Predicting attitudes toward ambiguity using natural language processing on free descriptions for open-ended question measurements

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Abstract

Individual traits and reactions to ambiguity differ and are conceptualized in terms of an individual’s attitudes toward ambiguity or ambiguity tolerance. The development of natural language processing technology has made it possible to measure mental states and reactions through open-ended questions, rather than predefined numerical rating scales, which have traditionally been the dominant method in psychological research. This study presented three ambiguity-related situations and responses collected online from 591 participants in an open-ended format. After the analysis with bidirectional encoder representations from transformers, correlations were calculated using scores from the numerical evaluation by conventional questionnaire, and a significant moderate positive correlation was found. Therefore, this study found that attitudes toward ambiguity can be measured using an open-ended response method of reporting everyday life states. It is a novel methodology that can be expanded to other scales in psychology and can potentially be used in educational and clinical situations where participants can be asked to respond with minimal burden.

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Hitsuwari, J., Okano, H., & Nomura, M. (2024). Predicting attitudes toward ambiguity using natural language processing on free descriptions for open-ended question measurements. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-59118-z

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