Quantification choices for individual differences: an example of mapping self-report to psychophysiological responses

Morriss, J., Biagi, N. ORCID: https://orcid.org/0000-0002-7119-0767 and Wake, S. (2024) Quantification choices for individual differences: an example of mapping self-report to psychophysiological responses. International Journal of Psychophysiology, 205. 112427. ISSN 1872-7697 doi: 10.1016/j.ijpsycho.2024.112427

Abstract/Summary

A popular focus in affective neuroscience research has been to map the relationships between individual differences (e.g. personality and environmental experiences) and psychophysiological responses, in order to further understand the effect of individual differences upon neurobehavioral systems that support affect and arousal. Despite this trend, there have been a lack of practical examples demonstrating how the quantification of individual differences (e.g. categorical or continuous) impacts the observed relationships between different units of analysis (e.g. self-report > psychophysiological responses). To address this gap, we conducted a two-stage aggregated meta-analysis of self-reported intolerance of uncertainty (IU) and skin conductance responses during threat extinction (k = 18, n = 1006) using different quantification choices for individual differences in self-reported intolerance of uncertainty (continuous, categorical via median split, and categorical via extremes – one standard deviation above/below). Results from the meta-analyses revealed that the different quantification techniques produced some consistent (e.g. higher IU was significantly associated with skin conductance responding during late extinction training) and inconsistent IU-related effects. Furthermore, the number of statistically significant effects and effect sizes varied based on the quantification of individual differences in IU (e.g. categorical, compared to continuous was associated with more statistically significant effects, and larger effect sizes). The current study highlights how conducting different quantification methods for individual differences may help researchers understand the individual difference construct of interest (e.g. characterisation, measurement), as well as examine the stability and reliability of individual difference-based effects and correspondence between various units of analysis.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/117979
Item Type	Article
Refereed	Yes
Divisions	Henley Business School > Digitalisation, Marketing and Entrepreneurship
Publisher	Elsevier
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