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Identity Development in Adolescence and Adulthood  

Jane Kroger

Psychoanalyst Erik Erikson was the first professional to describe and use the concept of ego identity in his writings on what constitutes healthy personality development for every individual over the course of the life span. Basic to Erikson’s view, as well as those of many later identity writers, is the understanding that identity enables one to move with purpose and direction in life, and with a sense of inner sameness and continuity over time and place. Erikson considered identity to be psychosocial in nature, formed by the intersection of individual biological and psychological capacities in combination with the opportunities and supports offered by one’s social context. Identity normally becomes a central issue of concern during adolescence, when decisions about future vocational, ideological, and relational issues need to be addressed; however, these key identity concerns often demand further reflection and revision during different phases of adult life as well. Identity, thus, is not something that one resolves once and for all at the end of adolescence, but rather identity may continue to evolve and change over the course of adult life too. Following Erikson’s initial writings, subsequent theorists have laid different emphases on the role of the individual and the role of society in the identity formation process. One very popular elaboration of Erikson’s own writings on identity that retains a psychosocial focus is the identity status model of James Marcia. While Erikson had described one’s identity resolution as lying somewhere on a continuum between identity achievement and role confusion (and optimally located nearer the achievement end of the spectrum), Marcia defined four very different means by which one may approach identity-defining decisions: identity achievement (commitment following exploration), moratorium (exploration in process), foreclosure (commitment without exploration), and diffusion (no commitment with little or no exploration). These four approaches (or identity statuses) have, over many decades, been the focus of over 1,000 theoretical and research studies that have examined identity status antecedents, behavioral consequences, associated personality characteristics, patterns of interpersonal relations, and developmental forms of movement over time. A further field of study has focused on the implications for intervention that each identity status holds. Current research seeks both to refine the identity statuses and explore their dimensions further through narrative analysis.


Imaging the Infant Brain  

Hao Huang

The most dynamic postnatal brain development takes place during human infancy. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The improvements in noninvasive imaging techniques, especially magnetic resonance imaging, magnetic resonance spectroscopy, electroencephalography, magnetoencephalography, positron emission tomography, and near-infrared spectroscopy, have provided unprecedented opportunities to quantify and map the early developmental changes at whole brain and regional levels. Unique to infant brain imaging, tailored infant image acquisition and analysis methods—such as motion correction, high-resolution imaging, optimization of imaging parameters for smaller and immature brain, age-specific brain atlas and parcellation scheme, age-specific white matter tractography, functional connectivity analysis given incomplete brain networks, and advanced gray and white matter segmentation for infant brains should be taken into consideration. Delineating functional, physiological, and structural changes of the infant brain through imaging provides insights into the complicated processes of both typical development and the neuropathological mechanisms underlying various brain disorders with early onset in infancy, such as autistic spectrum disorder. Identification of imaging biomarkers of neurodevelopmental disorders during infancy by leveraging techniques such as machine learning may offer a valuable time window for early intervention.


Imprinting as Social Learning  

Timothy D. Johnston

Imprinting is a form of rapid, supposedly irreversible learning that results from exposure to an object during a specific period (a critical or sensitive period) during early life and produces a preference for the imprinted object. The word “imprinting” is an English translation of the German Prägung (“stamping in”), coined by Konrad Lorenz in 1935 to refer to the process that he studied in geese. Two types of imprinting have traditionally been distinguished: filial imprinting, involving the formation of an immediate social attachment to the mother or a mother-substitute, and sexual imprinting, involving the formation of a sexual preference that is manifested later in life. Both types of imprinting were subject to extensive experimental study beginning around 1950. Originally described in precocial birds (ducks, geese, and domestic chickens), imprinting has also been used to explain the formation of early social attachments in other species, including human infants. Imprinting has served as a useful model for studying the neural processes involved in learning and behavioral development and has provided a framework for thinking about other developmental processes.


Inflammation As a Biomarker Method in Lifespan Developmental Methodology  

Stephanie J. Wilson, Alex Woody, and Janice K. Kiecolt-Glaser

Inflammatory markers provide invaluable tools for studying health and disease across the lifespan. Inflammation is central to the immune system’s response to infection and wounding; it also can increase in response to psychosocial stress. In addition, depression and physical symptoms such as pain and poor sleep can promote inflammation and, because these factors fuel each other, all contribute synergistically to rising inflammation. With increasing age, persistent exposure to pathogens and stress can induce a chronic proinflammatory state, a process known as inflamm-aging. Inflammation’s relevance spans the life course, from childhood to adulthood to death. Infection-related inflammation and stress in childhood, and even maternal stress during pregnancy, may presage heightened inflammation and poor health in adulthood. In turn, chronically heightened inflammation in adulthood can foreshadow frailty, functional decline, and the onset of inflammatory diseases in older age. The most commonly measured inflammatory markers include C-reactive protein (CRP) and proinflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α). These biomarkers are typically measured in serum or plasma through blood draw, which capture current circulating levels of inflammation. Dried blood spots offer a newer, sometimes less expensive collection method but can capture only a limited subset of markers. Due to its notable confounds, salivary sampling cannot be recommended. Inflammatory markers can be added to a wide range of lifespan developmental designs. Incorporating even a single inflammatory assessment to an existing longitudinal study can allow researchers to examine how developmental profiles and inflammatory status are linked, but repeated assessments must be used to draw conclusions about the associations’ temporal order and developmental changes. Although the various inflammatory indices can fluctuate from day to day, ecological momentary assessment and longitudinal burst studies have not yet incorporated daily inflammation measurement; this represents a promising avenue for future research. In conclusion, mounting evidence suggests that inflammation affects health and disease across the lifespan and can help to capture how stress “gets under the skin.” Incorporating inflammatory biomarkers into developmental studies stands to enhance our understanding of both inflammation and lifespan development.


Integrated Theories of Biological Aging  

Conscience P. Bwiza, Jyung Mean Son, and Changhan Lee

Aging is a progressive process with multiple biological processes collectively deteriorating with time, ultimately causing loss of physiological functions necessary for survival and reproduction. It is also thought to have a strong evolutionary basis, largely resulting from the lack of selection force. Here, we discuss the evolutionary aspects of aging and a selection of theories founded on a variety of biological functions that have been shown to be involved in aging in multiple model organisms, ranging from the simple yeast, worms, flies, killifish, and rodents, to non-human primates and humans. The conglomerate of distinct theories has together revolutionized aging research in the past several decades, far more than what humankind has known since the dawn of civilization. However, not one theory alone can independently explain aging and should not be interpreted out of context of the cell and organism in its entirety. That said, the 21st century has been and will be an exciting time in the field of aging, with scientific advances on health span and lifespan being made at multiple fronts of biology and medicine in an unprecedented scale.


Intergenerational Transmission of Risk for Behavioral Problems Including Substance Use  

Deborah M. Capaldi, David C. R. Kerr, and Stacey S. Tiberio

Intergenerational studies are key to informing research, preventive intervention, and policy regarding family influences on healthy development and maladjustment. Continuities in family socialization and contextual risks across generations, as well as genetic factors, are associated with the development of psychopathology—including externalizing problems in children—and with intergenerational associations in the use of marijuana, alcohol, tobacco, and other drugs; these continuities are reflected in the low-to-moderate associations generally found in prospective studies. Until recent years, estimates of intergenerational continuities in problem behaviors and the processes explaining such associations (e.g., parenting behaviors) have been based largely on retrospective reports by adults about their own parents’ behaviors. Now there are some long-term prospective studies spanning as many as 30 years that can assess linkages between behaviors in one generation and the next. Whereas such studies have considerable design and implementation challenges, and are very expensive, it is of critical importance to examine the magnitude of associations of behaviors across generations. For example, a modest association across generations suggests either that genetic factors have a limited influence on that behavior or that they are subject to considerable moderation by environmental factors. These prospective studies relate to theoretical developments regarding intergenerational influences that are reviewed—for example, individual differences in genetic sensitivity to environmental influences. The theoretical approach employed in the Oregon Youth Study—Three Generation Study is a Dynamic Developmental Systems (DDS) model of continuous feedback across systems throughout development. A new hypothesis encompassed by DDS is developmental congruence of intergenerational associations in problem behaviors. As used in geometry, congruence refers to figures of a similar shape and size. This term has been adapted to refer to the expectation that ages of onset and patterns of growth in key behaviors will show similarity across generations. This is based on the theory that genetic and temperamental factors increase an individual’s risk when these factors are expressed at sensitive developmental periods. Thus, the timing of these manifestations (e.g., susceptibility to deviant peer influences) is expected to be similar across generations. Developmental similarity is also likely due to continuities in social-risk context and family mechanisms, such as parenting.


Interprofessional Training and Practice: The Need for More Engagement, Training, and Research in Geropsychology  

Nancy A. Pachana and Gwen Yeo

Interdisciplinary teams consisting of a variety of health professionals working toward common patient goals have become an important innovation in clinical practice. In many parts of the world interdisciplinary teams have become part of practice, including in geriatrics. However, many gaps and the need for further empirical research and translation into practice remain. This is particularly true for the discipline of psychology, as much of the extant literature in engagement, training and practice in geriatric settings or educational settings does not include psychologists. Many advances in interprofessional teams, in acute settings in particular, do not include psychologists as part of the team. With respect to training, educating trainee health professionals, including psychologists, in interdisciplinary practice has still not become a standard part of training curricula internationally. Several excellent models of interprofessional and interdisciplinary training, including international models of interdisciplinary team competencies, have been developed. However, both the empirical testing of these models and their implementation in educational and practice settings is lacking. Within the geriatric healthcare context, the evidence base for both interprofessional care and the need for enhanced training models incorporating interprofessional skills is evolving, and further research on efficacy in evolving clinical contexts and translation into educational contexts worldwide is required. Ultimately, psychology must increase its presence within both interprofessional research and applied contexts.


Intraindividual Variability in Lifespan Developmental Methodology  

Eric S. Cerino and Karen Hooker

Intraindividual variability (IIV) refers to short-term fluctuations that may be more rapid, and are often conceptualized as more reversible, than developmental change that unfolds over a longer period of time, such as years. As a feature of longitudinal data collected on micro timescales (i.e., seconds, minutes, days, or weeks), IIV can describe people, contexts, or general processes characterizing human development. In contrast to approaches that pool information across individuals and assess interindividual variability in a population (i.e., between-person variability), IIV is the focus of person-centered studies addressing how and when individuals change over time (i.e., within-person variability). Developmental psychologists interested in change and how and when it occurs, have devised research methods designed to examine intraindividual change (IIC) and interindividual differences in IIC. Dispersion, variability, inconsistency, time-structured IIV, and net IIV are distinct operationalizations of IIV that, depending on the number of measures, occasions, and time of measurement, reflect unique information about IIV in lifespan developmental domains of interest. Microlongitudinal and measurement-burst designs are two methodological approaches with intensive repeated measurement that provide a means by which various operationalizations of IIV can be accurately observed over an appropriate temporal frame to garner clearer understanding of the dynamic phenomenon under investigation. When methodological approaches are theoretically informed and the temporal frame and number of assessments align with the dynamic lifespan developmental phenomenon of interest, researchers gain greater precision in their observations of within-person variability and the extent to which these meaningful short-term fluctuations influence important domains of health and well-being. With technological advancements fueling enhanced methodologies and analytic approaches, IIV research will continue to be at the vanguard of pioneering designs for elucidating developmental change at the individual level and scaling it up to generalize to populations of interest.


Language Acquisition  

Erica H. Wojcik, Irene de la Cruz-Pavía, and Janet F. Werker

Language is a structured form of communication that is unique to humans. Within the first few years of life, typically developing children can understand and produce full sentences in their native language or languages. For centuries, philosophers, psychologists, and linguists have debated how we acquire language with such ease and speed. Central to this debate has been whether the learning process is driven by innate capacities or information in the environment. In the field of psychology, researchers have moved beyond this dichotomy to examine how perceptual and cognitive biases may guide input-driven learning and how these biases may change with experience. There is evidence that this integration permeates the learning and development of all aspects of language—from sounds (phonology), to the meanings of words (lexical-semantics), to the forms of words and the structure of sentences (morphosyntax). For example, in the area of phonology, newborns’ bias to attend to speech over other signals facilitates early learning of the prosodic and phonemic properties of their native language(s). In the area of lexical-semantics, infants’ bias to attend to novelty aids in mapping new words to their referents. In morphosyntax, infants’ sensitivity to vowels, repetition, and phrase edges guides statistical learning. In each of these areas, too, new biases come into play throughout development, as infants gain more knowledge about their native language(s).


Language and Cognitive Aging  

Lori E. James and Sara Anne Goring

The questions of whether and why language processes change in healthy aging require complicated answers. Although comprehension appears to be more stable across adulthood than does production, there is evidence for age-related changes and also for constancy within both input and output components of language. Further, these changes can be considered at various levels of the language hierarchy, such as sensory input, words, sentences, and discourse. As concluded in several other comprehensive reviews, older adults’ language production ability declines much more noticeably than does their comprehension, presumably because comprehension is able to benefit from contextual processing in a way that production cannot. Specifically, lexical and orthographic retrieval become more difficult during normal aging, and these changes appear to represent the most noticeable age-related declines in language production. Some theories of age-related decline focus on global deterioration of cognitive function, whereas other theories predict changes in specific processes related to language function. Both types of theories have received empirical support as applied to language performance, although additional theoretical development is still needed to capture the patterns of effects. Further, in order to truly understand how cognitive aging impacts the ability to understand and produce language, it is necessary to examine how age-related shifts in goals, expertise, and compensatory strategies influence language processes. There are important implications of research on language and cognitive aging, in that language can play a role in physical health and psychological well-being. In summary, our review of the existing literature on language and cognitive aging supports previous claims that language ability is asymmetrically impacted by age, with smaller overall effects of aging on comprehension than production processes.


Language Development  

Carolyn Quam and Teresa Roberts

Language is a complex human capacity. The speed with which young children learn it is a remarkable feat. Across diverse cultures and family structures, children learn thousands of languages. Despite tremendous variation across languages, commonalities hold in structure and learning mechanisms. Children undergo perceptual and expressive development. They learn to organize and process language structure at the levels of semantics, phonology, morphology, syntax, and pragmatics. Rates of learning of linguistic patterns are shaped by frequency, complexity, concreteness of form-to-meaning mappings, and the number of exceptions to a rule. In languages with written forms, children apply language knowledge to reading and writing.


Life Space in Older Adults  

Markus Wettstein, Hans-Werner Wahl, and Michael Schwenk

When referring to life space, researchers usually mean the area in which individuals move in their everyday lives. Life space can be measured based on different approaches, by means of self-reports (i.e., questionnaires or diaries) or by more recent approaches of technology-based objective assessment (e.g., via Global Positioning System [GPS] devices or smartphones). Life space is an important indicator of older adults’ out-of-home mobility and is meaningfully associated with autonomy, well-being, and quality of life. Substantial relationships between life space and socio-demographic indicators, health, and cognitive abilities have been reported in previous research. Future research on life space in old age will benefit from a more comprehensive and stronger interdisciplinary perspective, from taking into account different time scales (i.e., short- and long-term variability), and from considering life space as a multidimensional measure that can be best assessed based on multi-method approaches with multiple indicators.


Longitudinal, Cross-Sectional, and Sequential Designs in Lifespan Developmental Psychology  

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.


Longitudinal Structural Equation Modeling in Lifespan Developmental Analyses  

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.


Measurement Burst Designs in Lifespan Developmental Research  

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.


Metamemory and Cognitive Aging  

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.


Methodology for Twin Studies of Aging  

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.


Mixed Methods Research in Adult Development and Aging  

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.


Mixture Modeling for Lifespan Developmental Research  

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.


Moderation in Lifespan Developmental Analyses  

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.