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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jun 20, 2017
Open Peer Review Period: Jun 20, 2017 - Jul 12, 2017
Date Accepted: Feb 15, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

The Perceived Benefits of an Artificial Intelligence–Embedded Mobile App Implementing Evidence-Based Guidelines for the Self-Management of Chronic Neck and Back Pain: Observational Study

Lo WLA, Lei D, Li L, Huang DF, Tong KF

The Perceived Benefits of an Artificial Intelligence–Embedded Mobile App Implementing Evidence-Based Guidelines for the Self-Management of Chronic Neck and Back Pain: Observational Study

JMIR Mhealth Uhealth 2018;6(11):e198

DOI: 10.2196/mhealth.8127

PMID: 30478019

PMCID: 6288595

The Perceived Benefits of an Artificial Intelligence–Embedded Mobile App Implementing Evidence-Based Guidelines for the Self-Management of Chronic Neck and Back Pain: Observational Study

  • Wai Leung Ambrose Lo; 
  • Di Lei; 
  • Le Li; 
  • Dong Feng Huang; 
  • Kin-Fai Tong

ABSTRACT

Background:

Chronic musculoskeletal neck and back pain are disabling conditions among adults. Use of technology has been suggested as an alternative way to increase adherence to exercise therapy, which may improve clinical outcomes.

Objective:

The aim was to investigate the self-perceived benefits of an artificial intelligence (AI)–embedded mobile app to self-manage chronic neck and back pain.

Methods:

A total of 161 participants responded to the invitation. The evaluation questionnaire included 14 questions that were intended to explore if using the AI rehabilitation system may (1) increase time spent on therapeutic exercise, (2) affect pain level (assessed by the 0-10 Numerical Pain Rating Scale), and (3) reduce the need for other interventions.

Results:

An increase in time spent on therapeutic exercise per day was observed. The median Numerical Pain Rating Scale scores were 6 (interquartile range [IQR] 5-8) before and 4 (IQR 3-6) after using the AI-embedded mobile app (95% CI 1.18-1.81). A 3-point reduction was reported by the participants who used the AI-embedded mobile app for more than 6 months. Reduction in the usage of other interventions while using the AI-embedded mobile app was also reported.

Conclusions:

This study demonstrated the positive self-perceived beneficiary effect of using the AI-embedded mobile app to provide a personalized therapeutic exercise program. The positive results suggest that it at least warrants further study to investigate the physiological effect of the AI-embedded mobile app and how it compares with routine clinical care.


 Citation

Please cite as:

Lo WLA, Lei D, Li L, Huang DF, Tong KF

The Perceived Benefits of an Artificial Intelligence–Embedded Mobile App Implementing Evidence-Based Guidelines for the Self-Management of Chronic Neck and Back Pain: Observational Study

JMIR Mhealth Uhealth 2018;6(11):e198

DOI: 10.2196/mhealth.8127

PMID: 30478019

PMCID: 6288595

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