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• Review Article
• Published: 07 May 2024

Mechanisms linking social media use to adolescent mental health vulnerability

• Amy Orben   ORCID: orcid.org/0000-0002-2937-4183 1 ,
• Adrian Meier   ORCID: orcid.org/0000-0002-8191-2962 2 ,
• Tim Dalgleish   ORCID: orcid.org/0000-0002-7304-2231 1 &
• Sarah-Jayne Blakemore 3 , 4  

Nature Reviews Psychology ( 2024 ) Cite this article

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• Psychiatric disorders
• Science, technology and society

Research linking social media use and adolescent mental health has produced mixed and inconsistent findings and little translational evidence, despite pressure to deliver concrete recommendations for families, schools and policymakers. At the same time, it is widely recognized that developmental changes in behaviour, cognition and neurobiology predispose adolescents to developing socio-emotional disorders. In this Review, we argue that such developmental changes would be a fruitful focus for social media research. Specifically, we review mechanisms by which social media could amplify the developmental changes that increase adolescents’ mental health vulnerability. These mechanisms include changes to behaviour, such as sharing risky content and self-presentation, and changes to cognition, such as modifications in self-concept, social comparison, responsiveness to social feedback and experiences of social exclusion. We also consider neurobiological mechanisms that heighten stress sensitivity and modify reward processing. By focusing on mechanisms by which social media might interact with developmental changes to increase mental health risks, our Review equips researchers with a toolkit of key digital affordances that enables theorizing and studying technology effects despite an ever-changing social media landscape.

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Introduction.

Adolescence is a period marked by profound neurobiological, behavioural and environmental changes that facilitate the transition from familial dependence to independent membership in society 1 , 2 . This critical developmental stage is also characterized by diminished well-being and increased vulnerability to the onset of mental health conditions 3 , 4 , 5 , particularly socio-emotional disorders such as depression, and eating disorders 4 , 6 (Fig. 1 ). Notable symptoms of socio-emotional disorders include heightened negative affect, mood dysregulation and an increased focus on distress or challenges concerning interpersonal relationships, including heightened sensitivity to peers or perceptions of others 6 . Although some risk factors for socio-emotional disorders do not necessarily occur in adolescence (including genetic predispositions, adverse childhood experiences and poverty 7 , 8 , 9 ), the unique developmental characteristics of this period of life can interact with pre-existing vulnerabilities, increasing the risk of disorder onset 10 .

Meta-analytic proportion of age of onset of anxiety (red), obsessive-compulsive disorder (purple), eating disorders (orange), personality disorders (green), schizophrenia (grey) and mood disorders (blue). The peak age of onset (dotted lines) is 5.5 and 15.5 years for anxiety, 14.5 years for obsessive-compulsive disorder, 15.5 years for eating disorders and 20.5 years for personality disorders, schizophrenia and mood disorders. Adapted from ref. 258 , CC BY 4.0 ( https://creativecommons.org/licenses/by/4.0/ ).

Over the past decade, declines in adolescent mental health have become a great concern 11 , 12 . The prevalence of socio-emotional disorders has increased in the adolescent age range (10–24 years 2 ) 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , leading to mounting pressures on child and adolescent mental health services 16 , 21 , 22 . This increase has not been as pronounced among other age groups when compared with adolescents 20 , 22 , 23 (measured in ref.  20 , ref.  22 and ref.  23 as age 12–25 years, 12–20 years and 18–25 years, respectively), even if some studies have found increases across the entire lifespan 24 , 25 . Although these trends might not be generalizable across the world 26 or to subclinical indicators of distress 15 , similar trends have been found in a range of countries 27 . Declines in adolescent mental health, especially socio-emotional problems, are consistent across datasets and researchers have argued that they are not solely driven by changes in social attitudes, stigma or reporting of distress 28 , 29 .

Concurrently, adolescents’ lives have become increasingly digital, with most young people using social media platforms throughout the day 30 . Ninety-five per cent of UK adolescents aged 15 years use social media 31 , and 50% of US adolescents aged 13–17 years report being almost constantly online 32 . The social media environment impacts adolescent and adult life across many domains (for example, by enabling social communication or changing the way news is accessed) and influences individuals, dyads and larger social systems 33 , 34 , 35 , 36 . Because social media is inherently social and relational 37 , it potentially overlaps and interacts with the developmental changes that make adolescents vulnerable to the onset of mental health problems 38 , 39 (Fig. 2 ). Thus, it has been intensely debated whether the increase in social media use during the past decade has a causal role in the decline of adolescent mental health 40 . Indeed, rapid changes to the environment experienced before and during adolescence might be a fruitful area to explore when examining current mental health trends 41 .

During adolescence, the interaction between genetic programming (yellow), social determinants (red) and environmental factors (blue), as well as the developmental changes discussed in this Review, increases the risk for onset of mental health conditions. Digital environments, mediated behaviours and experiences, and the impact that this technology has on society and economy more generally, are one aspect of the complex forces that might lead to the declines in adolescent mental health observed in the last decade. Adapted from ref. 259 , Springer Nature Limited.

Although there are many environmental changes that could be relevant, a substantial body of research has emerged to investigate the potential link between social media use and declines in adolescent mental health 42 , 43 using various research approaches, including cross-sectional studies 44 , longitudinal observational data analyses 45 , 46 , 47 and experimental studies 48 , 49 . However, the scientific results have been mixed and inconclusive (for reviews, see refs. 43 , 50 , 51 , 52 , 53 ), which has made it difficult to establish evidence-based recommendations, regulations and interventions aimed at ensuring that social media use is not harmful to adolescents 54 , 55 , 56 , 57 .

Many researchers attribute the mixed results to insufficient study specificity. For instance, the relationship between social media use and mental health varies notably across individuals 45 , 58 and developmental time windows 59 . Yet studies often examine adolescents without differentiating them based on age or developmental stage 60 , which prevents systematic accounts of individual and subgroup differences. Additionally, most studies only rely on self-reported measures of time spent on social media 61 , 62 , and overlook more nuanced aspects of social media use such as the nature of the activities 63 and the content or features that users engage with 52 . These factors need to be considered to unpack any broader relationships 35 , 64 , 65 , 66 . Furthermore, the measurement of mental health often conflates positive and negative mental health outcomes as well as various mental health conditions, which could all be differentially related to social media use 52 , 67 .

This research space presents substantial complexity 68 . There is an ever-increasing range of potential combinations of social media predictors, well-being and mental health outcomes and participant groups of varying backgrounds and demographics that can become the target of scientific investigation. However, the pressure to deliver policy and public-facing recommendations and interventions leaves little time to investigate comprehensively each of these combinations. Researchers need to be able to pinpoint quickly the research programmes with the maximum potential to create translational and real-world impact for adolescent mental health.

In this Review, we aim to delineate potential avenues for future research that could lead to concrete interventions to improve adolescent mental health by considering mechanisms at the nexus between pre-existing processes known to increase adolescent mental health vulnerability and digital affordances introduced by social media. First, we describe the affordance approach to understanding the effects of social media. We then draw upon research on adolescent development, mental health and social media to describe behavioural, cognitive and neurobiological mechanisms by which social media use might amplify changes during adolescent development to increase mental health vulnerability during this period of life. The specific mechanisms within each category were chosen because they have a strong evidence base showing that they undergo substantive changes during adolescent development, are implicated in mental health risk and can be modulated by social media affordances. Although the ways in which social media can also improve mental health resilience are not the focus of our Review and therefore are not reviewed fully here, they are briefly discussed in relation to each mechanism. Finally, we discuss future research focused on how to systematically test the intersection between social media and adolescent mental health.

Social media affordances

To study the impact of social media on adolescent mental health, its diverse design elements and highly individualized uses must be conceptualized. Initial research predominately related access to or time spent on social media to mental health outcomes 46 , 69 , 70 . However, social media is not similar to a toxin or nutrient for which each exposure dose has a defined link to a health-related outcome (dose–response relationship) 56 . Social media is a diverse environment that cannot be summarized by the amount of time one spends interacting with it 71 , 72 , and individual experiences are highly varied 45 .

Previous psychological reviews often focused on social media ‘features’ 73 and ‘affordances’ 74 interchangeably. However, these terms have distinct definitions in communication science and information systems research. Social media features are components of the technology intentionally designed to enable users to perform specific actions, such as liking, reposting or uploading a story 75 , 76 . By contrast, affordances describe the perceptions of action possibilities users have when engaging with social media and its features, such as anonymity (the difficulty with which social media users can identify the source of a message) and quantifiability (how countable information is).

The term ‘affordance’ came from ecological psychology and visuomotor research, and was described as mainly determined by human perception 77 . ‘Affordance’ was later adopted for design and human–computer interaction contexts to refer to the action possibilities that are suggested to the user by the technology design 78 . Communication research synthesizes both views. Affordances are now typically understood as the perceived — and therefore flexible — action possibilities of digital environments, which are jointly shaped by the technology’s features and users’ idiosyncratic perceptions of those features 79 .

Latent action possibilities can vary across different users, uses and technologies 79 . For example, ‘stories’ are a feature of Instagram designed to share content between users. Stories can also be described in terms of affordances when users perceive them as a way to determine how long their content remains available on the platform (persistence) or who can see that content (visibility) 80 , 81 , 82 , 83 , 84 . Low persistence (also termed ephemerality) and comparatively low visibility can be achieved through a technology feature (Instagram stories), but are not an outcome of technology use itself; they are instead perceived action possibilities that can vary across different technologies, users and designs 79 .

The affordances approach is particularly valuable for theorizing at a level above individual social media apps or specific features, which makes this approach more resilient to technological changes or shifts in platform popularity 79 , 85 . However, the affordances approach can also be related back to specific types of social media by assessing the extent to which certain affordances are ‘built into’ a particular platform through feature design 35 . Furthermore, because affordances depend on individuals’ perceptions and actions, they are more aligned than features with a neurocognitive and behavioural perspective to social media use. Affordances, similar to neurocognitive and behavioural research, emphasize the role of the user (how the technology is perceived, interpreted and used) rather than technology design per se. In this sense, the affordances approach is essential to overcome technological determinism of mental health outcomes, which overly emphasizes the role of technology as the driver of outcomes but overlooks the agency and impact of the people in question 86 . This flexibility and alignment with psychological theory has contributed to the increasing popularity of the affordance approach 35 , 73 , 74 , 85 , 87 and previous reviews have explored relevant social media affordances in the context of interpersonal communication among adults and adolescents 35 , 88 , 89 , adolescent body image concerns 73 and work contexts 33 . Here, we focus on the affordances of social media that are relevant for adolescent development and its intersection with mental health (Table  1 ).

Behavioural mechanisms

Adolescents often use social media differently to adults, engaging with different platforms and features and, potentially, perceiving or making use of affordances in distinctive ways 35 . These usage differences might interact with developmental characteristics and changes to amplify mental health vulnerability (Fig.  3 ). We examine two behavioural mechanisms that might govern the impact of social media use on mental health: risky posting behaviours and self-presentation.

Social media affordances can amplify the impact that common adolescent developmental mechanisms (behavioural, cognitive and neurobiological) have on mental health. At the behavioural level (top), affordances such as permanence and publicness lead to an increased impact of risk-taking behaviour on mental health compared with similar behaviours in non-mediated environments. At the cognitive level (middle), high quantifiability influences the effects of social comparison. At the neurobiological level (bottom), low synchronicity can amplify the effects of stress on the developing brain.

Risky posting behaviour

Sensation-seeking peaks in adolescence and self-regulation abilities are still not fully developed in this period of life 90 . Thus, adolescents often engage in more risky behaviours than other age groups 91 . Adolescents are more likely to take risks in situations involving peers 92 , 93 , perhaps because they are motivated to avoid social exclusion 94 , 95 . Whether adolescent risk-taking behaviour is inherently adaptive or maladaptive is debated. Although some risk-taking behaviours can be adaptive and part of typical development, others can increase mental health vulnerability. For example, data from a prospective UK panel study of more than 5,500 young people showed that engaging in more risky behaviours (including social and health risks) at age 16 years increases the odds of a range of adverse outcomes at age 18 years, such as depression, anxiety and substance abuse 96 .

Social media can increase adolescents’ engagement in risky behaviours both in non-mediated and mediated environments (environments in which the behaviour is executed in or through a technology, such as a mobile phone and social media). First, affordances such as quantifiability in conjunction with visibility and association (the degree with which links between people, between people and content or between a presenter and their audience can be articulated) can promote more risky behaviours in non-mediated environments and in-person social interactions. For example, posts from university students containing references to alcohol gain more likes than posts not referencing alcohol and liking such posts predicts an individual’s subsequent drinking habits 97 . Users expecting likes from their audience are incentivized to engage in riskier posting behaviour (such as more frequent or more extreme posts containing references to alcohol). The relationship between risky online behaviour and offline behaviour is supported by meta-analyses that found a positive correlation between adolescents’ social media use and their engagement in behaviours that might expose them to harm or risk of injury (for example, substance use or risky sexual behaviours) 98 . Further, affordances such as persistence and visibility can mean that risky behaviours in mediated and non-mediated environments remain public for long periods of time, potentially influencing how an adolescent is perceived by peers over the longer term 39 , 99 .

Adolescence can also be a time of more risky social media use. For most forms of semi-public and public social media use, users typically do not know who exactly will be able to see their posts. Thus, adolescents need to self-present to an ‘imagined audience’ 100 and avoid posting the wrong kind of content as the boundaries between different social spheres collapse (context collapse 101 ). However, young people can underestimate the risks of disclosing revealing information in a social media environment 102 . Affordances such as visibility, replicability (social media posts remain in the system and can be screenshotted and shared even if they are later deleted 39 ), association and persistence could heighten the risk of experiencing cyberbullying, victimization and online harassment 103 . For example, adolescents can forward privately received sexual images to larger friendship groups, increasing the risk of online harassment over the subject of the sexual images 104 . Further, low bandwidth (a relative lack of socio-emotional cues) and high anonymity have the potential to disinhibit interactions between users and make behaviours and reactions more extreme 105 , 106 . For example, anonymity was associated with more trolling behaviours during an online group discussion in an experiment with 242 undergraduate students 107 .

Thus, social media might drive more risky behaviours in both mediated and non-mediated contexts, increasing mental health vulnerability. However, the evidence is still not clear cut and often discounts adolescent agency and understanding. For example, mixed-methods research has shown that young people often understand the risks of posting private or sexual content and use social media apps that ensure that posts are deleted and inaccessible after short periods of time to counteract them 39 (even though posts can still be captured in the meantime). Future work will therefore need to investigate how adolescents understand and balance such risks and how such processes relate to social media’s impact on mental health.

Self-presentation and identity

The adolescent period is characterized by an abundance of self-presentation activities on social media 74 , where the drive to present oneself becomes a fundamental motivation for engagement 108 . These activities include disclosing, concealing and modifying one’s true self, and might involve deception, to convey a desired impression to an audience 109 . Compared with adults, adolescents more frequently take part in self-presentation 102 , which can encompass both realistic and idealized portrayals of themselves 110 . In adults, authentic self-presentation has been associated with increased well-being, and inauthentic presentation (such as when a person describes themselves in ways not aligned with their true self) has been associated with decreased well-being 111 , 112 , 113 .

Several social media affordances shape the self-presentation behaviours of adolescents. For example, the editability of social media profiles enables users to curate their online identity 84 , 114 . Editability is further enhanced by highly visible (public) self-presentations. Additionally, the constant availability of social media platforms enables adolescents to access and engage with their profiles at any time, and provides them with rapid quantitative feedback about their popularity among peers 89 , 115 . People receive more direct and public feedback on their self-presentation on social media than in other types of environment 116 , 117 . The affordances associated with self-presentation can have a particular impact during adolescence, a period characterized by identity development and exploration.

Social media environments might provide more opportunities than offline environments for shaping one’s identity. Indeed, public self-presentation has been found to invoke more prominent identity shifts (substantial changes in identity) compared with private self-presentation 118 , 119 . Concerns have been raised that higher Internet use is associated with decreased self-concept clarity. Only one study of 101 adolescents as well as adults reviewed in a 2021 meta-analysis 120 showed that the intensity of Facebook use (measured by the Facebook Intensity Scale) predicted a longitudinal decline in self-concept clarity 3 months later, but the converse was not the case and changes in self-concept clarity did not predict Facebook use 121 . This result is still not enough to show a causal relationship 121 . Further, the affordances of persistence and replicability could also curtail adolescents’ ability to explore their identity freely 122 .

By contrast, qualitative research has highlighted that social media enables adolescents to broaden their horizons, explore their identity and identify and reaffirm their values 123 . Social media can help self-presentation by enabling adolescents to elaborate on various aspects of their identity, such as ethnicity and race 124 or sexuality 125 . Social media affordances such as editability and visibility can also facilitate this process. Adolescents can modify and curate self-presentations online, try out new identities or express previously undisclosed aspects of their identity 126 , 127 . They can leverage social media affordances to present different facets of themselves to various social groups by using different profiles, platforms and self-censorship and curation of posts 128 , 129 . Presenting and exploring different aspects of one’s identity can have mental health implications for minority teens. Emerging research shows a positive correlation between well-being and problematic Internet use in transgender, non-binary and gender-diverse adolescents (age 13–18 years), and positive sentiment has been associated with online identity disclosures in transgender individuals with supportive networks (both adolescent and adult) 130 , 131 .

Cognitive mechanisms

Adolescents and adults might experience different socio-cognitive impacts from the same social media activity. In this section, we review four cognitive mechanisms via which social media and its affordances might influence the link between adolescent development and mental health vulnerabilities (Fig.  3 ). These mechanisms (self-concept development, social comparison, social feedback and exclusion) roughly align with a previous review that examined self-esteem and social media use 115 .

Self-concept development

Self-concept refers to a person’s beliefs and evaluations about their own qualities and traits 132 , which first develops and becomes more complex throughout childhood and then accelerates its development during adolescence 133 , 134 , 135 . Self-concept is shaped by socio-emotional processes such as self-appraisal and social feedback 134 . A negative and unstable self-concept has been associated with negative mental health outcomes 136 , 137 .

Perspective-taking abilities also develop during adolescence 133 , 138 , 139 , as does the processing of self-relevant stimuli (measured by self-referential memory tasks, which assess memory for self-referential trait adjectives 140 , 141 ). During adolescence, direct self-evaluations and reflected self-evaluations (how someone thinks others evaluate them) become more similar. Further, self-evaluations have a distinct positive bias during childhood, but this positivity bias decreases in adolescence as evaluations of the self are integrated with judgements of other people’s perspectives 142 . Indeed, negative self-evaluations peak in late adolescence (around age 19 years) 140 .

The impact of social media on the development of self-concept could be heightened during adolescence because of affordances such as personalization of content 143 (the degree to which content can be tailored to fit the identity, preferences or expectations of the receiver), which adapts the information young people are exposed to. Other affordances with similar impacts are quantifiability, availability (the accessibility of the technology as well as the user’s accessibility through the technology) and public visibility of interactions 89 , which render the evaluations of others more prominent and omnipresent. The prominence of social evaluation can pose long-term risks to mental health under certain conditions and for some users 144 , 145 . For example, receiving negative evaluations from others or being exposed to cyberbullying behaviours 146 , 147 can, potentially, have heightened impact at times of self-concept development.

A pioneering cross-sectional study of 150 adolescents showed that direct self-evaluations are more similar to reflected self-evaluations, and self-evaluations are more negative, in adolescents aged 11–21 years who estimate spending more time on social media 148 . Further, longitudinal data have shown bidirectional negative links between social media use and satisfaction with domains of the self (such as satisfaction with family, friends or schoolwork) 47 .

Although large-scale evidence is still unavailable, these findings raise the interesting prospect that social media might have a negative influence on perspective-taking and self-concept. There is less evidence for the potential positive influence of social media on these aspects of adolescent development, demonstrating an important research gap. Some researchers hypothesize that social media enables self-concept unification because it provides ample opportunity to find validation 89 . Research has also discussed how algorithmic curation of personalized social media feeds (for example, TikTok algorithms tailoring videos viewed to the user’s interests) enables users to reflect on their self-concept by being exposed to others’ experiences and perspectives 143 , an area where future research can provide important insights.

Social comparison

Social comparison (thinking about information about other people in relation to the self 149 ) also influences self-concept development and becomes particularly important during adolescence 133 , 150 . There are a range of social media affordances that can amplify the impact of social comparison on mental health. For example, quantifiability enables like or follower counts to be easily compared with others as a sign of status, which facilitates social ranking 151 , 152 , 153 , 154 . Studies of older adolescents and adults aged, on average, 20 years have also found that the number of likes or reactions received predict, in part, how successful users judge their self-presentation posts on Facebook 155 . Furthermore, personalization enables the content that users see on social media to be curated so as to be highly relevant and interesting for them, which should intensify comparisons. For example, an adolescent interested in sports and fitness content will receive personalized recommendations fitting those interests, which should increase the likelihood of comparisons with people portrayed in this content. In turn, the affordance of association can help adolescents surround themselves with similar peers and public personae online, enhancing social comparison effects 63 , 156 . Being able to edit posts (via the affordance of editability) has been argued to contribute to the positivity bias on social media: what is portrayed online is often more positive than the offline experience. Thus, upward comparisons are more likely to happen in online spaces than downward or lateral comparisons 157 . Lastly, the verifiability of others’ idealized self-presentations is often low, meaning that users have insufficient cues to gauge their authenticity 158 .

Engaging in comparisons on social media has been associated with depression in correlational studies 159 . Furthermore, qualitative research has shown that not receiving as many positive evaluations as expected (or if positive evaluations are not provided quickly enough) increases negative emotions in children and adolescents aged between age 9 and 19 years 39 . This result aligns with a reinforcement learning modelling study of Instagram data, which found that the likes a user receives on their own posts become less valuable and less predictive of future posting behaviour if others in their network receive more likes on their posts 160 . Although this study did not measure mood or mental health, it shows that the value of the likes are not static but inherently social; their impact depends on how many are typically received by other people in the same network.

Among the different types of social comparison that adolescents engage in (comparing one’s achievements, social status or lifestyle), the most substantial concerns have been raised about body-related comparisons. One review suggested that social media affordances create a ‘perfect storm’ for body image concerns that can contribute to both socio-emotional and eating disorders 73 . Social media affordances might increase young people’s focus on other people’s appearances as well as on their own appearance by showing idealized, highly edited images, providing quantified feedback and making the ability to associate and compare oneself with peers constantly available 161 , 162 . The latter puts adolescents who are less popular or receive less social support at particular risk of low self-image and social distress 35 .

Affordances enable more prominent and explicit social comparisons in social media environments relative to offline environments 158 , 159 , 163 , 164 , 165 . However, this association could have a positive impact on mental health 164 , 166 . Initial evidence suggests beneficial outcomes of upward comparisons on social media, which can motivate behaviour change and yield positive downstream effects on mental health 164 , 166 . Positive motivational effects (inspiration) have been observed among young adults for topics such as travelling and exploring nature, as well as fitness and other health behaviours, which can all improve mental health 167 . Importantly, inspiration experiences are not a niche phenomenon on social media: an experience sampling study of 353 Dutch adolescents (mean age 13–15 years) found that participants reported some level of social media-induced inspiration in 33% of the times they were asked to report on this over the course of 3 weeks 168 . Several experimental and longitudinal studies show that inspiration is linked to upward comparison on social media 157 , 164 , 166 . However, the positive, motivating side of social comparison on social media has only been examined in a few studies and requires additional investigation.

Social feedback

Adolescence is also a period of social reorientation, when peers tend to become more important than family 169 , peer acceptance becomes increasingly relevant 170 , 171 , 172 and young people spend increasing amounts of time with peers 173 . In parallel, there is a heightened sensitivity to negative socio-emotional or self-referential cues 140 , 174 , higher expectation of being rejected by others 175 and internalization of such rejection 142 , 176 compared with other phases in life development. A meta-analysis of both adolescents and adults found that oversensitivity to social rejection is moderately associated with both depression and anxiety 177 .

Social media affordances might amplify the potential impact of social feedback on mental health. Wanting to be accepted by peers and increased susceptibility to social rewards could be a motivator for using social media in the first place 178 . Indeed, receiving likes as social reward activated areas of the brain (such as the nucleus accumbens) that are also activated by monetary reward 179 . Quantifiability amplifies peer acceptance and rejection (via like counts), and social rejection has been linked to adverse mental health outcomes 170 , 180 , 181 , 182 . Social media can also increase feelings of being evaluated, the risk of social rejection and rumination about potential rejection due to affordances such as quantifiability, synchronicity (the degree to which an interaction happens in real time) and variability of social rewards (the degree to which social interaction and feedback occur on variable time schedules). For example, one study of undergraduate students found that active communication such as messaging was associated with feeling better after Facebook use; however, this was not the case if the communication led to negative feelings such as rumination (for example, after no responses to the messages) 183 .

In a study assessing threatened social evaluation online 184 , participants were asked to record a statement about themselves and were told their statements would be rated by others. To increase the authenticity of the threat, participants were asked to rate other people’s recordings. Threatened social evaluation online in this study decreased mood, most prominently in people with high sensitivity to social rejection. Adolescents who are more sensitive to social rejection report more severe depressive symptoms and maladaptive ruminative brooding in both mediated and non-mediated social environments, and this association is most prominent in early adolescence 185 . Not receiving as much online social approval as peers led to more severe depressive symptoms in a study of American ninth-grade adolescents (between age 14 and 15 years), especially those who were already experiencing peer victimization 153 . Furthermore, individuals with lower self-esteem post more negative and less positive content than individuals with higher self-esteem. Posted negative content receives less social reward and recognition from others than positive content, possibly creating a vicious cycle 186 . Negative experiences pertaining to social exclusion and status are also risk factors for socio-emotional disorders 180 .

The impact of social media experiences on self-esteem can be very heterogeneous, varying substantially across individuals. As a benefit, positive social feedback obtained via social media can increase users’ self-esteem 115 , an association also found among adolescents 187 . For instance, receiving likes on one’s profile or posted photographs can bolster self-esteem in the short term 144 , 188 . A study linking behavioural data and self-reports from Facebook users found that receiving quick responses on public posts increased a sense of social support and decreased loneliness 189 . Furthermore, a review of reviews consistently documented that users who report more social media use also perceive themselves to have more social resources and support online 52 , although this association has mostly been studied among young adults using social network sites such as Facebook. Whether such social feedback benefits extend to adolescents’ use of platforms centred on content consumption (such as TikTok or Instagram) is an open question.

Social inclusion and exclusion

Adolescents are more sensitive to the negative emotional impacts of being excluded than are adults 170 , 190 . It has been proposed that, as the importance of social affiliation increases during this period of life 134 , 191 , 192 , adolescents are more sensitive to a range of social stimuli, regardless of valence 193 . These include social feedback (such as compliments or likes) 95 , 194 , negative socio-emotional cues (such as negative facial expressions or social exclusion) 174 and social rejection 172 , 185 . By contrast, social inclusion (via friendships in adolescence) is protective against emotional disorders 195 and more social support is related to higher adolescent well-being 196 .

Experiencing ostracism and exclusion online decreases self-esteem and positive emotion 197 . This association has been found in vignette experiments where participants received no, only a few or a lot of likes 198 , or experiments that used mock-ups of social media sites where others received more likes than participants 153 . Being ostracized (not receiving attention or feedback) or rejected through social media features (receiving dislikes and no likes) is also associated with a reduced sense of belonging, meaningfulness, self-esteem and control 199 . Similar results were found when ostracism was experienced over messaging apps, such as not receiving a reply via WhatsApp 200 .

Evidence on whether social media also enables adolescents to experience positive social inclusion is mostly indirect and mixed. Some longitudinal surveys have found that prosocial feedback received on social media during major life events (such as university admissions) helps to buffer against stress 201 . Adult participants of a longitudinal study reported that social media offered more informational support than offline contexts, but offline contexts more often offered emotional or instrumental support 202 . Higher social network site use is, on average, associated with a perception of having more social resources and support in adults (for an overview of meta-analyses, see ref. 52 ). However, most of these studies have not investigated social support among adolescents, and it is unclear whether early findings (for example, on Facebook or Twitter) generalize to a social media landscape more strongly characterized by content consumption than social interaction (such as Instagram or TikTok).

Still, a review of social media use and offline interpersonal outcomes among adolescents documents both positive (sense of belonging and social capital) and negative (alienation from peers and perceived isolation) correlates 203 . Experience sampling research on emotional support among young adults has further shown that online social support is received and perceived as effective, and its perceived effectiveness is similar to in-person social support 204 . Social media use also has complex associations with friendship closeness among adolescents. For example, one experience sampling study found that greater use of WhatsApp or Instagram is associated with higher friendship closeness among adolescents; however, within-person examinations over time showed small negative associations 205 .

Neurobiological mechanisms

The long-term impact of environmental changes such as social media use on mental health might be amplified because adolescence is a period of considerable neurobiological development 95 (Fig.  3 ). During adolescence, overall cortical grey matter declines and white matter increases 206 , 207 . Development is particularly protracted in brain regions associated with social cognition and executive functions such as planning, decision-making and inhibiting prepotent responses. The changes in grey and white matter are thought to reflect axonal growth, myelination and synaptic reorganization, which are mechanisms of neuroplasticity influenced by the environment 208 . For example, research in rodents has demonstrated that adolescence is a sensitive period for social input, and that social isolation in adolescence has unique and more deleterious consequences for neural, behavioural and mental health development than social isolation before puberty or in adulthood 206 , 209 . There is evidence that brain regions involved in motivation and reward show greater activation to rewarding and motivational stimuli (such as appetitive stimuli and the presence of peers) in early and/or mid adolescence compared with other age groups 210 , 211 , 212 , 213 , 214 .

Little is known about the potential links between social media and neurodevelopment due to the paucity of research investigating these associations. Furthermore, causal chains (for example, social media increasing stress, which in turn influences the brain) have not yet been accurately delineated. However, it would be amiss not to recognize that brain development during adolescence forms part of the biological basis of mental health vulnerability and should therefore be considered. Indeed, the brain is proposed to be particularly plastic in adolescence and susceptible to environmental stimuli, both positive and negative 208 . Thus, even if adults and adolescents experienced the same affective consequences from social media use (such as increases in peer comparison or stress), these consequences might have a greater impact in adolescence.

A cross-sectional study (with some longitudinal elements) suggested that habitual checking of social media (for example, checking for rewards such as likes) might exacerbate reward sensitivity processes, leading to long-term hypersensitization of the reward system 215 . Specifically, frequently checking social media was associated with reduced activation in brain regions such as the dorsolateral prefrontal cortex and the amygdala in response to anticipated social feedback in young people. Brain activation during the same social feedback task was measured over subsequent years. Upon follow-up, anticipating feedback was associated with increased activation of the same brain regions among the individuals who checked social media frequently initially 215 . Although longitudinal brain imaging measurements enabled trajectories of brain development to be specified, the measures of social media use were only acquired once in the first wave of data collection. The study therefore cannot account for confounds such as personality traits, which might influence both social media checking behaviours and brain development. Other studies of digital screen use and brain development have found no impact on adolescent functional brain organization 216 .

Brain development and heightened neuroplasticity 208 render adolescence a particularly sensitive period with potentially long-term impacts into adulthood. It is possible that social media affordances that underpin increased checking and reward-seeking behaviours (such as quantifiability, variability of social rewards and permanent availability of peers) might have long-term consequences on reward processing when experienced during adolescence. However, this suggestion is still speculative and not backed up by evidence 217 .

Stress is another example of the potential amplifying effect of social media on adolescent mental health vulnerability due to neural development. Adolescents show higher stress reactivity because of maturational changes to, and increased reactivity in, the hypothalamic–pituitary–adrenal axis 218 , 219 . Compared with children and adults, adolescents experience an increase in self-consciousness and associated emotional states such as self-reported embarrassment and related physiological measures of arousal (such as skin conductance), and heightened neural response patterns compared with adults, when being evaluated or observed by peers 220 . Similarly, adolescents (age 13–17 years) show higher stress responses (higher levels of cortisol or blood pressure) compared with children (age 7–12 years) when they perform in front of others or experience social rejection 221 .

Such changes in adolescence might confer heightened risk for the onset of mental health conditions, especially socio-emotional disorders 6 . Both adolescent rodents and humans show prolonged hypothalamic–pituitary–adrenal activation after experiencing stress compared with conspecifics of different ages 218 , 219 . In animal models, stress during adolescence has been shown to result in increased anxiety levels in adulthood 222 and alterations in emotional and cognitive development 223 . Furthermore, human studies have linked stress in adolescence to a higher risk of mental health disorder onset 218 and reviews of cross-species work have illustrated a range of brain changes due to adolescent stress 224 , 225 .

There is still little conclusive neurobiological evidence about social media use and stress, and a lack of understanding about which affordances might be involved (although there has been a range of work studying digital stress; Box  1 ). Studies of changes in cortisol levels or hypothalamic–pituitary–adrenal functioning and their relation to social media use have been mixed and inconclusive 226 , 227 . These results could be due to the challenge of studying stress responses in adolescents, particularly as cortisol fluctuates across the day and one-point readings can be unreliable. However, the increased stress sensitivity during the adolescent developmental period might mean that social media use can have a long-term influence on mental health due to neurobiological mechanisms. These processes are therefore important to understand in future research.

Box 1 Digital stress

Digital stress is not a unified construct. Thematic content analyses have categorized digital stress into type I stressors (for example, mean attacks, cyberbullying or shaming) and type II stressors (for example, interpersonal stress due to pressure to stay available) 260 . Other reviews have noted its complexity, and categorized digital stress into availability stress (stress that results from having to be constantly available), approval anxiety (anxiety regarding others’ reaction to their own profile, posts or activities online), fear of missing out (stress about being absent from or not experiencing others’ rewarding experiences) and communication overload (stress due to the scale, intensity and frequency of online communication) 261 .

Digital stress has been systematically linked to negative mental health outcomes. Higher digital stress was longitudinally associated with higher depressive symptoms in a questionnaire study 262 . Higher social media stress was also longitudinally related to poorer sleep outcomes in girls (but not boys) 263 . Studies and reviews have linked cyberbullying victimization (a highly stressful experience) to decreased mental health outcomes such as depression, and psychosocial outcomes such as self-esteem 103 , 146 , 147 , 264 , 265 . A systematic review of both adolescents and adults found a medium association ( r  = 0.26–0.34) between different components of digital stress and psychological distress outcomes such as anxiety, depression or loneliness, which was not moderated by age or sex (except for connection overload) 266 . However, the causal structure giving rise to such results is still far from clear. For example, surveys have linked higher stress levels to more problematic social media use and fear of missing out 267 , 268 .

Thus, the impact of digital stress on mental health is probably complex and influenced by the type of digital stressor and various affordances. For example, visibility and availability increase fear of negative public evaluation 269 and high availability and a social norm of responding quickly to messages drive constant monitoring in adolescents due to a persistent fear of upsetting friends 270 .

A range of relevant evidence from qualitative and quantitative studies documents that adolescents often ruminate about online interactions and messages. For example, online salience (constantly thinking about communication, content or events happening online) was positively associated with stress on both between-person and within-person levels in a cross-sectional quota sample of adults and three diary studies of young adults 271 , 272 . Online salience has also been associated with lower well-being in a pre-registered study of momentary self-reports from young adults with logged online behaviours. However, this study also noted that positive thoughts were related to higher well-being 273 . Furthermore, although some studies found no associations between the amount of communication and digital stress 272 , a cross-sectional study found that younger users’ (age 14–34 years and 35–49 years) perception of social pressure to be constantly available was related to communication load (measured by questions about the amount of use, as well as the urge to check email and social media) and Internet multitasking, whereas this was not the case for older users aged 50–85 years 274 . By contrast, communication load and perceived stress were associated only among older users.

Summary and future directions

To help to understand the potential role of social media in the decline of adolescent mental health over the past decade, researchers should study the mechanisms linking social media, adolescent development and mental health. Specifically, social media environments might amplify the socio-cognitive processes that render adolescents more vulnerable to mental health conditions in the first place. We outline various mechanisms at three levels of adolescent development — behavioural, cognitive and neurobiological — that could be involved in the decline of adolescent mental health as a function of social media engagement. To do so, we delineate specific social media affordances, such as quantification of social feedback or anonymity, which can also have positive impacts on mental health.

Our Review sets out clear recommendations for future research on the intersection of social media and adolescent mental health. The foundation of this research lies in the existing literature investigating the underlying processes that heighten adolescents’ risk of developing socio-emotional disorders. Zooming in on the potential mechanistic targets impacted by social media uses and affordances will produce specific research questions to facilitate controlled and systematic scientific inquiry relevant for intervention and translation. This approach encourages researchers to pinpoint the mechanisms and levels of explanation they want to include and will enable them to identify what factors to additionally consider, such as participants’ age 60 , the specific mental health outcomes being measured, the types of social media being examined and the populations under study 52 , 228 . Targeted and effective research should prioritize the most promising areas of study and acknowledge that all research approaches have inherent limitations 229 . Researchers must embrace methodological diversity, which in turn will facilitate triangulation. Surveys, experience sampling designs in conjunction with digital trace data, as well as experimental or neuroimaging paradigms and computational modelling (such as reinforcement learning) can all be used to address research questions comprehensively 230 . Employing such a multi-method approach enables the convergence of evidence and strengthens the reliability of findings 231 .

Mental health and developmental research can also become more applicable to the study of social media by considering how studies might already be exploring features of the digital environment, such as its design features and perceived affordances. Many cognitive neuroscience studies that investigate social processes and mental health during adolescence necessarily design tasks that can be completed in controlled experimental or brain scanning environments. Consequently, they tend to focus on digitally mediated interactions. However, researchers conceptualize and generalize their results to face-to-face interactions. For example, it is common across the discipline to not explicitly describe the interactions under study as being about social processes in digital environments (such as studies that assess social feedback based on the number of ‘thumbs up’ or ‘thumbs down’ received in social media 232 ). Considering whether cognitive neuroscience studies include key affordances of mediated (or non-mediated) environments, and discussing these in published papers, will make studies searchable within the field of social media research, enabling researchers to broaden the impact of their work and systematically specify generalizations to offline environments 233 .

To bridge the gap between knowledge about mediated and non-mediated social environments, it is essential to directly compare the two 233 . It is often assumed that negative experiences online have a detrimental impact on mental health. However, it remains unclear whether this mechanism is present in both mediated and non-mediated spaces or whether it is specific to the mediated context. For instance, our Review highlights that the quantification of social feedback through likes is an important affordance of social media 160 . Feedback on social media platforms might therefore elicit a greater sense of certainty because it is quantified compared with the more subjective and open-to-interpretation feedback received face to face 151 . Conducting experiments in which participants receive feedback that is more or less quantified and uncertain, specifically designed to compare mediated and non-mediated environments, would provide valuable insights. Such research efforts could also establish connections with computational neuroscience studies demonstrating that people tend to learn faster from stimuli that are less uncertain 234 .

We have chosen not to make recommendations concerning interventions targeting social media use to improve adolescent mental health for several reasons. First, we did not fully consider the bidirectional interactions between environment and development 35 , 235 , or the factors modulating adolescents’ differential susceptibility to the effects of social media 45 , 58 . For example, mental health status also influences how social media is used 47 , 58 , 59 , 236 , 237 (Box  2 ). These bidirectional interactions could be addressed using network or complexity science approaches 238 . Second, we do not yet know how the potential mechanisms by which social media might increase mental health vulnerability compare in magnitude, importance, scale and ease and/or cost of intervention with other factors and mechanisms that are already well known to influence mental health, such as poverty or loneliness. Last, social media use will probably interact with these predictors in ways that have not been delineated and can also support mental health resilience (for example, through social support or online self-help programmes). These complexities should be considered in future research, which will need to pinpoint not just the existence of mechanisms but their relative importance, to identify policy and intervention priorities.

Our Review has used a broad definition of mental health. Focusing on specific diagnostic or transdiagnostic symptomatology might reveal different mechanisms of interest. Furthermore, our Review is limited to mechanisms related to behaviour and neurocognitive development, disregarding other levels of explanation (such as genetics and culture) 34 , and also studying predominately Western-centric samples 239 . Mechanisms do not operate solely in linear pathways but exist within networks of interacting risk and resilience factors, characterized by non-linear and complex dynamics across diverse timescales 9 . Mechanisms and predisposing factors can interact and combine, amplifying mental health vulnerability. Mental health can be considered a dynamic system in which gradual changes to external conditions can have substantial downstream consequences due to system properties such as feedback loops 240 , 241 , 242 . These consequences are especially prominent in times of change and pre-existing vulnerability, such as adolescence 10 .

Indeed, if social media is a contributing factor to the current decline in adolescent mental health, as is commonly assumed, then it is important to identify and investigate mechanisms that are specifically tailored to the adolescent age range and make the case for why they matter. Without a thorough examination of these mechanisms and policy analysis to indicate whether they should be a priority to address, there is insufficient evidence to support the hypothesis that social media is the primary — or even just an influential and important — driver of mental health declines. Researchers need to stop studying social media as monolithic and uniform, and instead study its features, affordances and outcomes by leveraging a range of methods including experiments, questionnaires, qualitative research and industry data. Ultimately, this comprehensive approach will enhance researchers’ ability to address the potential challenges that the digital era poses on adolescent mental health.

Box 2 Effects of mental health on social media use

Although a lot of scientific discussion has focused on the impact of social media use on mental health, cross-sectional studies cannot differentiate between whether social media use is influencing mental health or mental health is influencing social media use, or a third factor is influencing both 51 . It is likely that mental health status influences social media use creating reinforcing cycles of behaviour, something that has been considered in the communication sciences literature under the term ‘transactional media effects’ 58 , 236 , 237 . According to communication science models, media use and its consequences are components of reciprocal processes 275 .

There are similar models in mental health research. For example, people’s moods influence their judgements of events, which can lead to self-perpetuating cycles of negativity (or positivity); a mechanism called ‘mood congruency’ 276 . Behavioural studies have also shown that people experiencing poor mental health behave in ways that decrease their opportunity to experience environmental reward such as social activities, maintaining poor mental health 277 , 278 . Although for many people these behaviours are a form of coping (for example, by avoiding stressful circumstances), they often worsen symptoms of mental health conditions 279 .

Some longitudinal studies found that a decrease in adolescent well-being predicted an increase in social media use 1 year later 47 , 59 . However, other studies have found no relationships between well-being and social media use over long-term or daily time windows 45 , 46 . One reason behind the heterogeneity of the results could be that how mental health impacts social media use is highly individual 45 , 280 .

Knowledge on the impact of mental health on social media use is still in its infancy and studies struggle to reach coherent conclusions. However, findings from the mental health literature can be used to generate hypotheses about how aspects of mental health might impact social media use. For example, it has been repeatedly found that young people with anxiety or eating disorders engage in more social comparisons than individuals without these disorders 281 , 282 , and adolescents with depression report more unfavourable social comparisons on social media than adolescents without depression 283 . Similar results have been found for social feedback seeking (for example, reassurance), including in social media environments 159 . Specifically, depressive symptoms were more associated with social comparison and feedback seeking, and these associations were stronger in women and in adolescents who were less popular. Individuals from the general population with lower self-esteem post more negative and less positive content than individuals with higher self-esteem, which in turn is associated with receiving less positive feedback from others 185 . There are therefore a wide range of possible ways in which diverse aspects of mental health might influence specific facets of how social media is used — and, in turn, how it ends up impacting the user.

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Acknowledgements

A.O. and T.D. were funded by the Medical Research Council (MC_UU_00030/13). A.O. was funded by the Jacobs Foundation and a UKRI Future Leaders Fellowship (MR/X034925/1). S.-J.B. is funded by Wellcome (grant numbers WT107496/Z/15/Z and WT227882/Z/23/Z), the MRC, the Jacobs Foundation, the Wellspring Foundation and the University of Cambridge.

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11 social psychology research topics to explore in 2024

Last updated

6 March 2024

Reviewed by

Miroslav Damyanov

Social psychology is a constantly evolving field of study. It explores how our environment and other people influence our thoughts, feelings, beliefs, and goals. Social psychology uncovers how social interaction, perception, and influence impact individuals and groups. 

Taking a specific path to follow your interests and learn more about available areas can narrow your focus to find the ideal research project. 

Let’s take a look at current topics in social psychology to inspire your research. 

• Understanding social psychology research

Psychologists conduct experiments to better understand how different environmental factors and the influence of other people shape feelings and behaviors. 

Research projects explore various topics, from how a position of power can change behavior to the impact of positive social interactions. 

Various research designs allow researchers to develop projects that range from observational to experimental. 

What is an example of social psychology research?

Zimbardo randomly assigned college students the roles of prison guards or prisoners in a simulated prison environment. Despite knowing their roles were random, the guards exhibited increasing cruelty towards the prisoners. 

Researchers halted the study after six days due to extreme psychological distress. It revealed the profound impact of social roles and situations on human behavior, highlighting how people can adopt negative behaviors when given authority, even in a controlled setting.

• How to choose social psychology research topics

Social psychology is a diverse, highly studied area of science, so developing a unique project on a relevant topic can be challenging. 

When choosing a subject, begin by exploring your interests. After considering questions you'd like answers to and topics that intrigue you, narrow your scope. Explore specific areas of research, research designs, and subtopics. 

Once you've narrowed down your choices, seek literature and past studies on the subject. Consider how past research can raise additional questions about the topic. 

Develop your ideas by determining how to measure and test your research questions. 

Once you have a firm plan for your project, talk to your instructor for advice and approval before launching your studies. 

• Social psychology research topics

Social psychology has many nuances that influence human beliefs and behavior. Various elements of situations and relationships affect short- and long-term emotions and actions. 

The major research areas in social psychology are an ideal starting point to investigate as part of a psychology research project. 

These key focus areas within social psychology can be compelling psychology research topics:

1. Attitudes and attitude change

Research projects surrounding attitudes generally examine the components of attitudes and how they develop and can be changed. 

The three components of attitude are affective, behavioral, and cognitive. They’re also known as the ABCs. 

We form attitudes through a combination of upbringing, experience, and genetics. People can self-measure them in surveys or through researchers’ observations. 

Attitudes can change due to influence and environmental factors. They hugely affect human behavior, making them an important research topic in social psychology.

2. Attachment and relationships

Social connections shape our lives from the earliest moments, taking various forms that significantly impact our well-being. These connections have numerous advantages, such as heightened happiness and satisfaction. 

Social psychology explores these connections, examining diverse attachment styles to explain love, friendship, and attraction. 

Research in this domain investigates the repercussions of poorly formed social bonds and seeks to answer questions about how relationships influence group behavior. 

Additionally, studies in social psychology dissect the elements contributing to attraction, shedding light on the intricate dynamics that shape our social bonds and interactions. 

3. Authority and leadership

As revealed in the Stanford Experiment, authority can directly affect behavior. 

However, social psychology can further delve into the dynamics of people interacting with those in leadership roles. 

Milgram's Obedience to Authority study exemplifies this exploration. Stanley Milgram wanted to investigate how easily authority figures could influence people to commit atrocities.

In this study, participants assumed the role of teachers administering electric shocks to learners for incorrect answers. 65% delivered 450 volts of electricity under the directive of an authority figure. 

Research can consider the positive or negative elements of authority based on specific applications, settings, and environments. 

For example, we might consider obedience to authority positive in the workplace or classroom.

Social psychology research about groups delves into how behavior changes in group settings. 

Groups form for various reasons, and everything from leadership to group dynamics can impact how people behave. These behavioral changes can be beneficial or harmful. 

Research into group behavior can focus on decision-making, internal conflicts, conflicts with other groups, how groups affect individual identities, and much more. 

Studies can also investigate how positive group behaviors can influence someone. 

5. Prejudice

Prejudice and discrimination take different forms, which people may not be aware of. The origin and consequences of prejudice present many topics of study for researchers. 

Topics related to how prejudices form and why people maintain inaccurate stereotypes can uncover why people depend on stereotypes to make decisions. 

Many studies focus on the effects of discrimination and how to reduce prejudice. 

Research in this category can overlap with many other categories. For instance, group behavior and social influences can contribute to the formation of stereotypes and social categorization. 

6. Self and social identity

Many elements form the human perception of self. How we perceive ourselves may be substantially different from the viewpoint of others. 

Social psychologists are interested in learning how a person’s self-perception can influence factors like behavior and internal feelings like confidence. 

Our concept of self derives from various sources, such as abilities, social comparisons, interactions with others, and status. 

Researching how the perception of the inner self impacts social behaviors can unveil how social factors influence critical feelings like self-esteem. 

7. Pro- and anti-social behavior

How people’s social surroundings impact the way they respond to certain situations is defined as pro- or anti-social behavior. 

Positive and negative behaviors are based on accepted social norms. How someone responds during a specific event can reinforce or undermine those norms. 

For example, helping a stranger is prosocial, while vandalism is antisocial behavior. 

Studies have shown that prosocial behavior is contagious: Those who experience or observe it are more likely to help others. 

Antisocial behavior can have a similar effect but in a negative direction. Observing seemingly harmless acts, like littering and graffiti, can weaken social norms. This potentially invites more dangerous antisocial behavior.

Researchers can elaborate on this knowledge to consider why people help others without considering personal costs. They can also dig into what deters someone from taking an action they know is "the right thing to do." 

Exploring how society impacts positive and negative behaviors can shed light on ways to reduce negative behavior.

8. Social influence

Persuasion, peer pressure, obedience, and conformity are all forms of social influence. Like other areas of social psychology, these influences can be positive or negative. 

One of the earliest studies on social influence was Soloman Asch’s Conformity Line Experiment . 

Researchers put a participant in a test with seven conformists without knowing the conformists weren't true participants. Researchers asked them to compare the image of a target line with lines A, B, and C on another image. 

Early in the experiment, all conformists answered correctly, followed by the participant, who was always last. 

After a few rounds, the conformists began to provide wrong answers unanimously. On average, about a third of participants followed along with conformists to confirm clearly incorrect answers. 75% of participants confirmed at least one wrong answer. 

The control group had no conformists. Less than 1% of participants gave the wrong answer. 

Doctor and author Robert Cialdini takes the concept of influence further. He identified six universal principles of influence and persuasion to help people defend against dishonest influences. 

His studies conclude that these influences can sway people:

Reciprocation: The feeling we should repay what someone has provided

Social proof: When unsure about a decision, we follow the actions of others 

Liking: We generally agree with people we like and want them to agree with us

Authority: We are more likely to say yes to authority figures

Scarcity: We want more of what is less available

Commitment and consistency: Once we make a choice, we follow it with corresponding actions to justify the decision (even if we no longer believe in the choice)

Researchers can study how social influence guides the decision-making process and explore the positive and negative effects of conformity. Other experiments can explore the consequences of peer pressure and whether it can be beneficial. 

9. Social cognition

In the most basic sense, cognition is the brain gathering and understanding knowledge through sensations, thoughts, and experiences. It allows us to make sense of new information. 

Social cognition is how the brain processes information about individuals and groups of people. It includes the role of heuristics . These mental shortcuts enable us to function without constantly stopping to interpret everything in the environment. 

Research under the umbrella of social cognition can explore first impressions, how appearance affects our judgment, and how social interactions affect behavior. 

These studies can help psychologists understand how someone’s perception of social norms affects their self-image and behavior.

10. Violence and aggression

Exploration into violence and aggression attempts to better understand the factors and situations that cause aggression and how it impacts behaviors. 

Several types of aggressive behavior exist, ranging from gossiping to physical violence. Studies in this area examine the different types of aggression and the variables contributing to aggressive behavior. 

For instance, a pattern of aggression may relate to witnessing the behavior of a family member or traumatic experiences. Conversely, situational variables may trigger a single incidence of aggression.

A greater understanding of the role of social learning in aggressive behavior can lead to research about how social norms and public policy can decrease violent behavior. 

Learning more about the variables contributing to aggression and violence means researchers can use new knowledge to work toward solutions. 

11. Social representations

Social representations are a form of heuristics: a set of beliefs that make something unfamiliar easily understood. They allow people to apply specific bits of evidence-based data to individuals’ or groups’ actions to make ideas more familiar. 

Researchers may study the role of social representations in making new psychological or scientific information accessible to the average person. Studies may explore how we make sense of new information and how people organize and separate facts for rapid learning.

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Introducing Resilience Outcome Expectations: New Avenues for Resilience Research and Practice

• Research Paper
• Published: 06 May 2024

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• J. Hephsebha   ORCID: orcid.org/0000-0002-3884-7472 1 &
• Amrita Deb 1  

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The present paper introduces Resilience Outcome Expectations (ROE) as the belief in achieving positive adaptation results through one’s action despite an adversarial experience. Resilience is one of the most researched areas in positive psychology and is considered a key to managing mental health and well-being when faced with challenges. The study of resilience has progressed in four waves, encompassing identifying individual factors, recognizing complex processes, developing interventions, and exploring neuroscientific underpinnings for positive adaptation. Additionally, resilience research has been explored in various contexts and cultures, establishing its association with several variables like well-being, self-efficacy, and social support, among many others. Similarly, since the conceptualization of the outcome expectation’s (OE), considerable research has been conducted, illustrating its relevance and significance in different areas such as psychotherapy, exercise, and addictions. There is evidence to indicate that OEs are crucial in motivating, goal-setting toward behavior change, and translating goals into action. Despite such conclusive findings available in these areas, no study has exclusively investigated resilience and OEs. Hence, this paper spotlights new avenues for research by introducing ROE and outlining its usefulness in psychology research. Finally, potential implications of ROE for future directions in research, assessment, and practice are presented.

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Resilience is one of the most researched topics in positive psychology. Yet new ideas continue to gain the interest of researchers. It is defined as the ability of a dynamic system to adapt successfully to challenges that threatens its function, survival, or development through multisystem processes (Masten et al., 2021 ). The study of resilience has advanced in four significant waves of research as put forth by researchers such as Wright et al. ( 2013 ). The first wave of resilience focused primarily on identifying individual factors and environmental characteristics that facilitate survival in adversity (Masten & Garmezy, 1985 ). The second wave recognized the complex underlying and interwoven processes that foster positive adaptation (Cicchetti, 2010 ; Masten, 2007 ). The third wave aimed to test the theories of resilience and promote resilience through developing interventions (Masten, 2011 ) such that the occurrence of negative outcomes can be prevented in the first place (Wright et al., 2013 ). The fourth wave focused on the multilevel neuroscientific underpinnings of resilience (Masten, 2007 ), such as the complex interactions between genes and the environment (Gottlieb, 2007 ).

With time, resilience research has expanded to cover different contexts and cultures and established its association with several variables like well-being, self-efficacy, and social support among many others. Although resilience research has systematically progressed in four waves, none of these waves have made any attempt to explore outcome expectations (OEs) in resilience research. Considering the importance of resilience in OEs and the lack of attention to it, this paper attempts to introduce the concept and outline its usefulness in psychology research.

1 Resilience Outcome Expectations (ROE)

Resilience Outcome Expectations (ROE) are introduced as the belief in achieving positive adaptation results through one’s action despite an adversarial experience. This description is derived from Bandura’s ( 2001 ) definition of OEs, which presents it as the desired outcomes of intentional actions in which an individual engages. To the best of the authors’ knowledge, the term ROE has not been used in literature before. Subsequently, this paper proposes that the term ROE be used to refer to expected outcomes in resilience stemming from one’s course of actions.

Although there are no studies exclusively exploring OEs and resilience, there have been several attempts to connect expectations to resilience. For example, Arampatzi et al.’s ( 2019 ) study on positive expectations and resilience found that individuals with more positive expectations for the future experienced smaller decreases in subjective well-being and adapted faster to the adverse event as compared to those with less positive expectations. Additionally, individuals with consistent positive expectations before and during the adverse event had higher subjective well-being than those who shifted from positive to negative expectations. Research by Carver et al. ( 2010 ), Cohn et al. ( 2009 ), and Rand ( 2018 ) further present that positive expectations can serve as a source of psychological capital, engendering positive emotions, building better social relationships, and developing adaptive capacities to cope with life’s challenges. Moreover, individuals with higher levels of different types of positive expectancies, such as self-efficacy (Luszczynska et al., 2005 ), optimism (Carver et al., 2010 ), and hope (Roesch et al., 2010 ) are more likely to engage in active problem-focused coping and use lesser passive coping strategies like avoidance enabling them to remain resilient and exhibit growth despite difficult times. Therefore, individuals who expect positive future outcomes tend to evaluate stressful events more positively (Hecht, 2013 ). As a result, positive expectations serve as an anxiety and stress buffer, allowing people to remain happy in the wake of adverse events (Arampatzi et al., 2019 ).

Besides contributing to the improvement in psychological health and well-being (Carver et al., 2010 ; Conversano et al., 2010 ; Long & Gallagher, 2018 ), positive expectancies are also inversely associated with psychological distress markers, including aspects of depression, anxiety (Rand, 2018 ) and posttraumatic stress symptoms (Gallagher et al., 2019 ). Furthermore, fewer behavioral problems and resistance to peer pressure were associated with positive expectations among adolescents (Dubow et al., 2001 ). Such expectations contributed to resilience by acting as a buffer against negative outcomes (Tevendale et al., 2008 ; Raffaelli & Koller, 2005 ). Similarly, in response to challenging times, it is proposed that individuals with high ROE levels might expect to achieve positive outcomes from their actions. Thus, higher ROE may promote resilience in the face of contemporary adverse events like pandemic or war.

Overall, these studies outline the potential of positive expectations helping in achieving healthy adaptation. Hence, further research on how OEs can be important in resilience research is necessary.

2 OE and its Application: A Brief Background

Albert Bandura introduced the construct of OEs with his Social-Cognitive Theory in 1986. It refers to the anticipation of physical, self-evaluative, or affective, and social outcomes of one’s behavior (Bandura, 2001 ). OEs are believed to be crucial in motivating, goal-setting toward behavior change, and translating goals into action (Williams et al., 2005 ). Since then, an enormous amount of research has been conducted in different areas, indicating the significance of OEs in research. Some relevant findings from such investigations covering topics like psychotherapy, lifestyle behaviors, and career are discussed below to establish their importance and understand their scope in psychology research.

Psychotherapy is one area in which OE’s has gained widespread attention (Constantino et al., 2020 ). This is evident from abundant literature on treatment outcome expectations (TOE), which is described as patients’ expectations about the consequences of participating in treatment (Constantino et al., 2011 ). Studies on TOE report that higher pre-treatment OEs were significantly correlated with better post-treatment outcomes among patients (Constantino et al., 2018 ), greater satisfaction with the treatment (Hoogendam et al., 2021 ), collaborative working relationships with their therapist (Constantino et al., 2011 ), increased therapeutic alliances, better client outcomes (Dew & Bickman, 2005 ), improved treatment response to depression (Rutherford et al., 2010 ), and homework compliance; and was negatively related to attrition (Greenberg et al., 2006 ; Price & Anderson, 2012 ).

Likewise, in the context of substance abuse, research revealed that OEs are essential to understanding substance abuse behaviors like initiation, maintenance, withdrawal, and treatment (Kouimtsidis et al., 2014 ). For example, higher negative smoking OEs and positive abstinence OEs were related to better intent to quit (Kaufmann et al., 2020 ). Also, positive smoking cessation expectations included better health, lesser social pressure, and more financial resources (Garey et al., 2017 ). Similarly, positive alcohol OEs predicted an increase in alcohol consumption, and negative alcohol OEs predicted a decrease (Blume & Blume, 2014 ; Blume & Guttu, 2015 ). Though advantages of positive OEs exist in research, it is noteworthy that holding positive expectations are not always desirable in all situations. For instance, in addition to the above-presented studies, research specific to health risk behaviors presents that individuals who consume excessive alcohol may have several positive OEs about its perceived benefits, such as social confidence, while others may have negative expectations, such as feeling sick (Barnett et al., 2014 ; Jones et al., 2001 ). According to the findings, positive expectations from drinking motivate the initiation and maintenance of drinking, whereas negative expectations influence its cessation (Blume & Blume, 2014 ; Jones et al., 2001 ; Patrick et al., 2009 ).

Additionally, research in the area of exercise presents that OEs have a role in adopting and sustaining specific exercise behaviors among older adults (Bohlen et al., 2022 ; Wójcicki et al., 2009 ). Also, it was linked to engagement in physical activities and served as a potential source of motivation for increasing physical activity behavior in persons with multiple sclerosis (Morrison & Stuifbergen, 2014 ). In other studies, physically active individuals had higher social and overall OE scores (Dlugonski et al., 2011 ; Suh et al., 2011 ).

Research on OE has also been conducted in the area of career development. OEs are crucial in predicting vocational interests (Adachi, 2004 ), academic motivation (Domene et al., 2011 ), career choices, and goals (Lent, 2013 ; Lent & Brown, 2013 ; Lent et al., 2000 ). OE allows individuals to act in ways that will lead to valued outcomes in their careers (Lent & Brown, 2013 ).

Besides the discussion pertaining to specific topics detailed above, an essential point about expectations is that “having unrealistic or excessively high expectations promotes negative progress, leading to feelings of frustration and failure” (Reesor et al., 2017 , p. 431). For instance, studies on weight loss report that unrealistic weight-loss expectations are widespread and are significantly associated with poor long-term outcomes (Foster et al., 2001 ). Moreover, when unreasonable expectations remain unmet, individuals can be disappointed, frustrated, and have a sense of failure (Polivy, 2001 ), resulting in goal abandonment and poor performance in goal accomplishment (Foster et al., 2001 ). Individuals in weight loss programs frequently have unrealistic expectations or are not fully aware of the required behavioral changes to meet their targets, resulting in frustration and giving up (Polivy, 2001 ). Therefore, it is vital to understand and distinguish between potentially possible and unattainable expectations to avoid failure and distress.

Overall, OE research is widespread, just like resilience research. It has been studied in various contexts and with multiple variables, as presented above through the work of researchers such as Bohlen et al. ( 2022 ), Constantino et al. ( 2020 ), Kouimtsidis et al. ( 2014 ), Lent and Brown ( 2013 ) among others. Yet, no study has attempted to exclusively research resilience and OE.

3 ROE and Related Constructs

A literature review has shown that several constructs, including OE, self-efficacy, dispositional optimism (DO), and hope, are commonly studied under the broad term of expectations. While these variables may appear similar in some ways, they are also distinctly different. Therefore, it is important to bring to attention the differences among these variables as well as their connections with ROE.

Bandura ( 1977 ) defined OEs as anticipated positive or negative consequences resulting from engaging in a behavior. It is the degree to which one believes a particular outcome will occur. Following this, ROE can be presented as the belief in achieving positive outcomes from the deliberate actions one chooses to engage in. In contrast, self-efficacy is the degree of conviction about successfully being able to execute the behavior required to produce an outcome (Bandura, 1977 ). Although self-efficacy and OEs are part of the cognitive process preceding an action, self-efficacy influences an individual’s choices, aspirations, amount of effort to be put in, and the extent of perseverance in the face of challenges (Bandura & Adams, 1977 ). However, OEs influence the satisfaction levels in task achievement and the enthusiasm to engage in similar or more challenging tasks (Takahashi, 2007 ). Following this, it can be deduced that self-efficacy differs from ROE in that self-efficacy represents the perceived capability to carry out a behavior, and ROE indicates an individual’s intention to carry out behavior to achieve resilient outcomes.

Like self-efficacy, DO, and hope are other research areas closely resembling OE. DO is an individual’s general expectation for the occurrence of good rather than bad things in life (Scheier & Carver, 1987 ). It is a personality trait that reflects the extent to which people have generalized positive expectations for their future (Carver & Scheier, 2014 ). Snyder and colleagues ( 1991 ) defined hope as a positive feeling and motivational state that emerges from the belief of having agency and pathways needed to achieve one’s goals. It is a cognitive goal-oriented thought pattern of bringing up multiple pathways to achieve a goal, maintaining motivation to follow such pathways, and actively developing new pathways if required (Snyder, 2002 ). As described, the focus of DO is on more generalized expectations and emphasizes less on how or why the goal is attained (Carver & Scheier, 2002 ). In contrast, hope emphasizes the presence of goal-directed determination and the identification of specific means to achieve those goals (Rand & Cheavens, 2009 ; Snyder, 2002 ; Snyder et al., 1991 ). On this note, DO differs from hope and ROE, as these constructs emphasize the actions one adopts to achieve their desired goals. This means that hope and ROE explicitly focuses on the personal self-initiated actions one chooses to engage in to successfully achieve a future desired outcome. Additionally, with DO, an individual can expect desirable outcomes due to luck, external circumstances, personal or other’s actions, unlike relying specifically on one’s self capabilities and actions to achieve a positive future outcome (Alarcon et al., 2013 ).

As evident from the discussion above, hope and OEs share a few similarities. Nevertheless, these two constructs are different, as confirmed by researchers (e.g., Clayton et al., 2008 ; David et al., 2004 ; Montgomery et al., 2003 ). For instance, OEs are grounded in learned associations, past experiences, reasoning, and a probabilistic estimation of occurrence (Leung et al., 2009 ). In contrast, hope is associated with desirability, where the incidence of an event is likely possible but not necessarily probable (Kamihara et al., 2015 ; Leung et al., 2009 ). “This OEs not mean that expectancies are better than hope, but that hope is different, mainly grounded on personal ideals, values, and beliefs instead of objective facts” (Krafft et al., 2021 , p.220). Both constructs represent possible outcomes. However, while many preferred outcomes involve personal assessments of their probability of occurrence, some persist despite indicating a lesser likelihood of accomplishment. Therefore, unlike hope, ROE is based on the probabilistic estimates of the occurrence of a positive outcome from one’s intentional acts.

Based on this discussion, it is possible to conclude that SE, DO, and hope are related to ROE but also distinct from it. The key features of ROE and its related constructs are summarized in Table 1 .

4 The Need for ROE Research

The literature reviewed above establishes the significance of OE in various contexts and how positive expectations act as a source to foster resilience. Also, forming OEs to achieve one’s goals is understood to help in planning and executing actions. However, there is limited evidence on how OE contributes to resilience and vice versa. A careful review of OE research shows that individuals in different contexts, like health, treatment, or recovery, frequently negotiate with adversities to overcome from and adapt to it, with the overall aim of improving their life conditions. Despite this aspect of OE research, resilience was not found to be the main focus of studies available in the literature. Yet, from the findings, it may be inferred that adaptation to challenges is a crucial part of the process through which individuals make their life circumstances better. For example, in the context of psychotherapy, Snippe et al. ( 2015 ) aimed to determine whether high early OE predicted the desired outcome, that is, symptom improvement. In this study, resilience was not the focus and, hence, not specifically investigated. However, the improvement in symptoms upon participating in the treatment despite experiencing the challenges associated with chronic illness might be indicative of resilience. Therefore, it is important to investigate these indications further to gain a specific understanding of the connections between OE and resilience. Such investigations on ROE can provide interesting insights into the process and outcome, including predictions after adversity.

5 Implications and Future Directions

In view of the gaps identified in OE and resilience literature, implications and future directions in specific areas are highlighted below.

5.1 Research

As ROE is an unexplored area of research, studies are yet to identify what individual and social factors contribute to ROE and how. The following section attempts to discuss these contributors that can aid future work in the area.

Resilience was earlier viewed as a set of individual characteristics that facilitated successful coping with distress (Kumpfer, 2002 ). The first wave of resilience research delineated many individual factors responsible for adaptation despite adversity. These included problem-solving skills, self-confidence, and high self-esteem (see Wright et al., 2013 ). Similarly, within OE research, studies on individual personality factors have identified a number of contributors. For instance, Brown and Cinamon ( 2015 ) confirmed that higher levels of conscientiousness among students contributed to better OEs in academics. Both resilience and OE studies have, on their own attempted to identify the role of individual factors. It is now important for researchers to identify factors that contribute to ROE.

In recent times, there has been growing interest in studying resilience through a multisystemic approach as recommended by Ungar and Theron ( 2020 ), among others. Observations from researchers, including Ungar ( 2013 ), do not suggest treating it as an individual construct as it is a quality of the environment and its capacity to facilitate growth. Individuals vary in coping across cultures despite experiencing similar adversities (Ungar, 2006 ). For instance, in Raghavan and Sandanapitchai’s ( 2019 ) multinational sample, participants who identified as Asian or South Asian scored significantly higher on resilience scores than their American counterparts. Hence, it can be derived from such findings that culture affects resilience. Similarly, it influences expectations too. Expectations about appropriate ways to cope with adversity are rooted in culture as they influence interactions between the environment and the individual (Ungar, 2013 ). Lent ( 2013 ) further confirms the role of cultural factors in influencing OEs. For example, the stress experienced by international students pursuing academics in different countries due to difficulties in adjusting to new cultural environments has negatively influenced their career OEs (see Franco et al., 2018 ). Therefore, future researchers must uncover the underlying cultural factors for forming and shaping ROE in the face of adversity.

5.2 Methods and Assessment

The dearth of literature on ROE draws attention to the lack of standardized tools to measure this variable. It is essential to develop specific instruments for a sound understanding of ROE. This will also ensure that it is considered distinct from self-efficacy, hope, optimism, or similar variables. ROE tools can be further used to study the associations between ROE and other factors contributing to well-being. In addition to the focus on quantifying ROE, there is a scope and necessity for qualitative studies as well. The subjectivity of ROE can be comprehended better through a mixed-method approach, with qualitative methods tapping into the intricacies of individual adaptation and systemic influences. Additionally, it is likely to facilitate an understanding of the ROE process, leading to adaptive outcomes. Moreover, considering the dynamic nature of expectations, they can be subject to change. Longitudinal study designs can help in capturing how the prior framed ROE are maintained until the desired outcome is achieved. More specifically, the extent of change in ROE, if any, can be tracked over time. Furthermore, life-altering experiences with adversities can be understood through in-depth case studies exploring personal journeys of resilience reintegration and the role of ROE in it.

Exploring the suggestions presented above will aid in developing theoretical models to track an individual’s resistance and recovery from adverse events, address the gaps in research and add to the literature specifically to ROE and broadly to the positive psychology field.

5.3 Clinical Practice

ROE has significant importance in clinical practice. As cognitions are flexible, expectations can be reinforced using psychotherapy or self-guided strategies (Gallagher et al., 2019 ). Consequently, individuals experiencing distress due to specific adversities can benefit from therapy or counseling aimed at developing and maintaining ROE. In therapeutic settings, clients can introspect and navigate various courses of action to achieve resilient outcomes by addressing their OEs. Likewise, it provides an opportunity to correct any unrealistic negative expectations that hinder attaining positive outcomes. Moreover, OEs are considered influential beliefs crucial to individual’s motivation to perform or change a behavior (Bandura, 1997; Fasbender, 2018 ). Hence, exploring ROE in therapy can enable the individual and their therapist to gain insights into the client’s motivational level and readiness to change. Besides traditional therapy accessed through professionals, self-help therapies via training programs and smartphone applications can be designed to incorporate self-administered ROE exercises for specific adverse situations.

Davis et al. ( 2009 ) observe that for most people, adversity need not be a major disaster, rather they could be the modest disruptions embedded in everyday lives. The recent pandemic is an example where even those not diagnosed with the coronavirus faced major or minor disruptions and had to incorporate changes into their regular lives while living in stressful situations. Similarly, experiences often may not be due to a severe, persistent underlying mental health condition and traumatic. Instead, the challenge might reflect the inability to manage a situation efficiently due to short-term stress. These include experiencing academic stressors like examination anxiety, assignment deadlines, or organizational stressors like work overload and role conflict. In all of the examples cited above, reinforcing ROE is expected to be helpful in identifying one’s goals and navigating different means of resources to achieve these outcomes. Thus, findings from ROE studies can be applied to a wide range of challenging situations.

Overall, it can be concluded that ROE has significant theoretical and practical implications.

6 Conclusion

Everyone experiences some adversity in life that disrupts their healthy functioning. These can range from daily hassles and regular life events to unexpected events like pandemics, natural calamities, and accidents. Furthermore, chronic, developmental, and genetically causing ailments greatly impact individuals and require resilience to resist, survive, and thrive. Moreover, multiple adversarial experiences affecting more than one area of life often lead to a cumulative risk. In such instances, ROE, the belief to achieve positive adaptation results through one’s action, can provide an individual with the right direction to achieve the desired results. Estimating desired yet probabilistic outcomes from one’s actions can help in realistic planning, adopting more adaptive pathways, and engaging in active coping strategies. Such expectations can aid in dealing with challenges effectively and contribute to their overall well-being.

Data Availability

No primary data was collected for the paper. Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

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This study is a part of the first author’s doctoral thesis which is funded by the University Grants Commission (UGC), Government of India.

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Hephsebha, J., Deb, A. Introducing Resilience Outcome Expectations: New Avenues for Resilience Research and Practice. Int J Appl Posit Psychol (2024). https://doi.org/10.1007/s41042-024-00164-3

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Accepted : 22 April 2024

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DOI : https://doi.org/10.1007/s41042-024-00164-3

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