Oscar Gonzalez and David P. MacKinnon
Lifespan developmental research studies how individuals change throughout their lifetime and how intraindividual or interindividual change leads to future outcomes. Lifespan researchers are interested in how developmental processes unfold and how specific developmental pathways lead to an outcome. Developmental processes have been previously studied using developmental cascade models, concepts of equifinality and multifinality, and developmental interventions. Statistical mediation analysis also provides a framework for studying developmental processes and developmental pathways by identifying intermediate variables, known as mediators, that transmit the effect between early exposures and future outcomes. The role of statistical mediation in lifespan developmental research is either to explain how the developmental process unfolds, or to identify mediators that researchers can target in interventions so that individuals change developmental pathways. The statistical mediation model is inherently causal, so the relations between the exposures, mediators, and outcomes have to be correctly specified, and ruling out alternative explanations for the relations is of upmost importance.
The statistical mediation model can be extended to deal with longitudinal data. For example, the autoregressive mediation model can represent change through time by examining lagged relations in multiwave datasets. On the other hand, the multilevel mediation model can deal with the clustering of repeated measures within individuals to study intraindividual and interindividual change. Finally, the latent growth curve mediation model can represent the variability of linear and nonlinear trajectories for individuals in the variables in the mediation model through time. As a result, developmental researchers have access to a range of models that could describe the theory of change they want to study. Researchers are encouraged to consider mechanisms of change and to formulate mediation hypotheses about lifespan development.
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.
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.
Shevaun D. Neupert and Jennifer A. Bellingtier
Daily diary designs allow researchers to examine processes that change together on a daily basis, often in a naturalistic setting. By studying within-person covariation between daily processes, one can more precisely establish the short-term effects and temporal ordering of concrete daily experiences. Additionally, the daily diary design reduces retrospective recall bias because participants are asked to recall events that occurred over the previous 24-hour period as opposed to a week or even a year. Therefore, a more accurate picture of individuals’ daily lives can be captured with this design. When conclusions are drawn between people about the relationship between the predictors and outcomes, the covariation that occurs within people through time is lost. In a within-person design, conclusions can be made about the simultaneous effects of within-person covariation as well as between-person differences. This is especially important when many interindividual differences (e.g., traits) may exist in within-person relationships (e.g., states).
Daily diary research can take many forms. Diary research can be conducted with printed paper questionnaires, divided into daily booklets where participants mail back each daily booklet at the end of the day or entire study period. Previous studies have called participants on the telephone to respond to interview questions each day for a series of consecutive days, allowing for quantitative as well as qualitative data collection. Online surveys that can be completed on a computer or mobile device allow the researcher to know the specific day and time that the survey was completed while minimizing direct involvement with the collection of each daily survey. There are many opportunities for lifespan developmental researchers to adopt daily diary designs across a variety of implementation platforms to address questions of important daily processes. The benefits and drawbacks of each method along with suggestions for future work are discussed, noting issues of particular importance for aging and lifespan development.
Gershon Tenenbaum and Edson Filho
Trustworthy measurement is essential to make inferences about people and events, as well as to make scientific inquiries and comprehend human behaviors. Measurement is used for validating and building theories, substantiating research endeavors, contributing to science, and supporting a variety of applications. Sport and exercise psychology is a theoretical and practical domain derived from two domains: psychology and kinesiology. As such, the measurement methods used by scientists and practitioners relate to the acquisition of motor skills (i.e., genetics and environment-deliberate practice), physiological measures (e.g., heart rate pulse, heart rate variability, breathing amplitude and frequency, galvanic skin response, and electrocardiogram), and psychological measures including introspective instruments in the form of questionnaires, interviews, and observations.
Sport and exercise psychology entails the measurement of motor performance (e.g., time-trials, one repetition maximum tests), cognitive development (e.g., knowledge base and structure, deliberate practice, perception-cognition, attention, memory), social aspects (e.g., team dynamics, cohesion, leadership, shared mental models, coach-performer interaction), the self (e.g., self-esteem, self-concept, physical self), affective and emotional states (e.g., mood, burnout), and psychological skills (e.g. imagery, goal-setting, relaxation, emotion regulation, stress management, self-talk, relaxation, and pre-performance routine). Sport and exercise psychologists are also interested in measuring the affective domain (e.g., quality of life, affect/emotions, perceived effort), psychopathological states (e.g., anxiety, depression), cognitive domain (e.g., executive functioning, information processing, decision making, attention, academic achievements, cognition and aging), social-cognitive concepts (e.g., self-efficacy, self-control, motivation), and biochemical markers of human functioning (e.g., genetic factors, hormonal changes). The emergence of neuroscientific methods have ushered in new methodological tools (e.g., electroencephalogram; fMRI) to assess central markers (brain systems) linked to performance, learning, and well-being in sport and exercise settings. Altogether, the measures in the sport and exercise domain are used to establish linkages among the emotional, cognitive, and motor systems.
Katy W. Martin-Fernandez and Yossef S. Ben-Porath
Attempts at informal personality assessment can be traced back to our distant ancestors. As the field of Clinical Psychology emerged and developed over time, efforts were made to create reliable and valid measures of personality and psychopathology that could be used in a variety of contexts. There are many assessment instruments available for clinicians to use, with most utilizing either a projective or self-report format. Individual assessment instruments have specific administration, scoring, and interpretive guidelines to aid clinicians in making accurate decisions based on a test taker’s answers. These measures are continuously adapted to reflect the current conceptualization of personality and psychopathology and the latest technology. Additionally, measures are adapted and validated to be used in a variety of settings, with a variety of populations. Personality assessment continues to be a dynamic process that can be utilized to accurately and informatively represent the test taker and aid in clinical decision making and planning.
Ronald E. Smith and Frank L. Smoll
Coaches occupy a central role in sport, fulfilling instructional, organizational, strategic, and social relationship functions, and their relationships with athletes influence both skill development and psychosocial outcomes of sport participation. This review presents the major theoretical models and empirical results derived from coaching research, focusing on the measurement and correlates of coaching behaviors and on intervention programs designed to enhance coaching effectiveness.
A strong empirical literature on motor skill development has addressed the development of technical sport skills, guided in part by a model that divides the skill acquisition process into cognitive, associative, and autonomous phases, each requiring specific coaching knowledge and instructional techniques. Social-cognitive theory’s mediational model, the multidimensional model of sport leadership, achievement goal theory, and self-determination theory have been highly influential in research on the psychosocial aspects of the sport environment. These conceptual models have inspired basic research on the antecedents and consequences of defined coaching behaviors as well as applied research on coach training programs designed to enhance athletes’ sport outcomes. Of the few programs that have been systematically evaluated, outcomes such as enjoyment, liking for coach and teammates, team cohesion, self-esteem, performance anxiety, athletes’ motivational orientation, and sport attrition can be influenced in a salutary fashion by a brief intervention with specific empirically derived behavioral guidelines that focus on creating a mastery motivational climate and positive coach-athlete interactions. However, other existing programs have yet to demonstrate efficacy in controlled outcome research.
Rebecca A. Zakrajsek and Jedediah E. Blanton
It is important for sport and exercise psychology (SEP) professionals to demonstrate that the interventions they employ make a difference. Assessing the degree of an intervention’s effectiveness depends first and foremost on the nature and scope of the intervention (i.e., the objective of the intervention) and its targeted group. Traditionally, interventions have been quite varied between the fields of sport psychology and exercise psychology; a common thread however, can be seen as an enhancement of the sport or exercise experience, along with an attempt to help the individual better self-regulate engagement with the targeted behavior or mindset. The central aim of enhancing the experience and increased self-regulation is oriented toward performance enhancement within sport psychology interventions, whereas within exercise psychology interventions the orientation is toward physical-activity adoption and better exercise program adherence. Although the two fields may have different objectives, it can be argued that sport psychology interventions—specifically psychological skills training (PST) interventions—can inform SEP professionals’ research and applied practices with both the sport and exercise populations.
Psychological skills training includes the strategies and techniques used to develop psychological skills, enhance sport performance, and facilitate a positive approach to competition. Since the early 1980s, a growing body of evidence has supported that the PST interventions SEP professionals employ do make a difference. In particular, evidence from research in sport contexts supports the use of a multimodal approach to PST interventions—combining different types of psychological strategies (e.g., goal-setting, self-talk, imagery, relaxation)—because a multimodal approach has demonstrated positive effects on both psychological skills and sport performance. The research investigating the effectiveness of PST interventions in enhancing performance has primarily centered on adult athletes who compete at competitive or elite levels. Elite athletes are certainly important consumers of SEP services; however, SEP professionals have rightfully challenged researchers and practitioners to target other consumers of SEP services who they argue are as deserving of PST as elite athletes. For example, young athletes and coaches are two populations that have traditionally been overlooked in the PST research. PST interventions targeting young athletes can help them to develop (at the start of their sporting careers) the type of psychological skills that facilitate a positive approach to competition and better abilities to self-regulate their emotional responses to stressful competitive situations. Coaches are also performers with unique needs who could benefit from PST interventions. Researchers have begun to target these two populations and the results might be considered the most intriguing aspects of the current PST literature. Future research related to PST interventions should target exercise populations. Exercise professionals often operate as coaches in healthy behavior change (e.g., strength and conditioning coaches, personal trainers, etc.) and as such should also employ, and monitor responses to, PST.
To facilitate further development and growth of PST intervention research in both sport and exercise settings, SEP professionals are encouraged to include a comprehensive evaluation of program effectiveness. In particular, four major areas to consider when evaluating PST programs are (a) the quality of the PST service delivery (e.g., the knowledge, delivery style, and characteristics of the SEP professional); (b) assessment of the sport psychological strategies participants used as a result of the PST program; (c) participants’ perceptions of the influence of the PST program on their psychological skills, performance, and enjoyment; and (d) measurement of participants psychological skills, performance, and enjoyment as a result of the PST program.
Kathleen Someah, Christopher Edwards, and Larry E. Beutler
There are many approaches to psychotherapy, commonly called “schools” or “theories.” These schools range from psychoanalytic, to variations of insight- and conflict-based approaches, through behavioral and cognitive behavioral approaches, to humanistic/existential approaches, and finally to integrative and eclectic approaches. Different and seemingly new approaches typically have been informed by older and more established ones. For instance, cognitive behavioral therapy (CBT), one of the more widely used approaches, evolved from traditional behavior therapy but has become sufficiently distinct by adding its own complex variations so as functionally to represent an approach of its own.
New approaches abound both in number and in complexity. Modern clinicians have had to become increasingly widely read and creative in trying to understand the ways in which patients may be helped. The sheer number of approaches, which has climbed into the hundreds, has challenged the field to find ways of ensuring that the treatments presented are effective. The advent of Evidence Based Practices (EBP) throughout the healthcare fields has placed the responsibility on those who advocate for particular types of treatment scientifically to demonstrate their efficacy and effectiveness. While this movement has brought standards to the field and has offered some assurance that psychotherapy is usually helpful, there remains much debate about whether the many different schools produce different results from one another. The debate about how best to optimize positive effects of psychotherapy continues, and there remain many questions to be asked of psychotherapy theories and of research on these approaches.
Matthew S. Fritz and Ann M. Arthur
Moderation occurs when the magnitude and/or direction of the relation between two variables depend on the value of a third variable called a moderator variable. Moderator variables are distinct from mediator variables, which are intermediate variables in a causal chain between two other variables, and confounder variables, which can cause two otherwise unrelated variables to be related. Determining whether a variable is a moderator of the relation between two other variables requires statistically testing an interaction term. When the interaction term contains two categorical variables, analysis of variance (ANOVA) or multiple regression may be used, though ANOVA is usually preferred. When the interaction term contains one or more continuous variables, multiple regression is used. Multiple moderators may be operating simultaneously, in which case higher-order interaction terms can be added to the model, though these higher-order terms may be challenging to probe and interpret. In addition, interaction effects are often small in size, meaning most studies may have inadequate statistical power to detect these effects.
When multilevel models are used to account for the nesting of individuals within clusters, moderation can be examined at the individual level, the cluster level, or across levels in what is termed a cross-level interaction. Within the structural equation modeling (SEM) framework, multiple group analyses are often used to test for moderation. Moderation in the context of mediation can be examined using a conditional process model, while moderation of the measurement of a latent variable can be examined by testing for factorial invariance. Challenges faced when testing for moderation include the need to test for treatment by demographic or context interactions, the need to account for excessive multicollinearity, and the need for care when testing models with multiple higher-order interactions terms.