• Jemma Todd, Patrick J F Clarke, Alicia Maria Hughes, and Dimitri van Ryckeghem.
• Clinical Psychology Unit, School of Psychology, The University of Sydney, Sydney, Australia.
• Pain. 2023 Mar 1; 164 (3): 598604598-604.

AbstractDespite a preponderance of pain-related attentional bias research, little is known about how these biases arise and change over time. We tested whether the degree of attentional bias malleability , that is, ability to acquire and relinquish patterns of selective attention towards pain information, predicts daily pain interference. Individuals with chronic pain (N = 66) completed a novel attentional bias malleability procedure based on a modified dot-probe paradigm. Participants received a contingency that encouraged an attentional preference toward and away from pain words across 2 counterbalanced blocks, and attentional bias was assessed before and after each contingency block. Participants then completed a daily diary for 7 days, including the Patient-Reported Outcomes Measurement Information System-29 pain severity and interference. Multilevel modelling was conducted to predict daily pain interference from attentional bias malleability constructs, controlling for pain severity and demographic factors. Greater attentional bias (F 1,391 = 3.97, P = 0.047), greater readiness to acquire an attentional bias (F 1,389 = 4.92, P = 0.027), and less readiness to lose an acquired attentional bias toward pain (F 1,354 = 5.18, P = 0.024) all predicted less pain interference. There was also an interaction between pain severity and overall attentional bias malleability (F 1,62 = 5.48, P = 0.023), such that as pain severity increased, those who showed greater attentional bias malleability showed less corresponding increase in their pain interference than those who showed less attentional bias malleability. This study adds new thinking to the dynamic nature of attentional bias and how such biases might arise and influence pain outcomes.Copyright © 2022 International Association for the Study of Pain.

11 keywords...

hide…