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Measuring Implicit Motives with the Picture Story Exercise (PSE): Databases of Expert-Coded German Stories, Pictures, and Updated Picture Norms


Schönbrodt, Felix D; Hagemeyer, Birk; Brandstätter, Veronika; Czikmantori, Thomas; Gröpel, Peter; Hennecke, Marie; Israel, Laura S F; Janson, Kevin T; Kemper, Nina; Köllner, Martin G; Kopp, Philipp M; Mojzisch, Andreas; Müller-Hotop, Raphael; Prüfer, Johanna; Quirin, Markus; Scheidemann, Bettina; Schiestel, Lena; Schulz-Hardt, Stefan; Sust, Larissa N N; Zygar-Hoffmann, Caroline; Schultheiss, Oliver C (2020). Measuring Implicit Motives with the Picture Story Exercise (PSE): Databases of Expert-Coded German Stories, Pictures, and Updated Picture Norms. Journal of Personality Assessment:Epub ahead of print.

Abstract

We present two openly accessible databases related to the assessment of implicit motives using Picture Story Exercises (PSEs): (a) A database of 183,415 German sentences, nested in 26,389 stories provided by 4,570 participants, which have been coded by experts using Winter's coding system for the implicit affiliation/intimacy, achievement, and power motives, and (b) a database of 54 classic and new pictures which have been used as PSE stimuli. Updated picture norms are provided which can be used to select appropriate pictures for PSE applications. Based on an analysis of the relations between raw motive scores, word count, and sentence count, we give recommendations on how to control motive scores for story length, and validate the recommendation with a meta-analysis on gender differences in the implicit affiliation motive that replicates existing findings. We discuss to what extent the guiding principles of the story length correction can be generalized to other content coding systems for narrative material. Several potential applications of the databases are discussed, including (un)supervised machine learning of text content, psychometrics, and better reproducibility of PSE research.

Abstract

We present two openly accessible databases related to the assessment of implicit motives using Picture Story Exercises (PSEs): (a) A database of 183,415 German sentences, nested in 26,389 stories provided by 4,570 participants, which have been coded by experts using Winter's coding system for the implicit affiliation/intimacy, achievement, and power motives, and (b) a database of 54 classic and new pictures which have been used as PSE stimuli. Updated picture norms are provided which can be used to select appropriate pictures for PSE applications. Based on an analysis of the relations between raw motive scores, word count, and sentence count, we give recommendations on how to control motive scores for story length, and validate the recommendation with a meta-analysis on gender differences in the implicit affiliation motive that replicates existing findings. We discuss to what extent the guiding principles of the story length correction can be generalized to other content coding systems for narrative material. Several potential applications of the databases are discussed, including (un)supervised machine learning of text content, psychometrics, and better reproducibility of PSE research.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Scopus Subject Areas:Social Sciences & Humanities > Clinical Psychology
Health Sciences > Psychiatry and Mental Health
Physical Sciences > Health, Toxicology and Mutagenesis
Uncontrolled Keywords:Arts and Humanities (miscellaneous), Clinical Psychology
Language:English
Date:24 March 2020
Deposited On:04 Feb 2021 09:17
Last Modified:05 Feb 2021 21:05
Publisher:Taylor & Francis
ISSN:0022-3891
OA Status:Closed
Publisher DOI:https://doi.org/10.1080/00223891.2020.1726936
PubMed ID:32207995
Project Information:
  • : FunderSNSF
  • : Grant ID100019_156516
  • : Project Titlethen what? Thinking of one’s goal as a self-regulatory strategy

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