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Randomized Controlled Trial
. 2023 May;45(3):242-254.
doi: 10.1080/13803395.2023.2221396. Epub 2023 Jun 6.

Neurocognitive predictors of adherence to an online pain self-management program adjunct to long-term opioid therapy

David E Fleck  1 , Marian Wilson  2   3 , Daniel Lewis  1 , Jeffrey A Welge  1 , Grace Arya  1 , Anoop Sathyan  4 , Kelly Cohen  4 , T John Winhusen  1   5
Affiliations
Randomized Controlled Trial

Neurocognitive predictors of adherence to an online pain self-management program adjunct to long-term opioid therapy

David E Fleck et al. J Clin Exp Neuropsychol. 2023 May.

Abstract

Introduction: While pain self-management programs can significantly improve patient outcomes, poor adherence is common and the need for research on predictors of adherence has been noted. A potential, but commonly overlooked, predictor is cognitive function. Our aim, then, was to examine the relative influence of various cognitive functional domains on engagement with an online pain self-management program.

Method: A secondary analysis of a randomized controlled trial testing the impact of E-health (a 4-month subscription to the online Goalistics Chronic Pain Management Program) plus treatment as usual, relative to treatment as usual alone, on pain and opioid dose outcomes in adults receiving long-term opioid therapy of morphine equivalence dose ≥20 mg; 165 E-health participants who completed an on-line neurocognitive battery were included in this sub-analysis. A variety of demographic, clinical, and symptom rating scales were also examined. We hypothesized that better processing speed and executive functions at baseline would predict engagement with the 4-month E-health subscription.

Results: Ten functional cognitive domains were identified using exploratory factor analysis and the resultant factor scores applied for hypothesis testing. The strongest predictors of E-health engagement were selective attention, and response inhibition and speed domains. An explainable machine learning algorithm improved classification accuracy, sensitivity, and specificity.

Conclusions: The results suggest that cognition, especially selective attention, inhibitory control, and processing speed, is predictive of online chronic pain self-management program engagement. Future research to replicate and extend these findings seems warranted.

Clinicaltrials.gov registration number: NCT03309188.

Keywords: Chronic Pain Management Program; Pain; cognition; neuropsychology; opioid therapy.

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Conflict of interest statement

Disclosure of Interest

Marian Wilson was a paid consultant for two grants from the NIH with Linda Ruehlman, Ph.D., the owner of the Goalistics company, to provide expertise to the program development and received no rights to the company, intellectual property, or profits. The remaining authors report no conflict of interest.

Figures

Figure 1.
Figure 1.
A 10-factor model of 30 WebNeuro measures in participants treated with long-term opioid therapy. Numbers represent the rotated factor loading from an exploratory factor analysis. Light gray highlights represent response measures from the same test that load to distinct domains for the same general cognitive ability (i.e., measures loading to Sustained and Controlled Attention Domains). Dark gray highlights represent response measures from two different tests that load to a common cognitive domain (i.e., measures loading to Response Inhibition & Processing Speed and Sustained Attention Domains). The dotted arrow represents a secondary cross-loading of Recognition Memory Test measures with the Planning & Learning Domains. Thick black arrows represent the functional cognitive domains that best predict E-health Engagement at 4 months.
See this image and copyright information in PMC

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