RealPic: Picture norms of real-world common items

Behav Res Methods. 2021 Aug;53(4):1746-1761. doi: 10.3758/s13428-020-01523-z. Epub 2021 Feb 10.

Abstract

Pictures are often used as stimuli in several fields, such as psychology and neuroscience. However, co-occurring image-related properties might impact their processing, emphasizing the importance of validating such materials to guarantee the quality of research and professional practices. This is particularly relevant for pictures of common items because of their wide applicability potential. Normative studies have already been conducted to create and validate such pictures, yet most of them focused on stimulus without naturalistic elements (e.g., line drawings). Norms for real-world pictures of common items are rare, and their normative examination does not always simultaneously assess affective, semantic and perceptive dimensions, namely in the Portuguese context. Real-world pictures constitute pictorial representations of the world with realistic details (e.g., natural color or position), thus improving their ecological validity and their suitability for empirical studies or intervention purposes. Consequently, the establishment of norms for real-world pictures is mandatory for exploring their ecological richness and to uncover their impact across several relevant dimensions. In this study, we established norms for 596 real-world pictures of common items (e.g., tomato, drum) selected from existing databases and distributed into 12 categories. The pictures were evaluated on nine dimensions by a Portuguese sample. The results present the norms by item, by dimension and their correlations as well as cross-cultural analyses. RealPic is a culturally based dataset that offers systematic and flexible standards and is suitable for selecting stimuli while controlling for confounding effects in empirical tasks and interventional applications.

Keywords: Affective; Cross-cultural analysis; Norms; Perceptive; Real-world pictures; Semantic.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Databases, Factual
  • Humans
  • Semantics*