Gordon Allport: Measurement and Classification of Personality

Gordon W. Allport (1897 – 1967) was one of the first psychologists to focus on the study of the personality, and is one of the founding figures of personality psychology. According to Allport, the psychoanalytic view of personality focused too deeply on the past, whereas the behavioral approach did not go deep enough. I am intrigued by his theory on Drive and Motive, between which he draws a clear distinction: a drive forms as a reaction to a motive, but may outgrow the motive as the reason for a behavior. "Allport gives the example of a man who seeks to perfect his task or craft. His original motive may be a sense of inferiority engrained in his childhood, but his diligence in his work and the motive it acquires later on is a need to excel in his chosen profession, which becomes the man's drive."

According to Allport (1937), this theory "avoids the absurdity of regarding the energy of life now, in the present, as somehow consisting of early archaic forms (instincts, prepotent reflexes, or the never-changing Id). Learning brings new systems of interests into existence just as it does new abilities and skills. At each stage of development these interests are always contemporary; whatever drives, drives now." 

References

https://en.wikipedia.org/wiki/Gordon_Allport

Allport, F. H., & Allport, G. W. (1921). Personality traits: Their classification and measurement. The Journal of Abnormal Psychology and Social Psychology, 16(1), 6.

Allport, G. W. (1921). Personality and character. Psychological Bulletin, 18(9), 441.

Allport, G. W. (1927). Concepts of trait and personality. Psychological Bulletin, 24(5), 284.

Allport, G. W. (1937). The functional autonomy of motives. The American Journal of Psychology, 50, 141-156.

Allport, G. W. (1962). The general and the unique in psychological science. Journal of Personality,  

30(3), 405-422

Research-data sharing websites

Peace, love and data is for everyone (well, it should be). Here is a list with online resources:


Epidemiological datasets

• The Survey of Health, Ageing and Retirement in Europe: http://www.share-project.org/ (requires registration)
• The European Values Study: http://www.europeanvaluesstudy.eu. Data can de downloaded from http://www.gesis.org/en/home/ (requires registration, which is automatically approved), which hosts a large number of other datasets from political and sociological studies.
• The Wisconsin Longitudinal Study (WLS): http://www.ssc.wisc.edu/wlsresearch/ . The WLS "is a long-term study of a random sample of 10,317 men and women who graduated from Wisconsin high schools in 1957. The WLS provides an opportunity to study the life course, intergenerational transfers and relationships, family functioning, physical and mental health and well-being, and morbidity and mortality from late adolescence through 2011. WLS data also cover social background, youthful aspirations, schooling, military service, labor market experiences, family characteristics and events, social participation, psychological characteristics and retirement."
• For a number of studies published in the European Journal of Psychological Assessment, datasets are available on the EJPA website: http://www.hogrefe.com/periodicals/european-journal-of-psychological-assessment/special-features/

Datasets from clinical trials

• National Institute of Drug Abuse (NIDA) Data Share: https://datashare.nida.nih.gov/  (Freely accesible: does not require registration) 
• Limited Access Datasets From NIMH Clinical Trials: http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/datasets/nimh-procedures-for-requesting-data-sets.shtml  (Not freely accesible: involves a review proces. "NIMH requires all investigators seeking access to data from NIMH-supported trials held by NIMH to execute and submit as their request the appropriate Data Use Certification pertaining to the trial. The datasets distributed by NIMH are referred to as "limited access datasets" because access is limited to qualified researchers who complete Data Use Certifications. The current listing of these datasets may be found on the Available Limited Access Datasets From NIMH Clinical Trials page.")
• For a number of studies published in the European Journal of Psychological Assessment, datasets are available on the EJPA website: http://www.hogrefe.com/periodicals/european-journal-of-psychological-assessment/special-features/

Miscellaneous

• Here is an overview of all NIH Data Sharing Repositories: http://www.nlm.nih.gov/NIHbmic/nih_data_sharing_repositories.html
• The Journal of Open Psychology Data publishes papers that describe datasets from published studies, which are available for (re)analysis. The JOPD website has a large, well-described list of Recommended Repositories which are recommended for archiving datasets that are described in JOPD papers. That list is not only useful for data from JOPD papers, but also a good source for data-sharing websites.
• The Yale Institution for Social and Policy Studies: http://isps.yale.edu/research/data. "The majority of digital content in the ISPS Data Archive currently consists of social science research data from experiments, program files with the code for analyzing these data, requisite documentation to use and understand the data, and associated files. Access to the ISPS Data Archive is provided at no cost and is granted for scholarship and research purposes only."

Teaching to the test

Teaching to the test is a threat to internal validity. It can be seen as a combination of maturation and testing effects (Cook & Campbell, 1979). Teaching to the test occurs when familiarity with a test enhances the performance of test takers. It is a well-known concept in educational settings, where it implies that students obtain higher grades on a test, (partly) because they are more familiar with the testing material or items, and not (exclusively) because they have developed greater ability or skill.

When a test is used for measuring something other than ability or skill, for example in a questionnaire about mental health, 'obtaining a higher grade' loses it's relevance. After all, obtaining a high grade is probably of importance for any test taker, smart or stupid, in a high stakes educational situation, in order to gain access to higher education, for example. However, obtaining a high grade on a questionnaire measuring depression in order to gain access to treatment is probably only of importance to test takers suffering from substantial depressive symptoms. At the same time, a test taker would need no (or very little) training in order to fake being depressed on a questionnaire, whereas faking arithmetic skill probably takes a lot more effort.

So, enhanced performance on mental health would in this case mean an enhanced ability to assess depressive symptomatology. This would not result in artificially higher (or lower) scores. What kind of artifact in the data this may cause, I'm not sure, but it seems imaginable such an increased ability would result in decreased error variances.


Literature

Cook, Thomas T.D. & Campbell, D.T. (1979). Quasi-Experimentation: Design & Analysis Issues for Field Settings. Rand McNally College Publishing Company, Chicago, IL.

Lazear, E.P. (2006). Speeding, Terrorism, and Teaching to the Test. The Quarterly Journal of Economics, 121 (3), 1029-1061.

(The last citation is not very relevant to the above, but nevertheless very interesting, as it demonstrates that, and in which cases, teaching to the test may be beneficial to a student's learning process. An interesting analogy is made to traffic patrols, tax fraud and fighting terrorism.)

Loneliness research

According to Jordan, Monin, Dweck, Lovett, John and Gross (2011), we tend to underestimate the extent to which others experience negative emotions, while we tend to overestimate the extent to which other experience positive emotions. At the same time, we tend to downregulate postive, as well as negative emotions (i.e., we experience them to a stronger extent than we express them). In turn, this makes us feel bad, as lower estimation of the prevalalence of negative emotional experiences predicted greater loneliness and rumination, lower life satisfaction. According to the authors, that explains why we like Chekhov, and Facebook makes us sad.

On a different note, according to Boomsma, Willemsen, Dolan, Hawkley and Cacioppo (2005), 48% of variation in loneliness can be explained by genes.




@article{JordyMoni11,
title ={Misery Has More Company Than People Think: Underestimating the Prevalence of Others’ Negative Emotions},
author ={Jordan, A.H. and Monin, B. and Dweck, C.S. and Lovett, B.J. and John, O.P. and Gross, J.J.},
journal ={Personality and Social Psychology Bulletin},
volume ={37},
number ={1},
pages ={},
year ={2011},
}

@article{BoomyWill05c,title={Genetic and environmental contributions to loneliness in adults: The Netherlands Twin Register Study},author={Boomsma, D.I. and Willemsen, G. and Dolan, C.V. and Hawkley, L.C. and Cacioppo, J.T.},journal={Behavior Genetics},volume={35},number={6},pages={745--752},year={2005},}