Evidence map›Paper›PMID 41509045›Full record

ReviewThe archives of bone and joint surgery2025

The Mobile Applications for Low Back and Neck Pain Therapy: App Review.

Yasaman Farjami Rad, Leila Shahmoradi, Noureddin Nakhostin Ansari, Scott Hasson, Amir Rakhshan, Maryam Ebrahimi, Meysam Rahmani

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in The archives of bone and joint surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yasaman Farjami RadSports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
Leila ShahmoradiHealth Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
Noureddin Nakhostin AnsariDepartment of Physiotherapy, School of Rehabilitation, Tehran University of Medical Sciences, Tehran, Iran.
Scott HassonDepartment of Physical Therapy, Augusta University, Augusta, Georgia, USA.
Amir RakhshanDepartment of Foreign Languages, Tehran University of Medical Sciences, Tehran, Iran.
Maryam EbrahimiDepartment of Health Information Technology, Neyshabur University of Medical Sciences, Neyshabur, Iran.
Meysam RahmaniDepartment of Health Information Technology, Saveh University of Medical Sciences, Saveh, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to assess mobile applications (apps) designed for physiotherapy targeting low back pain (LBP) and neck pain (NP) using the Mobile Application Rating Scale (MARS). The study employed an evaluation design, in which three reviewers conducted searches in English and Persian on Google Play in October 2024 to identify apps related to LBP and NP. After initial screening, the included apps were downloaded and installed on smartphones for further evaluation. The MARS questionnaire was utilized to evaluate apps. The total score obtained from the MARS questionnaire, along with the rating on the Google Play Store, was used to assess the quality and effectiveness of the apps. Eighteen apps, consisting of eight for NP and ten for LBP, were included in this study. Among LBP apps, the application "Back Pain Relief Exercises at Home" received the highest score (3.79/5). Moreover, the app "Lia - AI Posture Trainer" achieved the highest score among NP apps at 4.25/5. The findings showed that the apps available for NP and LBP are limited and low-quality. Given the increasing number of individuals suffering from these conditions, there is a clear need for up-to-date and high-quality software to provide daily patient support. These apps must be developed based on scientific studies and incorporate user feedback.

Indexed as

Back painDigital healthMobile applicationsNeck painSoftware validation

Identifiers

PMID41509045
PMCPMC12777711

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.