Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Previously submitted to: JMIR mHealth and uHealth (no longer under consideration since Feb 20, 2024)

Date Submitted: Jan 5, 2024
Open Peer Review Period: Jan 8, 2024 - Mar 4, 2024
(closed for review but you can still tweet)

NOTE: This is an unreviewed Preprint

Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).

Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.

Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).

Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.

Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.

Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

The efficacy of the smartphone App for the self-management of low back pain: a systematic review and assessment of their quality through Mobile Application rating scale (MARS) in Italy

  • Luca Scala; 
  • Gloria Giglioni; 
  • Luca Bertazzoni; 
  • Francesca Bonetti

ABSTRACT

Background:

Self-management interventions from mobile apps are valuable tools to support managing patients with low back pain (LBP). To date, there are no studies that have made a qualitative assessment of the content of downloadable apps in Italy related to LBP self-management.

Objective:

The purposes of this systematic review were to (a) summarize the available studies on the efficacy of smartphone apps for self-management of LBP and (b) assess quality and functionalities of several apps.

Methods:

According to the Prisma Checklist, six bibliographic databases were searched by two reviewers with the keywords 'low back pain', 'mobile application,' 'smartphone', and 'telemedicine'. Instead, mobile applications were searched on the Italian Apple App Store and Google Play Store using the keywords "Low back pain", "lumbago", and "lombalgia". Then, after extracting the data, each application was evaluated with the Mobile Application Rating Scale (MARS) by four reviewers.

Results:

After eliminating duplicates, 852 records were screened, and 16 were included in the systematic review: six Randomized Controlled Trials (RCT), three systematic reviews, three systematic assessments, one scoping review, and one non RCT. Of the six RCT included, four reported a statistically significant decrease in pain in favor of app group, and two RCTs did not. Only in a non-RCT was an increase in the disability score. In application research, we identified and evaluated 25 applications through the MARS. The overall scores ranged from 1.93 to 3.92 for the IOS app and 1,73 to 4,25 for the Play Store app. The highest values are reported in the "functionality" category and the lowest in the "information" category. ICC calculated on all applications reports good reliability values (ICC=0.791) with a 95% confidence interval ranging from 0.583 to 0.901.

Conclusions:

The findings suggest that we need more and higher quality comparison studies, and few apps meet satisfying quality, content, and functionality criteria for LBP Self-management. Integrating smartphone applications to support rehabilitation intervention is a topic that needs further exploration to assess its effects. However, to improve the “information” category, involving scientific institutions in developing new apps will be helpful.


 Citation

Please cite as:

Scala L, Giglioni G, Bertazzoni L, Bonetti F

The efficacy of the smartphone App for the self-management of low back pain: a systematic review and assessment of their quality through Mobile Application rating scale (MARS) in Italy

JMIR Preprints. 05/01/2024:55862

DOI: 10.2196/preprints.55862

URL: https://preprints.jmir.org/preprint/55862

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.