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Trait Paradigm of Psychology for Intelligence

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Published: Fri, 23 Feb 2018

Trait Paradigm of Psychology and How It Applies To the Measurement of Intelligence and Personality: An Explanation

It has long been observed that individuals differ one from another on many psychological dimensions. This is why Cervone and Lawrence (2007) say that traits, the primary unit of personality description, are relatively enduring ways in which individuals differ. Assessment at the level of traits is variable centered and nomothetic, focusing on differences among individuals, as opposed to the person-centered and idio-graphic approach that focuses on individuals, and that typically characterises assessment at deeper and more abstract levels of personality. An area of intense interest among psychologists is the measurement of individual differences in personality. Lubinski (2004) mentions personality is commonly defined as the constellation of traits, or typical and relatively stable patterns of responding to the environment, which are unique to various individuals. An important focus of educational psychology is the assessment of these traits and other related psychological attributes such as interests, preferences, and attitudes (Lubinski, 2004).

Personality traits describe individual differences in human beings’ typical ways of perceiving, thinking, feeling, and behaving that are generally consistent over time and across situations. Three major research areas are central to trait psychology. First, trait psychologists have attempted to identify sets of basic traits that adequately describe between-person variation in human personality. Second, social scientists across disciplines use personality traits to predict behavior and life outcomes. Third, trait psychologists attempt to understand the nature of behavioral consistency and the coherence of the person in relation to situational influences.

Cervone and Lawrence (2007) mention that there are two prominent approaches to identifying the basic personality traits and their organizational structure (McCrae and John 1992). The lexical approach emphasizes the evaluation of personality trait adjectives in the natural language lexicon and assumes that those personality descriptors encoded in everyday language reflect important individual differences, particularly if they are found across languages. The questionnaire approach attempts to assess important traits derived from psychologically based and biologically based personality theories. Self- and peerratings on sets of lexically derived or theoretically derived traits have typically been subjected to factor analysis to develop hierarchical organizations of traits reflecting a small number of broad superordinate dimensions overarching a large number of narrow-band traits. At the superordinate level, contemporary trait structural models vary in the number of dimensions necessary to organize lower-order traits, ranging from two to sixteen. Each of these models can be assessed via self- and peer-report using reliable and well-validated questionnaires and rating forms (Cervone and Lawrence, 2007).

In the most influential and widely used structural model, thirty traits are hierarchically organized into five broad bipolar dimensions, reflecting a convergence of the Big Five lexical traits and the questionnaire-based five-factor model. The Big Five/FFM dimensions are neuroticism, extraversion, openness, agreeableness, and conscientiousness. Adherents of the Big Five/FFM model assert that these dimensions can be found across languages and personality measures, providing a comprehensive and parsimonious account of individual differences in personality (Cervone and Lawrence, 2007).

Contemporary research on the heritability of traits has focused on the Big Five/FFM dimensions. Behavioral genetic studies have found substantial heritability ranging from 41 percent to 61 percent for the broad dimensions, with little evidence of shared environmental effects (Cervone and Lawrence, 2007). Heritability of the narrowband traits of the FFM is more modest, ranging from 30 percent to 50 percent. It is widely believed that traits are influenced by multiple genes; molecular genetic studies, however, have not replicated results linking specific genes to personality traits. In addition to the genetic correlates of traits, promising new efforts by neuropsychologists using functional brain imaging and electroencephalogram (EEG) recordings have begun to reveal the neural basis for traits.

Trait theory has been applied to industrial/organizational psychology where it has been used to predict employee satisfaction and job performance. Personality traits have also been of interest to forensic psychologists in predicting psychopathic and deviant behavior. Other areas in which traits have been successfully employed include: predicting mate selection as well as marital satisfaction, social psychology, counseling, studies of human development across the lifespan, cross-cultural studies, learning and educational outcomes, and health-related behaviors and outcomes (Cervone and Lawrence, 2007).

Individuals differ from one another behaviorally in myriad ways. Differential psychology, the scientific study of these individual differences, provides an organizational structure for this vast array of psychological attributes (Lubinski, 2004). In words of Cervone and Lawrence (2007) by examining broad behavioral patterns and using systematic assessments of relatively stable personal attributes, differential psychology allows longitudinal forecasting of a variety of important life outcomes. Because much of the research in this area focuses particular attention on predicting long-term life outcomes, and because work is such a large and important feature of adult life, the relationships between many commonly investigated individual difference constructs and various aspects of work behavior. For example educational-vocational choice, acquisition of job-related knowledge, job performance, job satisfaction and tenure are well understood.

Traditionally, the measurement of individual differences has relied on psychometric scales based on the aggregation of many items. Because any single item on a scale represents only a sliver of information about a personal attribute, aggregation is used to create a composite of several lightly correlated items. This approach distills the communality running through the items and constitutes highly reliable and useful information about the human characteristic under analysis (Gottfredson, 2003).

Although individuals are commonly described in the more popular press in terms of types, implying that people are members of distinct categories (e.g., extraverts or introverts), individual difference variables are rarely observed as discrete classes. Rather, the majority of individuals are found near the center of a continuous distribution, with few observations at either extreme. The distributional pattern of most individual difference variables is well represented by the normal (bell-shaped) curve (Cervone and Lawrence, 2007).

The major dimensions of individual differences can be classified into three overlapping clusters: cognitive abilities, preferences (interests and values), and personality (Gottfredson, 2003).

The predominant scientific conceptualization of cognitive abilities involves a hierarchical organization. Various models of additional specific abilities have been proposed, but the hierarchical nature of human abilities is salient in each (Lubinski, 2000). For example, John Carroll factor analyzed more than 460 data sets collected throughout the 20th century and found a general factor (g) at the apex that explained approximately half of the common variance among a heterogeneous collection of tests, revealing a communality running through many different types of more specialized abilities and the tests designed to measure them.

This general intelligence factor exhibits an extensive range of external correlates, implicating it as arguably the most scientifically significant dimension of human psychological diversity uncovered by differential psychology to date. It has repeatedly demonstrated its utility in the prediction of educationally and vocationally relevant outcomes, including the acquisition of job-related knowledge and job performance (Lubinski, 2000). For example, in a meta-analysis of 85 years of research on personnel selection methods, Frank Schmidt and John Hunter reported that g is the best single predictor of performance in job-training programs, exhibiting an average validity coefficient of .56. Schmidt and Hunter further reported that the validity of g in predicting job performance is second only to that of work sample measures. However, because the use of work samples is limited to use with incumbents and is much costlier to implement, g is usually considered more efficient.

The predictive validity of g in forecasting job performance varies as a function of job complexity, with stronger relationships among more complex positions. Hunter reports validity coefficients of .58 for professional and managerial positions, .56 for highly technical jobs, .40 for semiskilled labor, and .23 for unskilled labor. For the majority of jobs (62%), those classified as medium-complexity, a validity coefficient of .51 was observed.

The general factor of intelligence is supplemented by several more circumscribed, specific abilities that have demonstrated psychological importance. David Lubinski and his colleagues have shown that at least three add incremental validity to the variance-explained by g: verbal, mathematical, and spatial abilities. The importance of specific abilities may be even more apparent at higher levels of functioning (Cervone and Lawrence, 2007). In examinations of numerous job analysis data sets, for example, Linda Gottfredson found that, although the functional duties of jobs were characterized primarily by their cognitive complexity (i.e., demands on general intelligence), jobs requiring above-average intelligence were more dependent on profiles of specific abilities than were those jobs requiring average or below average general intelligence (Lillienfeld, Wood and Garb, 2000).

Dpecific abilities are relevant in the prediction of job performance, but they are also important in predicting the educational and vocational niches into which individuals self-select. This self-selection occurs even at extraordinary levels of general intellectual development. In a recent 10-year longitudinal study, for example, Lubinski compared the educational-vocational tracks chosen by three groups of profoundly gifted individuals (top 1 in 10,000 for their age): a high verbal group (individuals with advanced verbal reasoning ability, relative to their mathematical ability), a high math group (individuals with advanced mathematical reasoning ability, relative to their verbal ability), and a high flat profile group (individuals with comparably high verbal and mathematical abilities). Despite having similar levels of general cognitive ability, the three groups diverged in their professional developmental choices (Lillienfeld, Wood and Garb, 2000). High math participants were frequently pursuing training in scientific and technological professions, whereas high verbal participants were doing so in the humanities and arts. High flat participants were intermediate.

Holland’s model of interests organizes six general occupational themes in a hexagon with one theme at each vertex in the hexagon. The themes are ordered according to their pattern of inter-correlations: Adjacent themes in the hexagon are more highly correlated to one another, whereas opposite themes are least correlated. This model is known as the RIASEC model, an acronym for the six themes represented in the hexagon: realistic, investigative, artistic, social, enterprising, and conventional (Cervone and Lawrence, 2007). Individuals with high realistic interests exhibit preferences for working with things and tools; those with high investigative interests enjoy scientific pursuits; high artistic interests reflect desires for aesthetic pursuits and self-expression; social interests involve preferences for contact with people and opportunities to help people; individuals high in enterprising interests enjoy buying, marketing, and selling; and those with conventional interests are comfortable with office practices and well-structured tasks. Individuals’ relative normative strengths on each of the RIASEC’s general occupational themes are commonly assessed using the Strong Interest Inventory (Carroll, 1993).

Although the generalizability of the RIASEC model has emerged repeatedly in large samples, Dale Prediger has suggested that the model can be reduced to two relatively independent bipolar dimensions: people versus things, and data versus ideas. People versus things may be superimposed on the social and realistic themes, respectively (Carroll, 1993). Running to the first dimension, the second dimension, data versus ideas, locates data between the enterprising and conventional themes and ideas between the artistic and investigative themes. The people versus things dimension represents one of the largest sex differences on a trait uncovered in psychology (a full standard deviation, with women scoring higher on the desire to work with people, and men, with things), revealing important implications for the occupations that men and women choose.

Values constitute another category of personal preferences germane to learning and work, which have demonstrated their utility in the prediction of both educational and occupational criteria. Values are validly assessed by the Study of Values, which reports the intra-individual prominence of six personal values: theoretical, economic, political, social, aesthetic, and religious. These dimensions provided an additional 13% of explained variance above the 10% offered by math and verbal abilities in the prediction of undergraduate majors in gifted youth assessed over a 10-year interval; moreover, this finding has recently been generalized to occupational criteria, measured in commensurate terms, over a 20-year interval. However, although preferences do seem to play an important role in predicting occupational group membership and tenure, once individuals self-select into occupational fields, the utility of preferences for predicting job performance in those fields is limited (Carroll, 1993).

Empirical examinations of personality use trait models to understand a person’s typical interpersonal style and behavioral characteristics. These models have historically relied on a lexical approach that assumes that important dimensions of human personality are encoded in human language. This method has been fruitful: Lewis Goldberg, among others (Ackerman, 1996), has factor analyzed the lexicons of many languages and found a five-factor model of personality with remarkable similarities across cultures (see also investigations by Robert McCrae and Paul Costa). Although the labels for each of the factors have varied, similar underlying constructs consistently emerge: extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience.

Extraversion is characterized by terms such as talkative, sociable, or not reserved; agreeableness by good-natured, cooperative, or not cold; conscientiousness by responsible, thorough, or not disorganized; neuroticism (sometimes referred to as emotional stability, reversed) by anxious, emotional, or not calm; and openness to experience (sometimes referred to as culture or intellect) by imaginative, reflective, or not narrow. The normative standing of individuals on each of the dimensions of the five-factor model of personality is commonly assessed using the NEO Personality Inventory, although an analogous instrument, the IPIP-NEO (IPIP is International Personality Item Pool), is available in the public domain at http:/ / ipip.ori.org/

Collectively (and sometimes individually), these broad dimensions of personality are valid predictors of occupational training and subsequent performance. For example, across multiple occupational categories, conscientiousness alone exhibits validity coefficients in the low .20s for predicting training and job proficiency. This particular combination of personality factors, conscientiousness and emotional stability, is found in tests of integrity commonly used in personnel selection (Spies & Plake, 2005).

From an individual’s perspective, an appreciation of one’s cognitive abilities, preferences, and personality provide invaluable insight for directing one’s career development in personally rewarding ways. From an organizational perspective, one may use this information—available through measures of individual differences—to estimate the likelihood of desirable work behavior (e.g., citizenship, job performance, satisfaction, and tenure).

References

Ackerman, P. L., 1996, A Theory Of Adult Intellectual Development: Process, Personality, Interests, And Knowledge. Intelligence vol. 22 pp. 227-257 (1996).

Aiken, L. R. (2000), Psychological Testing And Assessment (10th ed.). Boston: Allyn & Bacon.

Carroll, J. B. (1993), Human Cognitive Abilities: A Survey Of Factor-Analytic Studies.

Cambridge, UK: Cambridge University Press.

Cervone, Lawrence A. Pervin, 2007, Personality: Theory and Research, Wiley; 10th edition (February 26, 2007), pp. 45-67.

Gottfredson, L. S., 2003, The Challenge And Promise Of Cognitive Career Assessment. Journal of Career Assessment vol. 11 pp. 115-135 (2003).

Lubinski, D., 2000, Scientific And Social Significance Of Assessing Individual Differences: “Sinking Shafts At A Few Critical Points.” Annual Review of Psychology vol. 51 pp. 405-444 (2000).

Lubinski, D., 2004, Introduction To The Special Section On Cognitive Abilities: 100 Years After Spearman’s (1904) “‘General intelligence,’ objectively determined and measured.” Journal of Personality and Social Psychology vol. 86 pp. 96-111 (2004).

Lillienfeld, S. O., Wood, J. M. , and Garb, H. N., 2000, The Scientific Status Of Projective Techniques. Psychological Science in the Public Interest vol. 1 (2000). pp. 27-66

Spies, R. A. , ed. , & Plake, B. S. (Eds.). (2005), The Sixteenth Mental Measurements Yearbook. Lincoln, NE: Buros Institute of Mental Measurements.
Candidate Number – 33156762

Rapid (complex) decision making based on facial appearance

Making first impressions, evaluating a person from the moment we first see them, happens spontaneously and seemingly without any cognitive effort. We do it naturally when we see and meet new people, in order to have an idea of who they are beforehand instead of unknowingly acting in a way they might find inappropriate. It appears that humans are excellent in judging personality traits and such things as complex social characteristics like dominance, hierarchy, warmth, and especially threat.

For instance, think about this example. You’re walking down a dark street, late at night trying to get home, and you see someone coming towards you. As you pass the person, you see a tall and bulky figure wearing a black hood that puts a shadow on a roughed up looking man. Before you can make a conscious thought, your legs have already moved as far away from him as possible, purely out of instinct, even thought a second later you realize it’s your neighbor and you shakily smile at them and keep walking. The first impression that had subconsciously and immediately formed in the mind had already controlled the body’s reaction to what it perceived to be a threat (a scary looking man). Yet, it also shows how incorrect first impressions can be, and that can have a huge effect on people’s lives. Since it’s such a big part of everyday life, psychologists have looked deeply into the workings of first impressions.

Social perception is the field of study which looks into how we form impressions and make inferences about other people. It is a very complex process, especially forming impressions of objects, animals and most importantly people. We form first impressions of others very quickly and usually based on little information. We give special attention to salient features, focusing first on the face, then physical features while moving on to appearance and clothes. Then the process continues to categorizing the first impression of a person into a member of a group, starting broadly, from age and gender, and narrowing down to explicit features. It is followed by our own previous knowledge that comes into effect of our impression as well as previous behavior that has been gathered about that impression, as then our own needs and goals influence how we perceive others. And that information is needed, as people can be unpredictable. In the past the information was needed in order to distinguish trustworthy people from those who mean us harm, when now it’s socially needed to interact suitably with people.

In order to understand first impressions, the biology behind it must be understood. From an evolutionary point of view, first impressions have adaptive advantages, such as picking the appropriate mate. The first impression we perceive of someone is essential for us to understand how physically attractive, reliable, and strong they are, as we make that decision based on physical appearance rather than the personality of the person, as we would like the offspring to be good looking, healthy, meaning characteristics that are advantageous to the perceiver’s reproductive needs, and we must act fast before the window of opportunity closes. Also if someone means us harm, or is ill, there is the possibility of us being harmed or falling ill ourselves, again we must act fast to avoid this. Usually the first impressions are most accurate, but there is always human error, as sometimes what we perceive to be trustworthy, isn’t. What the evolutionary point of view argues is that it’s possible that our ability to form first impressions isn’t due to practice, but instinct.

We seem to effortlessly form first impressions and even better with practice and experience. There are reasons to suggest that people may have an adaptive predisposition to form rapid first impressions when meeting someone. When people look at other people’s features it’s important to act fast, because for an instance, if someone is untrustworthy then they may look like they may harm, cheat or insult us and we should register the fact as quick as possible in order to act appropriately. If not, then the consequences may be being killed, hurt or cheated. It’s better to be prepared to fight off harm rather than mull over the intent of the other person. There have been several studies that have looked at trustworthiness and first impression. These are not just the source of benefits, but there are also the sources of threats, for instance when forming the first impression, it must be fast as there is competition, and sometimes the competition could mean us harm. Even good meaning individuals may pose a threat to our health or reproductive fitness.

Schiller et al 2009, investigated the brain mechanisms that rise when first impressions are rapidly formed when meeting a stranger (Schiller et al 2009). There were nineteen right-handed participants, who were told that they would see information about different people and were asked to give their impressions of them. In their neuro-imaging analysis, where they examined which regions showed the difference in evaluation effect out of regions that were broadly engaged in the impression-formation task, the only regions showing significantly greater bold responses to evaluation-relevant sentences were the amygdala the PCC and the thalamus. There were no regions showing the opposite effect.

The first study suggesting that the amygdala, a part of the brain that research has shown to perform a role in the processing and memory of emotional reactions has an important role in trustworthiness judgments, was conducted by Adolphs, Tranel, & Damasio, 1998. They showed that patients with bilateral amygdala damage perceived untrustworthy-looking faces as trustworthy, and couldn’t discriminate between trustworthy and untrustworthy faces (Adolphs, Tranel, and Damasio, 1998). Several years later, Engell, Haxby & Todorov, 2007, looked into the fact of whether a stranger is trustworthy, as one of the most important decisions in social environments and relations, something we consider when acquainting with new people (Engell, Haxby & Todorov, 2007). There is considerable data about the significance of trait impressions from faces, yet there is little research about the neural mechanisms causing these impressions. There were one hundred and twenty-nine undergraduate students participating in the study, where functional magnetic resonance imaging was used to show that the amygdala is involved in hidden evaluations of trustworthiness of faces, consistent with previous findings. They reported that the amygdala response increased as perceived trustworthiness decreased in a task that did not demand person evaluation. Engell, Haxby & Todorov also tested whether the increased amygdala response was due to an individual’s own personal perception or to face characteristics that are perceived as untrustworthy throughout individuals. The amygdala response was better predicted by agreed ratings of trustworthiness than by an individual’s own judgments. Individual judgments accounted for little outstanding variance in the amygdala after controlling for the shared variance with agreed ratings. The findings of this study suggested that the amygdala categorizes faces automatically according to face characteristics that are seen to show trustworthiness.

More recently, Todorov & Duchaine, 2008, looked at developmental prosopagnosics who had severe impairments in their memory for faces and perception of facial identity who showed they could make normal trustworthiness judgments of novel faces (Todorov & Duchaine, 2008). Their control group consisted of forty-eight undergraduate students, mostly male with the mean age of twenty, which were younger compared to the four developmental prosopagnosics used in the experiment, where they were presented with face sets with the question “How trustworthy is this person?” and asked to respond on the scale below the photograph. What they found was that there were no significant differences between male and female control participants on both their agreement in the ratings of the faces and their mean trustworthiness judgments. They also tested the four prosopagnosics on three different face sets: set one consisted of faces that contrasted on multiple proportions and which were also used to demonstrate injuries in trustworthiness judgments of patients with bilateral amygdala damage. The other two sets consisted of normal faces with a direct look, with neutral expression and similar age. Todorov & Duchaine found that on all the tests, two of the prosopagnosics made judgments that agreed with the control’s judgments while the other two showed weak. The implications of this experiment suggest that there is a correlation that the tests mapped the same underlying judgment irrespective of the specific face stimuli. The normal performance of two of the prosopagnosics suggested that forming person impressions from faces involves mechanisms functionally independent of mechanisms for encoding the identity of faces.

A later study by Oosterhof & Todorov, 2009, proposed that changes in trustworthiness match to the subtle changes in expressions, which show whether the person displaying the emotion should be avoided or approached (Oosterhof & Todorov, 2009). Oosterhof and Todorov used a dynamic paradigm where faces expressed either happiness or anger. There were sixty undergraduate students participating in the experiment, with twenty-one participating in the selection of trustworthy and untrustworthy faces, and thirty-nine participated in the dynamic stimuli study. They manipulated changes in face trustworthiness at the same time as with the change in the face expression, for instance changes from high to low trustworthiness increased the intensity of participant’s perceived anger but decreased the intensity of participant’s perceived happiness. What they found was that trustworthy faces who expressed happiness were seen as happier than untrustworthy faces, and untrustworthy faces who expressed anger were seen as angrier than trustworthy faces, which makes sense as the more angry and unapproachable someone looks, the more likely we are to avoid them for our own safety as they would look intimidating to us.

When we first make an interaction with someone, our facial recognition of them is essential for the social interaction. It’s not a conscious thought per se, when the decision of how trustworthy someone is, but it happens, and we decide whether the person we’ve just met is someone we can relate to, then maybe consider a friend, and later depend on them with everything that we care about. It’s not a light matter, our lives are who and what we are, and unfortunately as it is we cannot rely sorely on ourselves, and we need other people, may it be for help, comfort or just a chat. And of course, the people we look for are those who won’t turn their backs on us when we need them and will be there to support us. It’s a simple survival skill, trust those who won’t hurt us and we can live normally.

When people are emotionally animated it is much easier to perceive the expressions they convey, particularly threatening and fearful ones very swiftly, which helps us respond to danger quickly. But how fast are first impressions exactly? Several researches have looked into how fast first impressions are made.

In 2006, Bar et al looked into the fact that first impressions of people’s personalities are often formed by using the visual appearance of their faces (Bar, Neta, & Linz, 2006). They reported four experiments; with the first measuring the speed of how first impressions of intelligence and threatening personality are made. They used sixty adults, mostly women, where the participants in the experiment were shown one face at a time and were asked to rate, on a scale ranging from 1 to 5, the level that they perceived each face to belong first to threatening person, and later followed with an intelligent person at the second part of the experiment. What Bat et al did was present the faces for different time lengths to different groups of participants, the first group was presented the faces for a short time and the other group was presented with faces for a longer time and then the correlation between the judgments of each group was measured, they identified how quickly participants judged a face as having a certain personality. The results demonstrate that consistent first impressions can be formed very quickly, based on whatever information is available within the first 39 ms. First impressions were less consistent under these conditions when the judgments were about intelligence, suggesting that survival-related traits are judged more quickly. The study showed that when faces are particularly emotionally expressive, people can detect these expressions that are being conveyed, such as threatening and fearful expressions, very quickly and mostly subconsciously. While Bar, Neta, & Linz, 2006, looked at neutral expressions in their study, Blair, Morris, Frith, Perrett, & Dolan, 1999, looked at emotions portrayed by the face.

Blair et al, 1999, used functional neuroimaging to test two hypotheses: one, whether the amygdala has a neural response to sad and angry facial expressions and two, whether the orbito-frontal cortex has a specific neural response to angry facial expressions (Blair, Morris, Frith, Perrett, & Dolan, 1999). There were thirteen male participants, all with the mean age of 25 who were PET scanned, while performing a sex discrimination task that consisted of grey-scale images of faces that expressed different degrees of sadness and anger. They found that increasing force of sad facial expressions was associated with enhanced activity in the left amygdala and right temporal pole. The results also indicated


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