Michael J. Zickar
Personnel and vocational testing has made a huge impact in public and private organizations by helping organizations choose the best employees for a particular job (personnel testing) and helping individuals choose occupations for which they are best suited (vocational testing). The history of personnel and vocational testing is one in which scientific advances were influenced by historical and technological developments.
The first systematic efforts at personnel and vocational testing began during World War I when the US military needed techniques to sort through a large number of applicants in a short amount of time. Techniques of psychological testing had just begun to be developed at around the turn of the 20th century and those techniques were quickly applied to the US military effort. After the war, intelligence and personality tests were used by business organizations to help choose applicants most likely to succeed in their organizations. In addition, when the Great Depression occurred, vocational interest tests were used by government organizations to help the unemployed choose occupations that they might best succeed in.
The development of personnel and vocational tests was greatly influenced by the developing techniques of psychometric theory as well as general statistical theory. From the 1930s onward, significant advances in reliability and validity theory provided a framework for test developers to be able to develop tests and validate them. In addition, the civil rights movement within the United States, and particularly the Civil Rights Act of 1964, forced test developers to develop standards and procedures to justify test usage. This legislation and subsequent court cases ensured that psychologists would need to be involved deeply in personnel testing. Finally, testing in the 1990s onward was greatly influenced by technological advances. Computerization helped standardize administration and scoring of tests as well as opening up the possibility for multimedia item formats. The introduction of the internet and web-based testing also provided additional challenges and opportunities.
Robert J. Sternberg
Intelligence needs to be understood in the cultural contexts in which it is displayed. For one thing, people in different cultures have different conceptions (implicit theories) of what intelligence is. Asian and African cultures tend to have broader and more encompassing views of intelligence than do Western cultures. Asians and Africans place less emphasis on mental speed and more emphasis on social and emotional aspects of behavior, as well as on wisdom. These implicit theories are important because in everyday life, people’s behavior is guided not so much by scores on standardized or other tests but rather by people’s implicit theories. For example, hiring and promotion decisions are usually based on such implicit theories, not on test scores.
Studies of performances by people, especially children, in different cultures suggest that the strengths of individuals across cultures are not necessarily well represented by conventional intelligence tests. For example, in some cultures, knowledge of herbal medications used to combat parasitic illnesses, or knowledge of hunting and gathering, or knowledge of how to effectively ice fish, can be more important to assessing intelligence than scores on a standardized test. Eskimo children may know how to navigate across the frozen tundra in the winter without obvious landmarks, yet they may not be able to attain high scores on conventional intelligence tests. Some of those who would score highly on such tests would be unable to do such navigation, to their peril.
There is no such thing as a culture-free test of intelligence, and there probably is no test that is genuinely culture-fair either. At best, tests should be culture-relevant, measuring the cognitive and other skills relevant to effectively adapt to particular cultures. These skills are likely to be partially but not fully overlapping across cultures. Thus, intelligence needs to be understood in its cultural contexts, not divorced from such contexts.
Igor Grossmann and Franki Kung
The concept of wisdom is ancient and deeply embedded in the cultural history of humanity. However, only since 1980s have psychologists begun to study it scientifically. Taking a culturally and philosophically informed perspective, this article integrates insights from the quantitative science of wisdom. Analysis of epistemological traditions and research on folk theories of wisdom suggest cultural similarities in the domain of cognition (e.g., wisdom as reasoning ability and knowledge). These similarities can be contrasted with cultural differences concerning folk-theoretical affective and prosocial themes of wisdom, as well as expression of various wisdom-related themes, rooted in distinct sociocultural and ecological environments. Empirical evidence indicates that wisdom is an individually and culturally malleable construct, consistent with an emerging constructionist account of wisdom and its development. Future research can benefit from integration of ecological and cultural-historical factors for the meaning of wisdom and its expression.
In the literature of mainstream scientific psychology, German scholar William Stern has been known primarily (if at all) as the inventor of the intelligence quotient (IQ). In fact, however, Stern’s contributions to psychology were much greater and more consequential than this. In this all-inclusive article, I have sought to provide readers with a fuller appreciation for the breadth and depth of Stern’s work, and, in particular, for that comprehensive system of thought that he elaborated under the name “critical personalism.” Drawing frequently on translated quotations from Stern’s published works, and on his personal correspondence with the Freiburg philosopher Jonas Cohn, I have endeavored to show how Stern was much more than “the IQ guy.” During the first 20 years of his academic career, spent at the University of Breslau in what is now the Polish city of Wroclaw, Stern founded that sub-discipline of psychology that would be concentrated on the study of individual differences in various aspects of human psychological functioning. He also made major contributions to that sub-discipline referred to at the time as “child” psychology, and laid the foundations for a comprehensive system of thought that he would name “critical personalism.” After relocating to Hamburg in 1916, Stern continued his scholarly efforts in these domains, taught courses both in psychology and in philosophy at the university that opened its doors there in 1919, and played major administrative roles there in the institutional homes of both disciplines until forced to flee Nazi Germany in 1934. The present chapter highlights ways in which, over the course of his scholarly career, Stern boldly opposed certain trends within mainstream thinking that were ascendant during his time.
Ananiev’s approach shares the Activity Theory (AT) paradigm, dominant in Soviet psychology. Ananiev builds on the main fundamentals of the AT paradigm, considering psyche as a special procreation of the matter, engendered by the active interaction of the individual with the environment. The unique feature of his approach to AT is that he turned it “toward the inside,” focusing on the relation of the human individual to his own physicality, to his own bodily substrate. Ananiev sought by his intention to keep a holistic vision of a human being, considering the latter in the context of his real life, that is, the bodily substrate in its biological specificity in context of the concrete sociohistorical life course of the personality. Like no other psychologist, Ananiev did not limit his research to the sphere of narrowly defined mental phenomena. He conducted a special kind of research, labeled as “complex,” in the course of which characteristics of the same subjects: sociological, socio-psychological, mental, physiological, and psychophysiological indicators—life events of the subjects—were monitored for many years. He focused on ontogenetic development in adulthood, which he, ahead of his time, considered as a period of dynamic changes and differentiated development of functions. The focus of his attention was on individual differences in the ontogenetic development of mental and psycho-physiological functions, especially those deviations from general regularities that resulted from the impact of the life course of the individual. Individualization, the increase of individual singularity, is the main effect of human development and its measure for Ananiev.
Ananiev developed a number of theoretical models and concepts. The best-known of Ananiev’s heritage is his theoretical model of human development, often named the “individuality concept.” According to this model, humans do not have any preassigned “structure of personality” or “initial harmony.” The starting point of human development is a combination of potentials—resources and reserves, biological and social. The human creates himself in the process of interaction with the world. Specialization, individually specific development of functions, appears here not as a distortion of the pre-set harmony of the whole but as the way of self-determining progressive human development. The most important practical task of psychology he viewed as psychological support and provision in the process of developing a harmonious individuality, based on the individual potentials.
Sara J. Czaja and Chin Chin Lee
The expanding power of computers and the growth of information technologies such as the Internet have made it possible for large numbers of people to have direct access to an increasingly wide array of information sources and services. Use of technology has become an integral component of work, education, communication, entertainment, and health care. Moreover, home appliances, security systems, and other communication devices are becoming more integrated with network resources providing faster and more powerful interactive services. Older adults represent an increasing large proportion of the population and will need to be active users of technology to function independently and receive the potential benefits of technology. Thus, it is critically important to understand how older adults respond to and adopt new information technologies. Technology offers many potential benefits for older people such as enhanced access to information and resources and health-care services, as well as opportunities for cognitive and social engagement. Unfortunately, because of a number of factors many older people confront challenges and barriers when attempting to access and use technology systems.
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.
Li Chu, Yang Fang, Vivian Hiu-Ling Tsang, and Helene H. Fung
Cognitive processing of social and nonsocial information changes with age. These processes range from the ones that serve “mere” cognitive functions, such as recall strategies and reasoning, to those that serve functions that pertain to self-regulation and relating to others. However, aging and the development of social cognition unfold in different cultural contexts, which may assume distinct social norms and values. Thus, the resulting age-related differences in cognitive and social cognitive processes may differ across cultures. On the one hand, biological aging could render age-related differences in social cognition universal; on the other hand, culture may play a role in shaping some age-related differences. Indeed, many aspects of cognition and social cognition showed different age and culture interactions, and this makes the study of these phenomena more complex. Future aging research on social cognition should take cultural influences into consideration.
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.
Lizbeth Benson and Nilam Ram
In ecological sciences, biodiversity is the dispersion of organisms across species and is used to describe the complexity of systems where species interact with each other and the environment. Some argue that biodiversity is important to cultivate and maintain because higher levels are indicative of health and resilience of the ecosystem. Because each species performs functional roles, more diverse ecosystems have greater capability to respond, maintain function, resist damage, and recover quickly from perturbations or disruptions. In the behavioral sciences, diversity-type constructs and metrics are being defined and operationalized across a variety of functional domains (socioemotional, self, cognitive, activities and environment, stress, and biological). Emodiversity, for instance, is the dispersion of an individual’s emotion experiences across emotion types (e.g., happy, anger, sad). Although not always explicitly labeled as such, many core propositions in lifespan developmental theory—such as differentiation, dedifferentiation, and integration—imply intraindividual change in diversity and/or interindividual differences in diversity. For example, socioemotional theories of aging suggest that as individuals get older, they increasingly self-select into more positive valence and low arousal emotion inducing experiences, which might suggest that diversity in positive and low arousal emotion experiences increases with age. When conceptualizing and studying diversity, important considerations include that diversity (a) provides a holistic representation of human systems, (b) differs in direction, interpretation, and linkages to other constructs such as health (c) exists at multiple scales, (d) is context-specific, and (e) is flexible to many study designs and data types. Additionally, there are also a variety of methodological considerations in study of diversity-type constructs including nuances pertaining theory-driven or data-driven approaches to choosing a metric. The relevance of diversity to a broad range of phenomena and the utility of biodiversity metrics for quantifying dispersion across categories in multivariate and/or repeated measures data suggests further use of biodiversity conceptualizations and methods in studies of lifespan development.