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DeMond M. Grant and Evan J. White
Cognitive control is the ability to direct attention and cognitive resources toward achieving one’s goals. However, research indicates that anxiety biases multiple cognitive processes, including cognitive control. This occurs in part because anxiety leads to excessive processing of threatening stimuli at the expense of ongoing activities. This enhanced processing of threat interferes with several cognitive processes, which includes how individuals view and respond to their environment. Specifically, research indicates that anxious individuals devote their attention toward threat when considering both early, automatic processes and later, sustained attention. In addition, anxiety has negative effects on working memory, which involves the ability to hold and manipulate information in one’s consciousness. Anxiety has been found to decrease the resources necessary for effective working memory performance, as well as increase the likelihood of negative information entering working memory. Finally, anxiety is characterized by focusing excessive attention on mistakes, and there is also a reduction in the cognitive control resources necessary to correct behavior. Enhancing our knowledge of how anxiety affects cognitive control has broad implications for understanding the development of anxiety disorders, as well as emerging treatments for these conditions.
This article aims to provide a narrative overview on injury prevention in sport and performance psychology. Research and applied interest in psychological injury prevention in sport and performance psychology has risen in popularity over the past few decades. To date, existing theoretical models, pure and applied research, and practice-based evidence has focused on conceptualizing and examining psychological injury occurrence and prevention through stress-injury mechanisms, and predominantly in sport injury settings. However, given the inherited similarities across the different performance domains however, it is the authors’ belief that existing injury prevention knowledge can be transferable beyond sport but should be done with caution. A range of cognitive-affective-behavioral strategies such as goal setting, imagery, relaxation strategies, self-talk, and social support have been found beneficial in reducing injuries, particularly when used systematically (a) prior to injury occurrence as part of performance enhancement program and/or as a specific injury prevention measure, (b) during injury rehabilitation, and (c) as part of a return-to-activity process to minimize the risk of secondary injuries and reinjuries. Existing theoretical and empirical evidence also indicates that using cognitive-affective-behavioral strategies for injury prevention are effective when used as part of a wider, multi-modal intervention. Equally, such interventions may also need to address possible behavioral modifications required in sleep, rest, and recovery. Considering the existing empirical and anecdotal evidence to date, this paper argues that injury prevention efforts in sport and performance psychology should be cyclical, biopsychosocial, and person-centered in nature. In short, injury prevention should be underpinned by recognition of the interplay between personal (both physical and psychological), environmental, and contextual characteristics, and how they affect the persons’ cognitive-affective-behavioral processes before, during, and after injury occurrence, at different phases of rehabilitation, and during the return to activity or retirement from activity process. Moreover, these holistic injury prevention efforts should be underpinned by a philosophy that injury prevention is inherently intertwined with performance enhancement, with the focus being on the individual and their overall well-being.
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.
Nasreen A. Sadeq and Victor Molinari
The need for facilities that provide residential aged care is expected to increase significantly in the near future as the global population ages at an unprecedented rate. Many older adults will need to be placed in a residential care setting, such as an assisted living facility (ALF) or nursing home, when their caregivers can no longer effectively manage serious medical or psychiatric conditions at home. Although the types of residential care settings worldwide vary considerably, long-term care residents (LTC) and staff benefit from environmental and cultural changes in LTC settings. Unlike traditional medical models of LTC, culture change advocates for a shift toward holistic, person-centered care that takes place in homelike environments and accounts for the psychosocial needs of residents. Carving out a role for family members and training professional caregivers to address behavioral problems and quality-of-life issues remain a challenge. In LTC settings, preliminary research indicates that implementing person-centered changes addressing resident and caregiver needs may lead to better health outcomes, as well as increased satisfaction among patients, families, and staff. With the burgeoning world population of older adults, it is incumbent that they be provided with optimal humane culturally sensitive care.
Stuart Linke and Elizabeth Murray
Alcohol-use disorders are widespread and associated with a greatly increased risk of health-related and societal harms. The majority of harms associated with consumption are experienced by those who drink above recommended guidelines, rather than those who are alcohol dependent. Brief interventions and treatments based on screening questionnaires and feedback have been developed for this group, which are effective tools for reducing consumption in primary care and in other settings. Most people who drink excessively do not receive help to reduce the risks associated with excessive consumption. Digital versions of brief and extended interventions have the potential to reach populations that might derive benefit from them. Digital interventions utilize the same principles as do traditional face-to-face versions, but they have the advantages of availability, confidentiality, flexibility, low marginal costs, and treatment integrity. The evidence for the feasibility, acceptability, costs, and effectiveness of digital interventions is encouraging, and the evidence for effectiveness is particularly strong in studies of student populations. There are, however, a number of unresolved questions. It is not clear which components of interventions are required to maximize effectiveness, whether digital versions are enhanced by the addition of personal contact from a facilitator or a health professional, or how to increase take up of the offer of a digital intervention and reduce attrition from a program. These questions are common to many online behavior-change interventions and there are opportunities for cross-disciplinary learning between psychologists, health professionals, computer scientists, and e-health researchers.
Gregory A. Hinrichsen
In clinical practice with older adults, depression is a common presenting problem and is usually interwoven with one or more life problems. These problems are often the focus of psychotherapy. Interpersonal Psychotherapy (IPT) is a highly researched and effective treatment for depression in adults and older adults. IPT is time-limited, and as an individual psychotherapy it is usually conducted over 16 sessions. IPT focuses on one or two of four interpersonally relevant problems that may be a cause or consequence of depression. These include: role transitions (life change), interpersonal role disputes (conflict with another person), grief (complicated bereavement), and interpersonal deficits (social isolation and loneliness). The four IPT problem areas reflect issues that are frequently seen in psychotherapy with depressed older people.
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.
David Bunce and Sarah Bauermeister
Intraindividual variability in the present context refers to the moment-to-moment variation in attentional or executive engagement over a given time period. Typically, it is measured using the response latencies collected across the trials of a behavioral neurocognitive task. In aging research, the measure has received a lot of recent interest as it may provide important insights into age-related cognitive decline and neuropathology as well as having potential as a neurocognitive assessment tool in healthcare settings. In the present chapter, we begin by reviewing the key empirical findings relating to age and intraindividual variability. Here, research shows that intraindividual variability increases with age and predicts a range of age-related outcomes including gait impairment, falls and errors more broadly, mild cognitive impairment, dementia, and mortality. Brain imaging research suggests that greater variability is associated with age-related or neuropathological changes to a frontal–cingulate–parietal network and that white matter compromise and dopamine depletion may be key underlying mechanisms. We then consider the cognitive and neurobiological theoretical underpinnings of the construct before providing a description of the various methods and metrics that have been used to compute measures of variability – reaction time cut-offs, raw and residualized intraindividual standard deviations, coefficient of variation, ex-Gaussian curve and fast Fourier transformation. A further section considers the range of neurocognitive tasks that have been used to assess intraindividual variability. Broadly, these tasks can be classified on a continuum of cognitive demands as psychomotor, executive control or higher-order cognitive tasks (e.g., episodic memory). Finally, we provide some pointers concerning the pressing issues that future research needs to address in the area. We conclude that the existing body of theoretical and empirical work underlines the potential of intraindividual reaction time variability measures as additions to the neuropsychological test batteries that are used in the early detection of a range of age-related neurocognitive disorders in healthcare settings.
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.
Anja Van den Broeck and Sharon K. Parker
Job design or work design refers to the content, structure, and organization of tasks and activities. It is mostly studied in terms of job characteristics, such as autonomy, workload, role problems, and feedback. Throughout history, job design has moved away from a sole focus on efficiency and productivity to more motivational job designs, including the social approach toward work, Herzberg’s two-factor model, Hackman and Oldham’s job characteristics model, the job demand control model of Karasek, Warr’s vitamin model, and the job demands resources model of Bakker and Demerouti. The models make it clear that a variety of job characteristics make up the quality of job design that benefits employees and employers alike. Job design is crucial for a whole range of outcomes, including (a) employee health and well-being, (b) attitudes like job satisfaction and commitment, (c) employee cognitions and learning, and (d) behaviors like productivity, absenteeism, proactivity, and innovation. Employee personal characteristics play an important role in job design. They influence how employees themselves perceive and seek out particular job characteristics, help in understanding how job design exerts its influence, and have the potential to change the impact of job design.
Vincente Martínez-Tur and Carolina Moliner
Traditionally, justice in teams refers to a specific climate—called justice climate—describing shared perceptions about how the team as a whole is treated. Justice at the individual level has been a successful model from which to build the concept of justice in teams. Accordingly, there is a parallelism between the individual and team levels in the investigation of justice, where scholars’ concerns and responses have been very similar, despite studying different levels of construct. However, the specific particularities of teams are increasingly considered in research. There are three concepts (faultlines, subgrouping, and intergroup justice) that contribute to knowledge by focusing on particularities of teams that are not present at the individual level. The shift toward team-based structures provides an opportunity to observe the existence of dividing lines that may split a team into subgroups (faultlines) and the difficulty, in many cases, of conceiving of the team members as part of a single group. This perspective about teams also stimulates the study of the subgroup as a source of justice and the focus on intergroup justice within the team. In sum, the organizational context facilitates shared experiences and perceptions of justice beyond individual differences but also can result in potential conflicts and discrepancies among subgroups within the team in their interpretation of fairness.
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).
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.
W. James Weese and P. Chelladurai
The study of leadership has a long and distinguished history. Over the past 100 years, researchers have pursued distinct lines of inquiry summarized in the trait theories, the behavioral theories, the contingency theories, and the transactional/transformational theories of leadership. More recent cognitive approaches have dominated the leadership literature base with emphasis on the areas of emotional intelligence and servant leadership. Even as new leadership models emerge, it is important to note that portions of the older theories continue to inform our understandings. The voluminous research base confirms three things about leadership. Leadership is a social process, involving people and engaging their emotions, motivations, and moods. Secondly, leadership is about influence. True leaders influence the thoughts and behaviors of people and groups without the manipulation of rewards or punishments. Some writers suggest that leadership is synonymous with influence. Finally, leaders focus, inspire, and motivate people and groups toward the accomplishment of a predetermined goal or objective. They bring clarity to a desired end and they inspire colleagues to channel their talents and energies toward its attainment. The theoretical developments of leadership, and the latest developments in particular (i.e., emotional intelligence and servant leadership), hold great promise for application in the sports domain.
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.
Loneliness or perceived social isolation is a subjective experience relating to dissatisfaction with one’s social relationships. Most research has focused on the experience of loneliness in old age, but levels of loneliness are also known to be high among teenagers and young adults. While poor health may be associated with increased feelings of loneliness, there is now considerable evidence on the role of loneliness as a risk factor for poor mental and physical health. Studies show that loneliness is associated with an increased risk of developing dementia and chronic diseases, and also with a higher rate of mortality. Risky health behaviors, a poor cardiovascular profile and compromised immune functioning have all been proposed as potential pathways through which loneliness may affect health. However, much still remains to be understood about these mechanisms.
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.
Matthew S. Fritz and Houston F. Lester
Mediator variables are variables that lie between the cause and effect in a causal chain. In other words, mediator variables are the mechanisms through which change in one variable causes change in a subsequent variable. The single-mediator model is deceptively simple because it has only three variables: an antecedent, a mediator, and a consequent. Determining that a variable functions as a mediator is a difficult process, however, because causation can be inferred only when many strict assumptions are met, including, but not limited to, perfectly reliable measures, correct temporal design, and no omitted confounders. Since many of these assumptions are difficult to assess and rarely met in practice, the significance of a statistical test of mediation alone usually provides only weak evidence of mediation.
New methodological approaches are constantly being developed to circumvent these limitations. Specifically, new methods are being created for the following purposes: (1) to assess the impact of violating assumptions (e.g., sensitivity analyses) and (2) to make fewer assumptions and provide more flexible analysis techniques (e.g., Bayesian analysis or bootstrapping) that may be more robust to assumption violations. Despite these advances, the importance of the design of a study cannot be overstated. A statistical analysis, no matter how sophisticated, cannot redeem a study that measured the wrong variables or used an incorrect temporal design.