The University of Southampton
University of Southampton Institutional Repository

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

Quantification choices for individual differences: an example of mapping self-report to psychophysiological responses
Quantification choices for individual differences: an example of mapping self-report to psychophysiological responses
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.
Individual differences, Intolerance of uncertainty, Meta-analysis, Multiverse-type analysis, Psychophysiology, Threat extinction, Trait anxiety
0167-8760
Morriss, Jayne
a6005806-07cf-4283-8766-900003a7306f
Biagi, Nicolo
82fc64ac-a95f-433b-803b-349a62019d86
Wake, Shannon
b0425fcc-1bc7-4982-add5-e8affb055d50
Morriss, Jayne
a6005806-07cf-4283-8766-900003a7306f
Biagi, Nicolo
82fc64ac-a95f-433b-803b-349a62019d86
Wake, Shannon
b0425fcc-1bc7-4982-add5-e8affb055d50

Morriss, Jayne, Biagi, Nicolo and Wake, Shannon (2024) Quantification choices for individual differences: an example of mapping self-report to psychophysiological responses. International Journal of Psychophysiology, 205, [112427]. (doi:10.1016/j.ijpsycho.2024.112427).

Record type: Article

Abstract

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.

Text
SI_methods_manuscript_R1_preprint - Accepted Manuscript
Available under License Creative Commons Attribution.
Download (840kB)
Text
1-s2.0-S0167876024001314-main - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)

More information

Accepted/In Press date: 27 August 2024
e-pub ahead of print date: 31 August 2024
Published date: 4 September 2024
Keywords: Individual differences, Intolerance of uncertainty, Meta-analysis, Multiverse-type analysis, Psychophysiology, Threat extinction, Trait anxiety

Identifiers

Local EPrints ID: 493896
URI: http://eprints.soton.ac.uk/id/eprint/493896
ISSN: 0167-8760
PURE UUID: 744e7146-b0ed-4e4e-a25f-844a6eba1215
ORCID for Jayne Morriss: ORCID iD orcid.org/0000-0002-7928-9673

Catalogue record

Date deposited: 17 Sep 2024 16:33
Last modified: 21 Sep 2024 02:08

Export record

Altmetrics

Contributors

Author: Jayne Morriss ORCID iD
Author: Nicolo Biagi
Author: Shannon Wake

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×