Learning to predict pain: differences in people with persistent neck pain and pain-free controls
| Autor: | Daniel S. Harvie, Ann Meulders, Jeroen Weermeijer, Nick Olthof |
|---|---|
| Přispěvatelé: | Harvie, Daniel S, Weermeijer, Jeroen D, Olthof, Nick A, Meulders, Ann, Section Experimental Health Psychology, RS: FPN CPS I |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
neck pain
lcsh:Medicine MUSCULAR RESPONSES Psychiatry and Psychology Chronic pain Audiology associative learning 0302 clinical medicine DEFICITS Neck pain Fibromyalgia Fear avoidance model Fear avoidance FIBROMYALGIA SCALE generalization Contingency learning fear learning Fear learning extinction General Neuroscience 05 social sciences Extinction General Medicine Fear-avoidance model contingency learning medicine.symptom General Agricultural and Biological Sciences Psychology chronic pain medicine.medical_specialty fear avoidance Generalization 050105 experimental psychology General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Generalization (learning) Associative learning CHRONIC BACK-PAIN medicine 0501 psychology and cognitive sciences VALIDITY FEAR-AVOIDANCE Anesthesiology and Pain Management Predictive learning DISABILITY lcsh:R Extinction (psychology) fear avoidance model medicine.disease predictive learning Orthopedics 030217 neurology & neurosurgery |
| Zdroj: | PeerJ PEERJ, 8:9345. PeerJ Inc. PeerJ, Vol 8, p e9345 (2020) |
| ISSN: | 2167-8359 |
| Popis: | Background Learning to predict threatening events enables an organism to engage in protective behavior and prevent harm. Failure to differentiate between cues that truly predict danger and those that do not, however, may lead to indiscriminate fear and avoidance behaviors, which in turn may contribute to disability in people with persistent pain. We aimed to test whether people with persistent neck pain exhibit contingency learning deficits in predicting pain relative to pain-free, gender-and age-matched controls. Method We developed a differential predictive learning task with a neck pain-relevant scenario. During the acquisition phase, images displaying two distinct neck positions were presented and participants were asked to predict whether these neck positions would lead to pain in a fictive patient with persistent neck pain (see fictive patient scenario details in Appendix A). After participants gave their pain-expectancy judgment in the hypothetical scenario, the verbal outcome (PAIN or NO PAIN) was shown on the screen. One image (CS+) was followed by the outcome “PAIN”, while another image (CS−) was followed by the outcome “NO PAIN”. During the generalization phase, novel but related images depicting neck positions along a continuum between the CS+ and CS− images (generalization stimuli; GSs) were introduced to assess the generalization of acquired predictive learning to the novel images; the GSs were always followed by the verbal outcome “NOTES UNREADABLE” to prevent extinction learning. Finally, an extinction phase was included in which all images were followed by “NO PAIN” assessing the persistence of pain-expectancy judgments following disconfirming information. Results Differential pain-expectancy learning was reduced in people with neck pain relative to controls, resulting from patients giving significantly lower pain-expectancy judgments for the CS+, and significantly higher pain-expectancy judgments for the CS−. People with neck pain also demonstrated flatter generalization gradients relative to controls. No differences in extinction were noted. Discussion The results support the hypothesis that people with persistent neck pain exhibit reduced differential pain-expectancy learning and flatter generalization gradients, reflecting deficits in predictive learning. Contrary to our hypothesis, no differences in extinction were found. These findings may be relevant to understanding behavioral aspects of chronic pain. |
| Databáze: | OpenAIRE |
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