Measuring Implicit Motives with the Picture Story Exercise (PSE): Databases of Expert-Coded German Stories, Pictures, and Updated Picture Norms
Measuring Implicit Motives with the Picture Story Exercise (PSE): Databases of Expert-Coded German Stories, Pictures, and Updated Picture Norms
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用图画故事练习(PSE)衡量隐性动机:专家编码的德国故事、图片和更新的图片规范数据库
DOI:
10.1080/00223891.2020.1726936
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发表时间:
2020
影响因子:
3.4
通讯作者:
Schultheiss
中科院分区:
文献类型:
--
作者:
Schönbrodt;Hagemeyer;Brandstätter;Czikmantori;Gröpel;Hennecke;Israel;L. S. F;Schultheiss
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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