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An artificial intelligence-powered, patient-centric digital tool for self-management of chronic pain: a prospective, multicenter clinical trial.

Authors :
Barreveld, Antje M
Klement, Maria L Rosén
Cheung, Sophia
Axelsson, Ulrika
Basem, Jade I
Reddy, Anika S
Borrebaeck, Carl A K
Mehta, Neel
Source :
Pain Medicine. Sep2023, Vol. 24 Issue 9, p1100-1110. 11p.
Publication Year :
2023

Abstract

Objective To investigate how a behavioral health, artificial intelligence (AI)-powered, digital self-management tool affects the daily functions in adults with chronic back and neck pain. Design Eligible subjects were enrolled in a 12-week prospective, multicenter, single-arm, open-label study and instructed to use the digital coach daily. Primary outcome was a change in Patient-Reported Outcomes Measurement Information Systems (PROMIS) scores for pain interference. Secondary outcomes were changes in PROMIS physical function, anxiety, depression, pain intensity scores and pain catastrophizing scale (PCS) scores. Methods Subjects logged daily activities, using PainDrainerTM, and data analyzed by the AI engine. Questionnaire and web-based data were collected at 6 and 12 weeks and compared to subjects' baseline. Results Subjects completed the 6- (n = 41) and 12-week (n = 34) questionnaires. A statistically significant Minimal Important Difference (MID) for pain interference was demonstrated in 57.5% of the subjects. Similarly, MID for physical function was demonstrated in 72.5% of the subjects. A pre- to post-intervention improvement in depression score was also statistically significant, observed in 100% of subjects, as was the improvement in anxiety scores, evident in 81.3% of the subjects. PCS mean scores was also significantly decreased at 12 weeks. Conclusion Chronic pain self-management, using an AI-powered, digital coach anchored in behavioral health principles significantly improved subjects' pain interference, physical function, depression, anxiety, and pain catastrophizing over the 12-week study period. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15262375
Volume :
24
Issue :
9
Database :
Academic Search Index
Journal :
Pain Medicine
Publication Type :
Academic Journal
Accession number :
171389213
Full Text :
https://doi.org/10.1093/pm/pnad049