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

Barreveld, Antje M. ; Rosén Klement, Maria L. LU ; Cheung, Sophia ; Axelsson, Ulrika LU orcid ; Basem, Jade I. ; Reddy, Anika S. ; Borrebaeck, Carl A.K. LU and Mehta, Neel (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
; ; ; ; ; ; and
organization
publishing date
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
  • scopus:85169501320
  • pmid:37104747
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
2025-11-02 07:17:07
@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}},
}