in social media, companies, and brands leverage influencers on social media platforms to disseminate advertising content, utilizing the influencers’ relationships and influence over consumers for marketing purposes. In addition to consumer’s internal factors, elements such as companies, brands, influencers, and the advertisements themselves also impact consumer behavior. Although factors like the brand image perception of companies may influence consumer behavior, considering that in influencer marketing, companies and brands do not directly interact with consumers, this study prioritizes the dimensions of influencers and advertisements. Furthermore, the impact of social factors on individual cognition and behavior is significant, thus, the current study integrates influencers, advertisements, and social dimensions as the Stimulus (S) component.

Influencer factors: parasocial identification

Self-determination theory posits that relationships are one of the key motivators influencing individual behavior. In the context of social media research, users anticipate establishing a parasocial relationship with influencers, resembling real-life relationships. Hence, we consider the parasocial identification arising from users’ parasocial interactions with influencers as the relational motivator. Parasocial interaction refers to the one-sided personal relationship that individuals develop with media characters (Donald & Richard, 1956 ). During this process, individuals believe that the media character is directly communicating with them, creating a sense of positive intimacy (Giles, 2002 ). Over time, through repeated unilateral interactions with media characters, individuals develop a parasocial relationship, leading to parasocial identification. However, parasocial identification should not be directly equated with the concept of social identification in social identity theory. Social identification occurs when individuals psychologically de-individualize themselves, perceiving the characteristics of their social group as their own, upon identifying themselves as part of that group. In contrast, parasocial identification refers to the one-sided interactional identification with media characters (such as celebrities or influencers) over time (Chen et al., 2021 ). Particularly when individuals’ needs for interpersonal interaction are not met in their daily lives, they turn to parasocial interactions to fulfill these needs (Shan et al., 2020 ). Especially on social media, which is characterized by its high visibility and interactivity, users can easily develop a strong parasocial identification with the influencers they follow (Wei et al., 2022 ).

Parasocial identification and self-disclosure willingness

Theories like uncertainty reduction, personal construct, and social exchange are often applied to explain the emergence of parasocial identification. Social media, with its convenient and interactive modes of information dissemination, enables consumers to easily follow influencers on media platforms. They can perceive the personality of influencers through their online content, viewing them as familiar individuals or even friends. Once parasocial identification develops, this pleasurable experience can significantly influence consumers’ cognitions and thus their behavioral responses. Research has explored the impact of parasocial identification on consumer behavior. For instance, Bond et al. found that on Twitter, the intensity of users’ parasocial identification with influencers positively correlates with their continuous monitoring of these influencers’ activities (Bond, 2016 ). Analogous to real life, where we tend to pay more attention to our friends in our social networks, a similar phenomenon occurs in the relationship between consumers and brands. This type of parasocial identification not only makes consumers willing to follow brand pages but also more inclined to voluntarily provide personal information (Chen et al., 2021 ). Based on this logic, we speculate that a similar relationship may exist between social media influencers and their fans. Fans develop parasocial identification with influencers through social media interactions, making them more willing to disclose their information, opinions, and views in the comment sections of the influencers they follow, engaging in more frequent social interactions (Chung & Cho, 2017 ), even if the content at times may be brand or company-embedded marketing advertisements. In other words, in the presence of influencers with whom they have established parasocial relationships, they are more inclined to disclose personal information, thereby promoting consumer engagement behavior. Therefore, we propose the following research hypotheses:

H4: Parasocial identification is positively correlated with consumer self-disclosure willingness.

H4a: Self-disclosure willingness mediates the impact of parasocial identification on content consumption in consumer engagement behavior.

H4b: Self-disclosure willingness mediates the impact of parasocial identification on content contribution in consumer engagement behavior.

H4c: Self-disclosure willingness mediates the impact of parasocial identification on content creation in consumer engagement behavior.

Parasocial identification and information trust

Information Trust refers to consumers’ willingness to trust the information contained in advertisements and to place themselves at risk. These risks include purchasing products inconsistent with the advertised information and the negative social consequences of erroneously spreading this information to others, leading to unpleasant consumption experiences (Minton, 2015 ). In advertising marketing, gaining consumers’ trust in advertising information is crucial. In the context of influencer marketing on social media, companies, and brands leverage the social connection between influencers and their fans. According to cognitive empathy theory, consumers project their trust in influencers onto the products endorsed, explaining the phenomenon of ‘loving the house for the crow on its roof.’ Research indicates that parasocial identification with influencers is a necessary condition for trust development. Consumers engage in parasocial interactions with influencers on social media, leading to parasocial identification (Jin et al., 2021 ). Consumers tend to reduce their cognitive load and simplify their decision-making processes, thus naturally adopting a positive attitude and trust towards advertising information disseminated by influencers with whom they have established parasocial identification. This forms the core logic behind the success of influencer marketing advertisements (Breves et al., 2021 ); furthermore, as mentioned earlier, because consumers trust these advertisements, they are also willing to share this information with friends and family and even engage in content re-creation. Therefore, we propose the following research hypotheses:

H5: Parasocial identification is positively correlated with information trust.

H5a: Information trust mediates the impact of parasocial identification on content consumption in consumer engagement behavior.

H5b: Information trust mediates the impact of parasocial identification on content contribution in consumer engagement behavior.

H5c: Information trust mediates the impact of parasocial identification on content creation in consumer engagement behavior.

Influencer factors: source credibility

Source credibility refers to the degree of trust consumers place in the influencer as a source, based on the influencer’s reliability and expertise. Numerous studies have validated the effectiveness of the endorsement effect in advertising (Schouten et al., 2021 ). The Source Credibility Model, proposed by the renowned American communication scholar Hovland and the “Yale School,” posits that in the process of information dissemination, the credibility of the source can influence the audience’s decision to accept the information. The credibility of the information is determined by two aspects of the source: reliability and expertise. Reliability refers to the audience’s trust in the “communicator’s objective and honest approach to providing information,” while expertise refers to the audience’s trust in the “communicator being perceived as an effective source of information” (Hovland et al., 1953 ). Hovland’s definitions reveal that the interpretation of source credibility is not about the inherent traits of the source itself but rather the audience’s perception of the source (Jang et al., 2021 ). This differs from trust and serves as a precursor to the development of trust. Specifically, reliability and expertise are based on the audience’s perception; thus, this aligns closely with the audience’s perception of influencers (Kim & Kim, 2021 ). This credibility is a cognitive statement about the source of information.

Source credibility and self-disclosure willingness

Some studies have confirmed the positive impact of an influencer’s self-disclosure on their credibility as a source (Leite & Baptista, 2022 ). However, few have explored the impact of an influencer’s credibility, as a source, on consumers’ self-disclosure willingness. Undoubtedly, an impact exists; self-disclosure is considered a method to attempt to increase intimacy with others (Leite et al., 2022 ). According to social exchange theory, people promote relationships through the exchange of information in interpersonal communication to gain benefits (Cropanzano & Mitchell, 2005 ). Credibility, deriving from an influencer’s expertise and reliability, means that a highly credible influencer may provide more valuable information to consumers. Therefore, based on the social exchange theory’s logic of reciprocal benefits, consumers might be more willing to disclose their information to trustworthy influencers, potentially even expanding social interactions through further consumer engagement behaviors. Thus, we propose the following research hypotheses:

H6: Source credibility is positively correlated with self-disclosure willingness.

H6a: Self-disclosure willingness mediates the impact of Source credibility on content consumption in consumer engagement behavior.

H6b: Self-disclosure willingness mediates the impact of Source credibility on content contribution in consumer engagement behavior.

H6c: Self-disclosure willingness mediates the impact of Source credibility on content creation in consumer engagement behavior.

Source credibility and information trust

Based on the Source Credibility Model, the credibility of an endorser as an information source can significantly influence consumers’ acceptance of the information (Shan et al., 2020 ). Existing research has demonstrated the positive impact of source credibility on consumers. Djafarova, in a study based on Instagram, noted through in-depth interviews with 18 users that an influencer’s credibility significantly affects respondents’ trust in the information they post. This credibility is composed of expertise and relevance to consumers, and influencers on social media are considered more trustworthy than traditional celebrities (Djafarova & Rushworth, 2017 ). Subsequently, Bao and colleagues validated in the Chinese consumer context, based on the ELM model and commitment-trust theory, that the credibility of brand pages on Weibo effectively fosters consumer trust in the brand, encouraging participation in marketing activities (Bao & Wang, 2021 ). Moreover, Hsieh et al. found that in e-commerce contexts, the credibility of the source is a significant factor influencing consumers’ trust in advertising information (Hsieh & Li, 2020 ). In summary, existing research has proven that the credibility of the source can promote consumer trust. Influencer credibility is a significant antecedent affecting consumers’ trust in the advertised content they publish. In brand communities, trust can foster consumer engagement behaviors (Habibi et al., 2014 ). Specifically, consumers are more likely to trust the advertising content published by influencers with higher credibility (more expertise and reliability), and as previously mentioned, consumer engagement behavior is more likely to occur. Based on this, the study proposes the following research hypotheses:

H7: Source credibility is positively correlated with information trust.

H7a: Information trust mediates the impact of source credibility on content consumption in consumer engagement behavior.

H7b: Information trust mediates the impact of source credibility on content contribution in consumer engagement behavior.

H7c: Information trust mediates the impact of source credibility on content creation in consumer engagement behavior.

Advertising information factors: informative value

Advertising value refers to “the relative utility value of advertising information to consumers and is a subjective evaluation by consumers.” In his research, Ducoffe pointed out that in the context of online advertising, the informative value of advertising is a significant component of advertising value (Ducoffe, 1995 ). Subsequent studies have proven that consumers’ perception of advertising value can effectively promote their behavioral response to advertisements (Van-Tien Dao et al., 2014 ). Informative value of advertising refers to “the information about products needed by consumers provided by the advertisement and its ability to enhance consumer purchase satisfaction.” From the perspective of information dissemination, valuable advertising information should help consumers make better purchasing decisions and reduce the effort spent searching for product information. The informational aspect of advertising has been proven to effectively influence consumers’ cognition and, in turn, their behavior (Haida & Rahim, 2015 ).

Informative value and innovativeness

As previously discussed, consumers’ innovativeness refers to their psychological trait of favoring new things. Studies have shown that consumers with high innovativeness prefer novel and valuable product information, as it satisfies their need for newness and information about new products, making it an important factor in social media advertising engagement (Shi, 2018 ). This paper also hypothesizes that advertisements with high informative value can activate consumers’ innovativeness, as the novelty of information is one of the measures of informative value (León et al., 2009 ). Acquiring valuable information can make individuals feel good about themselves and fulfill their perception of a “novel image.” According to social exchange theory, consumers can gain social capital in interpersonal interactions (such as social recognition) by sharing information about these new products they perceive as valuable. Therefore, the current study proposes the following research hypothesis:

H8: Informative value is positively correlated with innovativeness.

H8a: Innovativeness mediates the impact of informative value on content consumption in consumer engagement behavior.

H8b: Innovativeness mediates the impact of informative value on content contribution in consumer engagement behavior.

H8c: Innovativeness mediates the impact of informative value on content creation in consumer engagement behavior.

Informative value and information trust

Trust is a multi-layered concept explored across various disciplines, including communication, marketing, sociology, and psychology. For the purposes of this paper, a deep analysis of different levels of trust is not undertaken. Here, trust specifically refers to the trust in influencer advertising information within the context of social media marketing, denoting consumers’ belief in and reliance on the advertising information endorsed by influencers. Racherla et al. investigated the factors influencing consumers’ trust in online reviews, suggesting that information quality and value contribute to increasing trust (Racherla et al., 2012 ). Similarly, Luo and Yuan, in a study based on social media marketing, also confirmed that the value of advertising information posted on brand pages can foster consumer trust in the content (Lou & Yuan, 2019 ). Therefore, by analogy, this paper posits that the informative value of influencer-endorsed advertising can also promote consumer trust in that advertising information. The relationship between trust in advertising information and consumer engagement behavior has been discussed earlier. Thus, the current study proposes the following research hypotheses:

H9: Informative value is positively correlated with information trust.

H9a: Information trust mediates the impact of informative value on content consumption in consumer engagement behavior.

H9b: Information trust mediates the impact of informative value on content contribution in consumer engagement behavior.

H9c: Information trust mediates the impact of informative value on content creation in consumer engagement behavior.

Advertising information factors: ad targeting accuracy

Ad targeting accuracy refers to the degree of match between the substantive information contained in advertising content and consumer needs. Advertisements containing precise information often yield good advertising outcomes. In marketing practice, advertisers frequently use information technology to analyze the characteristics of different consumer groups in the target market and then target their advertisements accordingly to achieve precise dissemination and, consequently, effective advertising results. The utility of ad targeting accuracy has been confirmed by many studies. For instance, in the research by Qiu and Chen, using a modified UTAUT model, it was demonstrated that the accuracy of advertising effectively promotes consumer acceptance of advertisements in WeChat Moments (Qiu & Chen, 2018 ). Although some studies on targeted advertising also indicate that overly precise ads may raise concerns about personal privacy (Zhang et al., 2019 ), overall, the accuracy of advertising information is effective in enhancing advertising outcomes and is a key element in the success of targeted advertising.

Ad targeting accuracy and information trust

In influencer marketing advertisements, due to the special relationship recognition between consumers and influencers, the privacy concerns associated with ad targeting accuracy are alleviated (Vrontis et al., 2021 ). Meanwhile, the informative value brought by targeting accuracy is highlighted. More precise advertising content implies higher informative value and also signifies that the advertising content is more worthy of consumer trust (Della Vigna, Gentzkow, 2010 ). As previously discussed, people are more inclined to read and engage with advertising content they trust and recognize. Therefore, the current study proposes the following research hypotheses:

H10: Ad targeting accuracy is positively correlated with information trust.

H10a: Information trust mediates the impact of ad targeting accuracy on content consumption in consumer engagement behavior.

H10b: Information trust mediates the impact of ad targeting accuracy on content contribution in consumer engagement behavior.

H10c: Information trust mediates the impact of ad targeting accuracy on content creation in consumer engagement behavior.

Social factors: subjective norm

The Theory of Planned Behavior, proposed by Ajzen ( 1991 ), suggests that individuals’ actions are preceded by conscious choices and are underlain by plans. TPB has been widely used by scholars in studying personal online behaviors, these studies collectively validate the applicability of TPB in the context of social media for researching online behaviors (Huang, 2023 ). Additionally, the self-determination theory, which underpins this chapter’s research, also supports the notion that individuals’ behavioral decisions are based on internal cognitions, aligning with TPB’s assertions. Therefore, this paper intends to select subjective norms from TPB as a factor of social influence. Subjective norm refers to an individual’s perception of the expectations of significant others in their social relationships regarding their behavior. Empirical research in the consumption field has demonstrated the significant impact of subjective norms on individual psychological cognition (Yang & Jolly, 2009 ). A meta-analysis by Hagger, Chatzisarantis ( 2009 ) even highlighted the statistically significant association between subjective norms and self-determination factors. Consequently, this study further explores its application in the context of influencer marketing advertisements on social media.

Subjective norm and self-disclosure willingness

In numerous studies on social media privacy, subjective norms significantly influence an individual’s self-disclosure willingness. Wirth et al. ( 2019 ) based on the privacy calculus theory, surveyed 1,466 participants and found that personal self-disclosure on social media is influenced by the behavioral expectations of other significant reference groups around them. Their research confirmed that subjective norms positively influence self-disclosure of information and highlighted that individuals’ cognitions and behaviors cannot ignore social and environmental factors. Heirman et al. ( 2013 ) in an experiment with Instagram users, also noted that subjective norms could promote positive consumer behavioral responses. Specifically, when important family members and friends highly regard social media influencers as trustworthy, we may also be more inclined to disclose our information to influencers and share this information with our surrounding family and friends without fear of disapproval. In our subjective norms, this is considered a positive and valuable interactive behavior, leading us to exhibit engagement behaviors. Based on this logic, we propose the following research hypotheses:

H11: Subjective norms are positively correlated with self-disclosure willingness.

H11a: Self-disclosure willingness mediates the impact of subjective norms on content consumption in consumer engagement behavior.

H11b: Self-disclosure willingness mediates the impact of subjective norms on content contribution in consumer engagement behavior.

H11c: Self-disclosure willingness mediates the impact of subjective norms on content creation in consumer engagement behavior.

Subjective norm and information trust

Numerous studies have indicated that subjective norms significantly influence trust (Roh et al., 2022 ). This can be explained by reference group theory, suggesting people tend to minimize the effort expended in decision-making processes, often looking to the behaviors or attitudes of others as a point of reference; for instance, subjective norms can foster acceptance of technology by enhancing trust (Gupta et al., 2021 ). Analogously, if a consumer’s social network generally holds positive attitudes toward influencer advertising, they are also more likely to trust the endorsed advertisement information, as it conserves the extensive effort required in gathering product information (Chetioui et al., 2020 ). Therefore, this paper proposes the following research hypotheses:

H12: Subjective norms are positively correlated with information trust.

H12a: Information trust mediates the impact of subjective norms on content consumption in consumer engagement behavior.

H12b: Information trust mediates the impact of subjective norms on content contribution in consumer engagement behavior.

H12c: Information trust mediates the impact of subjective norms on content creation in consumer engagement behavior.

Conceptual model

In summary, based on the Stimulus (S)-Organism (O)-Response (R) framework, this study constructs the external stimulus factors (S) from three dimensions: influencer factors (parasocial identification, source credibility), advertising information factors (informative value, Ad targeting accuracy), and social influence factors (subjective norms). This is grounded in social capital theory and the theory of planned behavior. drawing on self-determination theory, the current study constructs the individual psychological factors (O) using self-disclosure willingness, innovativeness, and information trust. Finally, the behavioral response (R) is constructed using consumer engagement, which includes content consumption, content contribution, and content creation, as illustrated in Fig. 1 .

figure 1

Consumer engagement behavior impact model based on SOR framework.

Materials and methods

Participants and procedures.

The current study conducted a survey through the Wenjuanxing platform to collect data. Participants were recruited through social media platforms such as WeChat, Douyin, Weibo et al., as samples drawn from social media users better align with the research purpose of our research and ensure the validity of the sample. Before the survey commenced, all participants were explicitly informed about the purpose of this study, and it was made clear that volunteers could withdraw from the survey at any time. Initially, 600 questionnaires were collected, with 78 invalid responses excluded. The criteria for valid questionnaires were as follows: (1) Respondents must have answered “Yes” to the question, “Do you follow any influencers (internet celebrities) on social media platforms?” as samples not using social media or not following influencers do not meet the study’s objective, making this question a prerequisite for continuing the survey; (2) Respondents had to correctly answer two hidden screening questions within the questionnaire to ensure that they did not randomly select scores; (3) The total time taken to complete the questionnaire had to exceed one minute, ensuring that respondents had sufficient time to understand and thoughtfully answer each question; (4) Respondents were not allowed to choose the same score for eight consecutive questions. Ultimately, 522 valid questionnaires were obtained, with an effective rate of 87.00%, meeting the basic sample size requirements for research models (Gefen et al., 2011 ). Detailed demographic information of the study participants is presented in Table 1 .

Measurements

To ensure the validity and reliability of the data analysis results in this study, the measurement tools and scales used in this chapter were designed with reference to existing established research. The main variables in the survey questionnaire include parasocial identification, source credibility, informative value, ad targeting accuracy, subjective norms, self-disclosure willingness, innovativeness, information trust, content consumption, content contribution, and content creation. The measurement scale for parasocial identification was adapted from the research of Schramm and Hartmann, comprising 6 items (Schramm & Hartmann, 2008 ). The source credibility scale was combined from the studies of Cheung et al. and Luo & Yuan’s research in the context of social media influencer marketing, including 4 items (Cheung et al., 2009 ; Lou & Yuan, 2019 ). The scale for informative value was modified based on Voss et al.‘s research, consisting of 4 items (Voss et al., 2003 ). The ad targeting accuracy scale was derived from the research by Qiu Aimei et al., 2018 ) including 3 items. The subjective norm scale was adapted from Ajzen’s original scale, comprising 3 items (Ajzen, 2002 ). The self-disclosure willingness scale was developed based on Chu and Kim’s research, including 3 items (Chu & Kim, 2011 ). The innovativeness scale was formulated following the study by Sun et al., comprising 4 items (Sun et al., 2006 ). The information trust scale was created in reference to Chu and Choi’s research, including 3 items (Chu & Choi, 2011 ). The scales for the three components of social media consumer engagement—content consumption, content contribution, and content creation—were sourced from the research by Buzeta et al., encompassing 8 items in total (Buzeta et al., 2020 ).

All scales were appropriately revised for the context of social media influencer marketing. To avoid issues with scoring neutral attitudes, a uniform Likert seven-point scale was used for each measurement item (ranging from 1 to 7, representing a spectrum from ‘strongly disagree’ to ‘strongly agree’). After the overall design of the questionnaire was completed, a pre-test was conducted with 30 social media users to ensure that potential respondents could clearly understand the meaning of each question and that there were no obstacles to answering. This pre-test aimed to prevent any difficulties or misunderstandings in the questionnaire items. The final version of the questionnaire is presented in Table 2 .

Data analysis

Since the model framework of the current study is derived from theoretical deductions of existing research and, while logically constructed, does not originate from an existing research model, this study still falls under the category of exploratory research. According to the analysis suggestions of Hair and other scholars, in cases of exploratory research model frameworks, it is more appropriate to choose Smart PLS for Partial Least Squares Path Analysis (PLS) to conduct data analysis and testing of the research model (Hair et al., 2012 ).

Measurement of model

In this study, careful data collection and management resulted in no missing values in the dataset. This ensured the integrity and reliability of the subsequent data analysis. As shown in Table 3 , after deleting measurement items with factor loadings below 0.5, the final factor loadings of the measurement items in this study range from 0.730 to 0.964. This indicates that all measurement items meet the retention criteria. Additionally, the Cronbach’s α values of the latent variables range from 0.805 to 0.924, and all latent variables have Composite Reliability (CR) values greater than the acceptable value of 0.7, demonstrating that the scales of this study have passed the reliability test requirements (Hair et al., 2019 ). All latent variables in this study have Average Variance Extracted (AVE) values greater than the standard acceptance value of 0.5, indicating that the convergent validity of the variables also meets the standard (Fornell & Larcker, 1981 ). Furthermore, the results show that the Variance Inflation Factor (VIF) values for each factor are below 10, indicating that there are no multicollinearity issues with the scales in this study (Hair, 2009 ).

The current study then further verified the discriminant validity of the variables, with specific results shown in Table 4 . The square roots of the average variance extracted (AVE) values for all variables (bolded on the diagonal) are greater than the Pearson correlation coefficients between the variables, indicating that the discriminant validity of the scales in this study meets the required standards (Fornell & Larcker, 1981 ). Additionally, a single-factor test method was employed to examine common method bias in the data. The first unrotated factor accounted for 29.71% of the variance, which is less than the critical threshold of 40%. Therefore, the study passed the test and did not exhibit serious common method bias (Podsakoff et al., 2003 ).

To ensure the robustness and appropriateness of our structural equation model, we also conducted a thorough evaluation of the model fit. Initially, through PLS Algorithm calculations, the R 2 values of each variable were greater than the standard acceptance value of 0.1, indicating good predictive accuracy of the model. Subsequently, Blindfolding calculations were performed, and the results showed that the Stone-Geisser Q 2 values of each variable were greater than 0, demonstrating that the model of this study effectively predicts the relationships between variables (Dijkstra & Henseler, 2015 ). In addition, through CFA, we also obtained some indicator values, specifically, χ 2 /df = 2.528 < 0.3, RMSEA = 0.059 < 0.06, SRMR = 0.055 < 0.08. Given its sensitivity to sample size, we primarily focused on the CFI, TLI, and NFI values, CFI = 0.953 > 0.9, TLI = 0.942 > 0.9, and NFI = 0.923 > 0.9 indicating a good fit. Additionally, RMSEA values below 0.06 and SRMR values below 0.08 were considered indicative of a good model fit. These indices collectively suggested that our model demonstrates a satisfactory fit with the data, thereby reinforcing the validity of our findings.

Research hypothesis testing

The current study employed a Bootstrapping test with a sample size of 5000 on the collected raw data to explore the coefficients and significance of the paths in the research model. The final test data results of this study’s model are presented in Table 5 .

The current study employs S-O-R model as the framework, grounded in theories such as self-determination theory and theory of planned behavior, to construct an influence model of consumer engagement behavior in the context of social media influencer marketing. It examines how influencer factors, advertisement information factors, and social influence factors affect consumer engagement behavior by impacting consumers’ psychological cognitions. Using structural equation modeling to analyze collected data ( N  = 522), it was found that self-disclosure willingness, innovativeness, and information trust positively influence consumer engagement behavior, with innovativeness having the largest impact on higher levels of engagement. Influencer factors, advertisement information factors, and social factors serve as effective external stimuli, influencing psychological motivators and, consequently, consumer engagement behavior. The specific research results are illustrated in Fig. 2 .

figure 2

Tested structural model of consumer engagement behavior.

The impact of psychological motivators on different levels of consumer engagement: self-disclosure willingness, innovativeness, and information trust

The research analysis indicates that self-disclosure willingness and information trust are key drivers for content consumption (H1a, H2a validated). This aligns with previous findings that individuals with a higher willingness to disclose themselves show greater levels of engagement behavior (Chu et al., 2023 ); likewise, individuals who trust advertisement information are more inclined to engage with advertisement content (Kim, Kim, 2021 ). Moreover, our study finds that information trust has a stronger impact on content consumption, underscoring the importance of trust in the dissemination of advertisement information. However, no significant association was found between individual innovativeness and content consumption (H3a not validated).

Regarding the dimension of content contribution in consumer engagement, self-disclosure willingness, information trust, and innovativeness all positively impact it (H1b, H2b, and H3b all validated). This is consistent with earlier research findings that individuals with higher self-disclosure willingness are more likely to like, comment on, or share content posted by influencers on social media platforms (Towner et al., 2022 ); the conclusions of this paper also support that innovativeness is an important psychological driver for active participation in social media interactions (Kamboj & Sharma, 2023 ). However, at the level of consumer engagement in content contribution, while information trust also exerts a positive effect, its impact is the weakest, although information trust has the strongest impact on content consumption.

In social media advertising, the ideal outcome is the highest level of consumer engagement, i.e., content creation, meaning consumers actively join in brand content creation, seeing themselves as co-creators with the brand (Nadeem et al., 2021 ). Our findings reveal that self-disclosure willingness, innovativeness, and information trust all positively influence content creation (H1c, H2c, and H3c all validated). The analysis found that similar to the impact on content contribution, innovativeness has the most significant effect on encouraging individual content creation, followed by self-disclosure willingness, with information trust having the least impact.

In summary, while some previous studies have shown that self-disclosure willingness, innovativeness, and information trust are important factors in promoting consumer engagement (Chu et al., 2023 ; Nadeem et al., 2021 ; Geng et al., 2021 ), this study goes further by integrating and comparing all three within the same research framework. It was found that to trigger higher levels of consumer engagement behavior, trust is not the most crucial psychological motivator; rather, the most effective method is to stimulate consumers’ innovativeness, thus complementing previous research. Subsequently, this study further explores the impact of different stimulus factors on various psychological motivators.

The influence of external stimulus factors on psychological motivators: influencer factors, advertisement information factors, and social factors

The current findings indicate that influencer factors, such as parasocial identification and source credibility, effectively enhance consumer engagement by influencing self-disclosure willingness and information trust. This aligns with prior research highlighting the significance of parasocial identification (Shan et al., 2020 ). Studies suggest parasocial identification positively impacts consumer engagement by boosting self-disclosure willingness and information trust (validated H4a, H4b, H4c, and H5a), but not content contribution or creation through information trust (H5b, H5c not validated). Source credibility’s influence on self-disclosure willingness was not significant (H6 not validated), thus negating the mediating effect of self-disclosure willingness (H6a, H6b, H6c not validated). Influencer credibility mainly affects engagement through information trust (H7a, H7b, H7c validated), supporting previous findings (Shan et al., 2020 ).

Advertisement factors (informative value and ad targeting accuracy) promote engagement through innovativeness and information trust. Informative value significantly impacts higher-level content contribution and creation through innovativeness (H8b, H8c validated), while ad targeting accuracy influences consumer engagement at all levels mainly through information trust (H10a, H10b, H10c validated).

Social factors (subjective norms) enhance self-disclosure willingness and information trust, consistent with previous research (Wirth et al., 2019 ; Gupta et al., 2021 ), and further promote consumer engagement across all levels (H11a, H11b, H11c, H12a, H12b, and H12c all validated).

In summary, influencer, advertisement, and social factors impact consumer engagement behavior by influencing psychological motivators, with influencer factors having the greatest effect on content consumption, advertisement content factors significantly raising higher-level consumer engagement through innovativeness, and social factors also influencing engagement through self-disclosure willingness and information trust.

Implication

From a theoretical perspective, current research presents a comprehensive model of consumer engagement within the context of influencer advertising on social media. This model not only expands the research horizon in the fields of social media influencer advertising and consumer engagement but also serves as a bridge between two crucial themes in new media advertising studies. Influencer advertising has become an integral part of social media advertising, and the construction of a macro model aids researchers in understanding consumer psychological processes and behavioral patterns. It also assists advertisers in formulating more effective strategies. Consumer engagement, focusing on the active role of consumers in disseminating information and the long-term impact on advertising effectiveness, aligns more closely with the advertising effectiveness measures in the new media context than traditional advertising metrics. However, the intersection of these two vital themes lacks comprehensive research and a universal model. This study constructs a model that elucidates the effects of various stimuli on consumer psychology and engagement behaviors, exploring the connections and mechanisms through different mediating pathways. By differentiating levels of engagement, the study offers more nuanced conclusions for diverse advertising objectives. Furthermore, this research validates the applicability of self-determination theory in the context of influencer advertising effectiveness. While this psychological theory has been utilized in communication behavior research, its effectiveness in the field of advertising requires further exploration. The current study introduces self-determination theory into the realm of influencer advertising and consumer engagement, thereby expanding its application in the field of advertising communication. It also responds to the call from the advertising and marketing academic community to incorporate more psychological theories to explain the ‘black box’ of consumer psychology. The inclusion of this theory re-emphasizes the people-centric approach of this research and highlights the primary role of individuals in advertising communication studies.

From a practical perspective, this study provides significant insights for adapting marketing strategies to the evolving media landscape and the empowered role of audiences. Firstly, in the face of changes in the communication environment and the empowerment of audience communication capabilities, traditional marketing approaches are becoming inadequate for new media advertising needs. Traditional advertising focuses on direct, point-to-point effects, whereas social media advertising aims for broader, point-to-mass communication, leveraging audience proactivity to facilitate the viral spread of content across online social networks. Secondly, for brands, the general influence model proposed in this study offers guidance for influencer advertising strategy. If the goal is to maximize reach and brand recognition with a substantial advertising budget, partnering with top influencers who have a large following can be an effective strategy. However, if the objective is to maximize cost-effectiveness with a limited budget by leveraging consumer initiative for secondary spread, the focus should be on designing advertising content that stimulates consumer creativity and willingness to innovate. Thirdly, influencers are advised to remain true to their followers. In influencer marketing, influencers attract advertisers through their influence over followers, converting this influence into commercial gain. This influence stems from the trust followers place in the influencer, thus influencers should maintain professional integrity and prioritize the quality of information they share, even when presented with advertising opportunities. Lastly, influencers should assert more control over their relationships with advertisers. In traditional advertising, companies and brands often exert significant control over the content. However, in the social media era, influencers should negotiate more creative freedom in their advertising partnerships, asserting a more equal relationship with advertisers. This approach ensures that content quality remains high, maintaining the trust influencers have built with their followers.

Limitations and future directions

while this study offers valuable insights into the dynamics of influencer marketing and consumer engagement on social media, several limitations should be acknowledged: Firstly, constrained by the research objectives and scope, this study’s proposed general impact model covers three dimensions: influencers, advertisement information, and social factors. However, these dimensions are not limited to the five variables discussed in this paper. Therefore, we call for future research to supplement and explore more crucial factors. Secondly, in the actual communication environment, there may be differences in the impact of communication effectiveness across various social media platforms. Thus, future research could also involve comparative studies and explorations between different social media platforms. Thirdly, the current study primarily examines the direct effects of various factors on consumer engagement. However, the potential interaction effects between these variables (e.g., how influencers’ credibility might interact with advertisement information quality) are not extensively explored. Future research could investigate these complex interrelationships for a more holistic understanding. Lastly, our study, being cross-sectional, offers preliminary insights into the complex and dynamic nature of engagement between social media influencers and consumers, yet it does not incorporate the temporal dimension. The diverse impacts of psychological needs on engagement behaviors hint at an underlying dynamism that merits further investigation. Future research should consider employing longitudinal designs to directly observe how these dynamics evolve over time.

The findings of the current study not only theoretically validate the applicability of self-determination theory in the field of social media influencer marketing advertising research but also broaden the scope of advertising effectiveness research from the perspective of consumer engagement. Moreover, the research framework offers strategic guidance and reference for influencer marketing strategies. The main conclusions of this study can be summarized as follows.

Innovativeness is the key factor in high-level consumer engagement behavior. Content contribution represents a higher level of consumer engagement compared to content consumption, as it not only requires consumers to dedicate attention to viewing advertising content but also to share this information across adjacent nodes within their social networks. This dissemination of information is a pivotal factor in the success of influencer marketing advertisements. Hence, companies and brands prioritize consumers’ content contribution over mere viewing of advertising content (Qiu & Kumar, 2017 ). Compared to content consumption and contribution, content creation is considered the highest level of consumer engagement, where consumers actively create and upload brand-related content, and it represents the most advanced outcome sought by enterprises and brands in advertising campaigns (Cheung et al., 2021 ). The current study posits that to pursue better outcomes in social media influencer advertising marketing, enhancing consumers’ willingness for self-disclosure, innovativeness, and trust in advertising information are effective strategies. However, the crux lies in leveraging the consumer’s subjective initiative, particularly in boosting their innovativeness. If the goal is simply to achieve content consumption rather than higher levels of consumer engagement, the focus should be on fostering trust in advertising information. There is no hierarchy in the efficacy of different strategies; they should align with varying marketing contexts and advertising objectives.

The greatest role of social media influencers lies in attracting online traffic. information trust is the core element driving content consumption, and influencer factors mainly affect consumer engagement behaviors through information trust. Therefore, this study suggests that the primary role of influencers in social media advertising is to attract online traffic, i.e., increase consumer behavior regarding ad content consumption (reducing avoidance of ad content), and help brands achieve the initial goal of making consumers “see and complete ads.” However, their impact on further high-level consumer engagement behaviors is limited. This mechanism serves as a reminder to advertisers not to overestimate the effects of influencers in marketing. Currently, top influencers command a significant portion of the ad budget, which could squeeze the budget for other aspects of advertising, potentially affecting the overall effectiveness of the campaign. Businesses and brands should consider deeper strategic implications when planning their advertising campaigns.

Valuing Advertising Information Factors, Content Remains King. Our study posits that in the social media influencer marketing context, the key to enhancing consumer contribution and creation of advertising content lies primarily in the advertising information factors. In other words, while content consumption is important, advertisers should objectively assess the role influencers play in advertising. In the era of social media, content remains ‘king’ in advertising. This view indirectly echoes the points made in the previous paragraph: influencers effectively perform initial ‘online traffic generation’ tasks in social media, but this role should not be overly romanticized or exaggerated. Whether it’s companies, brands, or influencers, providing consumers with advertisements rich in informational value is crucial to achieving better advertising outcomes and potentially converting consumers into stakeholders.

Subjective norm is an unignorable social influence factor. Social media is characterized by its network structure of information dissemination, where a node’s information is visible to adjacent nodes. For instance, if user A likes a piece of content C from influencer I, A’s follower B, who may not follow influencer I, can still see content C via user A’s page. The aim of marketing in the social media era is to influence a node and then spread the information to adjacent nodes, either secondarily or multiple times (Kumar & Panda, 2020 ). According to the Theory of Planned Behavior, an individual’s actions are influenced by significant others in their lives, such as family and friends. Previous studies have proven the effectiveness of the Theory of Planned Behavior in influencing attitudes toward social media advertising (Ranjbarian et al., 2012 ). Current research further confirms that subjective norms also influence consumer engagement behaviors in influencer marketing on social media. Therefore, in advertising practice, brands should not only focus on individual consumers but also invest efforts in groups that can influence consumer decisions. Changing consumer behavior in the era of social media marketing doesn’t solely rely on the company’s efforts.

As communication technology advances, media platforms will further empower individual communicative capabilities, moving beyond the era of the “magic bullet” theory. The distinction between being a recipient and a transmitter of information is increasingly blurred. In an era where everyone is both an audience and an influencer, research confined to the role of the ‘recipient’ falls short of addressing the dynamics of ‘transmission’. Future research in marketing and advertising should thus focus more on the power of individual transmission. Furthermore, as Marshall McLuhan famously said, “the medium is the extension of man.” The evolution of media technology remains human-centric. Accordingly, future marketing research, while paying heed to media transformations, should emphasize the centrality of the ‘human’ element.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to privacy issues. Making the full data set publicly available could potentially breach the privacy that was promised to participants when they agreed to take part, and may breach the ethics approval for the study. The data are available from the corresponding author on reasonable request.

Abbasi AZ, Tsiotsou RH, Hussain K, Rather RA, Ting DH (2023) Investigating the impact of social media images’ value, consumer engagement, and involvement on eWOM of a tourism destination: a transmittal mediation approach. J Retail Consum Serv 71:103231. https://doi.org/10.1016/j.jretconser.2022.103231

Article   Google Scholar  

Ajzen I (2002) Perceived behavioral control, self‐efficacy, locus of control, and the theory of planned behavior 1. J Appl Soc Psychol 32(4):665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x

Ajzen I (1991) The theory of planned behavior. Organ Behav Hum Decis Process 50(2):179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Altman I, Taylor DA (1973) Social penetration: the development of interpersonal relationships. Holt, Rinehart & Winston

Anaya-Sánchez R, Aguilar-Illescas R, Molinillo S, Martínez-López FJ (2020) Trust and loyalty in online brand communities. Span J Mark ESIC 24(2):177–191. https://doi.org/10.1108/SJME-01-2020-0004

Astuti BA, Hariyawan A (2021) Perspectives of social capital and self-determination on e-WOM at millennial generation in Yogyakarta. Integr J Bus Econ 5(1):399475. https://doi.org/10.33019/ijbe.v5i1.338

Bao Z, Wang D (2021) Examining consumer participation on brand microblogs in China: perspectives from elaboration likelihood model, commitment–trust theory and social presence. J Res Interact Mark 15(1):10–29. https://doi.org/10.1108/JRIM-02-2019-0027

Barta S, Belanche D, Fernández A, Flavián M (2023) Influencer marketing on TikTok: the effectiveness of humor and followers’ hedonic experience. J Retail Consum Serv 70:103149. https://doi.org/10.1016/j.jretconser.2022.103149

Bond BJ (2016) Following your “friend”: social media and the strength of adolescents’ parasocial relationships with media personae. Cyberpsych Behav Soc Netw 19(11):656–660. https://doi.org/10.1089/cyber.2016.0355

Breves P, Amrehn J, Heidenreich A, Liebers N, Schramm H (2021) Blind trust? The importance and interplay of parasocial relationships and advertising disclosures in explaining influencers’ persuasive effects on their followers. Int J Advert 40(7):1209–1229. https://doi.org/10.1080/02650487.2021.1881237

Brodie RJ, Ilic A, Juric B, Hollebeek L (2013) Consumer engagement in a virtual brand community: an exploratory analysis. J Bus Res 66(1):105–114. https://doi.org/10.1016/j.jbusres.2011.07.029

Buzeta C, De Pelsmacker P, Dens N (2020) Motivations to use different social media types and their impact on consumers’ online brand-related activities (COBRAs). J Interact Mark 52(1):79–98. https://doi.org/10.1016/j.intmar.2020.04.0

Chen KJ, Lin JS, Shan Y (2021) Influencer marketing in China: The roles of parasocial identification, consumer engagement, and inferences of manipulative intent. J Consum Behav 20(6):1436–1448. https://doi.org/10.1002/cb.1945

Chetioui Y, Benlafqih H, Lebdaoui H (2020) How fashion influencers contribute to consumers’ purchase intention. J Fash Mark Manag 24(3):361–380. https://doi.org/10.1108/JFMM-08-2019-0157

Cheung ML, Pires GD, Rosenberger III PJ, De Oliveira MJ (2021) Driving COBRAs: the power of social media marketing. Mark Intell Plan 39(3):361–376. https://doi.org/10.1108/MIP-11-2019-0583

Cheung MY, Luo C, Sia CL, Chen H (2009) Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. Int J Electron Comm 13(4):9–38. https://doi.org/10.2753/JEC1086-4415130402

Chung S, Cho H (2017) Fostering parasocial relationships with celebrities on social media: Implications for celebrity endorsement. Psychol Mark 34(4):481–495. https://doi.org/10.1002/mar.21001

Chu SC, Choi SM (2011) Electronic word-of-mouth in social networking sites: a cross-cultural study of the United States and China. J Glob Mark 24(3):263–281. https://doi.org/10.1080/08911762.2011.592461

Chu SC, Kim Y (2011) Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. Int J Advert 30(1):47–75. https://doi.org/10.2501/IJA-30-1-047-075

Chu TH, Sun M, Crystal Jiang L (2023) Self-disclosure in social media and psychologicalwell-being: a meta-analysis. J Soc Pers Relat 40(2):576–599. https://doi.org/10.1177/02654075221119429

Cropanzano R, Mitchell MS (2005) Social exchange theory: an interdisciplinary review. J Manag 31(6):874–900. https://doi.org/10.1177/0149206305279602

Della Vigna S, Gentzkow M (2010) Persuasion: empirical evidence. Annu Rev Econ 2(1):643–669. https://doi.org/10.1146/annurev.economics.102308.124309

Dijkstra TK, Henseler J (2015) Consistent and asymptotically normal PLS estimators for linear structural equations. Comput Stat Data 81:10–23. https://doi.org/10.1016/j.csda.2014.07.008

Article   MathSciNet   Google Scholar  

Djafarova E, Rushworth C (2017) Exploring the credibility of online celebrities’ Instagram profiles in influencing the purchase decisions of young female users. Comput Hum Behav 68:1–7. https://doi.org/10.1016/j.chb.2016.11.009

D Horton D, Richard Wohl R (1956) Mass communication and para-social interaction: Observations on intimacy at a distance. Psychiatry 19(3):215–229. https://doi.org/10.1080/00332747.1956.11023049

Ducoffe RH (1995) How consumers assess the value of advertising. J Curr Issues Res Adver 17(1):1–18. https://doi.org/10.1080/10641734.1995.10505022

Fornell C, Larcker DF (1981) Structural equation models with unobservable variables and measurement error: Algebra and statistics. J Mark Res 18(3):382–388. https://doi.org/10.1177/002224378101800313

Gefen D, Straub DW, Rigdon EE (2011) An update and extension to SEM guidelines for administrative and social science research. Mis Quart 35(2):iii–xiv. https://doi.org/10.2307/23044042

Geng S, Yang P, Gao Y, Tan Y, Yang C (2021) The effects of ad social and personal relevance on consumer ad engagement on social media: the moderating role of platform trust. Comput Hum Behav 122:106834. https://doi.org/10.1016/j.chb.2021.106834

Giles DC (2002) Parasocial interaction: a review of the literature and a model for future research. Media Psychol 4(3):279–305. https://doi.org/10.1207/S1532785XMEP0403_04

Gräve JF, Bartsch F (2022) # Instafame: exploring the endorsement effectiveness of influencers compared to celebrities. Int J Advert 41(4):591–622. https://doi.org/10.1080/02650487.2021.1987041

Gupta R, Ranjan S, Gupta A (2021) Consumer’s perceived trust and subjective norms as antecedents of mobile wallets adoption and continuance intention: a technology acceptance approach. Recent Adv Technol Accept Models Theor 211–224. https://doi.org/10.1007/978-3-030-64987-6_13

Habibi MR, Laroche M, Richard MO (2014) The roles of brand community and community engagement in building brand trust on social media. Comput Hum Behav 37:152–161. https://doi.org/10.1016/j.chb.2014.04.016

Hagger MS, Chatzisarantis NL (2009) Integrating the theory of planned behaviour and self‐determination theory in health behaviour: a meta‐analysis. Brit J Health Psych 14(2):275–302. https://doi.org/10.1348/135910708X373959

Haida A, Rahim HL (2015) Social media advertising value: A Study on consumer’s perception. Int Acad Res J Bus Technol 1(1):1–8. https://www.researchgate.net/publication/280325676_Social_Media_Advertising_Value_A_Study_on_Consumer%27s_Perception

Google Scholar  

Hair JF (2009) Multivariate data analysis. Prentice Hall, Upper Saddle River

Hair JF, Ringle CM, Gudergan SP, Fischer A, Nitzl C, Menictas C (2019) Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice. Bus Res 12(1):115–142. https://doi.org/10.1007/s40685-018-0072-4

Hair JF, Sarstedt M, Ringle CM, Mena JA (2012) An assessment of the use of partial least squares structural equation modeling in marketing research. Acad Mark Sci 40:414–433. https://doi.org/10.1007/s11747-011-0261-6

Heirman W, Walrave M, Ponnet K (2013) Predicting adolescents’ disclosure of personal information in exchange for commercial incentives: An application of an extended theory of planned behavior. Cyberpsych Behav Soc Netw16(2):81–87. https://doi.org/10.1089/cyber.2012.0041

Hewei T, Youngsook L (2022) Factors affecting continuous purchase intention of fashion products on social E-commerce: SOR model and the mediating effect. Entertain Comput 41:100474. https://doi.org/10.1016/j.entcom.2021.100474

Hovland CI, Janis IL, Kelley HH (1953) Communication and persuasion. Yale University Press

Hsieh JK, Li YJ (2020) Will you ever trust the review website again? The importance of source credibility. Int J Electron Commerce 24(2):255–275. https://doi.org/10.1080/10864415.2020.1715528

Huang YC (2023) Integrated concepts of the UTAUT and TPB in virtual reality behavioral intention. J Retail Consum Serv 70:103127. https://doi.org/10.1016/j.jretconser.2022.103127

Hudders L, Lou C (2023) The rosy world of influencer marketing? Its bright and dark sides, and future research recommendations. Int J Advert 42(1):151–161. https://doi.org/10.1080/02650487.2022.2137318

Itani OS, Kalra A, Riley J (2022) Complementary effects of CRM and social media on customer co-creation and sales performance in B2B firms: The role of salesperson self-determination needs. Inf Manag 59(3):103621. https://doi.org/10.1016/j.im.2022.103621

Jang W, Kim J, Kim S, Chun JW (2021) The role of engagement in travel influencer marketing: the perspectives of dual process theory and the source credibility model. Curr Issues Tour 24(17):2416–2420. https://doi.org/10.1080/13683500.2020.1845126

Jin SV, Ryu E, Muqaddam A (2021) I trust what she’s# endorsing on Instagram: moderating effects of parasocial interaction and social presence in fashion influencer marketing. J Fash Mark Manag 25(4):665–681. https://doi.org/10.1108/JFMM-04-2020-0059

Kamboj S, Sharma M (2023) Social media adoption behaviour: consumer innovativeness and participation intention. Int J Consum Stud 47(2):523–544. https://doi.org/10.1111/ijcs.12848

Kaushik AK, Rahman Z (2014) Perspectives and dimensions of consumer innovativeness: a literature review and future agenda. J Int Consum Mark 26(3):239–263. https://doi.org/10.1080/08961530.2014.893150

Kelley JB, Alden DL (2016) Online brand community: through the eyes of self-determination theory. Internet Res 26(4):790–808. https://doi.org/10.1108/IntR-01-2015-0017

K Kim DY, Kim HY (2021) Trust me, trust me not: A nuanced view of influencer marketing on social media. J Bus Res 134:223–232. https://doi.org/10.1016/j.jbusres.2021.05.024

Koay KY, Ong DLT, Khoo KL, Yeoh HJ (2020) Perceived social media marketing activities and consumer-based brand equity: Testing a moderated mediation model. Asia Pac J Mark Logist 33(1):53–72. https://doi.org/10.1108/APJML-07-2019-0453

Kumar S, Panda BS (2020) Identifying influential nodes in Social Networks: Neighborhood Coreness based voting approach. Phys A: Stat Mech Appl 553:124215. https://doi.org/10.1016/j.physa.2020.124215

Lee D, Hosanagar K, Nair HS (2018) Advertising content and consumer engagement on social media: evidence from Facebook. Manag Sci 64(11):5105–5131. https://doi.org/10.1287/mnsc.2017.2902

Lee DH, Im S, Taylor CR (2008) Voluntary self‐disclosure of information on the Internet: a multimethod study of the motivations and consequences of disclosing information on blogs. Psychol Mark 25(7):692–710. https://doi.org/10.1002/mar.20232

Lee J, Rajtmajer S, Srivatsavaya E, Wilson S (2023) Online self-disclosure, social support, and user engagement during the COVID-19 pandemic. ACM Trans Soc Comput 6(3-4):1–31. https://doi.org/10.1145/3617654

Lee Y, Lee J, Hwang Y (2015) Relating motivation to information and communication technology acceptance: self-determination theory perspective. Comput Hum Behav 51:418–428. https://doi.org/10.1016/j.chb.2015.05.021

Leite FP, Baptista PDP (2022) The effects of social media influencers’ self-disclosure on behavioral intentions: The role of source credibility, parasocial relationships, and brand trust. J Mark Theory Pr 30(3):295–311. https://doi.org/10.1080/10696679.2021.1935275

Leite FP, Pontes N, de Paula Baptista P (2022) Oops, I’ve overshared! When social media influencers’ self-disclosure damage perceptions of source credibility. Comput Hum Behav 133:107274. https://doi.org/10.1016/j.chb.2022.107274

León SP, Abad MJ, Rosas JM (2009) Giving contexts informative value makes information context-specific. Exp Psychol. https://doi.org/10.1027/1618-3169/a000006

Lou C, Tan SS, Chen X (2019) Investigating consumer engagement with influencer-vs. brand-promoted ads: The roles of source and disclosure. J Interact Advert 19(3):169–186. https://doi.org/10.1080/15252019.2019.1667928

Lou C, Yuan S (2019) Influencer marketing: how message value and credibility affect consumer trust of branded content on social media. J Interact Advert 19(1):58–73. https://doi.org/10.1080/15252019.2018.1533501

Luo M, Hancock JT (2020) Self-disclosure and social media: motivations, mechanisms and psychological well-being. Curr Opin Psychol 31:110–115. https://doi.org/10.1016/j.copsyc.2019.08.019

Article   PubMed   Google Scholar  

Mahmood S, Khwaja MG, Jusoh A (2019) Electronic word of mouth on social media websites: role of social capital theory, self-determination theory, and altruism. Int J Space-Based Situat Comput 9(2):74–89. https://doi.org/10.1504/IJSSC.2019.104217

Majerczak P, Strzelecki A (2022) Trust, media credibility, social ties, and the intention to share towards information verification in an age of fake news. Behav Sci 12(2):51. https://doi.org/10.3390/bs12020051

Article   PubMed   PubMed Central   Google Scholar  

McAllister DJ (1995) Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations. Acad Manag J 38(1):24–59. https://doi.org/10.5465/256727

Mehrabian A, Russell JA (1974). An approach to environmental psychology. The MIT Press

Minton EA (2015) In advertising we trust: Religiosity’s influence on marketplace and relational trust. J Advert 44(4):403–414. https://doi.org/10.1080/00913367.2015.1033572

Moorman C, Deshpande R, Zaltman G (1993) Factors affecting trust in market research relationships. J Mark 57(1):81–101. https://doi.org/10.1177/002224299305700106

Muntinga DG, Moorman M, Smit EG (2011) Introducing COBRAs: Exploring motivations for brand-related social media use. Int J Advert 30(1):13–46. https://doi.org/10.2501/IJA-30-1-013-046

Nadeem W, Tan TM, Tajvidi M, Hajli N (2021) How do experiences enhance brand relationship performance and value co-creation in social commerce? The role of consumer engagement and self brand-connection. Technol Forecast Soc 171:120952. https://doi.org/10.1016/j.techfore.2021.120952

Oestreicher-Singer G, Zalmanson L (2013) Content or community? A digital business strategy for content providers in the social age. MIS Quart 37(2):591–616. https://www.jstor.org/stable/43825924

Okazaki S (2009) Social influence model and electronic word of mouth: PC versus mobile internet. Int J Advert 28(3):439–472. https://doi.org/10.2501/S0265048709200692

Piehler R, Schade M, Kleine-Kalmer B, Burmann C (2019) Consumers’ online brand-related activities (COBRAs) on SNS brand pages: an investigation of consuming, contributing and creating behaviours of SNS brand page followers. Eur J Mark 53(9):1833–1853. https://doi.org/10.1108/EJM-10-2017-0722

Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879. https://doi.org/10.1037/0021-9010.88.5.879

Pop RA, Săplăcan Z, Dabija DC, Alt MA (2022) The impact of social media influencers on travel decisions: The role of trust in consumer decision journey. Curr Issues Tour 25(5):823–843. https://doi.org/10.1080/13683500.2021.1895729

Pradhan B, Kishore K, Gokhale N (2023) Social media influencers and consumer engagement: a review and future research agenda. Int J Consum Stud 47(6):2106–2130. https://doi.org/10.1111/ijcs.12901

Qiu A, Chen M (2018) 基于UTAUT修正模型的微信朋友圈广告接受意愿分析 [Analysis of WeChat moments advertising acceptance intention based on a modified UTAUT model]. Stat Decis 34(12):99–102. https://doi.org/10.13546/j.cnki.tjyjc.2018.12.024

Qiu L, Kumar S (2017) Understanding voluntary knowledge provision and content contribution through a social-media-based prediction market: a field experiment. Inf Syst Res 28(3):529–546. https://doi.org/10.1287/isre.2016.0679

Racherla P, Mandviwalla M, Connolly DJ (2012) Factors affecting consumers’ trust in online product reviews. J Consum Behav 11(2):94–104. https://doi.org/10.1002/cb.385

Ranjbarian B, Gharibpoor M, Lari A (2012) Attitude toward SMS advertising and derived behavioral intension, an empirical study using TPB (SEM method). J Am Sci 8(7):297–307. https://www.ceeol.com/search/article-detail?id=466212

Robertshaw GS, Marr NE (2006) The implications of incomplete and spurious personal information disclosures for direct marketing practice. J Database Mark Custom Strategy Manag. 13:186–197. https://doi.org/10.1057/palgrave.dbm.3240296

Roh T, Seok J, Kim Y (2022) Unveiling ways to reach organic purchase: Green perceived value, perceived knowledge, attitude, subjective norm, and trust. J Retail Consum Serv 67:102988. https://doi.org/10.1016/j.jretconser.2022.102988

Schivinski B, Christodoulides G, Dabrowski D (2016) Measuring consumers’ engagement with brand-related social-media content: Development and validation of a scale that identifies levels of social-media engagement with brands. J Advert Res 56(1):64–80. https://doi.org/10.2501/JAR-2016-004

Schouten AP, Janssen L, Verspaget M (2021) Celebrity vs. Influencer endorsements in advertising: the role of identification, credibility, and product-endorser fit. Leveraged marketing communications, Routledge. pp. 208–231

Schramm H, Hartmann T (2008) The PSI-Process Scales. A new measure to assess the intensity and breadth of parasocial processes. Communications. https://doi.org/10.1515/COMM.2008.025

Shan Y, Chen KJ, Lin JS (2020) When social media influencers endorse brands: the effects of self-influencer congruence, parasocial identification, and perceived endorser motive. Int J Advert 39(5):590–610. https://doi.org/10.1080/02650487.2019.1678322

Shi Y (2018) The impact of consumer innovativeness on the intention of clicking on SNS advertising. Mod Econ 9(2):278–285. https://doi.org/10.4236/me.2018.92018

Article   CAS   Google Scholar  

Simon F, Tossan V (2018) Does brand-consumer social sharing matter? A relational framework of customer engagement to brand-hosted social media. J Bus Res 85:175–184. https://doi.org/10.1016/j.jbusres.2017.12.050

Steinhoff L, Arli D, Weaven S, Kozlenkova IV (2019) Online relationship marketing. J Acad Mark Sci 47:369–393. https://doi.org/10.1007/s11747-018-0621-6

Stutzman F, Capra R, Thompson J (2011) Factors mediating disclosure in social network sites. Comput Hum Behav 27(1):590–598. https://doi.org/10.1016/j.chb.2010.10.017

Sun T, Youn S, Wu G, Kuntaraporn M (2006) Online word-of-mouth (or mouse): An exploration of its antecedents and consequences. J Comput-Mediat Comm 11(4):1104–1127. https://doi.org/10.1111/j.1083-6101.2006.00310.x

Sweet KS, LeBlanc JK, Stough LM, Sweany NW (2020) Community building and knowledge sharing by individuals with disabilities using social media. J Comput Assist Lear 36(1):1–11. https://doi.org/10.1111/jcal.12377

Tak P, Gupta M (2021) Examining travel mobile app attributes and its impact on consumer engagement: An application of SOR framework. J Internet Commer 20(3):293–318. https://doi.org/10.1080/15332861.2021.1891517

Towner E, Grint J, Levy T, Blakemore SJ, Tomova L (2022) Revealing the self in a digital world: a systematic review of adolescent online and offline self-disclosure. Curr Opin Psychol 45:101309. https://doi.org/10.1016/j.copsyc.2022.101309

Vander Schee BA, Peltier J, Dahl AJ (2020) Antecedent consumer factors, consequential branding outcomes and measures of online consumer engagement: current research and future directions. J Res Interact Mark 14(2):239–268. https://doi.org/10.1108/JRIM-01-2020-0010

Van-Tien Dao W, Nhat Hanh Le A, Ming-Sung Cheng J, Chao Chen D (2014) Social media advertising value: The case of transitional economies in Southeast Asia. Int J Advert 33(2):271–294. https://doi.org/10.2501/IJA-33-2-271-294

Viswanathan V, Hollebeek LD, Malthouse EC, Maslowska E, Jung Kim S, Xie W (2017) The dynamics of consumer engagement with mobile technologies. Serv Sci 9(1):36–49. https://doi.org/10.1287/serv.2016.0161

Voss KE, Spangenberg ER, Grohmann B (2003) Measuring the hedonic and utilitarian dimensions of consumer attitude. J Mark Res 40(3):310–320. https://doi.org/10.1509/jmkr.40.3.310.19238

Vrontis D, Makrides A, Christofi M, Thrassou A (2021) Social media influencer marketing: A systematic review, integrative framework and future research agenda. Int J Consum Stud 45(4):617–644. https://doi.org/10.1111/ijcs.12647

Wang T, Yeh RKJ, Chen C, Tsydypov Z (2016) What drives electronic word-of-mouth on social networking sites? Perspectives of social capital and self-determination. Telemat Inf 33(4):1034–1047. https://doi.org/10.1016/j.tele.2016.03.005

Watson JB (1917) An Attempted formulation of the scope of behavior psychology. Psychol Rev 24(5):329. https://doi.org/10.1037/h0073044

Wehmeyer ML (1999) A functional model of self-determination: Describing development and implementing instruction. Focus Autism Dev Dis 14(1):53–61. https://www.imdetermined.org/wp-content/uploads/2018/06/SD5_A-Functional-Model-of.pdf

Wei X, Chen H, Ramirez A, Jeon Y, Sun Y (2022) Influencers as endorsers and followers as consumers: exploring the role of parasocial relationship, congruence, and followers’ identifications on consumer–brand engagement. J Interact Advert 22(3):269–288. https://doi.org/10.1080/15252019.2022.2116963

Wirth J, Maier C, Laumer S (2019) Subjective norm and the privacy calculus: explaining self-disclosure on social networking sites. Paper presented at the 27th European Conference on Information Systems (ECIS). Stockholm & Uppsala, Sweden, 8–14, June 2019 https://aisel.aisnet.org/ecis2019_rp

Xiao L, Li X, Zhang Y (2023) Exploring the factors influencing consumer engagement behavior regarding short-form video advertising: a big data perspective. J Retail Consum Serv 70:103170. https://doi.org/10.1016/j.jretconser.2022.103170

Yang J, Peng MYP, Wong S, Chong W (2021) How E-learning environmental stimuli influence determinates of learning engagement in the context of COVID-19? SOR model perspective. Front Psychol 12:584976. https://doi.org/10.3389/fpsyg.2021.584976

Yang K, Jolly LD (2009) The effects of consumer perceived value and subjective norm on mobile data service adoption between American and Korean consumers. J Retail Consum Serv 16(6):502–508. https://doi.org/10.1016/j.jretconser.2009.08.005

Yang S, Zhou S, Cheng X (2019) Why do college students continue to use mobile learning? Learning involvement and self‐determination theory. Brit J Educ Technol 50(2):626–637. https://doi.org/10.1111/bjet.12634

Yusuf AS, Busalim AH (2018) Influence of e-WOM engagement on consumer purchase intention in social commerce. J Serv Mark 32(4):493–504. https://doi.org/10.1108/JSM-01-2017-0031

Zhang G, Yue X, Ye Y, Peng MYP (2021) Understanding the impact of the psychological cognitive process on student learning satisfaction: combination of the social cognitive career theory and SOR model. Front Psychol 12:712323. https://doi.org/10.3389/fpsyg.2021.712323

Zhang J, Liu J, Zhong W (2019) 广告精准度与广告效果:基于隐私关注的现场实验 [Ad targeting accuracy and advertising effectiveness: a field experiment based on privacy concerns]. Manag Sci 32(06):123–132

CAS   Google Scholar  

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The authors thank all the participants of this study. The participants were all informed about the purpose and content of the study and voluntarily agreed to participate. The participants were able to stop participating at any time without penalty. Funding for this study was provided by Minjiang University Research Start-up Funds (No. 324-32404314).

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Gu, C., Duan, Q. Exploring the dynamics of consumer engagement in social media influencer marketing: from the self-determination theory perspective. Humanit Soc Sci Commun 11 , 587 (2024). https://doi.org/10.1057/s41599-024-03127-w

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The effect of social media on the development of students’ affective variables

1 Science and Technology Department, Nanjing University of Posts and Telecommunications, Nanjing, China

2 School of Marxism, Hohai University, Nanjing, Jiangsu, China

3 Government Enterprise Customer Center, China Mobile Group Jiangsu Co., Ltd., Nanjing, China

The use of social media is incomparably on the rise among students, influenced by the globalized forms of communication and the post-pandemic rush to use multiple social media platforms for education in different fields of study. Though social media has created tremendous chances for sharing ideas and emotions, the kind of social support it provides might fail to meet students’ emotional needs, or the alleged positive effects might be short-lasting. In recent years, several studies have been conducted to explore the potential effects of social media on students’ affective traits, such as stress, anxiety, depression, and so on. The present paper reviews the findings of the exemplary published works of research to shed light on the positive and negative potential effects of the massive use of social media on students’ emotional well-being. This review can be insightful for teachers who tend to take the potential psychological effects of social media for granted. They may want to know more about the actual effects of the over-reliance on and the excessive (and actually obsessive) use of social media on students’ developing certain images of self and certain emotions which are not necessarily positive. There will be implications for pre- and in-service teacher training and professional development programs and all those involved in student affairs.

Introduction

Social media has turned into an essential element of individuals’ lives including students in today’s world of communication. Its use is growing significantly more than ever before especially in the post-pandemic era, marked by a great revolution happening to the educational systems. Recent investigations of using social media show that approximately 3 billion individuals worldwide are now communicating via social media ( Iwamoto and Chun, 2020 ). This growing population of social media users is spending more and more time on social network groupings, as facts and figures show that individuals spend 2 h a day, on average, on a variety of social media applications, exchanging pictures and messages, updating status, tweeting, favoring, and commenting on many updated socially shared information ( Abbott, 2017 ).

Researchers have begun to investigate the psychological effects of using social media on students’ lives. Chukwuere and Chukwuere (2017) maintained that social media platforms can be considered the most important source of changing individuals’ mood, because when someone is passively using a social media platform seemingly with no special purpose, s/he can finally feel that his/her mood has changed as a function of the nature of content overviewed. Therefore, positive and negative moods can easily be transferred among the population using social media networks ( Chukwuere and Chukwuere, 2017 ). This may become increasingly important as students are seen to be using social media platforms more than before and social networking is becoming an integral aspect of their lives. As described by Iwamoto and Chun (2020) , when students are affected by social media posts, especially due to the increasing reliance on social media use in life, they may be encouraged to begin comparing themselves to others or develop great unrealistic expectations of themselves or others, which can have several affective consequences.

Considering the increasing influence of social media on education, the present paper aims to focus on the affective variables such as depression, stress, and anxiety, and how social media can possibly increase or decrease these emotions in student life. The exemplary works of research on this topic in recent years will be reviewed here, hoping to shed light on the positive and negative effects of these ever-growing influential platforms on the psychology of students.

Significance of the study

Though social media, as the name suggests, is expected to keep people connected, probably this social connection is only superficial, and not adequately deep and meaningful to help individuals feel emotionally attached to others. The psychological effects of social media on student life need to be studied in more depth to see whether social media really acts as a social support for students and whether students can use social media to cope with negative emotions and develop positive feelings or not. In other words, knowledge of the potential effects of the growing use of social media on students’ emotional well-being can bridge the gap between the alleged promises of social media and what it actually has to offer to students in terms of self-concept, self-respect, social role, and coping strategies (for stress, anxiety, etc.).

Exemplary general literature on psychological effects of social media

Before getting down to the effects of social media on students’ emotional well-being, some exemplary works of research in recent years on the topic among general populations are reviewed. For one, Aalbers et al. (2018) reported that individuals who spent more time passively working with social media suffered from more intense levels of hopelessness, loneliness, depression, and perceived inferiority. For another, Tang et al. (2013) observed that the procedures of sharing information, commenting, showing likes and dislikes, posting messages, and doing other common activities on social media are correlated with higher stress. Similarly, Ley et al. (2014) described that people who spend 2 h, on average, on social media applications will face many tragic news, posts, and stories which can raise the total intensity of their stress. This stress-provoking effect of social media has been also pinpointed by Weng and Menczer (2015) , who contended that social media becomes a main source of stress because people often share all kinds of posts, comments, and stories ranging from politics and economics, to personal and social affairs. According to Iwamoto and Chun (2020) , anxiety and depression are the negative emotions that an individual may develop when some source of stress is present. In other words, when social media sources become stress-inducing, there are high chances that anxiety and depression also develop.

Charoensukmongkol (2018) reckoned that the mental health and well-being of the global population can be at a great risk through the uncontrolled massive use of social media. These researchers also showed that social media sources can exert negative affective impacts on teenagers, as they can induce more envy and social comparison. According to Fleck and Johnson-Migalski (2015) , though social media, at first, plays the role of a stress-coping strategy, when individuals continue to see stressful conditions (probably experienced and shared by others in media), they begin to develop stress through the passage of time. Chukwuere and Chukwuere (2017) maintained that social media platforms continue to be the major source of changing mood among general populations. For example, someone might be passively using a social media sphere, and s/he may finally find him/herself with a changed mood depending on the nature of the content faced. Then, this good or bad mood is easily shared with others in a flash through the social media. Finally, as Alahmar (2016) described, social media exposes people especially the young generation to new exciting activities and events that may attract them and keep them engaged in different media contexts for hours just passing their time. It usually leads to reduced productivity, reduced academic achievement, and addiction to constant media use ( Alahmar, 2016 ).

The number of studies on the potential psychological effects of social media on people in general is higher than those selectively addressed here. For further insights into this issue, some other suggested works of research include Chang (2012) , Sriwilai and Charoensukmongkol (2016) , and Zareen et al. (2016) . Now, we move to the studies that more specifically explored the effects of social media on students’ affective states.

Review of the affective influences of social media on students

Vygotsky’s mediational theory (see Fernyhough, 2008 ) can be regarded as a main theoretical background for the support of social media on learners’ affective states. Based on this theory, social media can play the role of a mediational means between learners and the real environment. Learners’ understanding of this environment can be mediated by the image shaped via social media. This image can be either close to or different from the reality. In the case of the former, learners can develop their self-image and self-esteem. In the case of the latter, learners might develop unrealistic expectations of themselves by comparing themselves to others. As it will be reviewed below among the affective variables increased or decreased in students under the influence of the massive use of social media are anxiety, stress, depression, distress, rumination, and self-esteem. These effects have been explored more among school students in the age range of 13–18 than university students (above 18), but some studies were investigated among college students as well. Exemplary works of research on these affective variables are reviewed here.

In a cross-sectional study, O’Dea and Campbell (2011) explored the impact of online interactions of social networks on the psychological distress of adolescent students. These researchers found a negative correlation between the time spent on social networking and mental distress. Dumitrache et al. (2012) explored the relations between depression and the identity associated with the use of the popular social media, the Facebook. This study showed significant associations between depression and the number of identity-related information pieces shared on this social network. Neira and Barber (2014) explored the relationship between students’ social media use and depressed mood at teenage. No significant correlation was found between these two variables. In the same year, Tsitsika et al. (2014) explored the associations between excessive use of social media and internalizing emotions. These researchers found a positive correlation between more than 2-h a day use of social media and anxiety and depression.

Hanprathet et al. (2015) reported a statistically significant positive correlation between addiction to Facebook and depression among about a thousand high school students in wealthy populations of Thailand and warned against this psychological threat. Sampasa-Kanyinga and Lewis (2015) examined the relationship between social media use and psychological distress. These researchers found that the use of social media for more than 2 h a day was correlated with a higher intensity of psychological distress. Banjanin et al. (2015) tested the relationship between too much use of social networking and depression, yet found no statistically significant correlation between these two variables. Frison and Eggermont (2016) examined the relationships between different forms of Facebook use, perceived social support of social media, and male and female students’ depressed mood. These researchers found a positive association between the passive use of the Facebook and depression and also between the active use of the social media and depression. Furthermore, the perceived social support of the social media was found to mediate this association. Besides, gender was found as the other factor to mediate this relationship.

Vernon et al. (2017) explored change in negative investment in social networking in relation to change in depression and externalizing behavior. These researchers found that increased investment in social media predicted higher depression in adolescent students, which was a function of the effect of higher levels of disrupted sleep. Barry et al. (2017) explored the associations between the use of social media by adolescents and their psychosocial adjustment. Social media activity showed to be positively and moderately associated with depression and anxiety. Another investigation was focused on secondary school students in China conducted by Li et al. (2017) . The findings showed a mediating role of insomnia on the significant correlation between depression and addiction to social media. In the same year, Yan et al. (2017) aimed to explore the time spent on social networks and its correlation with anxiety among middle school students. They found a significant positive correlation between more than 2-h use of social networks and the intensity of anxiety.

Also in China, Wang et al. (2018) showed that addiction to social networking sites was correlated positively with depression, and this correlation was mediated by rumination. These researchers also found that this mediating effect was moderated by self-esteem. It means that the effect of addiction on depression was compounded by low self-esteem through rumination. In another work of research, Drouin et al. (2018) showed that though social media is expected to act as a form of social support for the majority of university students, it can adversely affect students’ mental well-being, especially for those who already have high levels of anxiety and depression. In their research, the social media resources were found to be stress-inducing for half of the participants, all university students. The higher education population was also studied by Iwamoto and Chun (2020) . These researchers investigated the emotional effects of social media in higher education and found that the socially supportive role of social media was overshadowed in the long run in university students’ lives and, instead, fed into their perceived depression, anxiety, and stress.

Keles et al. (2020) provided a systematic review of the effect of social media on young and teenage students’ depression, psychological distress, and anxiety. They found that depression acted as the most frequent affective variable measured. The most salient risk factors of psychological distress, anxiety, and depression based on the systematic review were activities such as repeated checking for messages, personal investment, the time spent on social media, and problematic or addictive use. Similarly, Mathewson (2020) investigated the effect of using social media on college students’ mental health. The participants stated the experience of anxiety, depression, and suicidality (thoughts of suicide or attempts to suicide). The findings showed that the types and frequency of using social media and the students’ perceived mental health were significantly correlated with each other.

The body of research on the effect of social media on students’ affective and emotional states has led to mixed results. The existing literature shows that there are some positive and some negative affective impacts. Yet, it seems that the latter is pre-dominant. Mathewson (2020) attributed these divergent positive and negative effects to the different theoretical frameworks adopted in different studies and also the different contexts (different countries with whole different educational systems). According to Fredrickson’s broaden-and-build theory of positive emotions ( Fredrickson, 2001 ), the mental repertoires of learners can be built and broadened by how they feel. For instance, some external stimuli might provoke negative emotions such as anxiety and depression in learners. Having experienced these negative emotions, students might repeatedly check their messages on social media or get addicted to them. As a result, their cognitive repertoire and mental capacity might become limited and they might lose their concentration during their learning process. On the other hand, it should be noted that by feeling positive, learners might take full advantage of the affordances of the social media and; thus, be able to follow their learning goals strategically. This point should be highlighted that the link between the use of social media and affective states is bi-directional. Therefore, strategic use of social media or its addictive use by students can direct them toward either positive experiences like enjoyment or negative ones such as anxiety and depression. Also, these mixed positive and negative effects are similar to the findings of several other relevant studies on general populations’ psychological and emotional health. A number of studies (with general research populations not necessarily students) showed that social networks have facilitated the way of staying in touch with family and friends living far away as well as an increased social support ( Zhang, 2017 ). Given the positive and negative emotional effects of social media, social media can either scaffold the emotional repertoire of students, which can develop positive emotions in learners, or induce negative provokers in them, based on which learners might feel negative emotions such as anxiety and depression. However, admittedly, social media has also generated a domain that encourages the act of comparing lives, and striving for approval; therefore, it establishes and internalizes unrealistic perceptions ( Virden et al., 2014 ; Radovic et al., 2017 ).

It should be mentioned that the susceptibility of affective variables to social media should be interpreted from a dynamic lens. This means that the ecology of the social media can make changes in the emotional experiences of learners. More specifically, students’ affective variables might self-organize into different states under the influence of social media. As for the positive correlation found in many studies between the use of social media and such negative effects as anxiety, depression, and stress, it can be hypothesized that this correlation is induced by the continuous comparison the individual makes and the perception that others are doing better than him/her influenced by the posts that appear on social media. Using social media can play a major role in university students’ psychological well-being than expected. Though most of these studies were correlational, and correlation is not the same as causation, as the studies show that the number of participants experiencing these negative emotions under the influence of social media is significantly high, more extensive research is highly suggested to explore causal effects ( Mathewson, 2020 ).

As the review of exemplary studies showed, some believed that social media increased comparisons that students made between themselves and others. This finding ratifies the relevance of the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ) and Festinger’s (1954) Social Comparison Theory. Concerning the negative effects of social media on students’ psychology, it can be argued that individuals may fail to understand that the content presented in social media is usually changed to only represent the attractive aspects of people’s lives, showing an unrealistic image of things. We can add that this argument also supports the relevance of the Social Comparison Theory and the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ), because social media sets standards that students think they should compare themselves with. A constant observation of how other students or peers are showing their instances of achievement leads to higher self-evaluation ( Stapel and Koomen, 2000 ). It is conjectured that the ubiquitous role of social media in student life establishes unrealistic expectations and promotes continuous comparison as also pinpointed in the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ).

Implications of the study

The use of social media is ever increasing among students, both at school and university, which is partly because of the promises of technological advances in communication services and partly because of the increased use of social networks for educational purposes in recent years after the pandemic. This consistent use of social media is not expected to leave students’ psychological, affective and emotional states untouched. Thus, it is necessary to know how the growing usage of social networks is associated with students’ affective health on different aspects. Therefore, we found it useful to summarize the research findings in recent years in this respect. If those somehow in charge of student affairs in educational settings are aware of the potential positive or negative effects of social media usage on students, they can better understand the complexities of students’ needs and are better capable of meeting them.

Psychological counseling programs can be initiated at schools or universities to check upon the latest state of students’ mental and emotional health influenced by the pervasive use of social media. The counselors can be made aware of the potential adverse effects of social networking and can adapt the content of their inquiries accordingly. Knowledge of the potential reasons for student anxiety, depression, and stress can help school or university counselors to find individualized coping strategies when they diagnose any symptom of distress in students influenced by an excessive use of social networking.

Admittedly, it is neither possible to discard the use of social media in today’s academic life, nor to keep students’ use of social networks fully controlled. Certainly, the educational space in today’s world cannot do without the social media, which has turned into an integral part of everybody’s life. Yet, probably students need to be instructed on how to take advantage of the media and to be the least affected negatively by its occasional superficial and unrepresentative content. Compensatory programs might be needed at schools or universities to encourage students to avoid making unrealistic and impartial comparisons of themselves and the flamboyant images of others displayed on social media. Students can be taught to develop self-appreciation and self-care while continuing to use the media to their benefit.

The teachers’ role as well as the curriculum developers’ role are becoming more important than ever, as they can significantly help to moderate the adverse effects of the pervasive social media use on students’ mental and emotional health. The kind of groupings formed for instructional purposes, for example, in social media can be done with greater care by teachers to make sure that the members of the groups are homogeneous and the tasks and activities shared in the groups are quite relevant and realistic. The teachers cannot always be in a full control of students’ use of social media, and the other fact is that students do not always and only use social media for educational purposes. They spend more time on social media for communicating with friends or strangers or possibly they just passively receive the content produced out of any educational scope just for entertainment. This uncontrolled and unrealistic content may give them a false image of life events and can threaten their mental and emotional health. Thus, teachers can try to make students aware of the potential hazards of investing too much of their time on following pages or people that publish false and misleading information about their personal or social identities. As students, logically expected, spend more time with their teachers than counselors, they may be better and more receptive to the advice given by the former than the latter.

Teachers may not be in full control of their students’ use of social media, but they have always played an active role in motivating or demotivating students to take particular measures in their academic lives. If teachers are informed of the recent research findings about the potential effects of massively using social media on students, they may find ways to reduce students’ distraction or confusion in class due to the excessive or over-reliant use of these networks. Educators may more often be mesmerized by the promises of technology-, computer- and mobile-assisted learning. They may tend to encourage the use of social media hoping to benefit students’ social and interpersonal skills, self-confidence, stress-managing and the like. Yet, they may be unaware of the potential adverse effects on students’ emotional well-being and, thus, may find the review of the recent relevant research findings insightful. Also, teachers can mediate between learners and social media to manipulate the time learners spend on social media. Research has mainly indicated that students’ emotional experiences are mainly dependent on teachers’ pedagogical approach. They should refrain learners from excessive use of, or overreliance on, social media. Raising learners’ awareness of this fact that individuals should develop their own path of development for learning, and not build their development based on unrealistic comparison of their competences with those of others, can help them consider positive values for their activities on social media and, thus, experience positive emotions.

At higher education, students’ needs are more life-like. For example, their employment-seeking spirits might lead them to create accounts in many social networks, hoping for a better future. However, membership in many of these networks may end in the mere waste of the time that could otherwise be spent on actual on-campus cooperative projects. Universities can provide more on-campus resources both for research and work experience purposes from which the students can benefit more than the cyberspace that can be tricky on many occasions. Two main theories underlying some negative emotions like boredom and anxiety are over-stimulation and under-stimulation. Thus, what learners feel out of their involvement in social media might be directed toward negative emotions due to the stimulating environment of social media. This stimulating environment makes learners rely too much, and spend too much time, on social media or use them obsessively. As a result, they might feel anxious or depressed. Given the ubiquity of social media, these negative emotions can be replaced with positive emotions if learners become aware of the psychological effects of social media. Regarding the affordances of social media for learners, they can take advantage of the potential affordances of these media such as improving their literacy, broadening their communication skills, or enhancing their distance learning opportunities.

A review of the research findings on the relationship between social media and students’ affective traits revealed both positive and negative findings. Yet, the instances of the latter were more salient and the negative psychological symptoms such as depression, anxiety, and stress have been far from negligible. These findings were discussed in relation to some more relevant theories such as the social comparison theory, which predicted that most of the potential issues with the young generation’s excessive use of social media were induced by the unfair comparisons they made between their own lives and the unrealistic portrayal of others’ on social media. Teachers, education policymakers, curriculum developers, and all those in charge of the student affairs at schools and universities should be made aware of the psychological effects of the pervasive use of social media on students, and the potential threats.

It should be reminded that the alleged socially supportive and communicative promises of the prevalent use of social networking in student life might not be fully realized in practice. Students may lose self-appreciation and gratitude when they compare their current state of life with the snapshots of others’ or peers’. A depressed or stressed-out mood can follow. Students at schools or universities need to learn self-worth to resist the adverse effects of the superficial support they receive from social media. Along this way, they should be assisted by the family and those in charge at schools or universities, most importantly the teachers. As already suggested, counseling programs might help with raising students’ awareness of the potential psychological threats of social media to their health. Considering the ubiquity of social media in everybody’ life including student life worldwide, it seems that more coping and compensatory strategies should be contrived to moderate the adverse psychological effects of the pervasive use of social media on students. Also, the affective influences of social media should not be generalized but they need to be interpreted from an ecological or contextual perspective. This means that learners might have different emotions at different times or different contexts while being involved in social media. More specifically, given the stative approach to learners’ emotions, what learners emotionally experience in their application of social media can be bound to their intra-personal and interpersonal experiences. This means that the same learner at different time points might go through different emotions Also, learners’ emotional states as a result of their engagement in social media cannot be necessarily generalized to all learners in a class.

As the majority of studies on the psychological effects of social media on student life have been conducted on school students than in higher education, it seems it is too soon to make any conclusive remark on this population exclusively. Probably, in future, further studies of the psychological complexities of students at higher education and a better knowledge of their needs can pave the way for making more insightful conclusions about the effects of social media on their affective states.

Suggestions for further research

The majority of studies on the potential effects of social media usage on students’ psychological well-being are either quantitative or qualitative in type, each with many limitations. Presumably, mixed approaches in near future can better provide a comprehensive assessment of these potential associations. Moreover, most studies on this topic have been cross-sectional in type. There is a significant dearth of longitudinal investigation on the effect of social media on developing positive or negative emotions in students. This seems to be essential as different affective factors such as anxiety, stress, self-esteem, and the like have a developmental nature. Traditional research methods with single-shot designs for data collection fail to capture the nuances of changes in these affective variables. It can be expected that more longitudinal studies in future can show how the continuous use of social media can affect the fluctuations of any of these affective variables during the different academic courses students pass at school or university.

As already raised in some works of research reviewed, the different patterns of impacts of social media on student life depend largely on the educational context. Thus, the same research designs with the same academic grade students and even the same age groups can lead to different findings concerning the effects of social media on student psychology in different countries. In other words, the potential positive and negative effects of popular social media like Facebook, Snapchat, Twitter, etc., on students’ affective conditions can differ across different educational settings in different host countries. Thus, significantly more research is needed in different contexts and cultures to compare the results.

There is also a need for further research on the higher education students and how their affective conditions are positively and negatively affected by the prevalent use of social media. University students’ psychological needs might be different from other academic grades and, thus, the patterns of changes that the overall use of social networking can create in their emotions can be also different. Their main reasons for using social media might be different from school students as well, which need to be investigated more thoroughly. The sorts of interventions needed to moderate the potential negative effects of social networking on them can be different too, all requiring a new line of research in education domain.

Finally, there are hopes that considering the ever-increasing popularity of social networking in education, the potential psychological effects of social media on teachers be explored as well. Though teacher psychology has only recently been considered for research, the literature has provided profound insights into teachers developing stress, motivation, self-esteem, and many other emotions. In today’s world driven by global communications in the cyberspace, teachers like everyone else are affecting and being affected by social networking. The comparison theory can hold true for teachers too. Thus, similar threats (of social media) to self-esteem and self-worth can be there for teachers too besides students, which are worth investigating qualitatively and quantitatively.

Probably a new line of research can be initiated to explore the co-development of teacher and learner psychological traits under the influence of social media use in longitudinal studies. These will certainly entail sophisticated research methods to be capable of unraveling the nuances of variation in these traits and their mutual effects, for example, stress, motivation, and self-esteem. If these are incorporated within mixed-approach works of research, more comprehensive and better insightful findings can be expected to emerge. Correlational studies need to be followed by causal studies in educational settings. As many conditions of the educational settings do not allow for having control groups or randomization, probably, experimental studies do not help with this. Innovative research methods, case studies or else, can be used to further explore the causal relations among the different features of social media use and the development of different affective variables in teachers or learners. Examples of such innovative research methods can be process tracing, qualitative comparative analysis, and longitudinal latent factor modeling (for a more comprehensive view, see Hiver and Al-Hoorie, 2019 ).

Author contributions

Both authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

This study was sponsored by Wuxi Philosophy and Social Sciences bidding project—“Special Project for Safeguarding the Rights and Interests of Workers in the New Form of Employment” (Grant No. WXSK22-GH-13). This study was sponsored by the Key Project of Party Building and Ideological and Political Education Research of Nanjing University of Posts and Telecommunications—“Research on the Guidance and Countermeasures of Network Public Opinion in Colleges and Universities in the Modern Times” (Grant No. XC 2021002).

Conflict of interest

Author XX was employed by China Mobile Group Jiangsu Co., Ltd. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

  • Aalbers G., McNally R. J., Heeren A., de Wit S., Fried E. I. (2018). Social media and depression symptoms: A network perspective. J. Exp. Psychol. Gen. 148 1454–1462. 10.1037/xge0000528 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Abbott J. (2017). Introduction: Assessing the social and political impact of the internet and new social media in Asia. J. Contemp. Asia 43 579–590. 10.1080/00472336.2013.785698 [ CrossRef ] [ Google Scholar ]
  • Alahmar A. T. (2016). The impact of social media on the academic performance of second year medical students at College of Medicine, University of Babylon, Iraq. J. Med. Allied Sci. 6 77–83. 10.5455/jmas.236927 [ CrossRef ] [ Google Scholar ]
  • Banjanin N., Banjanin N., Dimitrijevic I., Pantic I. (2015). Relationship between internet use and depression: Focus on physiological mood oscillations, social networking and online addictive behavior. Comp. Hum. Behav. 43 308–312. 10.1016/j.chb.2014.11.013 [ CrossRef ] [ Google Scholar ]
  • Barry C. T., Sidoti C. L., Briggs S. M., Reiter S. R., Lindsey R. A. (2017). Adolescent social media use and mental health from adolescent and parent perspectives. J. Adolesc. 61 1–11. 10.1016/j.adolescence.2017.08.005 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Chang Y. (2012). The relationship between maladaptive perfectionism with burnout: Testing mediating effect of emotion-focused coping. Pers. Individ. Differ. 53 635–639. 10.1016/j.paid.2012.05.002 [ CrossRef ] [ Google Scholar ]
  • Charoensukmongkol P. (2018). The impact of social media on social comparison and envy in teenagers: The moderating role of the parent comparing children and in-group competition among friends. J. Child Fam. Stud. 27 69–79. 10.1007/s10826-017-0872-8 [ CrossRef ] [ Google Scholar ]
  • Chukwuere J. E., Chukwuere P. C. (2017). The impact of social media on social lifestyle: A case study of university female students. Gender Behav. 15 9966–9981. [ Google Scholar ]
  • Drouin M., Reining L., Flanagan M., Carpenter M., Toscos T. (2018). College students in distress: Can social media be a source of social support? Coll. Stud. J. 52 494–504. [ Google Scholar ]
  • Dumitrache S. D., Mitrofan L., Petrov Z. (2012). Self-image and depressive tendencies among adolescent Facebook users. Rev. Psihol. 58 285–295. [ Google Scholar ]
  • Fernyhough C. (2008). Getting Vygotskian about theory of mind: Mediation, dialogue, and the development of social understanding. Dev. Rev. 28 225–262. 10.1016/j.dr.2007.03.001 [ CrossRef ] [ Google Scholar ]
  • Festinger L. (1954). A Theory of social comparison processes. Hum. Relat. 7 117–140. 10.1177/001872675400700202 [ CrossRef ] [ Google Scholar ]
  • Fleck J., Johnson-Migalski L. (2015). The impact of social media on personal and professional lives: An Adlerian perspective. J. Individ. Psychol. 71 135–142. 10.1353/jip.2015.0013 [ CrossRef ] [ Google Scholar ]
  • Fredrickson B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. Am. Psychol. 56 218–226. 10.1037/0003-066X.56.3.218 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Frison E., Eggermont S. (2016). Exploring the relationships between different types of Facebook use, perceived online social support, and adolescents’ depressed mood. Soc. Sci. Compu. Rev. 34 153–171. 10.1177/0894439314567449 [ CrossRef ] [ Google Scholar ]
  • Hanprathet N., Manwong M., Khumsri J., Yingyeun R., Phanasathit M. (2015). Facebook addiction and its relationship with mental health among Thai high school students. J. Med. Assoc. Thailand 98 S81–S90. [ PubMed ] [ Google Scholar ]
  • Hiver P., Al-Hoorie A. H. (2019). Research Methods for Complexity Theory in Applied Linguistics. Bristol: Multilingual Matters. 10.21832/HIVER5747 [ CrossRef ] [ Google Scholar ]
  • Iwamoto D., Chun H. (2020). The emotional impact of social media in higher education. Int. J. High. Educ. 9 239–247. 10.5430/ijhe.v9n2p239 [ CrossRef ] [ Google Scholar ]
  • Keles B., McCrae N., Grealish A. (2020). A systematic review: The influence of social media on depression, anxiety and psychological distress in adolescents. Int. J. Adolesc. Youth 25 79–93. 10.1080/02673843.2019.1590851 [ CrossRef ] [ Google Scholar ]
  • Ley B., Ogonowski C., Hess J., Reichling T., Wan L., Wulf V. (2014). Impacts of new technologies on media usage and social behavior in domestic environments. Behav. Inform. Technol. 33 815–828. 10.1080/0144929X.2013.832383 [ CrossRef ] [ Google Scholar ]
  • Li J.-B., Lau J. T. F., Mo P. K. H., Su X.-F., Tang J., Qin Z.-G., et al. (2017). Insomnia partially mediated the association between problematic Internet use and depression among secondary school students in China. J. Behav. Addict. 6 554–563. 10.1556/2006.6.2017.085 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Mathewson M. (2020). The impact of social media usage on students’ mental health. J. Stud. Affairs 29 146–160. [ Google Scholar ]
  • Neira B. C. J., Barber B. L. (2014). Social networking site use: Linked to adolescents’ social self-concept, self-esteem, and depressed mood. Aus. J. Psychol. 66 56–64. 10.1111/ajpy.12034 [ CrossRef ] [ Google Scholar ]
  • O’Dea B., Campbell A. (2011). Online social networking amongst teens: Friend or foe? Ann. Rev. CyberTher. Telemed. 9 108–112. [ PubMed ] [ Google Scholar ]
  • Radovic A., Gmelin T., Stein B. D., Miller E. (2017). Depressed adolescents positive and negative use of social media. J. Adolesc. 55 5–15. 10.1016/j.adolescence.2016.12.002 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Sampasa-Kanyinga H., Lewis R. F. (2015). Frequent use of social networking sites is associated with poor psychological functioning among children and adolescents. Cyberpsychol. Behav. Soc. Network. 18 380–385. 10.1089/cyber.2015.0055 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Sriwilai K., Charoensukmongkol P. (2016). Face it, don’t Facebook it: Impacts of social media addiction on mindfulness, coping strategies and the consequence on emotional exhaustion. Stress Health 32 427–434. 10.1002/smi.2637 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Stapel D. A. (2007). “ In the mind of the beholder: The interpretation comparison model of accessibility effects ,” in Assimilation and Contrast in Social Psychology , eds Stapel D. A., Suls J. (London: Psychology Press; ), 143–164. [ Google Scholar ]
  • Stapel D. A., Koomen W. (2000). Distinctiveness of others, mutability of selves: Their impact on self-evaluations. J. Pers. Soc. Psychol. 79 1068–1087. 10.1037//0022-3514.79.6.1068 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Tang F., Wang X., Norman C. S. (2013). An investigation of the impact of media capabilities and extraversion on social presence and user satisfaction. Behav. Inform. Technol. 32 1060–1073. 10.1080/0144929X.2013.830335 [ CrossRef ] [ Google Scholar ]
  • Tsitsika A. K., Tzavela E. C., Janikian M., Ólafsson K., Iordache A., Schoenmakers T. M., et al. (2014). Online social networking in adolescence: Patterns of use in six European countries and links with psychosocial functioning. J. Adolesc. Health 55 141–147. 10.1016/j.jadohealth.2013.11.010 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Vernon L., Modecki K. L., Barber B. L. (2017). Tracking effects of problematic social networking on adolescent psychopathology: The mediating role of sleep disruptions. J. Clin. Child Adolesc. Psychol. 46 269–283. 10.1080/15374416.2016.1188702 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Virden A., Trujillo A., Predeger E. (2014). Young adult females’ perceptions of high-risk social media behaviors: A focus-group approach. J. Commun. Health Nurs. 31 133–144. 10.1080/07370016.2014.926677 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Wang P., Wang X., Wu Y., Xie X., Wang X., Zhao F., et al. (2018). Social networking sites addiction and adolescent depression: A moderated mediation model of rumination and self-esteem. Pers. Individ. Differ. 127 162–167. 10.1016/j.paid.2018.02.008 [ CrossRef ] [ Google Scholar ]
  • Weng L., Menczer F. (2015). Topicality and impact in social media: Diverse messages, focused messengers. PLoS One 10 : e0118410 . 10.1371/journal.pone.0118410 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Yan H., Zhang R., Oniffrey T. M., Chen G., Wang Y., Wu Y., et al. (2017). Associations among screen time and unhealthy behaviors, academic performance, and well-being in Chinese adolescents. Int. J. Environ. Res. Public Health 14 : 596 . 10.3390/ijerph14060596 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Zareen N., Karim N., Khan U. A. (2016). Psycho-emotional impact of social media emojis. ISRA Med. J. 8 257–262. [ Google Scholar ]
  • Zhang R. (2017). The stress-buffering effect of self-disclosure on Facebook: An examination of stressful life events, social support, and mental health among college students. Comp. Hum. Behav. 75 527–537. 10.1016/j.chb.2017.05.043 [ CrossRef ] [ Google Scholar ]

Early Literature on Adolescent Social Media Use, Substance Use, and Depressive Symptoms During the COVID-19 Pandemic: A Scoping Review

  • Published: 11 May 2024
  • Volume 12 , pages 11–23, ( 2024 )

Cite this article

literature review social media thesis

  • Miranda L. M. Delawalla   ORCID: orcid.org/0000-0002-6906-2707 1 ,
  • Ruchi Tiwari   ORCID: orcid.org/0000-0002-5251-7250 2 ,
  • Yolanda N. Evans   ORCID: orcid.org/0000-0002-1886-0178 3 , 4 ,
  • Isaac C. Rhew   ORCID: orcid.org/0000-0001-9731-8776 1 , 5 &
  • Daniel A. Enquobahrie   ORCID: orcid.org/0000-0001-9844-0597 5 , 6  

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Purpose of Review

The COVID-19 pandemic led to unprecedented changes in daily life that impacted health among all populations, including adolescents. We conducted a scoping review of early literature (through June 20, 2021) on adolescent social media use, substance use, and depressive symptoms during the COVID-19 pandemic in the United States. Further, we summarized key findings and recommendations regarding study design and reporting for researchers in future public health emergencies.

Recent Findings

We identified 29 studies that met the criteria for inclusion, a majority of which reported on depressive symptoms and/or suicidality among adolescents (n=22), with fewer on social media use (n=7) and substance use (n=4). Prevalence of social media use and depressive symptoms was high. Longitudinal assessments indicate elevated depressive symptoms in the first month of the pandemic, but decreases in the few months following. Findings for substance use were varied, but two studies found lower e-cigarette use. Broadly, studies presented heterogenous measures of key constructs and this was particularly evident for depressive symptoms.

Our review highlights the critical need to use validated measures, leverage ongoing longitudinal studies, and focus on salient health risk behaviors in future studies addressing public health emergencies.

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Data Availability

No datasets were generated or analysed during the current study.

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Fegert JM, Vitiello B, Plener PL, Clemens V. Challenges and burden of the Coronavirus 2019 (COVID-19) pandemic for child and adolescent mental health: A narrative review to highlight clinical and research needs in the acute phase and the long return to normality. Child Adolesc Psychiatry Ment Health. 2020;14:1–11. https://doi.org/10.1186/s13034-020-00329-3 .

Article   Google Scholar  

Singh S, Roy D, Sinha K, Parveen S, Sharma G, Joshi G. Impact of COVID-19 and lockdown on mental health of children and adolescents: A narrative review with recommendations. Psychiatry Res. 2020;293:113429. https://doi.org/10.1016/j.psychres.2020.113429 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Silver RC, Holman EA, Garfin DR. Coping with cascading collective traumas in the United States. Nat Hum Behav. 2020. https://doi.org/10.1038/s41562-020-00981-x .

Johnston LD, Miech RA, Malley PMO, Bachman JG, Schulenberg JE, Patrick MeganE. Monitoring the Future national survey results on drug use 1975–2019: Overview, key findings on adolescent drug use. Institute for Social Research, University of Michigan; 2020.  https://monitoringthefuture.org/wp-content/uploads/2022/08/mtf-overview2019.pdf .

Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: Results from the 2019 National Survey on Drug Use and Health (HHS Publication No. PEP20–07–01–001, NSDUH Series H-55). Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration; 2020.  https://www.samhsa.gov/data/sites/default/files/reports/rpt29393/2019NSDUHFFRPDFWHTML/2019NSDUHFFR1PDFW090120.pdf .

Anderson M, Jiang J. Teens, Social Media & Technology 2018. Pew Research Center; 2018.  https://www.pewresearch.org/internet/2018/05/31/teens-social-media-technology-2018/ .

Uhls YT, Ellison NB, Subrahmanyam K. Benefits and Costs of Social Media in Adolescence. Pediatrics. 2017;140:S67-70. https://doi.org/10.1542/peds.2016-1758E .

Article   PubMed   Google Scholar  

Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2018;169:467–73. https://doi.org/10.7326/M18-0850 .

Willner CJ, Gatzke-Kopp LM, Bray BC. The dynamics of internalizing and externalizing comorbidity across the early school years. Dev Psychopathol. 2016;28:1033–52. https://doi.org/10.1017/S0954579416000687 .

Article   PubMed   PubMed Central   Google Scholar  

Cummings CM, Caporino NE, Kendall PC. Comorbidity of anxiety and depression in children and adolescents: 20 years after. Psychol Bull. 2014;140:816–45. https://doi.org/10.1037/a0034733 .

Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95:103208. https://doi.org/10.1016/j.jbi.2019.103208 .

Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81. https://doi.org/10.1016/j.jbi.2008.08.010 .

Murata S, Rezeppa T, Thoma B, Marengo L, Krancevich K, Chiyka E, et al. The psychiatric sequelae of the COVID-19 pandemic in adolescents, adults, and health care workers. Depress Anxiety. 2021;38:233–46. https://doi.org/10.1002/da.23120 .

Article   CAS   PubMed   Google Scholar  

Penner F, Hernandez Ortiz J, Sharp C. Change in Youth Mental Health During the COVID-19 Pandemic in a Majority Hispanic/Latinx US Sample. J Am Acad Child Adolesc Psychiatry. 2021;60:513–23. https://doi.org/10.1016/j.jaac.2020.12.027 .

Drouin M, McDaniel BT, Pater J, Toscos T. How Parents and Their Children Used Social Media and Technology at the Beginning of the COVID-19 Pandemic and Associations with Anxiety. Cyberpsychol Behav Soc Netw. 2020;23:727–36. https://doi.org/10.1089/cyber.2020.0284 .

Nelson KM, Gordon AR, John SA, Stout CD, Macapagal K. “Physical sex is over for now”: Impact of COVID-19 on the well-being and sexual health of adolescent sexual minority males in the US. J Adolesc Health. 2020;67:756–62. https://doi.org/10.1016/j.jadohealth.2020.08.027 .

O’Brien RP, Parra LA, Cederbaum JA. “Trying My Best”: Sexual Minority Adolescents’ Self-Care During the COVID-19 Pandemic. J Adolesc Health : Official Public Soc Adolesc Med. 2021;68:1053–8. https://doi.org/10.1016/j.jadohealth.2021.03.013 .

Campbell K, Weingart R, Ashta J, Cronin T, Gazmararian J. COVID-19 Knowledge and Behavior Change among High School Students in Semi-Rural Georgia. J Sch Health. 2021;91:526–34. https://doi.org/10.1111/josh.13029 .

Gazmararian J, Weingart R, Campbell K, Cronin T, Ashta J. Impact of COVID-19 Pandemic on the Mental Health of Students From 2 Semi-Rural High Schools in Georgia. J Sch Health. 2021;91:356–69. https://doi.org/10.1111/josh.13007 .

Gaiha SM, Cheng J, Halpern-Felsher B. Association Between Youth Smoking, Electronic Cigarette Use, and COVID-19. J Adolesc Health : Official Public Soc Adolesc Med. 2020;67:519–23. https://doi.org/10.1016/j.jadohealth.2020.07.002 .

Kreslake JM, Simard BJ, O’Connor KM, Patel M, Vallone DM, Hair EC. E-Cigarette Use Among Youths and Young Adults During the COVID-19 Pandemic: United States. Am J Public Health. 2020;2021:e1-9. https://doi.org/10.2105/AJPH.2021.306210 .

• Chaffee BW, Cheng J, Couch ET, Hoeft KS, Halpern-Felsher B. Adolescents’ Substance Use and Physical Activity Before and During the COVID-19 Pandemic. JAMA Pediatr. 2021. https://doi.org/10.1001/jamapediatrics.2021.0541 . Chaffee et al. report findings of a longitudinal study including data collected both before and after stay-at-home orders on substance use among adolescents. This study highlights extending existing studies to examine impacts of important public health events .

• McGuine TA, Biese KM, Petrovska L, Hetzel SJ, Reardon C, Kliethermes S, et al. Mental Health, Physical Activity, and Quality of Life of US Adolescent Athletes During COVID-19-Related School Closures and Sport Cancellations: A Study of 13 000 Athletes. J Athl Train. 2020;56:11–9. https://doi.org/10.4085/1062-6050-0478.20 . McGuine et al. provide an assessment of depressive symptoms in a large, national sample of adolescent athletes. Their study is an example of use of a common and validated measure of depressive symptoms (Patient Health Questionnaire 9-Item; PHQ-9), improving comparability across studies .

Article   PubMed Central   Google Scholar  

McGuine TA, Biese K, Hetzel SJ, Petrovska L, Kliethermes S, Reardon CL, et al. Changes in the Health of Adolescent Athletes: A Comparison of Health Measures Collected Before and During the CoVID-19 Pandemic. J Athl Train. 2021. https://doi.org/10.4085/1062-6050-0739.20 .

McGuine TA, Biese K, Hetzel SJ, Schwarz A, Kliethermes S, Reardon CL, et al. High School Sports During the CoVID-19 Pandemic: The Impact of Sport Participation on the Health of Adolescents. J Athl Train. 2021. https://doi.org/10.4085/1062-6050-0121.21 .

McKune SL, Acosta D, Diaz N, Brittain K, Beaulieu DJ-, Maurelli AT, et al. Psychosocial health of school-aged children during the initial COVID-19 safer-at-home school mandates in Florida: a cross-sectional study. BMC Public Health. 2021;21:603. https://doi.org/10.1186/s12889-021-10540-2 .

Fitzpatrick O, Carson A, Weisz JR. Using Mixed Methods to Identify the Primary Mental Health Problems and Needs of Children, Adolescents, and Their Caregivers during the Coronavirus (COVID-19) Pandemic. Child Psychiatry and Human Development 2020:1–12. https://doi.org/10.1007/s10578-020-01089-z .

Lorenzo NE, Zeytinoglu S, Morales S, Listokin J, Almas AN, Degnan KA, et al. Transactional Associations Between Parent and Late Adolescent Internalizing Symptoms During the COVID-19 Pandemic: The Moderating Role of Avoidant Coping. J Youth Adolesc. 2021;50:459–69. https://doi.org/10.1007/s10964-020-01374-z .

Hawes MT, Szenczy AK, Olino TM, Nelson BD, Klein DN. Trajectories of depression, anxiety and pandemic experiences; A longitudinal study of youth in New York during the Spring-Summer of 2020. Psychiatry Res. 2021;298:113778. https://doi.org/10.1016/j.psychres.2021.113778 .

Breaux R, Dvorsky MR, Marsh NP, Green CD, Cash AR, Shroff DM, et al. Prospective impact of COVID-19 on mental health functioning in adolescents with and without ADHD: protective role of emotion regulation abilities. Journal of Child Psychology and Psychiatry, and Allied Disciplines 2021. https://doi.org/10.1111/jcpp.13382 .

Chahal R, Kirshenbaum JS, Miller JG, Ho TC, Gotlib IH. Higher Executive Control Network Coherence Buffers Against Puberty-Related Increases in Internalizing Symptoms During the COVID-19 Pandemic. Biol Psychiatry: Cognitive Neurosci Neuroimaging. 2021;6:79–88. https://doi.org/10.1016/j.bpsc.2020.08.010 .

Yarrington JS, Lasser J, Garcia D, Vargas JH, Couto DD, Marafon T, et al. Impact of the COVID-19 Pandemic on Mental Health among 157,213 Americans. J Affect Disord. 2021;286:64–70. https://doi.org/10.1016/j.jad.2021.02.056 .

Rogers AA, Ha T, Ockey S. Adolescents’ Perceived Socio-Emotional Impact of COVID-19 and Implications for Mental Health: Results From a US.-Based Mixed-Methods Study. J Adolesc Health : Official Publication Soc Adolesc Med. 2021;68:43–52. https://doi.org/10.1016/j.jadohealth.2020.09.039 .

Sinko L, He Y, Kishton R, Ortiz R, Jacobs L, Fingerman M. “The Stay at Home Order is Causing Things to Get Heated Up”: Family Conflict Dynamics During COVID-19 From The Perspectives of Youth Calling a National Child Abuse Hotline. Journal of Family Violence 2021:1–10. https://doi.org/10.1007/s10896-021-00290-5 .

Ridout KK, Alavi M, Ridout SJ, Koshy MT, Harris B, Dhillon I, et al. Changes in Diagnostic and Demographic Characteristics of Patients Seeking Mental Health Care During the Early COVID-19 Pandemic in a Large, Community-Based Health Care System. The Journal of Clinical Psychiatry 2021;82. https://doi.org/10.4088/JCP.20m13685 .

Thompson EC, Thomas SA, Burke TA, Nesi J, MacPherson HA, Bettis AH, et al. Suicidal thoughts and behaviors in psychiatrically hospitalized adolescents pre- and post- COVID-19: A historical chart review and examination of contextual correlates. J Affect Disor Reports. 2021;4:100100. https://doi.org/10.1016/j.jadr.2021.100100 .

Fortgang RG, Wang SB, Millner AJ, Reid-Russell A, Beukenhorst AL, Kleiman EM, et al. Increase in suicidal thinking during COVID-19. Clin Psychol Sci. 2021;9:482–8. https://doi.org/10.1177/2167702621993857 .

• Yard E, Radhakrishnan L, Ballesteros MF, Sheppard M, Gates A, Stein Z, et al. Emergency Department Visits for Suspected Suicide Attempts Among Persons Aged 12–25 Years Before and During the COVID-19 Pandemic - United States, January 2019-May 2021. MMWR Morbidity Mortality Weekly Report. 2021;70:888–94. Yard et al. detail their study of suspected suicide visits both before and during the pandemic. This study provides a demonstration of leveraging existing surveillance data to examine potential impacts of a major public health event .

Deng J, Zhou F, Hou W, Heybati K, Lohit S, Abbas U, et al. Prevalence of mental health symptoms in children and adolescents during the COVID-19 pandemic: A meta-analysis. Ann N Y Acad Sci. 2023;1520:53–73. https://doi.org/10.1111/nyas.14947 .

Racine N, McArthur BA, Cooke JE, Eirich R, Zhu J, Madigan S. Global Prevalence of Depressive and Anxiety Symptoms in Children and Adolescents During COVID-19: A Meta-analysis. JAMA Pediatr. 2021;175:1142. https://doi.org/10.1001/jamapediatrics.2021.2482 .

Zolopa C, Burack JA, O’Connor RM, Corran C, Lai J, Bomfim E, et al. Changes in Youth Mental Health, Psychological Wellbeing, and Substance Use During the COVID-19 Pandemic: A Rapid Review. Adolesc Res Rev. 2022;7:161–77. https://doi.org/10.1007/s40894-022-00185-6 .

Madigan S, Eirich R, Pador P, McArthur BA, Neville RD. Assessment of Changes in Child and Adolescent Screen Time During the COVID-19 Pandemic: A Systematic Review and Meta-analysis. JAMA Pediatr. 2022;176:1188. https://doi.org/10.1001/jamapediatrics.2022.4116 .

Layman HM, Thorisdottir IE, Halldorsdottir T, Sigfusdottir ID, Allegrante JP, Kristjansson AL. Substance Use Among Youth During the COVID-19 Pandemic: a Systematic Review. Curr Psychiatry Rep. 2022;24:307–24. https://doi.org/10.1007/s11920-022-01338-z .

de Figueiredo CS, Sandre PC, Portugal LCL, Mázala-de-Oliveira T, da Silva CL, Raony Í, et al. COVID-19 pandemic impact on children and adolescents’ mental health: Biological, environmental, and social factors. Prog Neuropsychopharmacol Biol Psychiatry. 2021;106: 110171. https://doi.org/10.1016/j.pnpbp.2020.110171 .

Tandoc EC, Johnson E. Most students get breaking news first from Twitter. Newsp Res J. 2016;37:153–66. https://doi.org/10.1177/0739532916648961 .

Craft S, Ashley S, Maksl A. Elements of News Literacy. Electron News. 2016;10:143–60. https://doi.org/10.1177/1931243116656716 .

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This work was supported in part by a student project stipend from the Northwest Public Health Training Center at the Northwest Center for Public Health Practice (sponsored by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) (grant # 6 UB6HP31690-04–01)) and by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under grant #T76MC00011. REDCap at ITHS is supported by the National Center For Advancing Translational Sciences of the National Institutes of Health under Award Number UL1 TR002319. The authors have no conflicts of interest to disclose.

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M.D. and R.T. conducted scoping review procedures. M.D. wrote the main main manuscript text and prepared tables and figures. All authors (M.D., R.T., Y.E., I.R., and D.E.) reviewed the manuscript and contributed to interpretation of review findings.

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Delawalla , M.L.M., Tiwari, R., Evans, Y.N. et al. Early Literature on Adolescent Social Media Use, Substance Use, and Depressive Symptoms During the COVID-19 Pandemic: A Scoping Review. Curr Pediatr Rep 12 , 11–23 (2024). https://doi.org/10.1007/s40124-024-00313-x

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    Review of the affective influences of social media on students. Vygotsky's mediational theory (see Fernyhough, 2008) can be regarded as a main theoretical background for the support of social media on learners' affective states.Based on this theory, social media can play the role of a mediational means between learners and the real environment.

  20. Early Literature on Adolescent Social Media Use, Substance ...

    Purpose of Review The COVID-19 pandemic led to unprecedented changes in daily life that impacted health among all populations, including adolescents. We conducted a scoping review of early literature (through June 20, 2021) on adolescent social media use, substance use, and depressive symptoms during the COVID-19 pandemic in the United States. Further, we summarized key findings and ...

  21. A Structured Literature Review on the Research and Design of

    An environment that creates a balance between privacy and social interaction can promote these mediators. Creating enriched environments through elements that engage the senses and encourage more social and physical interaction is essential for recovery.

  22. Welcome to the Purdue Online Writing Lab

    Mission. The Purdue On-Campus Writing Lab and Purdue Online Writing Lab assist clients in their development as writers—no matter what their skill level—with on-campus consultations, online participation, and community engagement. The Purdue Writing Lab serves the Purdue, West Lafayette, campus and coordinates with local literacy initiatives.