Use of a smartphone app to improve adherence among low back pain group: A pilot RCT

Cunningham, Caitríona; Malone, Seamus

doi:10.1016/j.math.2016.10.046

Cited by 2 publications

(2 citation statements)

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“…Early literature showed that between 50% [30] and 70% [31] of people with chronic low back pain were nonadherent to a home exercise program. The use of technologies has been suggested to be a way to increase adherence to a home exercise program [32]. Previous studies that investigated the effectiveness of using mobile phone text message reminders indicated continued adherence to exercises in adults with recurrent low back pain [7].…”

Section: Discussionmentioning

confidence: 99%

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

Lo¹,

Lei²,

Li³

et al. 2018

JMIR Mhealth Uhealth

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

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Section: Discussionmentioning

confidence: 99%

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

Lo¹,

Lei²,

Li³

et al. 2018

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

show abstract

“…It has been proposed that one effective tactic for increasing program adherence when working out at home is to use technology to send alerts, messages, and reminders. (35) The specifically created range of progressive exercises, which target multiple problem areas leading to neck pain, were easily performed in an office setting because they could be done in either a sitting or standing position. The application that was created made this possible.…”

Section: Discussionmentioning

confidence: 99%

Evaluating Align's Effectiveness as a Telemedicine Physical Therapy App for Treating Neck Pain in Office Workers

2023

Journal of Chemical Health Risks

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Background: With rising healthcare costs that affect each patient's health and well-being, neck pain is emerging as a significant public health concern. One-year prevalence rates of cervical pain are significantly greater in computer professionals than in the overall population, indicating that they represent a particular population at high risk of developing neck discomfort. Patient-driven and patient-centred treatment must be included. One new development in healthcare is the use of mobile applications for management. The ability of mobile health (mHealth) to transcend geographical and temporal limitations and reach patients and healthcare professionals at any time and place makes it a preferred way of healthcare delivery. Nevertheless, there is scientific evidence for only a few mobile healthcare management applications.Objectives: To evaluate the usability and effectiveness of "Align" a mobile-based physical therapy application for treating office workers' neck pain. Methodology:Participants in this experimental descriptive study were enrolled after being assessed for inclusion criteria, and had pre-and post-assessments for outcome measurements, after which the intervention protocol was obtained via the smartphone mobile app. Twelve sessions in total over two weeks. Results:A decrease in the Numerical Pain Rating Scale scores (p<0.005) indicated a significant reduction in neck pain among the participants (N=107) who finished the intervention protocol. The Neck Disability score also showed a significant improvement, dropping by 4 points (p<0.005). Participants also demonstrated higher Positive Functioning Inventory and Postural Awareness scores (p<0.005). Conclusion:This study demonstrates the beneficial effects of the created mobile application for physical therapy for neck pain. The encouraging outcomes point to the necessity of additional research, such as randomised controlled trials, to determine how beneficial mobile applications are compared to standard clinical care.

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Use of a smartphone app to improve adherence among low back pain group: A pilot RCT

Cited by 2 publications

References 0 publications

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

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

Evaluating Align's Effectiveness as a Telemedicine Physical Therapy App for Treating Neck Pain in Office Workers

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