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Child and Adolescent Development

• First Online: 28 January 2017

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• Rosalyn H. Shute 3 &
• John D. Hogan 4  

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For school psychologists, understanding how children and adolescents develop and learn forms a backdrop to their everyday work, but the many new ‘facts’ shown by empirical studies can be difficult to absorb; nor do they make sense unless brought together within theoretical frameworks that help to guide practice. In this chapter, we explore the idea that child and adolescent development is a moveable feast, across both time and place. This is aimed at providing a helpful perspective for considering the many texts and papers that do focus on ‘facts’. We outline how our understanding of children’s development has evolved as various schools of thought have emerged. While many of the traditional theories continue to provide useful educational, remedial and therapeutic frameworks, there is also a need to take a more critical approach that supports multiple interpretations of human activity and development. With this in mind, we re-visit the idea of norms and milestones, consider the importance of context, reflect on some implications of psychology’s current biological zeitgeist and note a growing movement promoting the idea that we should be listening more seriously to children’s own voices.

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Shute, R.H., Hogan, J.D. (2017). Child and Adolescent Development. In: Thielking, M., Terjesen, M. (eds) Handbook of Australian School Psychology. Springer, Cham. https://doi.org/10.1007/978-3-319-45166-4_4

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Ecological Influences on Child and Adolescent Development: Evidence from a Philippine Birth Cohort

The largest number of children and young people in history are alive today, so the costs of them failing to realise their potential for development are high. Most live in low-income and lower-middle-income countries (LLMICs), where they are vulnerable to risks that may compromise their development. Yet many risk factors in LLMICs are not well understood. Moreover, recent studies suggest that in addition to the critical first 1,000 days there are several key periods of development in later childhood and adolescence which have received comparatively little research attention. This work responds to the gaps in the evidence, examining the influence of exposure to risks in the physical and social environment on health, education and development outcomes in a birth cohort of children from the Philippines. The first chapter provides a brief introduction to the theoretical and empirical evidence on the risks children face in LLMICs as well as a description of the Philippine country context and the birth cohort. The second chapter tests the associations between infant exposure to sanitation risks and subsequent school survival. The third chapter investigates the effects of housing instability in early to middle childhood on cognitive performance at 11 years of age. And, the fourth chapter examines the links between forms of social marginalisation and adolescent mental health and wellbeing. This work’s findings suggest infant exposure to faecal contamination in the home environment shortens the overall length of time children later spend at school. Preprimary-school age children appear to be at risk of developmental deficits and/or delays as a result of changes to their neighbourhood environment. And, adolescents who are excluded or become disengaged from the important socialising institutions of school and the workplace are at increased risk from developing mental disorders, while among older teens the protective effects associated with being in employment are greater than those linked to being in education.

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National Research Council (US) and Institute of Medicine (US) Forum on Adolescence; Kipke MD, editor. Adolescent Development and the Biology of Puberty: Summary of a Workshop on New Research. Washington (DC): National Academies Press (US); 1999.

Adolescent Development and the Biology of Puberty: Summary of a Workshop on New Research.

• Hardcopy Version at National Academies Press

Key Findings of Recent Studies

The workshop included a series of panel discussions that focused on adolescence as experienced by both human and nonhuman primates, including neuroendocrine physiology at puberty, the interplay between pubertal development and behavior, and implications for research, policy, and practice. Here we briefly summarize key findings from some of the studies that were discussed at the workshop (also see Crockett and Petersen, 1993; Grumbach and Styne, 1998; Pusey, 1990; Suomi, 1997;1991). As previously noted, this summary is not intended to provide a comprehensive review of the new research in this field; rather, it highlights important new findings that emerged during the workshop presentations and discussions.

• In the United States, the Onset of Puberty Occurs Earlier than was Previously Recognized.

Over the last 150 years, girls' sexual maturation, as measured by the age of menarche, is occurring at younger ages in all developed countries by at least two to three years. In the mid-nineteenth century, the average age at which girls reached menarche was approximately 15. The trend toward earlier menarche is now being documented in developing countries as well. Improved diets and more effective public health measures are the reasons often cited for this trend (Garn, 1992).

Research conducted during the 1990s greatly enhanced researchers' understanding of the age of puberty among girls. For example, although the onset of menarche is still considered to be a significant indicator of the tempo of maturation, researchers now view menarche as a late event in the pubertal process. At the workshop, Frank Biro presented data from the Growth and Health Study funded by the National Heart, Lung, and Blood Institute. This longitudinal study enrolled a cohort of over 2,000 girls, ages 9 to 10 years in 1987–1988; approximately half of the sample was white and half was black; the sample was recruited from clinics at three clinical centers located in Richmond, California, Cincinnati, Ohio, and metropolitan Washington, D.C. According to the study design, girls' maturation stage and body mass index were assessed annually; data for other variables, such as household income, nutrition, physical activity, cardiovascular risk factors, self-esteem and self-perception, and other psychosocial measures, were collected biennially (Brown et al., 1998). Almost half of the participants had begun puberty before the onset of the study. According to Biro, indicators of pubertal growth have been observed as early as age 7. These findings suggest that as children experience puberty and other developmental changes at earlier ages, there may be the need to consider how to design and deliver age-appropriate interventions during the middle childhood and preteen years, to help them avoid harmful or risky behaviors and develop a health-promoting lifestyle.

• There is Significant Variation Among Individuals in the Timing of Puberty.

There is variation in both the onset and the tempo of puberty. Research shows that the timing of puberty can affect other aspects of development, especially for girls. Jeanne Brooks-Gunn discussed the findings from a recent study, which recruited a community sample of nearly 2,000 high school students from urban and rural areas of western Oregon. The study found that early-maturing girls and late-maturing boys showed more evidence of adjustment problems than other adolescents (Graber et al., 1997).

• Multiple Factors Affect the Age of Puberty.

Research now suggests that the timing of puberty can be affected by a wide range of factors, including genetic and biological influences, stress and stressful life events, socioeconomic status, environmental toxins, nutrition and diet, exercise, amount of fat and body weight, and the presence of a chronic illness. Research also shows that the family, the peer group, the neighborhood, the school, the workplace, and the broader society have all been shown to influence adolescent developmental outcomes, although it is less clear if these factors influence pubertal development. With respect to school settings, research suggests that the transition from small elementary schools to larger, more anonymous middle schools can be a stressful event in the lives of children (National Research Council, 1993). Some of the stressful influences or events factors mentioned above have been correlated with pubertal timing, but a causal relationship cannot be assumed.

• Stress does not Trigger Puberty, But it does Modulate the Timing of Puberty.

In her remarks at the workshop, Elizabeth Susman took note of research correlating stress and the timing of puberty. 1 A review of this literature shows that researchers observe different effects of stress at different stages of puberty (Susman et al., 1989). For example, stress appears to delay maturation for young adolescents but to precipitate puberty for older adolescents. According to Susman, it makes sense that stress would delay maturation because stress hormones tend to suppress reproductive hormones (Susman, 1997; Graber and Warren, 1992). She added that her research has not yet resolved the question of directionality: Do environmental stressors affect the reproductive hormones, or does the rate of maturation affect the level of circulating stress hormones? Other participants at the meeting noted that social factors influence this process as well. For example, family conflict appears to be associated with earlier menarche in girls (Graber et al., 1995).

• There is some Evidence that, on Average, Girls experience more distress during adolescence than boys.

Some researchers have speculated that, for girls, the transition during puberty brings about greater vulnerability to other environmental stressors (Ge et al., 1995). In particular, a growing literature suggests that the early onset of puberty can have an adverse effect on girls' development (Caspi et al., 1993; Ge et al., 1996). It can affect their physical development (they tend to be shorter and heavier), their behavior (they have higher rates of conduct disorders); and emotional development (they tend to have lower self-esteem and higher rates of depression, eating disorders, and suicide). The youngest, most mature children are those at greatest risk for delinquency.

Early-maturing boys also appear to have higher rates of delinquency (Graber et al., 1997; Rutter and Smith, 1995). Generally speaking, however, boys who mature early fare better than late bloomers. Because they are taller and more muscular than their age-mates, they may be more confident, more popular, and more successful both in the classroom and on the playing field. In contrast, late-maturing boys have a poorer self-image, poorer school performance, and lower educational aspirations and expectations (Dorn et al., 1988; Litt, 1995).

• Girls from Ethnic Minority Groups may be Reaching Puberty Earlier than White Girls.

Data presented at the workshop show that for black girls, the average age of menarche is 12.1 years, compared with 12.9 years for white girls (see Brown et al., 1998). Black girls also begin pubertal development earlier than their white peers do—by 15 months. Interestingly, even though they reach menarche earlier, tempo of the pubertal development is slower. Researchers have also found that self-esteem does not follow the same developmental pattern in black and white girls. It appears that black girls' higher self-esteem may be rooted in cultural differences in attitudes toward physical appearance and obesity (Brown et al., 1998). In general, however, the factors that protect some girls and place others at risk are not well understood. It is important to note that these findings are preliminary in nature, and more research is need to further validate them, as well as determine if these differences apply to girls from other ethnic, and racial groups, such as Hispanics, American Indians, Asians, and Pacific Islanders.

• Puberty may be a Better Predictor of Aggression and Problem Behaviors than Age.

There is growing evidence to suggest that puberty rather than chronological age may signal the onset of delinquency and problem behaviors among some teenagers (Keenan and Shaw, 1997; Rutter et al., 1998). For example, early maturers—both mate and female—are more likely than other adolescents to report delinquency. Early-maturing females also appear to be at increased risk for victimization, especially sexual assault, and this may partially explain their greater likelihood of problem behaviors (Flannery et al., 1993; Raine et al., 1997). These findings suggest the need for interventions that are targeted to early-maturing adolescents who may be at increased risk for a wide range of behavior problems and associated poor developmental outcomes.

• Physical Maturation Appears to have Little Correlation with Cognitive Development.

Many developmental psychologists, most notably Jean Piaget, have documented an expanded capacity for abstract reasoning during adolescence. Today's adolescents are often capable of complex reasoning and moral judgment; their capacities frequently astonish parents and teachers. Indeed, IQ tests show an overall gain in cognitive capacities since the 1940s, when military personnel were tested in large numbers and achieved a median score of about 100. However, there appears to be little relationship between physical and cognitive maturation.

Researchers have tested the hypothesis that growth across the developmental spectrum—physical, cognitive, social, and emotional—proceeds on a similar timetable, and they have found little evidence to support this hypothesis. However, the research in this area is relatively weak, in part due to a lack of reliable, valid, easily administered instruments for assessing cognitive development (Litt, 1995). When cognitive development and capacities are not in sync with physical and sexual maturation, young people are more vulnerable; this also creates special challenges for designing and delivering age appropriate clinical interventions and services. Adults will often assume that adolescents who look older have a better grasp of the consequences of their actions.

• Brain Development Appears to Continue During Adolescence.

One of most remarkable findings in neurobiology over the last decade is the extent of change that can occur in the brain, even in the adult brain, as a function of the physical, social, and intellectual environment.

Starting in infancy and continuing into later childhood, there is a period of exuberant synapse growth followed by a period of synaptic ''pruning" which is largely completed by puberty. Although, neuroscientists have documented the time line of this synaptic waxing and waning, they are less sure about what it means for changes in childrens' and adolescents' cognitive development, behavior, intelligence, and capacity to learn. Generally, they point to correlations between changes in synaptic density or numbers and observed changes in behavior based on developmental and cognitive psychology. In coming decades, research tools such as positron emission tomography (PET) scans and functional magnetic resonance imaging (MRI) scans should greatly expand researchers' knowledge about adolescent brain development. In particular, functional imaging, if repeated over time, carries the potential for providing a better understanding of the functional connections between brain development and psychological performance (including cognitive development). New insights into brain development may also shed light on some psychopathologies and learning disabilities that affect preteens and adolescents, such as attention deficit/ hyperactivity disorder (ADHD), depressive disorders, and schizophrenia.

• Researchers are Also Providing New Insights into the Relationship Between Gender, Hormones, Brain Development, and Behavior.

In terms of the onset of puberty, boys generally follow girls by two years. For example, boys typically reach their maximum height velocity two years later than girls. In the realm of neuroscience, there is new evidence of divergent patterns of male and female brain development; these patterns have been observed between the ages of 5 and 7. Case in point: during this period, the amygdala (a part of the limbic system concerned with the expression and regulation of emotion and motivation) increases robustly in males, but not in females; the hippocampus (a part of the limbic system that plays an important role in organizing memories) increases robustly in females, but not in males. The basal ganglia are larger in females; this appears to be significant, since boys are more likely to have disorders, such as ADHD, that are associated with smaller basal ganglia. Girls may have extra protection against this type of disorder. Although there are clear differences in the path of brain development for girls and boys, it is not yet possible to look at a brain scan and determine whether the subject is male or female.

• Pregnancy During Adolescence may Alter the Physiological Development of Girls.

During pregnancy, young women at different points in pubertal development show comparable hormone profiles. Pregnancy in very young women may compromise their skeletal growth, preventing them from reaching maximum bone mass. Frank Biro noted that his research team, which followed several hundred adolescent pregnancies, found that, after giving birth, adolescent mothers were on average significantly heavier (by approximately 10 pounds) and fatter (having thicker skin folds) than their counterparts who had not given birth.

For the purposes of this discussion, stress is defined as a physical, mental, or emotional strain or tension. Stress is a normal part of everyone's life and need not be either good or bad; reactions to stress however, can vary considerably, with some reactions being unpleasant and/or undesirable.

• Cite this Page National Research Council (US) and Institute of Medicine (US) Forum on Adolescence; Kipke MD, editor. Adolescent Development and the Biology of Puberty: Summary of a Workshop on New Research. Washington (DC): National Academies Press (US); 1999. Key Findings of Recent Studies.
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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
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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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Social contextual risk taking in adolescence

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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Amy Orben & Tim Dalgleish

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Adrian Meier

Department of Psychology, University of Cambridge, Cambridge, UK

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Orben, A., Meier, A., Dalgleish, T. et al. Mechanisms linking social media use to adolescent mental health vulnerability. Nat Rev Psychol (2024). https://doi.org/10.1038/s44159-024-00307-y

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23 Conclusions: Adolescent Development Research and Its Impact on Global Policy

• Published: March 2018
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The concluding chapter of the volume integrates the most important points from each of the previous chapters and makes connections among the key points for researchers, policymakers, and individuals who work directly with adolescents and their families in applied settings. The chapter also provides a brief overview of additional issues facing adolescents that were not covered in depth in other chapters as well as a summary of methodological approaches to studying adolescents. The chapter ends with a set of recommendations for future research and actionable steps for policymakers and practitioners to improve the lives of adolescents in diverse settings around the world.

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Research on Child and Adolescent Development and Public Policy in Latin America

Affiliation.

• 1 Escuela de Psicología, Pontificia Universidad Católica de Chile.
• PMID: 27254830
• DOI: 10.1002/cad.20156

This commentary discusses the implication of child and adolescent development research for public policy in Latin America. As illustrated by the articles in this special issue, even though the research of child and adolescent development in Latin America is making significant progress, still more research is needed. Developmental research in the region faces the challenge of uncovering the mechanisms that affect child development in a context of high levels of poverty and inequality. In addition, researchers in the region should be particularly careful in using appropriate and rigorous methods, improving the design and adaptation of instruments that measure child and adolescent development, developing longitudinal datasets, and looking for causal evidence. Children and adolescents in Latin America will benefit from a further expansion of developmental research. Research in child and adolescent development using data from Latin America can advise policy makers and help improve the design and evaluation of interventions and public policies that promote child and adolescent well-being in the region.

© 2016 Wiley Periodicals, Inc.

• Adolescent Development*
• Child Development*
• Latin America
• Public Policy*

•   [email protected]

Psychology Research Guide

Child & adolescent development.

“Child development”, or “child and adolescent development” refers to the process of growth and maturation of the human individual from conception to adulthood. The term “adolescence” has particular connotations in particular cultural and social contexts. Child & Adolescent Psychology focuses on understanding the physical, social, psychological, and cognitive needs of young human beings. You can read more about the focus of Child & Adolescent Development on the American Psychological Association's Society of Clinical Child and Adolescent Psychology website This link opens in a new window . To find ideas for paper/research topics within child & adolescent development, visit these sites:

APA Psychology Topics This link opens in a new window (Try Bullying; Children; Education; Kids & the Media; Learning & Memory; Parenting; Teens)

Child & Adolescent Development Databases

Research in child & adolescent psychology utilizes core psychology resources, as well as resources in child & family development and sociology. You may find it helpful to search the following databases for your child & adolescent development topics or research questions, in addition to the core resources listed on the home page.

Child & Adolescent Development Subject Headings

You may find it helpful to take advantage of predefined subjects or subject headings in Shapiro Databases. These subjects are applied to articles and books by expert catalogers to help you find materials on your topic.

• Learn more about Subject Searching

Consider using databases to perform subject searches, or incorporating words from applicable subjects into your keyword searches. Here are some social psychology subjects to consider:

• adopted children
• Attachment Theory
• child abuse
• child behavior
• children of alcoholics
• cognitive development
• developmental stages
• early childhood development
• emotional development
• family relations
• middle school/junior high school/high school students
• parent child relations
• peer pressure
• personality

Child & Adolescent Development Organization Websites

• American Academy of Child and Adolescent Psychiatry (AACAP) This link opens in a new window A national professional medical association dedicated to treating and improving the quality of life for children, adolescents, and families affected by mental, behavioral, or developmental disorders.
• Child & Adolescent Development course module (UNHCR) This link opens in a new window This Resource Pack published by the United Nations High Commissioner on Refugees' Action for the Rights of Children (ARC) is a training module for those working with children and teen refugees. It covers major areas of child development acknowledging that " the concept of childhood is understood differently in different cultural and social contexts."
• Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD) This link opens in a new window NICHD’s mission is to lead research and training to understand human development, improve reproductive health, enhance the lives of children and adolescents, and optimize abilities for all.
• Society of Clinical Child & Adolescent Psychology (APA Division) This link opens in a new window The Society of Clinical Child and Adolescent Psychology is Division 53 of the American Psychological Association. Its purpose is to encourage the development and advancement of clinical child and adolescent psychology through integration of its scientific and professional aspects.
• Child Welfare Information Gateway - Understanding Adolescent Development This link opens in a new window United States Health & Human Services Children's Bureau Child Welfare Information Gateway has extensive resources on child & adolescent development. This link leads to their "Understanding Adolescent Development" resources page.
• << Previous: Applied Psychology
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• Open access
• Published: 24 October 2013

Research priorities for child and adolescent physical activity and sedentary behaviours: an international perspective using a twin-panel Delphi procedure

• Lauren Gillis 1 ,
• Grant Tomkinson 1 ,
• Timothy Olds 1 ,
• Carla Moreira 2 ,
• Candice Christie 3 ,
• Claudio Nigg 4 ,
• Ester Cerin 5 ,
• Esther Van Sluijs 6 ,
• Gareth Stratton 7 ,
• Ian Janssen 8 ,
• Jeremy Dorovolomo 9 ,
• John J Reilly 10 ,
• Jorge Mota 2 ,
• Kashef Zayed 11 ,
• Kent Kawalski 12 ,
• Lars Bo Andersen 13 ,
• Manuel Carrizosa 14 ,
• Mark Tremblay 15 ,
• Michael Chia 16 ,
• Mike Hamlin 17 ,
• Non Eleri Thomas 18 ,
• Ralph Maddison 19 ,
• Stuart Biddle 20 ,
• Trish Gorely 21 ,
• Vincent Onywera 22 &
• Willem Van Mechelen 23  

International Journal of Behavioral Nutrition and Physical Activity volume  10 , Article number:  112 ( 2013 ) Cite this article

44 Citations

43 Altmetric

Metrics details

The quantity and quality of studies in child and adolescent physical activity and sedentary behaviour have rapidly increased, but research directions are often pursued in a reactive and uncoordinated manner.

To arrive at an international consensus on research priorities in the area of child and adolescent physical activity and sedentary behaviour.

Two independent panels, each consisting of 12 experts, undertook three rounds of a Delphi methodology. The Delphi methodology required experts to anonymously answer questions put forward by the researchers with feedback provided between each round.

The primary outcome of the study was a ranked set of 29 research priorities that aimed to be applicable for the next 10 years. The top three ranked priorities were: developing effective and sustainable interventions to increase children’s physical activity long-term; policy and/or environmental change and their influence on children’s physical activity and sedentary behaviour; and prospective, longitudinal studies of the independent effects of physical activity and sedentary behaviour on health.

Conclusions

These research priorities can help to guide decisions on future research directions.

Recent research has shown that both physical activity and sedentary behaviour are associated with a wide range of current and future health outcomes [ 1 – 3 ]. In fact, physical activity and sedentary behaviour are two independent and not mutually exclusive behaviours with different effects on health outcomes [ 4 ]. In the short term, physical activity has been shown to be moderately and positively associated with bone health, aerobic fitness, blood lipid levels, self-esteem, mental activity and fundamental movement skills in children and adolescents [ 1 – 3 , 5 ]. In the long term, both physical activity and sedentary behaviour have been identified as major, independent, modifiable risk factors for mortality and morbidity from many chronic, non-communicable and potentially preventable diseases [ 6 – 9 ]. New evidence also suggests that the relation between sedentary behaviour and all-cause end cardiovascular disease mortality is independent of physical activity levels [ 7 ].

Chronic diseases place a large economic burden on health services and impose significant costs on society (e.g. premature death, underappreciated economic effects and greater reliance on treatment) [ 8 ]. Although the ill effects of chronic disease largely manifest in adulthood, it is increasingly understood that the development typically begins in childhood or adolescence [ 9 ]. Therefore, physical activity levels and sedentary behaviour performed in the early years could potentially influence the development of disease later on in life.

At present, a large quantity of research is being conducted into the physical activity and sedentary behaviour of children, yet the research community remains challenged to provide a solid evidence base [ 10 ]. This is in part due to a lack of international research collaboration and a high degree of study repetition. The aim of this study therefore was to arrive at a set of international research priorities for physical activity and sedentary behaviour to guide more meaningful and focussed research. Specifically, this study aimed to answer the following research question: “What are the most important international research issues for the next 10 years in child and adolescent physical activity and sedentary behaviour?” Agreement on research priorities may help to inform evidence-based policy, guide funding allocation, and direct research options for postgraduate students [ 11 , 12 ].

Existing literature

To identify existing evidence in this area, a systematic review of the English and non-English literature was performed using the following search terms: physical activit* OR motor activity (MeSH) OR sedentary behavio* AND child* OR adolescen* OR youth* AND research priorit* OR research agenda* OR research issue*. The databases PsychINFO (1887–), SPORTDiscus (1949–), Cochrane (1992–), CINAHL (1937–), ERIC (1966–) and PubMed (1950–) were searched in May 2012. Additional studies were also identified by contacting experts, Google searching and identifying potential studies in the reference lists of identified studies. Only four previously published papers that arrived at research priorities in child physical activity and/or sedentary behaviour were identified [ 11 , 13 – 15 ]. A working paper by Bull et al. [ 11 ] identified research priorities in physical activity with a focus on low to middle income countries. Evenson and Mota [ 13 ] highlighted research on the determinants and outcomes of physical activity and made recommendations for future study designs. Mountjoy et al. [ 15 ] identified existing gaps in physical activity research for children, with a focus on the need for greater collaboration between sport and existing programmes. The final study by Fulton et al. [ 14 ] had two aims. Firstly, the study aimed to review the current knowledge of existing methods for assessing physical activity and sedentary behaviour. Secondly, on the basis of this, the study aimed to set research priorities on the use of reliable and valid measurement tools to assess physical activity and sedentary behaviour in children aged 2–5 years.

While these studies were valuable contributions, they also had many limitations, including unsystematic participant selection, unstructured data collection procedures, and limited reporting on the process followed to arrive at the research priorities. Furthermore, the participants involved in the decision-making processes did not always represent the broader community of researchers, either from a geographical or institutional point of view. In addition, the anonymity of participants was not maintained during the consensus process. These limitations warranted a further study with an aim to arrive at a set of research priorities by employing a structured and rigorous methodology and improving reporting quality.

Methodology

Ethical approval for all aspects of the methodology was granted by the University of South Australia Human Research Ethics Committee in September 2011.

This study employed a Delphi procedure. This procedure is appropriate for research questions which cannot be answered with complete certainty, but rather by the subjective opinion of a collective group of informed experts [ 16 ]. It allowed systematic refinement of the experts’ opinions over the course of several rounds while minimising confounding factors present in other group response methods [ 17 – 20 ].

The experts who participated in the Delphi procedure were identified by a 3–step procedure. Firstly, the lead study investigators independently recommended known researchers for the study. Secondly, a lengthy and extensive search was carried out to identify potential researchers from every world region and sub-region. Identifying potential experts from these regions involved searching for staff of relevant international bodies, government departments, non-government organisations, professional organisations and educational institutions. Thirdly, following email communication with the experts who have previously been identified, new experts were referred to the study investigators.

Once participants had been identified, it was important to determine their eligibility for inclusion in the study. Thus they were assessed using pre-determined inclusion and exclusion criteria. To be eligible, a researcher had to be an author of at least one peer-reviewed scientific publication on the physical activity or sedentary behaviour of children or adolescents, and must hold (at the time of selection) a senior position in their organisation. In addition, the experts were deliberately chosen to give geographical coverage of every world region and sub-region. Relevant information was gathered from staff homepages, Scopus author searches, the Journal and Author Name Estimator ( http://www.biosemantics.org/jane/ ) and other relevant Internet searches to ascertain whether a researcher met these criteria.

Forty-six eligible experts were invited to participate, with each sent information and consent forms via email. As a whole, these participants were representative of every region and sub-region. Of those invited, 20 did not respond to the invitation, two declined to participate, and 24 returned signed consent forms. An outline of this process is illustrated in Figure  1 .

Purposive sampling process undertaken.

The 24 participating experts (17 male and 7 female) were randomly allocated to either Panel A or Panel B and assigned identification code names accordingly. Furthermore the following major institution types were represented by the selected experts; educational institutions, government organisations, non-government organisations, professional organisations and community organisations.

The Delphi procedure used three rounds [ 21 ], each consisting of data collection, data analysis and controlled feedback. The survey was administered entirely online using a Survey Gizmo questionnaire. A novel feature of this study was the use of two parallel panels of experts. The existence of an alternate panel was only made known to the participants in Round 3, when each panel was asked to rank the priorities of the other panel. This allowed quantitative comparisons to be made between each panel’s rankings of each research issue and cross-validated the rankings of research priorities developed by each panel.

To commence each round, experts were sent an email containing a direct link to the online questionnaire. Briefly, Round 1 required each expert to answer the question “What are the five most important research issues for the next 10 years in the area of child and adolescent physical activity and sedentary behaviour?” Each expert put forward five research issues which they believed were priorities in the area. They also provided a brief description of each issue and reasons why they believed the issue to be a priority. The three study investigators reviewed all issues that were provided by each panel, with common issues combined into a single issue. The experts were then fed back their panel’s list of research issues and asked to ensure that the five research issues they provided were accurately represented.

Round 2 then asked experts to “review the research issues put forward in Round 1 and rate how important they believe each issue is for global research in child and adolescent physical activity and sedentary behaviour”. Experts rated each research issue independently using a 5-point Likert scale (5 = very important, 4 = important, 3 = moderately important, 2 = of little importance and 1 = unimportant). The three study investigators then short-listed each panel’s research issues to 20 according to those with highest mean Likert scale ratings. Following this, the top 20 research issues from each panel were fed back to the experts of the relevant panels.

In Round 3, experts were first asked to “rank their panel’s top 20 research issues in order of perceived international importance in child and adolescent physical activity and sedentary behaviour over the next 10 years”. The experts were then similarly asked to rank the alternate panel’s top 20 research priorities. The data analysis procedure was as follows. Firstly, the overall sum of each panel’s rankings was calculated for Panel A and Panel B’s top 20 research issues. Secondly, the two lists of research issues were combined with common issues provided by both panels merged. This resulted in 29 unique issues. Thirdly, the experts’ individual rankings for each research issue were summed. This allowed the issues to be ranked according to the sum of Panel A and Panel B’s overall rankings for each issue. Intra-panel agreement was quantified using Spearman’s rho by creating a matrix to compare individuals’ rankings to one another within the same panel. Inter-panel agreement was also quantified using Spearman’s rho to compare the overall sum and rank for each issue between panels.

Expert demographics

All 24 experts completed the three Delphi rounds. Data was collected on the 24 experts’ geographical distributions, institutional affiliations and years worked in the study area.

As a group, the 24 experts represented every geographical region and 12 sub-regions. This geographical distribution is illustrated in Figure  2 .

Geographical distributions of participating experts. The numbers indicate the number of participating experts from that region.

In terms of institutional affiliation, twenty-three experts acknowledged they were affiliated with an educational institution, eleven were affiliated with a professional organisation, six with an international organisation, six with a non-government organisation and four with a government organisation. It was noted that due to the nature of their work, experts were often affiliated with more than one institution type.

In regards to years worked in the study area, twelve experts had worked in for greater than 16 years, five had worked for 11 to 15 years, four had worked for 6 to10 years and three had worked for less than five years.

Results from Delphi rounds

In Round 1, each expert put forward five research issues. Collectively this provided a total of 120 issues across all 24 experts, with 60 for each panel. Following qualitative reduction of overlapping issues, 26 issues from Panel A and 34 issues from Panel B, were carried forward to Round 2. On reviewing the amended list, all exerts agreed that the issues they had raised were adequately represented.

From Round 2, the mean Likert-scale ratings were used to determine the top 20 issues for each panel. For Panel A, the mean Likert-scale ratings of the top 20 issues ranged from 3.5 to 5.0, with 18 of 20 issues having a median rating of >4.0 (“important”). For Panel B, the mean Likert-scale ratings of the top 20 issues ranged from 4.0 to 4.8, with all 20 research issues having a median rating of >4.0.

In Round 3, the 20 issues from Panel A and 20 issues from Panel B were qualitatively analysed to form one list. Eleven of each panel’s top 20 research issues were common to both panels and were therefore combined, with the remaining 18 issues (nine from each panel) unique. The resultant was a set of 29 unique research issues that were then ranked in order of importance by summing Panel A and Panel B’s rankings for each issue Table  1 .

There was only weak intra-panel agreement. The mean inter-individual rho ( ± 95% CI) was 0.20 ±0.05 for Panel A and 0.13 ±0.04 for Panel B. The average standard deviation of the rankings for individual issues was 5.1 (Panel A) and 5.3 (Panel B). When Panel B ranked Panel A’s issues, the correlation was very strong ( rho ± 95% CI: 0.79 ±0.17), and when Panel A ranked Panel B’s issues, the correlation was strong ( rho ± 95% CI: 0.52 ±0.31). Figures  3 and 4 clearly illustrate the correlations for each research issue.

Agreement between Panel A’s rankings and Panel B’s rankings of Panel A’s identified issues. The line shown is the identity line.

Agreement between Panel B’s rankings and Panel A’s rankings of Panel B’s identified issues. The line shown is the identity line.

Study outcomes

The primary outcome of this study was the development of 29 international research priorities in child and adolescent physical activity and sedentary behaviour. In order for the research priorities to be useful, it is important that they be neither too general nor too specific. The research priorities in this study appear broad enough to enable them to be transferable to researchers’ specific regions and contexts.

The final set of research priorities address a broad range of areas from epidemiology, determinants and correlates, through to intervention effectiveness and translational research. Of the 29 identified research priorities, ten related directly to translational research centred on intervention design and effectiveness. These focussed on specific behaviours (active transport, screen time, sport, physical education), settings (schools, communities, whole of population), or vehicles (mass advertising, policy). Translational research, centred on intervention design and effectiveness, can potentially guide governments and stakeholders to fund interventions that are the most effective, sustainable and transferable for changing behaviours [ 7 ]. This is important because to date, the research community has not been very successful at developing interventions for children and adolescents that bring about long-term and sustained change in health behaviours [ 10 ]. In addition, little attention has been given to the importance of the intervention setting and establishing what works in what situation and with whom [ 22 ].

Nine of the research priorities had a focus on capturing and quantifying the health benefits of engaging in physical activity and limiting sedentary behaviour, These research priorities were concerned with the impact of physical activity and sedentary behaviour on obesity, cognition, and general health and well being, and on describing behavioural patterns (across the day or the life-course or in specific populations such as pre-school children). Epidemiological research was considered important to address the cause, distribution and patterns of childhood physical activity and sedentary behaviour on current and future health [ 2 , 6 , 9 , 23 ].

Six research issues related to determinants and correlates research such as psychosocial and cultural/parental factors, the impact of technology, and the importance of enjoyment and lifestyle in general. Research that focuses on the determinants and correlates of behaviours is important. This is because while many correlates appear to be intuitively obvious, at present they have mixed support from high quality research [ 3 ].

Four issues did not fit into the aforementioned categories. They were related to the theory of behaviour change, injury prevention, measurement of behaviours and the physical education in culture of movement. Objective measurement of behaviours was ranked highly and is thought to be a “necessary first step for conducting meaningful epidemiological surveillance, public health research and intervention research” [ 14 ] p.124.

Strengths and limitations

Unlike previously identified priority reports [ 11 , 13 – 15 ] this study employed a Delphi method to arrive at a more valid set of research priorities. Strengths related to the Delphi method include participant blinding, iterative data collection and controlled feedback between rounds. For example, the identities and responses of the experts were anonymised so that the identified research priorities could not be dominated by certain individuals [ 24 ]. Furthermore, the provision of controlled feedback allowed experts to individually consider their views in light of their panel’s collective opinion.

Other strengths related to the methodology were the use of criterion and purposive sampling methods. This procedure meant that all participants held a senior position in their respective organisations and had published in the study area. In addition, experts collectively represented every major world region and a wide range of discipline areas, affiliations and interests. This approach meant that the identified research issues were more likely to reflect the most important physical activity and sedentary behaviour issues facing the children and adolescents worldwide.

A novel component of this study was split-panel approach, which allowed comparisons to be made between the rankings given by the two expert panels. The experts from each panel were taken from the same population, given the same study information, answered identical online questionnaires and participated simultaneously and independently. One can therefore be confident that comparing the Round 3 rankings of Panel A and Panel B experts would provide valid measures of inter-panel agreement.

The weak intra-panel agreement was weak, which is likely a reflection of the natural variation of individual’s opinions and areas of interest within the broad study area. This weak agreement could also highlight the advantages of the methodology which retained anonymity and used an online mode of data collection. There were fewer pressures to conform to others opinions due to decreased likelihood of peer dominance and status. Evidence to reinforce confidence in the results is the strong to very strong (rho = 0.52–0.79) inter-panel agreement. While experts were invited from every United Nations sub-region (United Nations 2011), no experts from the following sub-regions took part: Southern Africa, Middle Africa, Caribbean, Eastern Europe, Australia, Central Asia and Western Asia. This was significant because many of these sub-regions are heavily involved in physical activity and sedentary behaviour research. Consequently, caution should be applied when recommending that the identified research priorities truly provide a global perspective. Nonetheless, these research priorities provide an international context from which priorities at the regional, national and local levels can be developed.

In addition the priorities were set for the broad area of child and adolescent physical activity and sedentary behaviour. Due to the generality of this topic, it may be that the research priorities are not relevant when conducting research into minority populations. For example, children and adolescents with disabilities may warrant different research issues not identified in this study.

Implications for research

We hope that the identification of a set of ranked research priorities may contribute to more co-ordinated international research. For example, research priorities can help inform post-graduate students regarding where the current evidence gaps exist. This may be especially helpful for researchers who reside in less developed or marginalised research regions. In addition, encouraging more guided research can help to conceptualise how findings can be used as a basis for policy decisions. Lastly, research priorities can help to direct valuable funding into priority areas and away from studies on over-researched or lower priority topics.

This study engaged two panels of study experts in a three-round Delphi communication procedure. The outcome of this procedure was the identification of a ranked set of 29 research priorities in child and adolescent physical activity and sedentary behaviour. For example, the top three ranked priorities were: developing effective and sustainable interventions to increase children’s physical activity long-term; policy and/or environmental change and their influence on children’s physical activity and sedentary behaviour; and prospective, longitudinal studies of the independent effects of physical activity and sedentary behaviour on health. We hope these research priorities will help inform the spectrum of future studies undertaken, guide post-graduate study choices, guide allocation of funding to priority areas and assist with policy decisions.

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The study was conceived by GT and TO. LG was primarily responsible for conducting the participant selection process and the three rounds of data collection. LG, GT and TO were each involved in data analysis. LG produced the first draft of the paper with all other authors providing sections and critically reviewing the paper. All authors approved submission.

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Gillis, L., Tomkinson, G., Olds, T. et al. Research priorities for child and adolescent physical activity and sedentary behaviours: an international perspective using a twin-panel Delphi procedure. Int J Behav Nutr Phys Act 10 , 112 (2013). https://doi.org/10.1186/1479-5868-10-112

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ORIGINAL RESEARCH article

Relationship between maternal grit and effortful control among 18–21-month-old toddlers.

• 1 Department of Psychology, Ochanomizu University, Tokyo, Japan
• 2 Graduate School of Education, The University of Tokyo, Tokyo, Japan
• 3 Department of Psychology and Humanities, College of Sociology, Edogawa University, Chiba, Japan
• 4 Research Organization of Open Innovation and Collaboration Ritsumeikan University, Osaka, Japan

Grit is known to be effective for long-term academic and social success. However, few studies have focused on the role of grit in parenting and its effect on the development of grit in children. Therefore, this study investigated the effect of maternal grit on children’s effortful control (EC), which is thought to be a precursor to grit, using parenting as a mediating factor. Participants in the current study were 412 children (age range: 18–21 months, M  = 34.67 months, SD  = 4.51 months) and their mothers. We assessed maternal grit, parenting style, maternal EC, and child EC, and found that maternal grit, maternal EC, and parenting style were positively correlated with child EC. Furthermore, maternal grit was related to EC in children not only directly, but also indirectly through responsive parenting. Additionally, maternal grit was found to be directly related to child EC only when assessed separately from maternal EC. The current study’s findings suggest that maternal grit is directly related to EC in children in a way that differs from the mother’s EC in child-rearing situations.

1 Introduction

Grit, which has recently attracted interest, has been defined as “perseverance and passion for long-term goals,” which entails maintaining effort and interest in long-term goals despite adversity ( Duckworth et al., 2007 ). The grit scale was developed by Duckworth et al. (2007) as a two-factor self-report scale for describing and predicting long-term outcomes based on perseverance of effort and consistency of interest in long-term goals. They also showed that people with higher grit scores have higher achievement outcomes, such as academic success and spelling contests. Extant research has focused on the effects of individual grit on one’s own abilities, such as academic performance and socioeconomic status (SES), with few studies conducted on the effects of personal grit on other factors, especially parenting ( Oriol et al., 2017 ; Alhadabi and Karpinski, 2020 ; Li and Li, 2021 ). For example, parenting may be related to grit in that parents continue to maintain effective support and attention toward long-term goals for their own child.

However, little is known about the role of grit in parenting, or its effects on the development of grit in children. In an experimental setting, 12–15 months infants who observed adults effortfully engaging in a task engaged in tasks for a longer duration than those who observed adults engaging in a task with less effort ( Leonard et al., 2017 ). Similarly, Shinya and Ishibashi (2022) revealed that observing adults’ effortful behavior affected infants’ enhanced sustained goal-directed attention across contexts. A recent study reported that maternal grit was positively associated with maternal responsiveness, controlled parenting, and grit among children aged 3–6 years ( Imafuku et al., 2021 ). Additionally, maternal parenting style was positively associated with maternal perseverance of effort, suggesting that children raised by parents with high grit learn about persistence through parenting. These findings suggest that social engagement by caregivers with persistence may influence the development of effortful behavior in infants, although the long-term mediating effect of parenting on grit in children has not yet been directly investigated.

Most research on grit has been conducted on adolescents and older individuals ( Oriol et al., 2017 ; Kevenaar et al., 2023 ), while few studies have focused on grit in children ( Imafuku et al., 2021 ), as there are no standardized methods of measuring grit and the formation process of grit remains subject to debate. Furthermore, a critical issue in fostering grit in children is determining how parental grit relates to the precursors of grit at earlier developmental stages, when grit in children has not yet been identified ( Lucca and Sommerville, 2018 ). One candidate precursor of grit is self-control, which is often referred to as a concept similar to grit. Self-control is derived from social psychology and involves the use of cognitive processes to regulate behavior, focus or shift attention, and inhibit behavior to achieve subdominant goals ( Yamagata et al., 2005a ; Karreman et al., 2006 ; Nigg, 2017 ). In the context of developmental psychology, self-control is often referred to as effortful control (EC), which is the ability to inhibit a dominant response and activate a subdominant response ( Ahadi and Rothbart, 1994 ; Rothbart and Bates, 2006 ).

Duckworth and Gross (2014) argued that self-control is the ability to regulate or resist attention in the presence of temptation, whereas grit involves consistently pursuing a higher-order goal over years or sometimes decades. Grit, self-control, and EC are indistinguishable at both the phenotypic and behavioral genetic levels of conscientiousness, suggesting that the overlap is substantially due to genetic factors ( Takahashi et al., 2021 ). Similarly, grit and self-control are significantly phenotypically correlated with academic performance, suggesting that these variables may share genetic factors ( Kevenaar et al., 2023 ). By contrast, the relationship between grit and EC still requires discussion, and some argue that grit and EC are different concepts. Studies on elementary and junior high school students have shown differences between grit and self-control in the context of academic performance ( Oriol et al., 2017 ). By estimating the covariance of both components, grit was found to be associated with academic self-efficacy at both educational stages, but only with school satisfaction at secondary school. Conversely, self-control showed a significant relationship with school satisfaction only among elementary school students. Taken together, these findings suggest that while grit and self-control share overlapping components, they may represent distinct concepts with unique components, especially in terms of the timescale associated with goal attainment.

Nevertheless, in children at an early stage of development, it is difficult to maintain long-term goals because episodic memory formation and mental time travel are underdeveloped ( Suddendorf and Redshaw, 2013 ; Blankenship and Kibbe, 2019 ) Therefore, it is possible that “EC (self- control),” which controls behavior for shorter-term goals, precedes and underlies “grit,” which is the ability to persistently pursue long-term goals ( Lucca and Sommerville, 2018 ). Actually, early EC is thought to emerge in the first year of life ( Diamond, 1991 , 2002 ), and has been shown to a predictor for later self-control and academic outcomes ( Blair and Razza, 2007 ; Valiente et al., 2010 ; Neuenschwander et al., 2012 ). Therefore, the present study focused on the EC—a representative measure of self-control and persistence in developmental psychology—as a child outcome predicted by maternal grit.

Moreover, assuming that grit and EC represent different variables, it is conceivable that the influence of maternal grit and EC on child EC differs when mediated by parenting. Lengua et al. (2007) reveal that not all aspects of parenting are associated with EF (which often overlaps with EC). It has been suggested that parents with high EF skills may refrain from indulgent and over-reactive, but positive parenting such as engaging children in family-discussions and encouraging them persistently, may not necessarily depend on high EF ( Korucu et al., 2019 ). Thus, maternal EC and maternal grit may therefore differ in their impact on parenting. Parents should demonstrate “self-control” by selecting certain behaviors, such as an appropriate response to their child, while inhibiting other behaviors, such as yelling. Further, parents must demonstrate “grit,” which persistently focuses on attaining long-term goals and sustaining their passion, to their children. Although there is some evidence that observing others’ effortful behavior over a short period in a general non-parenting context encourages children to imitate and encourage effortful behavior ( Leonard et al., 2017 ; Shinya and Ishibashi, 2022 ), the long-term effects of observing caregivers’ effortful behavior are still unknown. Therefore, the present study examined the possibility of different effects of parental grit and parental EC in the context of parenting.

Individual differences in child EC arise from both genetics and environmental factors ( Losoya et al., 1997 ; Willems et al., 2019 ). Early developmental stage of EC is heavily influenced by parents (e.g., Cumberland-Li et al., 2003 ; Eisenberg et al., 2005 ; Davenport et al., 2011 ); warm and supportive parenting not only contributes to predicting future of child EC ( Kochanska et al., 2000 ; Eisenberg et al., 2005 ), but also improves cognitive solving skills during childhood ( Whipple et al., 2011 ). Additionally, parenting styles have been found to be affected by parents’ EC. For example, mothers with high EC were found to exhibit higher levels of warmth, support, and positive emotions towards their children ( Mangelsdorf et al., 1990 ; Cumberland-Li et al., 2003 ; Davenport et al., 2011 ). Although parental EC and parenting influence child EC, research on the influence of parental grit remains scarce. Imafuku et al. (2021) examined child EC, parent–child grit, and parenting, and observed a positive correlation between each variable; however, the direct effect of parental grit on child EC and the indirect effect of parenting were not examined.

This study aimed to clarify the effects of maternal grit, maternal EC, and parenting style as strong predictors of child EC. To measure child EC, we conducted a questionnaire survey with mothers of children aged 18–21 months to determine the earliest stage of child EC (using the Early Child Behavior Questionnaire [ECBQ]; Putnam et al., 2006 ). As children’s EC become more consistent around the age of 3–4 years ( Kochanska et al., 2000 ), examining the children’ EC before 2 years of age, which is not crystalized the EC, is considered appropriate to examine the precursors of grit in children. We hypothesized that maternal grit would positively correlate with child EC and parenting ( Imafuku et al., 2021 ). In addition, previous studies have shown that maternal grit is associated with responsive parenting ( Imafuku et al., 2021 ) and that warm parenting promotes EC in children ( Kochanska et al., 2000 ; Eisenberg et al., 2005 ). Thus, we hypothesized that maternal grit predicts EC in children mediated by parenting style. Finally, given that structural differences between grit and EC have been debated ( Duckworth et al., 2007 ; Duckworth and Gross, 2014 ), we explored whether maternal grit is associated with child EC through parenting in the same way as parental EC. Accordingly, we hypothesized that maternal grit is a strong predictor of child EC, even after controlling for parenting.

2 Materials and methods

2.1 participants.

This study was approved by the ethical committee of Life Science Research Ethics and Safety, The University of Tokyo (approval number: 17–270). The participants were primary caregivers of children aged 18–21 months. They were recruited from a database using an online survey (Cross Marketing, Inc., Tokyo, Japan). We conducted the survey twice, obtaining 714 responses from March 22 to 24, 2021, and 644 responses from October 22 to November 1, 2021. To ensure the validity of responses, trap questions randomly inserted within the survey items were excluded. Additionally, all straight-line responses were excluded, resulting in the exclusion of 526 out of 1,358 respondents. Furthermore, responses with significantly long durations (nearly an hour or more) were excluded based on recorded start and end times. Of the collected data, 138 sets were from fathers; however, these were excluded from the current analysis for use in other studies. Hence, we utilized 412 data from mothers only. After obtaining all responses, we excluded the following data: respondents (1) who were not primary caregivers, including fathers, (2) whose children were outside the 37–45 week gestation range, and (3) who provided contradictory and incomplete answers. The final sample included 412 mothers (mean age = 34.67 months, SD = 4.51 months) of children aged 18–21 months (202 girls [49%], 210 boys [51%], mean age = 19.78 months, SD = 1.02 months). The mothers’ educational levels ranged from middle school to doctoral/postgraduate degrees as follows: middle school (2.2% of participants), high school (17.5%), college (32%), bachelor’s degree (42%), master’s or doctoral degree (5.1%), and other academic backgrounds (1%). The mothers self-reported family income (in Japanese yen) across 12 categories was as follows: 0–1,000,000 (1.2% of participants); 1,000,001–2,000,000 (2.9%); 2,000,001–3,000,000 (6.3%); 3,000,001–5,000,000 (28.6%); 5,000,001–6,000,000 (16%); 6,000,001–7,000,000 (14.3%); 7,000,001–9,000,000 (14.3%); 9,000,001–10,000,000 (4.4%); 10,000,001-12,000,000 (5.3%); 12,000,001–15,000,000 (3.4%); 15,000,001-20,000,000 (1.9%) and > 20,000,001 (1.2%).

2.2 Measurements

The survey comprised five sections: (1) Japanese version of the Short Grit Scale (Grit-S; Takehashi et al., 2018 ), (2) parenting style ( Nakamichi, 2013 ), (3) parenting EC ( Yamagata et al., 2005b ), (4) ECBQ-Short Form ( Nakagawa et al., 2011 ), and (5) demographic information.

2.2.1 Maternal grit

Grit was assessed using Japanese version of Short Grit Scale (Grit-S, Takehashi et al., 2018 ), which comprises 12 items that assess two factors: six items for perseverance of effort (e.g., I have overcome setbacks to conquer an important challenge) and six items for consistency of interest (e.g., new ideas and projects sometimes distract me from previous ones). Each item is rated on a five-point Likert scale ranging from 1 (not at all like me) to 5 (very much like me). The overall grit score was calculated as the average of total scores of the two factors. The internal consistency of the scales demonstrated acceptable reliability (effort: α  = 0.86; interest: α  = 0.77). The entire scale demonstrated acceptable internal consistency ( α  = 0.75).

2.2.2 Parenting style

Parenting style was assessed using the Japanese version of the Parenting Style Questionnaire ( Nakamichi, 2013 ), which was based on Baumrind (1966) . The questionnaire comprises 13 items that assess two factors: eight items for responsiveness (e.g., expressing affection by hugging and talking with gentle words) and five items for control (e.g., keeping your child quiet in places that require them to be quiet, such as libraries and movie theaters). Items are scored using a four-point Likert scale ranging from 1 (never) to 4 (always). The total responsiveness score ranges from 8 to 32, and that of control ranges from 5 to 20. The scores on the two dimensions of parenting (parenting score) were averaged for each sub-factor. Internal consistency values were α  = 0.84 for responsive parenting and α  = 0.71 for controlling parenting. The two subscales were significantly correlated ( r  = 0.47, p  < 0.001) and a composite score was created by calculating the average of the total scores of both subscales.

2.2.3 Maternal EC

Maternal EC was measured using the Japanese version of Adults Temperament Questionnaire (ATQ; Rothbart et al., 2000 ) developed by Yamagata et al. (2005b) . The ATQ includes four factors: negative affect, extraversion/surgency, EC, and orienting sensitivity. In this study, we used the 35 items in the EC dimension of ATQ, based on previous studies ( Tanaka et al., 2013 ; Nishimura and Matsuda, 2020 ). This dimension comprises three components: (1) inhibitory control—the ability to inhibit inappropriate behaviors (11 items); (2) activation control—the ability to perform an action in a situation that one has a strong tendency to avoid (12 items); and (3) attentional control—the ability to focus and shift attention (12 items; Rothbart et al., 2000 ). Each item is scored on a five-point Likert scale ranging from 1 (not true) to 5 (true). The score ranges from 11 to 55 for inhibitory control and from 12 to 60 for attentional control and activation control. Total maternal EC score was the average of the entire scale. Items in each of the subscales demonstrated adequate internal consistency (inhibitory control: α  = 0.65; activation control: α  = 0.79; and attentional control: α  = 0.82). The 35-item EC scale demonstrated acceptable reliability in our sample ( α  = 0.89).

2.2.4 Child EC

We measured child EC using Japanese version Early Childhood Behavior Questionnaire-short form (ECBQ; Nakagawa et al., 2011 ), comprising 107 items that assess 18 dimensions of temperament in children aged 18–36 months. We used only 34 items related to EC; based on previous studies ( Nakagawa et al., 2011 ; Inoue and Kondo, 2019 ), EC is a validated factor defined by the loadings of perceptual sensitivity (PS), attention shifting (AS), sociability (SC), positive anticipation (PA), low-intensity pleasure (LIP), and attention focusing (AF). Each item was scored on a seven-point Likert scale ranging from 1 (never) to 7 (always), and an 8 option of “not applicable.” The total score of child EC was calculated as the average total score of all the sub-factors. The internal consistency each sub-factor was as follows: PS ( α  = 0.78), AS ( α  = 0.70), SC ( α  = 0.96), PA ( α  = 0.88), LIP ( α  = 0.84), and AF ( α  = 0.55). The entire scale demonstrated acceptable reliability ( α  = 0.94). We excluded 1% of the data that were more than three standard deviations above or below the mean of the total number of eight points (not applicable).

2.3 Data analysis

The demographic information included the child’s sex and age, maternal age, maternal academic background, and family income. Before conducting the full-scale analysis, SES was standardized. SES was assessed based on family income and maternal education. Family income was assigned a 12-point scale and maternal education was assigned a 5-point scale. Following a previous study ( Moriguchi and Shinohara, 2019 ), family income and maternal education were individually converted to z-scores and averaged to create a total SES score.

To assess the first hypothesis we calculated descriptive statistics and correlations between the variables. Considering the second research question, a multiple regression model was used to examine the potential predictive relationships among maternal grit, maternal EC, parenting score, and child EC. To investigate whether maternal grit is associated with child EC, we conducted mediation analyses using AMOS (ver. 28). Finally, we examined the mediating role of parenting in the relationships between maternal grit, maternal EC, and child EC. We tested the significance of the indirect effect using bias-corrected bootstrapping procedures with 2,000 simulations. A bias-corrected bootstrapped effect with a 95% confidence interval (CI) that does not include zero would be evidence of an intermediary pathway linking maternal grit and maternal EC to child EC through the two dimensions of parenting.

3.1 Correlation analysis

Table 1 summarizes the means and standard deviations for the study variables. A series of correlation analyses were used to examine the relationships between the variables. Maternal grit was positively associated with responsiveness parenting ( r  = 0.18, p  < 0.001), maternal EC ( r  = 0.51, p  < 0.001), and child EC ( r  = 0.24, p  < 0.001). Further, child EC was positively associated with responsive parenting ( r  = 0.33, p  < 0.001), controlled parenting ( r  = 0.24, p  < 0.001), and parental EC ( r  = 0.28, p  < 0.001). The correlations between maternal EC and responsive parenting ( r  = 0.31, p  < 0.001) and controlling parenting ( r  = 0.16, p  < 0.01) were positive and statistically significant. Only maternal EC was positively associated with children’s age ( r  = 0.12, p  < 0.05). Children’s sex was also positively associated with only controlled parenting ( r = 0.10, p < 0.05). SES was not correlated with any of the other variables.

Table 1 . Means, standard deviations, and correlations among the study variables.

3.2 First mediation model

A structural equation model was used to examine parenting as a mediator between maternal grit and child EC. We used a mediation model via AMOS. The results (see Figure 1 ) revealed that the total standardized direct effect of maternal grit on child EC, without considering the effect of parenting, was significant ( β  = 0.24, p  < 0.001). The analysis of the association between maternal grit and responsive parenting suggested a significant positive effect ( β  = 0.18, p  < 0.01), while the coefficient of controlled parenting was not significant ( p  > 0.05). Independently, both responsive and controlled parenting significantly predicted child EC ( β  = 0.25, p  < 0.001; β  = 0.11, p  < 0.05). Finally, the regression model indicated that the standardized direct effect of maternal grit on child EC, considering the effect of parenting, was significant ( β  = 0.19, p  < 0.001), but the effect was smaller than before the mediation variable was considered.

Figure 1 . Mediation model of maternal grit on children’s effortful control. Demographic covariates not shown. Standardized effects were reported. The number before the arrow from “Maternal grit” to “Child EC” is the value before introducing the parameter, and the number after is the value after introducing the parameter. * p  < 0.05; ** p  < 0.01; *** p  < 0.001.

Although we evaluated the fit of this model, it did not show a high degree of fit ( χ 2 / df = 99.604, p = 0.00, CFI = 0.443, RMSEA = 0.490). Because the number of observed variables and sample size tend to produce estimates that suggest a poorer fit than their population counterparts in CFI and RMSEA ( Shi et al., 2019 ), it is difficult to conclude that this model is not necessarily appropriate. Furthermore, it is recommended to supplement reliability by using bootstrapping methods in mediation analyzes for small to medium-sized samples ( Shrout and Bolger, 2002 ). Therefore, to ascertain the significance of the effects, a bootstrap nonparametric resampling procedure with 2,000 bootstrap sample simulations with bias-corrected 95% confidence intervals (CI) was applied. Bootstrap analysis of the indirect effect of parenting on the association between maternal grit and child EC showed a bias-corrected 95% CI that did not include zero (CI [0.01, 0.10]).

These results, along with the statistical significance of the remaining paths, support the idea of a partial mediation model that accounts for 14.7% of the variance in child EC ( F [3,408] = 24.612, p  < 0.001). Children’s age and sex, SES were not statistically significant associated with child EC and were removed from subsequent mediation analysis in SEM.

3.3 Second mediation model

Overall, the model that additionally considered maternal EC to the first mediation model accounted for 15.8% of the variance in child EC ( F [4,407] = 20.232; p  < 0.001). The results from the mediation model suggest that the indirect effect of parenting on the association between maternal grit and child EC disappeared, and only a partial mediation between maternal and child EC was observed. More specifically, with both parenting dimensions as mediators, the estimated regression coefficient between maternal grit and parenting score was reduced to the point that maternal grit was no longer a significant predictor ( β  = 0.04, p  = 0.494; β  = −0.04, p  = 0.499). Additionally, the standardized direct effect of maternal grit on child EC was lower than that in the first model ( β  = 0.13, p  < 0.05).

By contrast, the estimated regression coefficient between maternal EC and responsive parenting was positive and significant ( β  = 0.29, p  < 0.001). Additionally, the coefficient of controlled parenting was positive and significant ( β  = 0.18, p  < 0.01). Moreover, the standardized direct effect of maternal EC on child EC, considering the effect of parenting, was significant ( β  = 0.14, p  < 0.05). Finally, the analysis of the association between both parenting dimensions and child EC suggested a significant positive effect ( β  = 0.22, p  < 0.001; β  = 0.11, p  < 0.05).

The model also did not show a high degree of fit ( χ 2 / df = 90.285, p = 0.00, CFI = 0.728, RMSEA = 0.466), to ascertain the significance of the effects, a bootstrap nonparametric resampling procedure with 2,000 bootstrap sample simulations. Estimates of the indirect effect along with bias-corrected 95% confidence intervals (CI) were provided. Bootstrap analysis of the indirect effect of parenting on the association between maternal and child EC suggested a bias-corrected 95% CI that did not include zero (CI [0.04, 0.12]). Figure 2 illustrates the second mediation model with standardized coefficients. Children’s age and sex, SES were not statistically significant associated with child EC and were removed from subsequent mediation analysis in SEM.

Figure 2 . Parenting as a partial mediator in the relationship between maternal grit, maternal effortful control and child effortful control. Demographic covariates not shown. Standardized effects were reported. * p  < 0.05; ** p  < 0.01; *** p  < 0.001.

4 Discussion

This study aimed to clarify whether maternal grit, through parenting, influences EC in early development of children, and whether maternal grit has a unique influence on child EC that is different from maternal EC. Therefore, we administered a mother-rated questionnaire focusing on toddlers (18–21 months old) in whom the earliest developmental stages of EC could be measured (using the ECBQ; Putnam et al., 2006 ). Additionally, mothers were asked to answer questionnaires regarding grit, EC, and parenting style. Maternal grit was positively associated with child EC, and this relationship was mediated by responsive parenting. Additionally, in models that included maternal EC, only the direct effect of maternal grit on child EC remained and the indirect effect through parenting disappeared. Furthermore, maternal EC showed not only a direct association with child EC but also an indirect association through parenting.

Our findings suggest that parenting is associated with maternal grit and child EC, and mediates their relationship. Similar to previous research, maternal responsive parenting was moderately correlated with maternal grit and child EC ( Imafuku et al., 2021 ). Our regression analysis confirmed the relationship between maternal grit and parenting style (responsiveness/controlled) in child EC. Furthermore, to examine the role of maternal parenting, a mediation analysis revealed that maternal responsive parenting significantly mediated the relationship between maternal grit and child EC.

These results are similar to those of previous studies wherein children whose parents provided warm and supportive parenting were associated with better EC ( Kochanska et al., 2000 ; Eisenberg et al., 2005 ). However, to our knowledge, the results of current study are the first to not only associate parenting with maternal grit and child EC ( Imafuku et al., 2021 ), but also show that maternal grit mediates responsive parenting and is associated with child EC. In other words, mothers with high grit are more likely to show responsive parenting, which may contribute to fostering their children’s effortful behavior. Furthermore, regression analysis showed that the direct effect of maternal grit on child EC remained significant even after parenting and maternal EC were considered as parameters. These results indicate that parental behavior may influence child EC in ways that are not directly related to parenting. Recent studies have shown that observing persistent effortful behavior can imitatively influence infant behavior and attention, albeit in the short term ( Leonard et al., 2017 ; Shinya and Ishibashi, 2022 ). Thus, the findings of the current study suggest that children may acquire effortful behavior not only through direct social interactions like parenting, but also through observation of parents’ persistent effortful attention and behaviors.

Although the relationship between maternal grit and responsive parenting weakened, considering the variance in maternal EC, maternal grit still showed a positive relationship with child EC. We found that maternal EC was not only directly associated with child’s EC but also indirectly, mediated by parenting. Previous studies have also shown that mothers with high EC provide positive parenting ( Davenport et al., 2011 ), and that such mothers’ responses have been shown to contribute to enhancing their children’s cognitive skills, including EC ( Whipple et al., 2011 ). To summarize, mothers who control their own behavior and show consistent parenting may foster EC in their children.

Interestingly, our results indicate that maternal grit and EC may differently affect child EC. As mentioned above, maternal grit was directly related to child EC without considering parenting as an mediating factor, whereas maternal EC was not only directly related to child EC, but also indirectly related to it via parenting. To our knowledge, this is the first study to empirically report that maternal grit and self-control (i.e., EC), which follow different processes, affect child EC in child rearing situations. Our findings also support previous research showing that grit has a different goal (having a single challenging overarching goal and working hard towards it) and timescale (longer duration) than self-control ( Duckworth and Gross, 2014 ). However, some argue that grit and EC are similar concepts ( Takahashi et al., 2021 ; Kevenaar et al., 2023 ), and that the relationship between them requires further discussion. Given the findings of the current study, at least in the context of parenting, it is possible that maternal grit and EC have different relationships with child EC. One possible explanation for this difference is the uniqueness of the sub-concepts of grit. While one of the two sub-concepts that comprise grit, persistence of effort, is relatively similar to EC, the other concept, consistency in passionate interests, is the driving force that leads to responses that actively seek and invent viable alternatives to seemingly unattainable goals and actions ( Duckworth and Gross, 2014 ). The nature of such grit may have indirect effects from parent to child, such as imitative learning, that go beyond direct parent–child interactions in daily life. Therefore, further research on the effects of grit and EC through parenting must be conducted, considering the structural differences between the two concepts.

Future research should consider the limitations of the current research. First, although the present study showed that maternal grit and EC are directly associated with child EC, we did not examine whether above three factors were due to observational and learning effects or genetic factors. Parent and child self-regulation studies have shown the possibility of direct genetic effects ( Bridgett et al., 2018 ). Twin studies in parental and child EC have shown a heritability of approximately 60%; although this heritability varies widely among informants, heritability estimates based on parental reports were stronger than self-reports or observations ( Willems et al., 2019 ). As grit is a relatively new concept that has only recently received attention, few studies have focused on the possibility that parent al and child grit are directly related. Therefore, further research is needed on the genetic influence of parental and child grit. Moreover, based on the findings of this study, it would be valuable to examine not only the relationship between parental and child EC, but also the influence of parenting on child grit. Therefore, it is necessary to conduct surveys or experiments that focus on the differences between grit and EC in children. Few studies have examined whether toddlers are capable of sustained action toward long-term goals. One study measured grit in children using the Grit-S, which was assessed by their parents ( Imafuku et al., 2021 ). In addition, maternal reports may be prone to bias, potentially resulting in less valid responses compared with an experimental assessment of children’s EC. Therefore, it is necessary to develop an age-appropriate scale that can objectively and quantitatively measure grit in children. The development of this scale will provide further insight into the differences between child grit, EC, and their developmental processes (differentiation and individual). Although we determined the children’s age range to be 18–21 months to examine precursors of grit in children, children’s EC becomes more consistent around the age of 3–4 years ( Kochanska et al., 2000 ). Therefore, it may be difficult to generalize our results to a larger age range, it may be difficult to generalize our results to a larger age range. Thus, conducting longitudinal studies would enable the establishment of causal relationships between parenting and children’s EC.

The current study’s findings indicate that maternal grit, EC, and parenting style are associated with child EC at 18–21 months of age. Maternal grit was found to be associated with child EC via responsive parenting. Moreover, a direct association between maternal grit and child EC was observed after controlling for maternal EC. Our study provides initial evidence that maternal grit is associated with EC in young children, in a way distinct from maternal EC in child rearing situations.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by The Ethics Committee of University of Tokyo. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

AJ: Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing, Project administration, Visualization. MI: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing. YS: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing. SI: Conceptualization, Funding acquisition, Supervision, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was supported by the Center for Early Childhood Development, Education, and Policy Research (CEDEP), Graduate School of Education, University of Tokyo; MEXT “Innovation Platform for Society 5.0” (Grant number: JPMXP0518071489), Doshisha University; and the Mayekawa Foundation Research Grant (2021; 2023).

Acknowledgments

The authors are extremely grateful to the parents who completed the survey.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

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

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Keywords: grit, parenting, toddler, effortful control, self control

Citation: Jung A, Ishibashi M, Shinya Y and Itakura S (2024) Relationship between maternal grit and effortful control among 18–21-month-old toddlers. Front. Psychol . 15:1346428. doi: 10.3389/fpsyg.2024.1346428

Received: 29 November 2023; Accepted: 06 May 2024; Published: 17 May 2024.

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Copyright © 2024 Jung, Ishibashi, Shinya and Itakura. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Mikako Ishibashi, [email protected]

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The copy number variant architecture of psychopathology and cognitive development in the ABCD study

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Importance: Childhood is a crucial developmental phase for mental health and cognitive function, both of which are commonly affected in patients with psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored. Objective: Investigating CNV associations with dimensions of child psychopathology and cognitive functions. Design, Setting, and Participants: ABCD study focuses on a cohort of over 11,875 youth aged 9 to 10, recruited from 21 sites in the US, aiming to investigate the role of various factors, including brain, environment, and genetic factors, in the etiology of mental and physical health from middle childhood through early adulthood. Data analysis occurred from April 2023 to April 2024. Main Outcomes and Measures: In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes. Results: In a final sample of 8,564 individuals (mean age=9.9 years, 4,532 males) passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and our phenotypes of interest, psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with overall psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to overall cognitive function, with particular contributions from fluid intelligence (14q11.2), working memory (10q26.3), and reading ability (14q11.2). Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased overall psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains. Conclusions and Relevance: In summary, our findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology.

Competing Interest Statement

AFA-B receives consulting income from Octave Bioscience. AFA-B and JS hold equity in and serve on the board of Centile Bioscience.

Funding Statement

The research was funded by R01MH132934 and R01MH133843.

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I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study used ONLY openly available human data that were originally located at https://abcdstudy.org/.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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All data produced are available online at https://abcdstudy.org/

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