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A large population cohort provides normative data for investigation of temperament.

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Title: A large population cohort provides normative data for investigation of temperament.
Authors: Miettunen, J. (AUTHOR), Kantojärvi, L. (AUTHOR), Ekelund, J. (AUTHOR), Veijola, J. (AUTHOR), Karvonen, J. T. (AUTHOR), Peltonen, L. (AUTHOR), Järvelin, M. R. (AUTHOR), Freimer, N. (AUTHOR), Lichtermann, D. (AUTHOR), Joukamaa, M. (AUTHOR)
Source: Acta Psychiatrica Scandinavica. Aug2004, Vol. 110 Issue 2, p150-157. 8p.
Subjects: Surveys, Psychological tests, Temperament, Psychometrics, Personality
Abstract: Miettunen J, Kantojärvi L, Ekelund J, Veijola J, Karvonen JT, Peltonen L, Järvelin MR, Freimer N, Lichtermann D, Joukamaa M. A large population cohort provides normative data for investigation of temperament. Acta Psychiatr Scand 2004: 110: 150–157. © Blackwell Munksgaard 2004. We evaluated the psychometric properties of widely used scales for assessing temperament in a large birth cohort. We simultaneously compared the properties of the temperament dimensions of the Tridimensional Personality Questionnaire (TPQ) and of the Temperament and Character Inventory (TCI). As part of the 31-year follow-up survey of the prospective Northern Finland 1966 Birth Cohort, the TPQ and TCI temperament questions were filled in by 4349 subjects (1974 males, 2375 males). Factor analysis and Cronbach's alpha were used to explore the psychometric properties of the scales. Of the three higher-order dimensions the reward dependence (RD) was the only one performing poorly in our study sample. Cronbach's alpha was higher in the TCI than in the TPQ. The results indicate good performance of the TCI and TPQ. Factor analysis support adoption of four temperament dimensions and suggest that developmental work is still needed in the RD dimension. [ABSTRACT FROM AUTHOR]
Copyright of Acta Psychiatrica Scandinavica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: <searchLink fieldCode="JN" term="%22Acta+Psychiatrica+Scandinavica%22">Acta Psychiatrica Scandinavica</searchLink>. Aug2004, Vol. 110 Issue 2, p150-157. 8p.
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  Data: Miettunen J, Kantojärvi L, Ekelund J, Veijola J, Karvonen JT, Peltonen L, Järvelin MR, Freimer N, Lichtermann D, Joukamaa M. A large population cohort provides normative data for investigation of temperament. Acta Psychiatr Scand 2004: 110: 150–157. © Blackwell Munksgaard 2004. We evaluated the psychometric properties of widely used scales for assessing temperament in a large birth cohort. We simultaneously compared the properties of the temperament dimensions of the Tridimensional Personality Questionnaire (TPQ) and of the Temperament and Character Inventory (TCI). As part of the 31-year follow-up survey of the prospective Northern Finland 1966 Birth Cohort, the TPQ and TCI temperament questions were filled in by 4349 subjects (1974 males, 2375 males). Factor analysis and Cronbach's alpha were used to explore the psychometric properties of the scales. Of the three higher-order dimensions the reward dependence (RD) was the only one performing poorly in our study sample. Cronbach's alpha was higher in the TCI than in the TPQ. The results indicate good performance of the TCI and TPQ. Factor analysis support adoption of four temperament dimensions and suggest that developmental work is still needed in the RD dimension. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Acta Psychiatrica Scandinavica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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