Individual Differences in Interpersonal Accuracy: A Multi-Level Meta-Analysis to Assess Whether Judging Other People is One Skill or Many.

Research into individual differences in interpersonal accuracy (IPA; the ability to accurately judge others' emotions, intentions, traits, truthfulness, and other social characteristics) has a long tradition and represents a growing area of interest in psychology. Measuring IPA has proved fruitful f...

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Detalles Bibliográficos
Publicado en:Journal of Nonverbal Behavior Vol. 41; no. 2; pp. 103 - 138
Autores principales: Schlegel, Katja, Boone, R., Hall, Judith
Formato: Artículo
Publicado: Springer Nature Jun2017
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Research into individual differences in interpersonal accuracy (IPA; the ability to accurately judge others' emotions, intentions, traits, truthfulness, and other social characteristics) has a long tradition and represents a growing area of interest in psychology. Measuring IPA has proved fruitful for uncovering correlates of this skill. However, despite this tradition and a considerable volume of research, very few efforts have been made to look collectively at the nature of the tests involved in assessing IPA, leaving questions of the broader structure of IPA unresolved. Is IPA a single skill or a clustering of many discrete skills or some combination of partially overlapping skills? In a multi-level meta-analysis of 103 published and unpublished participant samples (13,683 participants), we analyzed 622 correlations between pairs of IPA tests (135 different IPA tests altogether). The overall correlation between IPA tests was r = .19, corrected for the nesting of correlations within the studies that administered more than two IPA tests and reported several correlations for the same participant sample. Test domain and characteristics were evaluated to explain differences in effect sizes; in general, tests in similar domains and using similar methodologies were more highly correlated with each other, suggesting that there are domains within which individual differences cluster. Implications for future research and IPA measurement were discussed.