Susan Krauss Whitbourne
Research methods in lifespan development include single-factor designs that either follow a single cohort of individuals over time or compare age groups at a single time point. The two basic types of studies involving the manipulation of the single factors of age, cohort, and time of measurement are longitudinal and cross-sectional. Each of these has advantages and disadvantages, but both are characterized by limitations because they cannot definitively separate the joint influences of age, cohort, and type of measurement. The third group of designs involves manipulation of two or more levels of each factor to permit inferences to be drawn that separate personal from social aging.
The theoretical problems involved in both the single-factor and sequential designs combine with practical issues to present lifespan developmental researchers with a number of choices in approaching the variables of interest. The theoretical problems include the inevitable linking of personal with social aging, particularly evident in single-factor designs, and the fact that selective attrition leads to the differential availability of increasingly select older samples. Practical problems include the need to assign participants to appropriate age intervals and such clerical issues as the need to track participants in follow-up investigations. Researchers must also be aware of methodological issues related to task equivalence across individuals of different ages and the need to covary for potential confounds that could lead to differences across groups of participants due to such factors as education and health status.
The increasing recognition of the need to address these issues is leading to a body of literature that reflects the growing sophistication of the field along with the more widespread availability of sophisticated analytic methods. As these improvements continue to raise the level of scholarship in the field, there will be a greater understanding of both ontogenetic change as well as the influence of context on development from childhood through later life.
Philip Parker and Robert Brockman
Longitudinal structural equation modeling (LSEM) is used to answer lifespan relevant questions such as (a) what is the effect of one variable on change in and other, (b) what is the average trajectory or growth rate of some psychological variable, and (c) what variability is there in average trajectories and what predicts this variability. The first of these questions is often answered by a LSEM called an autoregressive cross-lagged (ACL) model. The other two questions are most typically answered by an LSEM called a latent growth curve (LGC). These models can be applied to a few time waves (measured over several years) or to many time waves (such as present in diary studies) and can be altered, expanded, or even integrated. However, decisions on what model to use must be driven by the research question. The right tool for the job is not always the most complex. And, more importantly, the right tool must be matched to the best possible research design. Sometimes in lifespan research the right tool is LSEM. However, researchers should prioritize research design as well as careful specification of the processes and mechanisms they are interested in rather than simply choosing the most complicated LSEM they can find.
Gawon Cho, Giancarlo Pasquini, and Stacey B. Scott
The study of human development across the lifespan is inherently about patterns across time. Although many developmental questions have been tested with cross-sectional comparisons of younger and older persons, understanding of development as it occurs requires a longitudinal design, repeatedly observing the same individual across time. Development, however, unfolds across multiple time scales (i.e., moments, days, years) and encompasses both enduring changes and transient fluctuations within an individual. Measurement burst designs can detect such variations across different timescales, and disentangle patterns of variations associated with distinct dimensions of time periods. Measurement burst designs are a special type of longitudinal design in which multiple “bursts” of intensive (e.g., hourly, daily) measurements are embedded in a larger longitudinal (e.g., monthly, yearly) study. The hybrid nature of these designs allow researchers to address questions not only of cross-sectional comparisons of individual differences (e.g., do older adults typically report lower levels of negative mood than younger adults?) and longitudinal examinations of intraindividual change (e.g., as individuals get older, do they report lower levels of negative mood?) but also of intraindividual variability (e.g., is negative mood worse on days when individuals have experienced an argument compared to days when an argument did not occur?). Researchers can leverage measurement burst designs to examine how patterns of intraindividual variability unfolding over short timescales may exhibit intraindividual change across long timescales in order to understand lifespan development. The use of measurement burst designs provides an opportunity to collect more valid and reliable measurements of development across multiple time scales throughout adulthood.
Christopher Hertzog and Taylor Curley
Metamemory is defined as cognitions about memory and related processes. Related terms in the literature include metacognition, self-evaluation, memory self-efficacy, executive function, self-regulation, cognitive control, and strategic behavior. Metamemory is a multidimensional construct that includes knowledge about how memory works, beliefs about memory (including beliefs about one’s own memory such as memory self-efficacy), monitoring of memory and related processes and products, and metacognitive control, in which adaptive changes in processing approaches and strategies may be contemplated if monitoring of memory processes (encoding, retention, retrieval) indicates that alternative strategies may be required. Older adults generally believe that their memory has declined and that, on average, they have less control over memory and lower memory self-efficacy than young and middle-aged adults. Many but not all aspects of online memory monitoring are well preserved in old age, such as the ability to discriminate between information that has been learned versus not learned. A major exception concerns confidence judgments concerning whether recognition memory decisions are correct; older adults are more prone to high-confidence memory errors, believing they are recognizing something they have not encountered previously. The evidence regarding metacognitive control is more mixed, with some hints that older adults do not use monitoring to adjust control behaviors (e.g., devoting more time and effort to studying items they believe have not yet been well-learned). However, any age deficits in self-regulation based on memory monitoring or adaptive strategy use can probably be addressed through instructions, practice, or training. In general, older adults seem capable of exerting metacognitive control in memory studies, although they may not necessarily do so without explicit support or prompting.
Michael J. Lyons, Chandra A. Reynolds, William S. Kremen, and Carol E. Franz
The rapidly increasing number of people age 65 and older around the world has important implications for public health and social policy, making it imperative to understand the factors that influence the aging process. Twin studies can provide information that addresses critical questions about aging. Twin studies capitalize on a naturally occurring experiment in which there are some pairs of individuals who are born together and share 100% of their segregating genes (monozygotic twins) and some pairs that share approximately 50% (dizygotic twins). Twins can shed light on the relative influence of genes and environmental factors on various characteristics at various times during the life course and whether the same or different genetic influences are operating at different times. Twin studies can investigate whether characteristics that co-occur reflect overlapping genetic or environmental determinants. Discordant twin pairs provide an opportunity for a unique and powerful case-control study. There are numerous methodological issues to consider in twin studies of aging, such as the representativeness of twins and the assumption that the environment does not promote greater similarity within monozygotic pairs than dizygotic pairs. Studies of aging using twins may include many different types of measures, such as cognitive, psychosocial, biomarkers, and neuroimaging. Sophisticated statistical techniques have been developed to analyze data from twin studies. Structural equation modeling has proven to be especially useful. Several issues, such as assessing change and dealing with missing data, are particularly salient in studies of aging and there are a number of approaches that have been implemented in twin studies. Twins lend themselves very well to investigating whether genes influence one’s sensitivity to environmental exposures (gene-environment interaction) and whether genes influence the likelihood that an individual will experience certain environmental exposures (gene-environment correlation). Prior to the advent of modern molecular genetics, twin studies were the most important source of information about genetic influences. Dramatic advances in molecular genetic technology hold the promise of providing great insight into genetic influences, but these approaches complement rather than supplant twin studies. Moreover, there is a growing trend toward integrating molecular genetic methods into twin studies.
Joseph E. Gaugler, Colleen M. Peterson, Lauren L. Mitchell, Jessica Finlay, and Eric Jutkowitz
Mixed methods research consists of collecting and analyzing qualitative and quantitative data within a singular study. The “methods” of mixed methods research vary, but the ultimate goal is to provide greater understanding and explanation via the integration of qualitative and quantitative data. Mixed methods studies have the potential to advance our understanding of complex phenomena over time in adult development and aging (e.g., depression following the death of a spouse), but the utility of this approach depends on its application. The authors systematically searched the literature (CINHAL, Embase, Ovid/Medline, PubMed, PsychInfo, and ProQuest) to identify longitudinal mixed methods studies focused on aging. They identified 6,351 articles published between 1994 and 2017, of which 174 met the inclusion criteria. The majority of mixed methods studies reported on the evaluation of interventions or educational programs. Non-interventional studies tended to report on experiences related to the progression of various health conditions, the needs and experiences of caregivers, and the lived experiences of older adults. About half (n = 81) of the mixed methods studies followed a sequential explanatory design where a qualitative component followed quantitative evaluation, and most of these studies achieved “integration” by comparing qualitative and quantitative data in Results sections. There was considerable heterogeneity across studies in terms of overall design (randomized trials, program evaluations, cohort studies, and case studies). As a whole, the literature suffered from key limitations, including a lack of reporting on sample selection methodology and mixed methods design characteristics. To maximize the value of mixed methods in adult development in aging research, investigators should conform to recommended guidelines (e.g., depict participant study flow and use recommended notation) and consider more sophisticated mixed methods applications to advance the state of the art.
Alexandre J.S. Morin and David Litalien
As part of the Generalized Structural Equation Modeling framework, mixture models are person-centered analyses seeking to identify distinct subpopulations, or profiles, of participants differing quantitatively and qualitatively from one another on a configuration of indicators and/or relations among these indicators. Mixture models are typological (resulting in a classification system), probabilistic (each participant having a probability of membership into all profiles based on prototypical similarity), and exploratory (the optimal model is typically selected based on a comparison of alternative specifications) in nature, and can take different forms. Latent profile analyses seek to identify subpopulations of participants differing from one another on a configuration of indicators and can be extended to factor mixture analyses allowing for the incorporation of latent factors to the model. In contrast, mixture regression analyses seek to identify subpopulations of participants’ differing from one another in terms of relations among profile indicators. These analyses can be extended to the multiple-group and/or longitudinal analyses, allowing researchers to conduct tests of profile similarity across different samples of participants or time points, and latent transition analyses can be used to assess probabilities of profiles transition over time among a sample of participants (i.e., within person stability and change in profile membership). Finally, growth mixture analyses are built from latent curve models and seek to identify subpopulations of participants following quantitatively and qualitatively distinct trajectories over time. All of these models can accommodate covariates, used either as predictors, correlates, or outcomes, and can even be extended to tests of mediation and moderation.
Johnson Ching Hong Li and Virginia Man Chung Tze
In behavioral, social, and developmental research, researchers often begin with a fundamental question that examines whether there is a significant relationship between an independent variable (IV; e.g., video games) and a dependent variable (DV; e.g., aggression). However, examining this simple IV-DV relationship is not sufficient in most research scenarios given that this relationship may differ across the levels of a third variable, which is known as a moderator. For example, researchers may examine the degree to which the relationship between an independent variable and a dependent variable differs across the levels of a moderator or moderators (e.g., gender, ethnicity, socioeconomic status, intervention) to provide a more complete picture of the IV-DV effect and how this effect is or is not applicable to certain groups of participants.
In lifespan developmental research, a key component lies in the study of change, growth, or trajectory of one’s life over time. Undoubtedly, not all individuals may follow the same developmental change or growth over time and examining moderators (e.g., gender, intervention, etc.) that may explain these individual changes is crucial for researchers to better understand the effects on their research investigation and for practical implications. The existing literature shows that conceptual and methodological strategies for moderation analysis have been developed and evolved in lifespan developmental psychology. In particular, researchers in lifespan developmental psychology have used various types of moderation analyses, including assessing whether moderators can explain the pretest and posttest difference based on the conventional analysis of variance (ANOVA) framework and evaluating whether moderators may explain how different individuals follow or deviate from the general growth and trajectory based on advanced latent growth curve modeling (LGCM). Researchers who study lifespan development have realized the importance of moderation effects in their work. In light of the complexity of current biological, psychological, and social factors embedded in lifespan developmental research, the trend of utilizing more sophisticated LGCM than ANOVA to understand the growth trajectories will receive more attention in the future.
Kimberly L. Fine and Kevin J. Grimm
Multilevel modeling is a data analytic framework that is appropriate when analyzing data that are dependent due to the clustering of observations in higher-level units. Clustered data appear in a variety of disciplines, which makes multilevel modeling a necessary data analytic tool for many researchers. Longitudinal data are a special kind of clustered data as the repeated observations are clustered within individuals. Multilevel models can be applied to longitudinal data to examine how individuals change over time and how individuals differ in their change processes over time. For longitudinal data, linear multilevel models, where the fixed- and random-effects parameters enter the model in a linear fashion, and nonlinear multilevel models, where at least one fixed-and/or random-effect parameter enters the model in a nonlinear fashion are commonly estimated to examine different forms of the individual change process. Multilevel structural equation modeling is an extension of multilevel modeling that allows for multivariate outcomes, and this framework is very useful for modeling multivariate longitudinal data (e.g., multivariate growth models and second-order growth models).
Joseph A. Mikels and Nathaniel A. Young
The adult life span is characterized as a time of divergent trajectories. It is a time of compounding losses (such as physical, sensory, and cognitive declines) and is also a time of surprising growth (such as improvements in well-being and emotion regulation). These divergent trajectories present theorists with the paradox of aging: in the face of accumulating losses, how is it that as people age, they generally feel good and experience greater well-being? Theorists have grappled with this paradox and have focused on how motivational, cognitive, control, and social factors impact emotional development across the adult life span. These foundational theories have paved the way to a deeper understanding of adult life-span development, but they do not draw as deeply from theories in affective science. Some of the latest perspectives on emotion and aging offer integrative views, such as how older adults may experience different discrete emotion (i.e., anger versus sadness) from an evolutionary functional perspective. Other perspectives consider how an array of appraisal processes may change across adulthood (such as shifts in evaluations of self-control versus other-control for younger versus older adults). These newer approaches dig deeper into mechanistic explanations and underscore the need for greater theoretical integration. Later life is clearly a time of increased well-being, but the field is only on the cusp of understanding the mysteries of emotional experience in later life.
Scott P. Johnson
Visual scenes tend to be very complex: a multitude of overlapping surfaces varying in shape, color, texture, and depth relative to the observer. Yet most observers effortlessly perceive that the visual environment is composed of distinct objects, laid out across space, each with a particular shape that can be inferred from partial views and incomplete information. Moreover, observers generally expect objects to be continuous across space and time, to have a certain shape, and to be solid in three-dimensional (3D) space. The cortical visual system processes information for objects first by coding visual features, then by linking features into units, and last by interpretation of units as objects that may be recognizable or otherwise relevant to the observer. This way of conceptualizing object perception maps roughly onto processes of lower-, middle-, and higher-level visual processing that have long formed the basis for investigations of visual perception in adults, as well as theories of object perception, the ways visual deprivation reduces object perception skills, and the developmental time course of object perception in infancy.
Sven Hroar Klempe
The term “psychology” was applied for the first time in the 16th century. Yet the most interesting examples appeared in three different contexts. The Croatian poet and humanist Marko Marulić (ca. 1520), the German philosopher and Calvinist Johann Thomas Freig (1575), and the German Lutheran philosopher Rudolph Goclenius (1590). Marulić’s manuscript is likely lost, and neither of the other two defined the term. Even the interests of the three went apparently in different directions. Marulić focused on poetry and history, Freig on physica, and Goclenius on theological issues. Nevertheless, they had something in common, and this may represent the gate through which the ways they conceived the term can be understood. They all dealt with the soul, but also that it was a highly disputable concept and not uniformly understood. Another commonality was the avoidance or reinterpretation of Aristotle’s philosophy. The Florentines’ cultivation of Plato had influenced Marulić. Freig was a Ramist, thus, also a humanist who approached philosophical questions rhetorically. Goclenius belonged partly to the same movement. Consequently, they all shared a common interest in texts and language. This is just one, yet quite important aspect of the origin of psychology as a science. Thus, these text- and humanity-oriented aspects of psychology are traceable from the very beginning. This reaches a peak point when Alexander Baumgarten publishes his two volumes on aesthetics, as they were based on Christian Wolff’s Psychologia empirica (1732). They are also traceable in Kant’s critical phase, and even more in Wundt’s folkpsychology. Thus there is a more or less continuous line from the very first uses of the term psychology and some tendencies in social and cultural psychology. In other words, psychology is pursued along an historical line that ends up in the German, and not the British enlightenment.
Kyungmin Kim and Yijung Kim
The parent-child relationship is one of the most significant social relations for many individuals. In particular, intergenerational ties to adult children often remain as one of the main social networks and sources of support provisions in later life. By reviewing the key literature on older parent-child relations, this article discussed the dynamics and complexity of intergenerational ties and their impact on the lives of older adults. First, we discussed theoretical perspectives that have guided recent research on intergenerational relations, including the life course perspective, and solidarity, conflict, and ambivalence models. Second, we reviewed the literature on structural aspects of the relations, including coresidence, proximity, and contact, and their implications for older adults’ health and well-being. Third, regarding a functional side of parent-child relations, we discussed the different types and implications of support exchanges between older adults and their adult children. Finally, our discussion concluded with the review of emotional qualities (i.e., positive, negative, and ambivalent) in parent-child relations and the factors that may complicate the intergenerational ties in later life. Our review revealed that the significance of parent-child ties remains with the changes in demographic, social, and cultural environments of our aging society, and the different dimensions of parent-child ties (i.e., structural, functional, and emotional) have important influences on older adults’ well-being, quality of life, and health. To better understand the implications of parent-child ties in later life, future research is needed to uncover the specific mechanisms by which different dimensions of intergenerational relations and health outcomes among family members are linked.
S.P.J. van Alphen and S.M.J. Heijnen-Kohl
Personality disorders severely impact a person’s functioning in many ways. Although a person may have found ways to cope throughout life, at an older age underlying dysfunctional patterns can emerge and cause much distress both for the person and those around them. Why normal personality traits shift to abnormality is not easily understood. In literature there are many theories with different definitions. In this chapter a few of the prominent theories on the description of personality will be discussed. For example, some psychologists have described personality as a complex pattern that is deeply tied to psychological characteristics that are largely unaware, hard to wipe out, and expressed in all aspects of functioning. Other psychologists define personality as individual differences in the tendency to display consistent patterns of thoughts, feelings, and behaviors. The American Psychiatric Association (2013) defines personality traits as enduring patterns in the way someone perceives, relates to, and thinks about the environment and oneself and that these patterns are exhibited in a wide range of social and personal context. These definitions of personality are all concerned with unique and stable characteristics in different situations. These theories are not age-specific, but age-related changes and differences in manifestations do occur. This complicates diagnosis as measurements for older adults have barely been developed or validated. The feasibility of measurements and various information sources will be addressed. Descriptions and diagnosis have the ability to enhance treatment for patients with personality disorders. Known treatment forms have successfully been applied to older adults as well and differing treatment levels will be distinguished. Treatment of first choice can be aimed at changing personality characteristics or enhancing adaptation, but in some cases supportive treatment is the best fit. In clinical practice a variety of possible interventions is needed to provide the best care for different manifestations of personality disorders.
Frank Oswald and Hans-Werner Wahl
Along with the social, economic, care-related, organizational, and technological context, the physical and infrastructural environment indoors and out of the home has gained attention in behavioral aging research as well as in gerontology as a whole since the 1960s. There is, however, an ongoing trend to downplay physical-infrastructural environments in behavioral aging research at the conceptual and empirical level. Therefore, substance is provided to support the usefulness of ecology and aging perspectives for the psychology of aging by mainly addressing North American and European research in the area.
Simon J. Haines, Jill Talley Shelton, Julie D. Henry, Gill Terrett, Thomas Vorwerk, and Peter G. Rendell
Tasks that involve remembering to carry out future intentions (such as remembering to attend an appointment), and the cognitive processes that enable the completion of such tasks (such as planning), are referred to as prospective memory (PM). PM is important for promoting quality of life across many domains. For instance, failures in remembering to meet social commitments are linked to social isolation, whereas failures in remembering to fulfill occupational goals are linked to poorer vocational outcomes. Declines in PM functioning are of particular concern for older adults because of the strong links between PM and functional capacity. The relationship between age and PM appears to be complex, dependent on many factors. While some aspects of PM appear to hold up relatively well in late adulthood, others appear to show consistent age-related decline. Variability in age differences appears to partially reflect the fact that there are diverse types of PM tasks, which impose demands on a range of cognitive processes that are differentially affected by aging. Specifically, the level and type of environmental support associated with different PM task types appears to be a meaningful determinant of age-related effects. Given the worldwide changing age demographics, the interest in age-related effects on PM will likely intensify, and a primary focus will be how to optimize and maintain PM capacity for this population. This is already reflected in the increasing research on interventions focused on enhancing PM capacity in late adulthood, and points to important future directions in this area of study.
Mary Fry and Candace M. Hogue
There is a large literature base within the field of sport psychology that provides tremendous direction to coaches and parents on how to structure youth sport so that young athletes develop sport skills and concurrently reap psychological benefits from their sport participation. Much of this research has employed Nicholls’ Achievement Goal Perspective Theory and a Caring Framework to (a) identity the processes children undergo as their cognitive development matures across the elementary years, allowing them to accurately judge their ability by adolescence, (b) formulate their personal definitions of success in sport (develop their goal orientations), and (c) note features of the team and overall sport climate created by coaches and parents. Of particular importance is athletes’ perceptions of the motivational climate prevailing on their teams. Athletes can perceive a caring and task-involving climate where coaches reward effort, improvement, and cooperation among teammates, make everyone feel they play an important role on the team, and treat mistakes as part of the learning process. In contrast, athletes can also perceive an ego-involving climate where the coach rewards ability and performance outcome, fosters rivalry among teammates, punishes mistakes, and gives most of the recognition to a few “stars.”
When athletes perceive a caring and task-involving climate on their teams, they are more likely to have fun, exert high effort, experience intrinsic motivation, have better interpersonal relationships with coaches and athletes, display better sportsperson-like values and behaviors, have better psychological well-being, and even perform better. In contrast, when athletes perceive an ego-involving climate on their teams they experience fewer adaptive and positive motivational outcomes and greater problematic outcomes (e.g., increased cortisol; greater endorsement of unsportsperson-like behaviors). Research has clearly identified the benefits of coaches and parents creating a caring and task-involving climate for young athletes, yet there are still many ego-involving climates in the youth sport world. A number of organizations are committed to helping coaches and parents transform youth sport culture into a positive arena where young people can develop their athletic skills and have a rewarding sport experience.
Bradley W. Young, Bettina Callary, and Scott Rathwell
Paralleling the graying of the baby boomer generation, there has been remarkable growth in the number of Masters athletes (adult sport participants generally 35+ years old) and Seniors athletes (55+) worldwide. The phenomenon of the aging or older athlete is an opportunity to study the psychological conditions and considerations that distinguish older sportspersons from their younger counterparts. Although the vast majority of sport psychology research focuses on youth and adolescents or young adults in a high-performance context, a critical mass of literature on middle-aged and older athletes has emerged. Much research has aimed to understand the sport motivation of older adults; this work has evolved from early descriptive works to increasingly theoretically grounded and analytically advanced efforts that seek to better understand older athletes’ sport commitment and their long-term goal striving behaviors. Another theme of inquiry relates to the nature of adult athletes’ social motivations and the role of social identity in explaining immersion into sport. Research has examined various social influences on older athletes, and specifically how different social agents and social norms come to bear on older athletes’ sport participation. Much work has interrogated how social support facilitates older sport participation as well as the unique negotiations that older adults make with significant others to sustain their experience. Another research theme has sought to determine the various psychosocial benefits of adult sport, cataloguing benefits related to personal growth, age-related adaptation, and successful aging outcomes. Although the discourse on adult sport has been overly positive, several contributions have problematized aspects of adult sport, challenged the assertion that adult athletes are models that many others could follow, and have further suggested that narratives of Masters athletes may reinforce ageist stigma.
Katherine A. Tamminen and Courtney Braun
Adolescent athletes face increasing opportunities for competition at higher levels, as well as increasing demands on their time, pressure from parents and coaches, and conflicts with teammates and opponents, all during a time when adolescents are exploring different aspects of their identity and sense of self. Sport is a context for adolescent development, and despite the wide array of positive benefits that have been associated with sport participation during adolescence and into adulthood, it is also acknowledged that sport participation does not automatically confer benefits to adolescent athletes, and it may lead to potentially negative experiences and poor psychosocial outcomes.
Key concerns for researchers and practitioners working with adolescent athletes include managing various stressors and the development of adaptive coping strategies, the risk of experiencing sport burnout, bullying, and the potential for withdrawing or dropping out of sport. Despite these concerns, a large body of research among adolescent athletes provides evidence that athletes’ performance and positive psychosocial development may be enhanced among adolescent athletes by intentionally structuring the sport environment to promote positive outcomes; in particular, coaches, parents, and peers play an important role in shaping the sport experiences of adolescent athletes. Furthermore, the psychosocial characteristics and competencies associated with sport participation may not automatically transfer to other areas of adolescents’ lives unless they are intentionally and systematically structured to do so. It is important for coaches, parents, and sport administrators who are involved in developing and delivering programs for adolescent athletes to be aware of some of the psychosocial concerns that are relevant for this population, and to consider intentionally structuring sport programs to promote high levels of achievement as well as healthy psychological and social development among young athletes.
The ability to withstand or adapt to environmental demands is an inherent aspect of performance sport. At the highest level of competition, phenomenal levels of psychological resilience are necessary to attain and sustain success. Although various biopsychosocial factors contribute to the development of this resilience, an important differentiating factor in the emergence of the world’s best athletes is an ability to benefit in some way from the adversity they encounter, to the extent that they psychosocially grow and develop their resilience beyond their pre-trauma functioning, resulting in superior performance. These interrelated experiences of adversity, growth, and resilience involve ongoing complex interactions of numerous personal and situational factors. To briefly elaborate, following adversity-related trauma, athletes go through a “transitional process” whereby growth is facilitated through a combination of internal and external processes. For the world’s best athletes, changes to their motivation and personality appear to be particularly salient psychological aspects of adversarial growth. With regard to the development of resilience, the combined influence of psychological (i.e., personality, motivation, confidence, focus, support) and environmental (i.e., challenge, support) factors underpin athletes’ enhanced ability to withstand or adapt to environmental demands. Although there are a variety of potential beneficial outcomes of these experiences, it appears that there may also be some darker aspects to the world’s best athletes’ development and performance that have less desirable effects on their mental health and relationships. The integrative synthesis of psychological resilience and adversarial growth offers one of the most exciting and insightful avenues for future research in sport and performance.