The Efficacy of the Smartphone App for the Self-Management of Low Back Pain: A Systematic Review and Assessment of Their Quality through the Mobile Application Rating Scale (MARS) in Italy

Smartphone apps for self-management are valuable tools to help manage low back pain (LBP) patients. 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) identify free applications available in Italy that offer strategies for LBP self-management and provide a qualitative assessment using the Mobile Application Rating Scale (MARS). According to the Prisma Checklist, six bibliographic databases were searched with the keywords ‘low back pain’, ‘mobile application’, ‘smartphone’, and ‘telemedicine’. In total, 852 records were screened, and 16 were included in the systematic review. Of the six RCTs included, four reported a statistically significant decrease in pain in favor of the app group, and two RCTs did not. Only in a non-RCT was there an increase in the disability score. In the application research conducted on mobile stores, we identified and rated 25 applications through 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 findings suggest that few apps meet satisfying quality, content, and functionality criteria for LBP self-management.


Introduction
Low back pain (LBP) is the musculoskeletal disorder with the most significant social burden and is considered the leading cause of disability worldwide [1].Healthcare costs and disability related to low back pain vary substantially among countries and are influenced by cultural and social contexts, as well as beliefs about the condition [1,2].The disability and costs associated with low back pain are projected to increase in the coming years, particularly in developing countries with limited economic resources [1,2].
Recent evidence suggests that self-management strategies are effective and should be promoted for patients with chronic low back pain [3,4].During the COVID-19 pandemic, healthcare services have had to adapt to ensure the safe delivery of care, which has led to a reduction in outpatient services and an increased reliance on alternative methods for providing rehabilitation and physical therapy.
Smartphone apps are increasingly being used to help patients with chronic conditions [5][6][7].Self-management interventions delivered via mobile apps are valuable tools for supporting the management of chronic LBP [5].These apps help reduce costs and end geographical barriers, making rehabilitation services more accessible to all.
Life 2024, 14, 760 2 of 19 Mobile health (mHealth) apps for pain management offer potential benefits to patients by enabling the monitoring of acute or chronic pain and providing information and support for pain management [7].
However, there is limited literature exploring the effectiveness of smartphone apps for self-managing low back pain (LBP), and the current evidence is still inconclusive [8].Furthermore, no rigorous evaluation of LBP self-management apps available in Italy has been conducted, and there is no guidance for healthcare professionals and consumers on selecting high-quality, evidence-based LBP apps.
Given the vast number of publicly available apps for LBP self-management, it is crucial to assess their quality and ensure they adhere to best practice guidelines.
The primary aim of this systematic review is to provide an updated synthesis of existing primary studies on the effectiveness of smartphone apps for self-managing LBP.Additionally, the secondary aim is to identify free apps available in Italy that offer strategies for LBP self-management and to provide a qualitative evaluation using the Mobile Application Rating Scale (MARS) [9] to clarify the validity of the content provided to users.

Materials and Methods
Our systematic review, registered with PROSPERO (ID: CRD42022357170), employs a mixed-methods approach to provide an overview of smartphone applications designed for the self-management of low back pain.The study involved a comprehensive search of the existing literature and mobile platforms for relevant applications.Conducted by health professionals from "Tor Vergata" University, the research team has extensive experience in studies related to outcome measures in Italy.This review adheres to the 27-item PRISMA guidelines for reporting systematic reviews.

Inclusion and Exclusion Criteria
Studies for this review were included according to the following criteria (Figure 1): types of studies, participants, and intervention.Studies were limited to people with low back pain (LBP), regardless of the clinical course or how long it had been since diagnosis.Studies with mixed diagnosis samples were included if a subgroup of participants with LBP could be identified and separate data were available.
for supporting the management of chronic LBP [5].These apps help reduce costs and end geographical barriers, making rehabilitation services more accessible to all.
Mobile health (mHealth) apps for pain management offer potential benefits to patients by enabling the monitoring of acute or chronic pain and providing information and support for pain management [7].
However, there is limited literature exploring the effectiveness of smartphone apps for self-managing low back pain (LBP), and the current evidence is still inconclusive [8].Furthermore, no rigorous evaluation of LBP self-management apps available in Italy has been conducted, and there is no guidance for healthcare professionals and consumers on selecting high-quality, evidence-based LBP apps.
Given the vast number of publicly available apps for LBP self-management, it is crucial to assess their quality and ensure they adhere to best practice guidelines.
The primary aim of this systematic review is to provide an updated synthesis of existing primary studies on the effectiveness of smartphone apps for self-managing LBP.Additionally, the secondary aim is to identify free apps available in Italy that offer strategies for LBP self-management and to provide a qualitative evaluation using the Mobile Application Rating Scale (MARS) [9] to clarify the validity of the content provided to users.

Materials and Methods
Our systematic review, registered with PROSPERO (ID: CRD42022357170), employs a mixed-methods approach to provide an overview of smartphone applications designed for the self-management of low back pain.The study involved a comprehensive search of the existing literature and mobile platforms for relevant applications.Conducted by health professionals from "Tor Vergata" University, the research team has extensive experience in studies related to outcome measures in Italy.This review adheres to the 27item PRISMA guidelines for reporting systematic reviews.

Inclusion and Exclusion Criteria
Studies for this review were included according to the following criteria (Figure 1): types of studies, participants, and intervention.Studies were limited to people with low back pain (LBP), regardless of the clinical course or how long it had been since diagnosis.Studies with mixed diagnosis samples were included if a subgroup of participants with LBP could be identified and separate data were available.All studies based on self-management using a smartphone app to relieve pain, improve function and promote physical well-being in individuals with low back pain were considered.The included papers described various LBP self-management interventions, such as exercises for motor control, strength or flexibility, pain management tips, mindfulness, or relaxation exercises.
There were no restrictions on study design or publication period.Only studies in English were considered.
The following were excluded: (a) studies related to telemedicine; (b) blended rehabilitation interventions (self-management combined with live sessions with healthcare professionals); and (c) study protocols.

Search Strategy
All the studies in the available literature that included the keywords ("low back pain", "mobile applications", "telemedicine", "smartphone") connected by the Boolean operator "AND" were considered.Appendix A shows the search queries strings used.Studies were selected for inclusion through individualized systematic searches of six electronic databases that were systematically searched in November 2022: PUBMED, SCOPUS, WEB OF SCIENCE, CYNAL, PSYCINFO, and PEDRO.All potential studies were selected by two reviewers.

Selection Process of Studies
The titles, abstracts, and keywords selected from the databases were independently screened by two physical therapists (LS and LB).After the initial screening, studies that did not meet the inclusion criteria were systematically excluded, while those that appeared relevant were identified.A final list of eligible studies was then compiled, with any disagreements resolved through consensus.The studies that met the criteria underwent a full-text review to confirm their inclusion.The online software "Rayyan" (version: 4406419348369) was used for the screening process.

Synthesis Method
Two reviewers independently extracted study characteristics using Microsoft Excel 2019 (Microsoft Inc., Redmond, WA, USA).The extracted data included the country of the study, study objectives, population characteristics, diagnosis, app name, app content, cost, developer information, treatment outcomes, and platform (iOS/Android).The included studies were then examined for similarities in participants, interventions, and results.In cases of heterogeneity among the studies, a narrative synthesis was provided.

APP Search Strategy
Mobile applications were searched in May 2022 on the Italian Apple App Store and Google Play Store using the keywords "Low back pain", "Lumbago", and "Lombalgia".The following inclusion criteria were applied: (a) the app was designed for LBP selfmanagement; (b) it targeted adult users; (c) it was available in Italian or English; (d) it was free or did not require in-app purchases for full functionality; (e) it was available for download from both the iOS and Google Play Stores; and (f) it had been updated within the last three years.Two reviewers based in Italy (L.S. and L.B.) conducted an initial screening of the mobile applications by title and description.Any discrepancies in app selection were resolved by a third reviewer (G.G.) to reach a consensus.Subsequently, the apps were downloaded and tested, with those not meeting the inclusion criteria being excluded.
After identifying the apps to be included, data were extracted and an evaluation was carried out using the Mobile App Rating Scale (MARS) by four reviewers (L.S., L.B., G.G., F.B.).The MARS consists of 23 questions designed to evaluate engagement, functionality, aesthetics, information, and subjective quality of mobile applications.Additionally, there are six final, app-specific questions that can be customized to reflect the target health behavior or functionality of the application or study; however, this section was not evaluated in this study.The total MARS score is the mean of the mean scores for each of the four subscales (engagement, functionality, aesthetics, and information), rated on a scale from zero to five.All reviewers received training in the use of MARS through a tutorial available on YouTube [10].Following the tutorial, the reviewers independently tested a single app, leading to a final discussion to reach a consensus.Discrepancies were resolved by a third reviewer, and ambiguous MARS items were clarified to ensure full comprehension of the scale.
Finally, the inter-rater reliability of MARS and the degree of agreement among evaluators were assessed by calculating the intraclass correlation coefficient (ICC) score [11].

Study Characteristics
At the end of the screening and selection process, sixteen studies were identified: six randomized controlled trials (RCTs), three systematic reviews, three systematic assessments, one scoping review, one observational study, and one non-randomized clinical trial.Of the six RCTs [12][13][14][15][16][17], four reported statistically significant reductions in pain levels favoring the mHealth app group compared to physiotherapy, web-based education, web-based email support, no training, or placebo groups.Conversely, two RCTs did not show statistically significant differences in pain levels between the mHealth app and control groups.The studies varied in how they reported participant ages, with the mean age ranging from 18 to 50 years.Two studies [12,19] did not report participant ages, and only one study [16] had a majority of female participants.
The study by Lo et al. [18] reported a statistically significant reduction in the Numeric Rating Scale (NRS) (p = 0.04) between pre-and post-treatment assessments.In the sole non-RCT study [19], there was an increase in the disability score (from 6.08 to 7.5; p = 0.01).No significant differences were found between groups or sessions in Pressure Pain Thresholds (PPTs).
The remaining seven studies [6,8,[20][21][22][23][24] were reviews aimed at evaluating papers discussing apps for self-management of low back pain [6,8,24], assessing apps qualitatively [20,22,23], or both [21].Further details on these studies can be found in Tables A1 and A2 (Appendix A).None of the applications from the studies were included in our evaluation as they were either not available in app stores or did not meet the inclusion criteria.

Overview of Apps Results
Our search yielded 762 items on the Play Store and 210 on iOS.Following the exclusion of 271 apps, screening was performed based on the app descriptions, resulting in 55 apps meeting the inclusion criteria for the Play Store and 17 for iOS.Subsequently, the apps were downloaded, and after a final screening, 20 apps from the Google Play Store and 5 from iOS were assessed using the MARS scale.The selection process is illustrated in Figure 2. All apps fell within the categories of health and well-being (iOS) and Health & Fitness (Google Play Store).Data extraction for the number of app downloads was only feasible for Android apps, as this information is not accessible on the Apple App Store.The app with the highest star rating on both platforms was "Atlas Low Back Pain"; however, not all apps had a sufficient number of ratings to display this score.evaluation as they were either not available in app stores or did not meet the inclusion criteria.

Overview of Apps Results
Our search yielded 762 items on the Play Store and 210 on iOS.Following the exclusion of 271 apps, screening was performed based on the app descriptions, resulting in 55 apps meeting the inclusion criteria for the Play Store and 17 for iOS.Subsequently, the apps were downloaded, and after a final screening, 20 apps from the Google Play Store and 5 from iOS were assessed using the MARS scale.The selection process is illustrated in Figure 2. All apps fell within the categories of health and well-being (iOS) and Health & Fitness (Google Play Store).Data extraction for the number of app downloads was only feasible for Android apps, as this information is not accessible on the Apple App Store.The app with the highest star rating on both platforms was "Atlas Low Back Pain"; however, not all apps had a sufficient number of ratings to display this score.App downloads ranged from 100+ to 100,000+.The most downloaded applications from the Google Play Store were "Esercizi per il mal di schiena" developed by FitStar Apps s.r.o.(100,000+ rating of 4.6 out of 5), "Back Pain Relief Yoga at Home" developed by Dr. Zio-Yoga Teacher (100,000+ rating of 4.4 out of 5), and "Posture Correction Exercises" developed by Gym Fitness Technology (100,000+ rating of 3.7 out of 5).The mean overall MARS score obtained was 2.88 out of 5.The highest-rated app was "Pain Guru" by Dr. Giresh Kanji (4.09), while the lowest score was for "Lower Back Pain Exercises" by Steveloper (1.88); both apps were found in the Google Play Store."Pain Guru" scored 4/5 in Engagement, 4.75 in Functionality, 4.5 in Aesthetics, and 3.14 in the Information subscale.In contrast, "Lower Back Pain Exercises" scored 1.8 in Engagement, 3.25 in Functionality, 1.33 in Aesthetics, and 1.14 in Information."Pain Guru" aims to investigate the cause of low back pain, aid in diagnosis, and provide necessary information for pain management.Conversely, "Lower Back Pain Exercises" aims to offer a list of exercises beneficial for managing low back pain; however, its rudimentary graphics and lack of comprehensive information impede user engagement.Notably, there was no correlation observed App downloads ranged from 100+ to 100,000+.The most downloaded applications from the Google Play Store were "Esercizi per il mal di schiena" developed by FitStar Apps s.r.o.(100,000+ rating of 4.6 out of 5), "Back Pain Relief Yoga at Home" developed by Dr. Zio-Yoga Teacher (100,000+ rating of 4.4 out of 5), and "Posture Correction Exercises" developed by Gym Fitness Technology (100,000+ rating of 3.7 out of 5).The mean overall MARS score obtained was 2.88 out of 5.The highest-rated app was "Pain Guru" by Dr. Giresh Kanji (4.09), while the lowest score was for "Lower Back Pain Exercises" by Steveloper (1.88); both apps were found in the Google Play Store."Pain Guru" scored 4/5 in Engagement, 4.75 in Functionality, 4.5 in Aesthetics, and 3.14 in the Information sub-scale.In contrast, "Lower Back Pain Exercises" scored 1.8 in Engagement, 3.25 in Functionality, 1.33 in Aesthetics, and 1.14 in Information."Pain Guru" aims to investigate the cause of low back pain, aid in diagnosis, and provide necessary information for pain management.Conversely, "Lower Back Pain Exercises" aims to offer a list of exercises beneficial for managing low back pain; however, its rudimentary graphics and lack of comprehensive information impede user engagement.Notably, there was no correlation observed between MARS scores and app ratings in the iOS and Google Play Stores.Detailed information regarding the apps evaluated using MARS is provided in The Intraclass correlation coefficient (ICC) (2,1) calculated across all applications indicated good reliability values (ICC = 0.791, 95% C.I. [0.583, 0.901]).ICC estimates and their 95% confidence intervals (95% C.I.) were computed for 20 Play Store apps and 5 iOS apps using the SPSS statistical package version 29 (SPSS Inc., Chicago, IL, USA), based on a mean rating (k = 2), absolute agreement, two-way random effect model or ICC (2,1).ICC values were interpreted as follows: poor if smaller than 0.50, fair for values between 0.50 and 0.75, good between 0.75 and 0.90, and excellent above 0.90 (2,1).

Discussion
Currently, smartphone applications are increasingly employed in managing various health conditions, including chronic illnesses and post-surgical recovery, with several demonstrating efficacy in enhancing investigated outcomes and treatment adherence [25,26].
Notably, while not explicitly endorsed in recent guidelines [27,28], mobile applications hold promise in advancing the landscape of low back pain (LBP) rehabilitation when juxtaposed with alternative musculoskeletal modalities [29].The diffuse presence of smartphones represents significant strides in the self-management of musculoskeletal disorders, in which these applications can operate autonomously or complementarily with live sessions to bolster treatment adherence.Noteworthy efforts have been made to assess the content quality of such applications, albeit predominantly within international contexts [20,22,23].Our review is focused on assessing free mobile applications without in-app purchases to ensure their suitability for integration into clinical practice, particularly in resource-constrained settings where more expensive self-management systems may not be feasible.
Among the primary studies analyzed, only the Kaia app is accessible to download for the general population on IOS or Play store in the Italian market.However, it was not evaluated through MARS because it was not free.
For the purpose of assessment using the MARS scale, we identified 25 apps on the IOS and Play Stores that met our predetermined inclusion criteria.Overall, the analyzed apps demonstrate below-average quality (see Table A3).Many of these apps received the highest scores in the "functionality" subcategory (SM = 3.76).This suggests that most apps prioritize operational aspects without due consideration for features that could enhance user engagement and relevance to a broader user base.Conversely, the lowest scores were observed in the "information" subcategory.High-quality information within the app is crucial for ensuring safe usage.While it is imperative to investigate the effectiveness of interventions facilitated by each specific mobile app, such studies are rarely undertaken.In our evaluation, a majority of the apps employed information and education as their intervention strategy, followed by advice, strategies, and skills training.The predominant technical feature used to support these strategies was sending reminders.However, in many instances, the proposed interventions lacked clear references, raising questions about the reliability of app usage.In addition, evaluation through MARS showed that most of the apps incorporated only exercise programs, neglecting education to support knowledge and self-care strategies.Indeed, the use of low-quality information does not reflect what is stated in the most recent guidelines on the management of low back pain [28], limiting its dissemination and use in the management of these patients.Notably, no scientific evidence was found to substantiate the efficacy of any of the apps included in this study; rather, all apps appeared to be commercially driven.Lastly, none of the downloadable apps included in the study have ever been tested in clinical efficacy studies.
MARS sections on engagement and aesthetics highlight that most of the included apps pay little attention to aspects of design and user engagement; this can be a major barrier to app usage adherence.
The studies analyzed in our review show that app-based self-management strategies could be effective in reducing pain in low back pain patients; these findings align with previous reviews conducted on mHealth applications focused on pain management [20,21,26].Ensuring the safety of apps intended for healthcare purposes remains a paramount concern for clinicians.Proper prescription and usage necessitate clear guidance on activities and exercises suitable for independent home-based practice versus those requiring supervised implementation.Ultimately, our study underscores that the quality of freely available apps in Italy generally falls below that of paid apps reported in other investigations [23].

Study Limitations
Firstly, it is important to acknowledge the potential for selection bias in the literature screening process of this review.Studies that did not explicitly mention a smartphone appbased intervention in the title or abstract were excluded.Additionally, our search focused solely on interventions utilizing smartphone apps in isolation, excluding those employing combined interventions, commonly referred to as "blended" approaches.Moreover, the generalizability of the findings may be limited due to several factors.Some studies with large sample sizes failed to report the duration or type of pain (acute, subacute, or chronic), which could impact the interpretation of results.Additionally, the absence of data regarding patients' acceptance of mHealth apps for LBP self-management, as well as details regarding the intensity and frequency of app usage, further restricts the generalizability of our findings.Furthermore, it is worth noting a significant limitation in the assessment using MARS, as highlighted in a study on mHealth Apps conducted in the German language [30].These apps are primarily judged based on acceptable or good quality, despite recent findings indicating otherwise [31].A review revealed that the quality of self-management tools for low back pain (LBP) was notably lacking.Despite the high reliability reported [9], it is essential to acknowledge the inherent subjectivity in reviewer assessments, which may have influenced the assigned scores.Consequently, caution is warranted when interpreting the results outlined in this review.Furthermore, it is conceivable that the features of the applications discussed here may differ from those of updated versions available in app stores at the time of publication.This dynamic nature of application development inevitably introduces a degree of uncertainty.
Indeed, while the decision to exclusively evaluate free apps offers potential advantages for the practical application of clinical findings, it may inadvertently alter the presentation of results in this review.The great range of paid apps available today could either confirm or challenge the findings of this study.The discussion surrounding the cost-effectiveness of paid apps remains ambiguous, as noted in the Lewkowicz et al. investigation [32].Conversely, free apps may represent an avenue to foster a culture of self-management, particularly in regions with developing healthcare infrastructures [33].

Future Study Recommendations
There is a clear need for larger scale RCTs examining the impact of smartphone apps on self-management of LBP, particularly with comparative treatments.Furthermore, the duration of interventions varies across studies, ranging from 6 to 12 weeks.As a result, drawing definitive conclusions regarding the long-term efficacy of mHealth apps for LBP self-management remains challenging, and their suitability for specific types of pain warrants further exploration.Thus, longer follow-up periods (>12 weeks) are essential to assess both the sustained effects and any clinically significant changes over time.
Given the current lack of evidence-based insights, increased support from scientific and academic institutions in the development of such mHealth solutions could encourage the development of higher quality and more clinically relevant apps.Moreover, based on our findings, we advocate for the formulation of guidelines to inform the development of new apps, with an emphasis on integrating clinical assessment and follow-up functionalities within the apps themselves.There was an increase in the disability score (6.08 vs. 7.5; p = 0.01).No significant differences between the groups or sessions were found in PPTs

Figure 1 .
Figure 1.Process selection of the study.

Figure 2 .
Figure 2. Process selection of the apps.

Figure 2 .
Figure 2. Process selection of the apps.

Table A1 .
Characteristics of the studies.

Table A2 .
Characteristics of the studies (review).

Table A3 .
Characteristics of the Apps.