An artificial intelligence-powered, patient-centric digital tool for self-management of chronic pain : a prospective, multicenter clinical trial
(2023) In Pain Medicine (United States) 24(9). p.1100-1110- 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... (More)
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.
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- author
- Barreveld, Antje M. ; Rosén Klement, Maria L. LU ; Cheung, Sophia ; Axelsson, Ulrika LU ; Basem, Jade I. ; Reddy, Anika S. ; Borrebaeck, Carl A.K. LU and Mehta, Neel
- organization
- publishing date
- 2023-09-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ACT, chronic pain, digital tool, patient-centric, self-management
- in
- Pain Medicine (United States)
- volume
- 24
- issue
- 9
- pages
- 11 pages
- publisher
- Oxford University Press
- external identifiers
-
- pmid:37104747
- scopus:85169501320
- ISSN
- 1526-2375
- DOI
- 10.1093/pm/pnad049
- language
- English
- LU publication?
- yes
- id
- 64d3e7d0-970c-4449-902d-a6f93ae1dfce
- date added to LUP
- 2023-10-27 16:45:57
- date last changed
- 2024-04-19 03:59:12
@article{64d3e7d0-970c-4449-902d-a6f93ae1dfce, abstract = {{<p>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.</p>}}, author = {{Barreveld, Antje M. and Rosén Klement, Maria L. and Cheung, Sophia and Axelsson, Ulrika and Basem, Jade I. and Reddy, Anika S. and Borrebaeck, Carl A.K. and Mehta, Neel}}, issn = {{1526-2375}}, keywords = {{ACT; chronic pain; digital tool; patient-centric; self-management}}, language = {{eng}}, month = {{09}}, number = {{9}}, pages = {{1100--1110}}, publisher = {{Oxford University Press}}, series = {{Pain Medicine (United States)}}, title = {{An artificial intelligence-powered, patient-centric digital tool for self-management of chronic pain : a prospective, multicenter clinical trial}}, url = {{http://dx.doi.org/10.1093/pm/pnad049}}, doi = {{10.1093/pm/pnad049}}, volume = {{24}}, year = {{2023}}, }