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1

Ryle, A. "Personality assessment." British Journal of Psychiatry 184, no. 1 (January 2004): 86. http://dx.doi.org/10.1192/bjp.184.1.86.

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2

Ozer, D. J., and S. P. Reise. "Personality Assessment." Annual Review of Psychology 45, no. 1 (January 1994): 357–88. http://dx.doi.org/10.1146/annurev.ps.45.020194.002041.

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3

Taylor, Neville, and Robert Pryor. "Personality Assessment." Australian Journal of Career Development 4, no. 3 (October 1995): 19–20. http://dx.doi.org/10.1177/103841629500400306.

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4

Wiggins, Jerry S. "Personality assessment." Clinical Psychology Review 18, no. 3 (April 1998): 384–85. http://dx.doi.org/10.1016/s0272-7358(97)00072-x.

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5

Stein, Randy, and Alexander B. Swan. "Deeply Confusing: Conflating Difficulty With Deep Revelation on Personality Assessment." Social Psychological and Personality Science 10, no. 4 (April 4, 2018): 514–21. http://dx.doi.org/10.1177/1948550618766409.

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The factors that contribute to lay expectations of personality assessments are not well understood. Five studies demonstrate that people conflate difficulty of personality assessment items with revelations of deep insights. As a result, popular yet invalid assessments of personality can be seen as “deeper” than assessments from social and personality psychology. In Study 1, participants evaluated items from a popular personality “type” assessment as more difficult and better at revealing deep insights into personality than Big-Five personality inventory items. Studies 2 and 3 replicate this effect experimentally using a manipulation of assessment items’ difficulty. Studies 4 and 5 show that the same effect also holds for a less direct method of supposed personality assessment (e.g., assessments that ask about which colors are associated with trivial concepts). Moderating factors and the popularity of shoddy personality assessments are discussed.
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6

Cervone, Daniel, William G. Shadel, and Simon Jencius. "Social-Cognitive Theory of Personality Assessment." Personality and Social Psychology Review 5, no. 1 (February 2001): 33–51. http://dx.doi.org/10.1207/s15327957pspr0501_3.

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This article presents a social-cognitive theory of personality assessment. We articulate the implications of social-cognitive theories of personality for the question of what constitutes an assessment of personality structure and behavioral dispositions. The theory consists of 5 social-cognitive principles of assessment. Personality assessments should (a) distinguish the task of assessing internal personality structures and dynamics from that of assessing overt behavioral tendencies, (b) attend to personality systems that function as personal determinants of action, (c) treat measures of separate psychological and physiological systems as conceptually distinct, (d) employ assessments that are sensitive to the unique qualities of the individual, and (e) assess persons in context. These principles are illustrated through a review of recent research. Social-cognitive theory is distinguished from an alternative theory of personality structure and assessment, 5-factor theory, by articulating the strategies of scientific explanation, conceptions of personality structure and dispositions, and the assessment practices that differentiate the approaches.
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7

Goldsmith, Scott J., Lawrence B. Jacobsberg, and Robin Bell. "Personality Disorder Assessment." Psychiatric Annals 19, no. 3 (March 1, 1989): 139–42. http://dx.doi.org/10.3928/0048-5713-19890301-08.

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8

Barends, Ard J., Reinout E. de Vries, and Mark van Vugt. "Gamified Personality Assessment." Zeitschrift für Psychologie 227, no. 3 (July 2019): 207–17. http://dx.doi.org/10.1027/2151-2604/a000379.

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Abstract. Unobtrusive behavioral cues of personality traits can be found in physical and virtual environments (e.g., office environments and social media profiles), but detecting and coding such cues are a painstaking effort, and therefore impractical for research purposes. Measuring people’s choices in a virtual, gamified environment may offer a suitable substitute. It is currently unknown whether Honesty-Humility can also be assessed in a virtual environment. In two studies, we demonstrate that Honesty-Humility can be inferred with at least modest validity from virtual behavior cues. In a third study, we tested the fakeability of the virtual cues. This study found that even under faking instructions the virtual cues were related to Honesty-Humility, however, the virtual cues were just as fakeable as self-reported Honesty-Humility. Our results imply that virtual cues can be incorporated in serious games to measure personality. Future research may investigate whether the identified virtual cues are able to predict important Honesty-Humility related outcomes.
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9

Sarason, Irwin G. "Personality Assessment Models." Contemporary Psychology: A Journal of Reviews 40, no. 11 (November 1995): 1056–57. http://dx.doi.org/10.1037/004105.

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10

Weiner, Irving B. "Society for Personality Assessment/Journal of Personality Assessment: A History." Journal of Personality Assessment 100, no. 1 (December 20, 2017): 2–15. http://dx.doi.org/10.1080/00223891.2017.1394869.

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11

Eysenck, H. J. "Personality and prediction: Principles of personality assessment." Personality and Individual Differences 11, no. 1 (January 1990): 97. http://dx.doi.org/10.1016/0191-8869(90)90177-s.

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12

Khan, Rafique. "Assessment of Personality of Indian Male Hockey Players." International Journal of Physical Education & Sports Sciences 12, no. 1 (October 1, 2017): 20–21. http://dx.doi.org/10.29070/12/57379.

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13

ITOH, Koskay. "Personality Assessment in Primates." Primate Research 13, no. 1 (1997): 53–64. http://dx.doi.org/10.2354/psj.13.53.

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14

Altmann, Tobias, and Niket Kapoor. "Personality Assessment To-Go." Zeitschrift für Psychologie 229, no. 4 (December 2021): 214–24. http://dx.doi.org/10.1027/2151-2604/a000465.

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Abstract. A particular feature of unproctored Internet Testing (UIT) is the participants’ freedom to decide on the formal aspects of their participation, such as time of day, device, and whether, how often, and for how long they might intermit their participation. A main point of discussion has been how these aspects alter the quality and content of an assessment. The issue remains understudied while simultaneously maintaining great importance for many fields. We examined this question in a UIT assessment of the Big Five personality factors in the present study. A sample of 441 participants who completed the assessment and 527 participants who aborted their participation was used to analyze quality (internal consistency, response styles) and content (mean score) differences. Results revealed several dependencies among small effect sizes. The discussion focuses on the potential practical implications of the present findings.
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15

Roskam, E. E. "Measurement and Personality Assessment." Biometrics 43, no. 1 (March 1987): 258. http://dx.doi.org/10.2307/2531981.

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16

WIDIGER, THOMAS A. "Paradigms of Personality Assessment." American Journal of Psychiatry 162, no. 8 (August 2005): 1558–59. http://dx.doi.org/10.1176/appi.ajp.162.8.1558.

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17

Weiner, Irving B. "Personality Assessment Well Done." Contemporary Psychology 45, no. 6 (December 2000): 687–88. http://dx.doi.org/10.1037/002350.

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18

Vasquez, Melba J. T. "Diversity-sensitive personality assessment." Journal of Personality Assessment 102, no. 4 (December 23, 2019): 584–85. http://dx.doi.org/10.1080/00223891.2019.1693390.

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19

Wiggins, J. S., and A. L. Pincus. "Personality: Structure and Assessment." Annual Review of Psychology 43, no. 1 (January 1992): 473–504. http://dx.doi.org/10.1146/annurev.ps.43.020192.002353.

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20

Edwards, Daniel W., Brian A. Dahmen, Richard L. Wanlass, Lori A. Holmquist, John J. Wicks, Christine Davis, and Thomas L. Morrison. "Personality Assessment in Neuropsychology." Assessment 10, no. 3 (September 2003): 222–27. http://dx.doi.org/10.1177/1073191103254491.

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21

Casey, Patricia R. "Clinical assessment of personality." Advances in Psychiatric Treatment 3, no. 3 (May 1997): 182–87. http://dx.doi.org/10.1192/apt.3.3.182.

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The importance of personality is recognised tacitly by the development of the multiaxial classifications of ICD–10 (World Health Organization, 1992) and DSM–IV (American Psychiatric Association, 1993). The separation of axis 1 or current mental state diagnosis from axis 2, on which personality is described, is a recognition that personality is separate from other aspects of the patient's diagnostic status. Nevertheless, many clinicians are sceptical that personality can be assessed reliably and some hold that the diagnosis should be abandoned as being merely judgemental and pejorative (Lewis & Appleby, 1988). There is some basis for scepticism in respect of reliability in view of the evidence that even with operational criteria the clinical assessment of personality is not transportable, and the level of agreement between practising clinicians is much less than that achieved during field trials (Mellsop et al, 1982).
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22

Banerjee, Penny J. M., Simon Gibbon, and Nick Huband. "Assessment of personality disorder." Advances in Psychiatric Treatment 15, no. 5 (September 2009): 389–97. http://dx.doi.org/10.1192/apt.bp.107.005389.

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SummaryIn 2003 the Department of Health, in conjunction with the National Institute for Mental Health in England, outlined the government's plan for the provision of mental health services for people with a diagnosis of personality disorder. This emphasised the need for practitioners to have skills in identifying, assessing and treating these disorders. It is important that personality disorders are properly assessed as they are common conditions that have a significant impact on an individual's functioning in all areas of life. Individuals with personality disorder are more vulnerable to other psychiatric disorders, and personality disorders can complicate recovery from severe mental illness. This article reviews the classification of personality disorder and some common assessment instruments. It also offers a structure for the assessment of personality disorder.
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23

Swartz, John D., and W. Paul McLemore. "Assessment of Personality (Book)." Journal of Personality Assessment 59, no. 2 (October 1992): 424–25. http://dx.doi.org/10.1207/s15327752jpa5902_15.

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24

Medoff, David. "Assessing Clinical Personality Assessment." Journal of Personality Assessment 82, no. 2 (April 2004): 241–43. http://dx.doi.org/10.1207/s15327752jpa8202_11.

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25

Main, Chris J., and Chris C. Spanswick. "Personality assessment and the Minnesota multiphasic personality inventory." Pain Forum 4, no. 2 (June 1995): 90–96. http://dx.doi.org/10.1016/s1082-3174(11)80005-x.

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26

Danner, Daniel, and Clemens M. Lechner. "Big Five Domains and Facets Contextualized to the Work Domain Outperform Noncontextualized Ones." Journal of Individual Differences 45, no. 3 (July 2024): 167–75. http://dx.doi.org/10.1027/1614-0001/a000421.

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Abstract: It is well-established that personality predicts a broad range of outcomes across life domains. However, the criterion validity of personality assessments is often limited. One strategy to increase criterion validity is to move from global, noncontextualized personality assessments toward contextualized personality assessments with reference to a specific context. We investigated whether a Big Five assessment contextualized to the work domain allows for better predictions of work-related outcomes than a noncontextualized Big Five assessment. Two hundred ninety respondents completed both the standard Big Five Inventory-2 (BFI-2) and a work-specific variant thereof. In addition, they provided information on a broad range of work-related outcomes (job satisfaction, turnover intentions, organizational citizenship behavior, burnout risk, and occupational commitment), as well as on global health, a not strictly work-related outcome. Results showed that the contextualized personality assessment generally outperformed the noncontextualized one in terms of criterion validity for all outcomes, with the exception of global health. This applied to both the five broad personality domains and the 15 narrow personality facets. We conclude that if maximizing criterion validity in the work domain is the goal, contextualized personality assessments are preferable to noncontextualized ones.
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27

Lloyd, A. S., and J. E. Martin. "Testing a method of equine personality assessment." BSAP Occasional Publication 35 (2006): 207–11. http://dx.doi.org/10.1017/s0263967x00042737.

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To date there have been few studies on equine personality, with many equine studies on individual differences focussing on the measurement of temperament. Personality is defined by Pervin and John (1997, ) as “Those characteristics of the person that account for consistent patterns of feeling, thinking and behaving” and is different to temperament in that it has a greater emphasis on social aspects of behaviour. Interest in this area of research has recently increased, which could be attributed to the potential implementation of personality assessment in management practices, welfare issues and potential applications in equine veterinary medicine (Mills, 1998).Assessment of animal personality often involves using human raters to assess the personality of animals familiar to them. In order to demonstrate reliable personality data three criteria should be met, these are as follows; 1) assessments made by independent observers must agree with one another, 2) these assessments must predict behaviours and real-world outcomes and 3) observer ratings must be shown to reflect genuine attributes of the individual rated and not just the observers’ implicit theories about personality (Kenrick and Funder, 1988; Gosling and Vazire, 2002).
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28

Krauskopf, C. J., and D. R. Saunders. "Career Assessment With the Personality Assessment System." Journal of Career Assessment 3, no. 3 (May 1995): 241–57. http://dx.doi.org/10.1177/106907279500300301.

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29

Krauskopf, C. J., and D. R. Saunders. "Career Assessment With the Personality Assessment System." Journal of Career Assessment 3, no. 4 (June 1995): 241–57. http://dx.doi.org/10.1177/106907279500300401.

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30

Ramos-Villagrasa, Pedro J., Elena Fernández-del-Río, Ramón Hermoso, and Jorge Cebrián. "Are serious games an alternative to traditional personality questionnaires? Initial analysis of a gamified assessment." PLOS ONE 19, no. 5 (May 2, 2024): e0302429. http://dx.doi.org/10.1371/journal.pone.0302429.

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Personality questionnaires stand as crucial instruments in personnel selection but their limitations turn the interest towards alternatives like game-related assessments (GRAs). GRAs developed for goals other than fun are called serious games. Within them, gamified assessments are serious games that share similarities with traditional assessments (questionnaires, situational judgment tests, etc.) but they incorporate game elements like story, music, and game dynamics. This paper aims to contribute to the research on serious games as an alternative to traditional personality questionnaires by analyzing the characteristics of a gamified assessment called VASSIP. This gamified assessment, based on an existing measure of the Big Five personality traits, incorporates game elements such as storyfication, immersion, and non-evaluable gamified dynamics. The study performed included 98 university students (77.6% with job experience) as participants. They completed the original personality measure (BFI-2-S), the gamified evaluation of personality (VASSIP), a self-report measure of the main dimensions of job performance (task performance, contextual performance, and counterproductive work behaviors), and measures of applicant reactions to BFI-2-S and VASSIP. Results showed that the gamified assessment behaved similarly to the original personality measure in terms of reliability and participants’ scores, although the scores in Conscientiousness were substantially higher in VASSIP. Focusing on self-reports of the three dimensions of job performance, regression models showed that the gamified assessment could explain all of them. Regarding applicant reactions, the gamified assessment obtained higher scores in perceptions of comfort, predictive validity, and attractiveness, although the effect size was small except for the latter. Finally, all applicant reactions except for attractiveness were related to age and personality traits. In conclusion, gamified assessments have the potential to be an alternative to traditional personality questionnaires but VASSIP needs more research before its application in actual selection processes.
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31

Milton, John. "A postal survey of the assessment procedure for personality disorder in forensic settings." Psychiatric Bulletin 24, no. 7 (July 2000): 254–57. http://dx.doi.org/10.1192/pb.24.7.254.

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Aims and MethodA survey of 50 in-patient forensic health care and prison services in England, Wales and Scotland was employed to evaluate: (a) how severe personality disorder is assessed; and (b) how assessments compare with recommendations concerning standardised assessment by the Working Group on Psychopathic Disorder (Reed, 1994).ResultsSeventy per cent of services responded, of whom 40% formally assessed personality disorder. Fifty-four instruments were routinely employed. Assessments of personality structure and cognitive/emotional styles were more common than structured diagnostic instruments or ratings of interpersonal functioning. Of the assessment tools, 25.7% of services provided at least one suggested by Reed (1994).Clinical ImplicationsA nationally agreed, focused repertoire of instruments should be encouraged within secure forensic settings offering assessments to individuals with severe personality disorder.
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32

Kaelber, Charles T., and Jack D. Maser. "Reassessing Personality Disorder Constructs: Challenges of Personality Disorders Assessment." Journal of Personality Disorders 6, no. 4 (December 1992): 279–86. http://dx.doi.org/10.1521/pedi.1992.6.4.279.

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33

Brooker, Harvey. "Book Review: Personality Disorders: Clinical Personality Assessment: Practical Approaches." Canadian Journal of Psychiatry 41, no. 7 (September 1996): 479–80. http://dx.doi.org/10.1177/070674379604100717.

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34

Mischel, Walter. "From Personality and Assessment (1968) to Personality Science, 2009." Journal of Research in Personality 43, no. 2 (April 2009): 282–90. http://dx.doi.org/10.1016/j.jrp.2008.12.037.

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35

Cervone, Daniel. "Personality assessment: Tapping the social-cognitive architecture of personality." Behavior Therapy 35, no. 1 (2004): 113–29. http://dx.doi.org/10.1016/s0005-7894(04)80007-8.

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36

Sugarman, Alan. "Where's the Beef? Putting Personality Back Into Personality Assessment." Journal of Personality Assessment 56, no. 1 (February 1991): 130–44. http://dx.doi.org/10.1207/s15327752jpa5601_12.

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37

Ock, JiSoo, and HyeRyeon An. "Machine Learning Approach to Personality Assessment and Its Application to Personnel Selection." Korean Journal of Industrial and Organizational Psychology 34, no. 2 (May 31, 2021): 213–36. http://dx.doi.org/10.24230/kjiop.v34i2.213-236.

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As we enter the digital age, new methods of personality testing-namely, machine learning-based personality assessment scales-are quickly gaining attraction. Because machine learning-based personality assessments are made based on algorithms that analyze digital footprints of people’s online behaviors, they are supposedly less prone to human biases or cognitive fallacies that are often cited as limitations of traditional personality tests. As a result, machine learning-based assessment tools are becoming increasingly popular in operational settings across the globe with the anticipation that they can effectively overcome the limitations of traditional personality testing. However, the provision of scientific evidence regarding the psychometric soundness and the fairness of machine learning-based assessment tools have lagged behind their use in practice. The current paper provides a brief review of empirical studies that have examined the validity of machine learning-based personality assessment, focusing primarily on social media text mining method. Based on this review, we offer some suggestions about future research directions, particularly regarding the important and immediate need to examine the machine learning-based personality assessment tools’ compliance with the practical and legal standards for use in practice (such as inter-algorithm reliability, test-retest reliability, and differential prediction across demographic groups). Additionally, we emphasize that the goal of machine learning-based personality assessment tools should not be to simply maximize the prediction of personality ratings. Rather, we should explore ways to use this new technology to further develop our fundamental understanding of human personality and to contribute to the development of personality theory.
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38

Sharma, Neha, Annu Annu, Vijay Kumar, Malkeet Kaur, and Dr Dinesh P. Sharma. "Personality Assessment of The Elite Indian Women Cricket Players." Indian Journal of Applied Research 4, no. 5 (October 1, 2011): 559–60. http://dx.doi.org/10.15373/2249555x/may2014/178.

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39

Douglas, Kevin S., Stephen D. Hart, and P. Randall Kropp. "Validity of the Personality Assessment Inventory for Forensic Assessments." International Journal of Offender Therapy and Comparative Criminology 45, no. 2 (April 2001): 183–97. http://dx.doi.org/10.1177/0306624x01452005.

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40

Willcox, Gregg. "Measuring Group Personality with Swarm AI." International Journal of Transdisciplinary Artificial Intelligence 2, no. 1 (August 1, 2020): 49–68. http://dx.doi.org/10.35708/tai1869-126249.

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The aggregation of individual personality assessments to predict team performance is widely accepted in management theory but has significant limitations: the isolated nature of individual personality surveys fails to capture much of the team dynamics that drive realworld team performance. Artificial Swarm Intelligence (ASI)—a technology that enables networked teams to think together in real-time and answer questions as a unified system—promises a solution to these limitations by enabling teams to collectively complete a personality assessment, whereby the team uses ASI to converge upon answers that best represent the group’s disposition. In the present study, the group personality of 94 small teams was assessed by having teams take a standard Big Five Inventory (BFI) assessment both as individuals, and as a realtime system enabled by an ASI technology known as Swarm AI. The predictive accuracy of each personality assessment method was assessed by correlating the BFI personality traits to a range of real-world performance metrics. The results showed that assessments of personality generated using Swarm AI were far more predictive of team performance than the traditional aggregation methods, showing at least a 91.8% increase in average correlation with the measured outcome variables, and in no case showing a significant decrease in predictive performance. This suggests that Swarm AI technology may be used as a highly effective team personality assessment tool that more accurately predicts future team performance than traditional survey approaches.
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41

Shin, Anthony K. "Tridimensional Personality Assessment : The HCTI." International Journal of Foreign Studies 10, no. 2 (December 31, 2017): 41–62. http://dx.doi.org/10.18327/ijfs.2017.12.10.41.

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42

Vasylenko, I. A. "SPECIFICITY OF PERSONALITY SELF-ASSESSMENT." Habitus, no. 23 (2021): 90–94. http://dx.doi.org/10.32843/2663-5208.2021.23.15.

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43

Tornetta, Paul, Joshua J. Jacobs, Robert S. Sterling, Monica Kogan, Keaton A. Fletcher, and Alan M. Friedman. "Personality Assessment in Orthopaedic Surgery." Journal of Bone and Joint Surgery 101, no. 4 (February 2019): e13. http://dx.doi.org/10.2106/jbjs.18.00578.

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44

Ho, Chia-Lin, Jennifer L. Welbourne, and Pierce J. Howard. "Personality Assessment in the Workplace." Journal of Cross-Cultural Psychology 45, no. 8 (June 5, 2014): 1249–72. http://dx.doi.org/10.1177/0022022114537553.

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45

Perry, William, and Eric Zillmer. "Overview: Neuropsychology and Personality Assessment." Assessment 3, no. 3 (September 1996): 207–8. http://dx.doi.org/10.1177/1073191196003003002.

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46

Greasley, Peter. "Handwriting Analysis and Personality Assessment." European Psychologist 5, no. 1 (March 2000): 44–51. http://dx.doi.org/10.1027//1016-9040.5.1.44.

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It has been estimated that graphology is used by over 80% of European companies as part of their personnel recruitment process. And yet, after over three decades of research into the validity of graphology as a means of assessing personality, we are left with a legacy of equivocal results. For every experiment that has provided evidence to show that graphologists are able to identify personality traits from features of handwriting, there are just as many to show that, under rigorously controlled conditions, graphologists perform no better than chance expectations. In light of this confusion, this paper takes a different approach to the subject by focusing on the rationale and modus operandi of graphology. When we take a closer look at the academic literature, we note that there is no discussion of the actual rules by which graphologists make their assessments of personality from handwriting samples. Examination of these rules reveals a practice founded upon analogy, symbolism, and metaphor in the absence of empirical studies that have established the associations between particular features of handwriting and personality traits proposed by graphologists. These rules guide both popular graphology and that practiced by professional graphologists in personnel selection.
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47

Bastiaens, Tim, Laurence Claes, and Samuel Greiff. "Dimensional Assessment of Personality Disorders." European Journal of Psychological Assessment 34, no. 5 (September 2018): 291–94. http://dx.doi.org/10.1027/1015-5759/a000506.

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48

Knoff, Howard M. "Best Practices in Personality Assessment." Preventing School Failure: Alternative Education for Children and Youth 34, no. 3 (April 1990): 25–30. http://dx.doi.org/10.1080/1045988x.1990.9944564.

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Elegbeleye, O. S. "The Yoruba Personality Assessment Criteria." Studies of Tribes and Tribals 3, no. 2 (December 2005): 85–91. http://dx.doi.org/10.1080/0972639x.2005.11886523.

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50

Nelson-Gray, R. O., and R. F. Farmer. "Behavioral assessment of personality disorders." Behaviour Research and Therapy 37, no. 4 (April 1999): 347–68. http://dx.doi.org/10.1016/s0005-7967(98)00142-9.

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