Self-management Of Low Back Pain Research Articles

Plausibility of Using a Checklist With YouTube to Facilitate the Discovery of Acute Low Back Pain Self-Management Content: Exploratory Study.

BackgroundAccess to guideline-consistent effective care for acute low back pain (ALBP) is generally regarded as limited. Researchers have recognized the potential of YouTube as a clinical and patient education resource that may improve access to appropriate care. However, the heterogeneity of evaluation approaches and variable quality of health information have generally limited the potential of YouTube as a self-management intervention.ObjectiveThis study aims to increase the understanding of ALBP content available on YouTube in 2020 and to establish the plausibility of using a simple checklist to facilitate the discovery of YouTube content consistent with current guidelines. We examined the following 4 research questions: how was the data set defined, what are the metadata characteristics of the videos in the data set, what is the information quality of ALBP YouTube videos, and what are the characteristics of the YouTube data set based on an ALBP self-management checklist?MethodsThis was an exploratory, qualitative infodemiology study. We identified videos in our data set through YouTube search based on popular ALBP-relevant search terms identified through Google Trends for YouTube. We accessed YouTube metadata using the YouTube data tools developed by the University of Amsterdam. We used a modified Brief DISCERN checklist to examine the information quality. We developed a checklist based on the 2018 Lancet Low Back Pain guidelines to examine self-management content.ResultsWe analyzed a data set of 202 YouTube videos authored by chiropractors, physicians, physiotherapists, and instructors of yoga and other disciplines. We identified clear differences in the ALBP videos in our data set based on the authors’ disciplines. We found that the videos authored by each discipline strongly featured a specific intervention domain, that is, education, treatment, or exercise. We also found that videos authored by physicians were consistently coded with the highest ALBP self-management content scores than all other disciplines.ConclusionsThe results returned by YouTube in response to a search for back pain–related content were highly variable. We suggest that a simple checklist may facilitate the discovery of guideline-concordant ALBP self-management content on YouTube. Further research may identify the clinical contexts in which the use of an ALBP checklist with YouTube is feasible.

App-Delivered Self-Management Intervention Trial selfBACK for People With Low Back Pain: Protocol for Implementation and Process Evaluation.

BackgroundImplementation and process evaluation is vital for understanding how interventions function in different settings, including if and why interventions have different effects or do not work at all.ObjectiveThis paper presents the protocol for an implementation and process evaluation embedded in a multicenter randomized controlled trial conducted in Denmark and Norway (the selfBACK project). selfBACK is a data-driven decision support system that provides participants with weekly self-management plans for low back pain. These plans are delivered through a smartphone app and tailored to individual participants by using case-based reasoning methodology. In the trial, we compare selfBACK in addition to usual care with usual care alone.MethodsThe aim of this study is to conduct a convergent mixed-methods implementation and process evaluation of the selfBACK app by following the reach, effectiveness, adoption, implementation, and maintenance framework. We will evaluate the process of implementing selfBACK and investigate how participants use the intervention in daily life. The evaluation will also cover the reach of the intervention, health care provider willingness to adopt it, and participant satisfaction with the intervention. We will gather quantitative measures by questionnaires and measures of data analytics on app use and perform a qualitative exploration of the implementation using semistructured interviews theoretically informed by normalization process theory. Data collection will be conducted between March 2019 and October 2020.ResultsThe trial opened for recruitment in February 2019. This mixed-methods implementation and evaluation study is embedded in the randomized controlled trial and will be collecting data from March 2019 to October 2020; dissemination of trial results is planned thereafter. The results from the process evaluation are expected 2021-2022.ConclusionsThis study will provide a detailed understanding of how self-management of low back pain can be improved and how a digital health intervention can be used as an add-on to usual care to support patients to self-manage their low back pain. We will provide knowledge that can be used to explore the possibilities of extending the generic components of the selfBACK system and key drivers that could be of use in other conditions and diseases where self-management is an essential prevention or treatment strategy.Trial RegistrationClinicalTrials.gov NCT03798288; https://www.clinicaltrials.gov/ct2/show/NCT03798288International Registered Report Identifier (IRRID)DERR1-10.2196/20308

Usability and Acceptability of an App (SELFBACK) to Support Self-Management of Low Back Pain: Mixed Methods Study.

BackgroundSelf-management is the key recommendation for managing nonspecific low back pain (LBP). However, there are well-documented barriers to self-management; therefore, methods of facilitating adherence are required. Smartphone apps are increasingly being used to support self-management of long-term conditions such as LBP.ObjectiveThe aim of this study was to assess the usability and acceptability of the SELFBACK smartphone app, designed to support and facilitate self-management of non-specific LBP. The app provides weekly self-management plans, comprising physical activity, strength and flexibility exercises, and patient education. The plans are tailored to the patient’s characteristics and symptom progress by using case-based reasoning methodology.MethodsThe study was carried out in 2 stages using a mixed-methods approach. All participants undertook surveys, and semistructured telephone interviews were conducted with a subgroup of participants. Stage 1 assessed an app version with only the physical activity component and a web questionnaire that collects information necessary for tailoring the self-management plans. The physical activity component included monitoring of steps recorded by a wristband, goal setting, and a scheme for sending personalized, timely, and motivational notifications to the user’s smartphone. Findings from Stage 1 were used to refine the app and inform further development. Stage 2 investigated an app version that incorporated 3 self-management components (physical activity, exercises, and education). A total of 16 participants (age range 23-71 years) with ongoing or chronic nonspecific LBP were included in Stage 1, and 11 participants (age range 32-56 years) were included in Stage 2.ResultsIn Stage 1, 15 of 16 participants reported that the baseline questionnaire was easy to answer, and 84% (13/16) found the completion time to be acceptable. Overall, participants were positive about the usability of the physical activity component but only 31% (5/16) found the app functions to be well integrated. Of the participants, 90% (14/16) were satisfied with the notifications, and they were perceived as being personalized (12/16, 80%). In Stage 2, all participants reported that the web questionnaire was easy to answer and the completion time acceptable. The physical activity and exercise components were rated useful by 80% (8/10), while 60% (6/10) rated the educational component useful. Overall, participants were satisfied with the usability of the app; however, only 50% (5/10) found the functions to be well integrated, and 20% (2/10) found them to be inconsistent. Overall, 80% (8/10) of participants reported it to be useful for self-management. The interviews largely reinforced the survey findings in both stages.ConclusionsThis study has demonstrated that participants considered the SELFBACK app to be acceptable and usable and that they thought it would be useful for supporting self-management of LBP. However, we identified some limitations and suggestions useful to guide further development of the SELFBACK app and other mobile health interventions.

Supporting self-management of low back pain with an internet intervention in primary care: a protocol for a randomised controlled trial of clinical and cost-effectiveness (SupportBack 2)

IntroductionSelf-management and remaining physically active are first-line recommendations for the care of patients with low back pain (LBP). With a lifetime prevalence of up to 85%, novel approaches to support...

A digital decision support system (selfBACK) for improved self-management of low back pain: a pilot study with 6-week follow-up

BackgroundVery few of the publicly available apps directed towards self-management of low back pain (LBP) have been rigorously tested and their theoretical underpinnings seldom described. The selfBACK app was developed in collaboration with end-users and clinicians and its content is supported by best evidence on self-management of LBP. The objectives of this pilot study were to investigate the basis for recruitment and screening procedures for the subsequent randomized controlled trial (RCT), to test the inclusion process in relation to questionnaires and app installation, and finally to investigate the change in primary outcome over time.MethodsThis single-armed pilot study enrolled 51 participants who had sought help for LBP of any duration from primary care (physiotherapy, chiropractic, or general practice) within the past 8 weeks. Participants were screened for eligibility using the PROMIS-Physical-Function-4a questionnaire. Participants were asked to use the selfBACK app for 6 weeks. The app provided weekly tailored self-management plans targeting physical activity, strength and flexibility exercises, and education. The construction of the self-management plans was achieved using case-based reasoning (CBR) methodology to capture and reuse information from previous successful cases. Participants completed the primary outcome pain-related disability (Roland-Morris Disability Questionnaire [RMDQ]) at baseline and 6-week follow-up along with a range of secondary outcomes. Metrics of app use were collected throughout the intervention period.ResultsFollow-up data at 6 weeks was obtained for 43 participants. The recruitment procedures were feasible, and the number needed to screen was acceptable (i.e., 1.6:1). The screening questionnaire was altered during the pilot study. The inclusion process, answering questionnaires and app installation, were feasible. The primary outcome (RMDQ) improved from 8.6 (SD 5.1) at baseline to 5.9 (SD 4.0) at 6-week follow-up (change score 1.8, 95% CI 0.7 to 2.9). Participants spent on average 134 min (range 0–889 min) using the app during the 6-week period.ConclusionThe recruitment, screening, and inclusion procedures were feasible for the subsequent RCT with a small adjustment. The improvement on the RMDQ from baseline to follow-up was small. Time pattern of app usage varied considerably between the participants.Trial registrationNCT03697759. Registered on August 10, 2018. https://clinicaltrials.gov/ct2/show/NCT03697759

Knowledge, attitude and practice of Lebanese community pharmacists with regard to self-management of low back pain

Purpose: To determine the knowledge, attitude and reported practice of Lebanese community pharmacists who advise persons who present with low back pain.Methods: This was a multi-center cross-sectional study conducted in over 300 community pharmacies across Lebanon from December 2017 to May 2018. Pharmacists working at a community pharmacy were considered eligible, and those who volunteered to participate completed the questionnaire. The questionnaire was designed for self-completion by the pharmacist and included demographic questions about the respondent, questions that assessed knowledge and attitude toward low back pain, and questions about treatment to reflect and characterize the nature of practice. The primary outcome was to determine the knowledge, attitude and reported practice of the Lebanese pharmacists advising people who presented with low back pain. The secondary outcome was to assess factors that affect knowledge, attitude, and practice.Results: The response of 320 community pharmacists was analysed. The proportion of pharmacists with good knowledge about low back pain (51. 7 %) was slightly higher than those with poor knowledge (48. 3 %). Oral therapy was the most prescribed dosage form for back pain compared to local patch and cream. Among oral dosage forms, non-steroidal anti-inflammatory drugs were the most prescribed medications (42 %). Of the patients’ referral to the physician if necessary, 73.1 % of the referrals were by pharmacists.Conclusion: Community pharmacists in Lebanon demonstrate an acceptable level of knowledge of back pain, yet major gaps still exist, particularly in terms of the quality of advice. Hence, more education is needed to provide better quality of advice.
 Keywords: Attitude, Knowledge, Low back pain, Reported practice, Quality of advice

The Kaia Back Pain Intervention for Self-management of Low Back Pain - a Randomized Controlled Study

The Kaia Back Pain Intervention for Self-management of Low Back Pain - a Randomized Controlled Study

Outcome measures used in the smartphone applications for the management of low back pain: a systematic scoping review

Smartphone applications (SPApps) have become a key tool for the self-management of low back pain (LBP). However, the scientific evidence behind the outcome measures used in SPApps for LBP is never investigated before. Therefore, this systematic review firstly assess the quality of the free SPApps for LBP, secondly examines the outcome measures used and thirdly evaluates the outcome measures against the International Classification of Functioning, Disability and Health (ICF) core set classifications for LBP. A systematic scoping review was conducted in the iTunes and Google Play™ on-line stores for LBP SPApps which are free to download. These searches were conducted using keywords suggested by the Cochrane Back and Neck Group. SPApps were screened and downloaded to assess the quality using the Mobile App Rating Scale (MARS). SPApps using outcome measures were reviewed separately to evaluate whether their outcome measures represented any of the ICF components for LBP. The overall quality of the apps has a mean MARS score of 2.5/5. Out of 74 apps reviewed, only four apps had outcome measures that could be linked to ICF components for LBP. Two of the four categories comprising the LBP core set were well represented. The overall quality of the SPApps for LBP is low. Only very few SPApps offer outcome measures to monitor their effectiveness in the management of LBP. There is very limited evidence to show that the outcome measures used in the apps represents all the four core sets of LBP criteria set by ICF.

Self-Management of Low Back Pain Using Neural Network

Low back pain (LBP) is a morbid condition that has afflicted several citizens in Europe. It has negatively impacted the European economy due to several man-days lost, with bed rest and forced inactivity being the usual LBP care and management steps. Direct models, which incorporate various regression analyses, have been executed for the investigation of this premise due to the simplicity of translation. However, such straight models fail to completely consider the impact of association brought about by a mix of nonlinear connections and autonomous factors.In this paper, we discuss a system that aids decision-making regarding the best-suited support system for LBP, allowing the individual to avail of reinforcement and improvement in its self-management. These activities are monitored with the help of a wearable sensor that helps in their detection and their classification as those that soothe or aggravate LBP and hence, should or should not be performed. This system helps the patients set their own boundaries and milestones with respect to suitable activities. This system also does windowing and feature extraction. The present study is an empirical and comparative analysis of the most suitable activities that patients suffering from low back pain can select. The evaluation shows that the system can distinguish between nine common daily activities effectively and helps self-monitor these activities for the effi- cient management of LBP.

Exploring Patients' Experiences of Internet-Based Self-Management Support for Low Back Pain in Primary Care.

ObjectiveWe explored patients’ experiences of using Internet-based self-management support for low back pain (LBP) in primary care, with and without physiotherapist telephone guidance.DesignExploratory descriptive qualitative study using thematic analysis, nested within a randomized feasibility trial.MethodsPatients with LBP who participated in a feasibility trial of the SupportBack Internet intervention (ISRCTN: 31034004) were invited to take part in semistructured telephone interviews after the three-month intervention period (a convenience sample from within the trial population). Fifteen participants took part (age range = 36–87 years, 66.7% female, characteristics representative of the trial population). Data were analyzed thematically.ResultsAnalysis resulted in the development of six themes (subthemes in parentheses): Perceptions of SupportBack’s design (Clarity and ease of use, Variety and range of information provided, Need for specificity and flexibility), Engaging with the SupportBack intervention, Promoting positive thought processes (Reassurance, Awareness of self-management), Managing behavior with SupportBack (Motivation and goal setting, Using activity as a pain management strategy, Preferences for walking or gentle back exercises), Feeling supported by telephone physiotherapists (Provision of reassurances and clarity, Physiotherapists are motivating), Severity and comorbidity as barriers (Preexisting condition or severity acting as a barrier, Less useful for mild low back pain).ConclusionsThe Internet intervention SupportBack appeared to feasibly support self-management of LBP. Reassurance and ongoing support to implement behavioral changes were central to reported benefits. The addition of physiotherapist telephone support further enhanced the patient experience and the potential utility of the intervention.

Does Disordered Sleep Moderate the Relationship Between Pain, Disability and Downstream Health Care Utilization in Patients With Low Back Pain?: A Longitudinal Cohort From the US Military Health System.

Prospective cohort. The purpose of this study was to evaluate the influence of disordered sleep on the relationship between pain and health care utilization (HCU) and pain-related disability and HCU in individuals with low back pain (LBP). Disordered sleep and pain influence LBP outcomes, but their relationship with health care seeking after an episode of LBP has not been investigated and could help identify who is at risk for long-term medical care. This study included patients with LBP participating in a self-management class at a large US military hospital between March 1, 2010 and December 4, 2012. Pain intensity, disability (Oswestry Disability Index), and sleepiness (Epworth Sleepiness Scale) were captured at baseline. Medical visits for a sleep disorder in the 12 months before the class and LBP-related healthcare utilization for the 12 months following the class were abstracted from the Military Health System Data Repository. Separate multivariate analyses evaluating pain intensity and disability as predictors of HCU were developed, with sleepiness and the presence of a sleep disorder as potential moderators. Analyses were adjusted for age, sex, history of back pain, and mental health comorbidities. A total of 757 consecutive participants were included, with 195 (26.8%) diagnosed with a subsequent sleep disorder. Sleepiness was not a significant predictor of HCU. The main effects of disability, pain intensity, and presence of a sleep disorder were significant across all analyses, with higher disability, pain intensity, and presence of a sleep disorder associated with higher predicted visits and costs for LBP. The presence of a sleep disorder was not a significant moderator in any model. Higher pain intensity and disability predicted higher pain-related HCU in the year following a LBP self-management class. The presence of a sleep disorder diagnosis, as recorded in medical records, had a significant independent effect on LBP-related health care visits and costs beyond the influences of pain intensity, disability, and other key demographic and health-related characteristics, but did not moderate these relationships. 3.

Metadata Correction: A Decision Support System to Enhance Self-Management of Low Back Pain: Protocol for the selfBACK Project.

[This corrects the article DOI: 10.2196/resprot.9379.].

Differences in Characteristics and Downstream Drug Use Among Opioid-Naïve and Prior Opioid Users with Low Back Pain.

Recent clinical practice guidelines have suggested conservative treatment approaches, including physical therapy, are indicated as first-line treatment for patients with low back pain (LBP); however, LBP continues to be managed with opioids, despite decreases in function, morbidity, and insignificant improvements in pain. The primary purpose was to compare characteristics and downstream medication use between patients with LBP with prior opioid exposure vs. those who were opioid-naïve. The secondary purpose was to explore the role of prior opioid use by LBP disability. Seven hundred and nine participants in a LBP self-management class were evaluated utilizing self-report data at baseline and longitudinal claims data from the Military Health System Data Repository. Participants were dichotomized into opioid-naïve and prior opioid use groups and then further divided into low and high disability groups based on Oswestry Disability Index (ODI) scores. Patient characteristics, comorbidities, and medication use were compared between groups. Prior opioid users had significantly higher baseline ODI and Fear Avoidance Beliefs Questionnaire physical activity subscale and work subscale scores as well as pre-index instances of mental health disorders, chronic pain, and insomnia than opioid-naïve individuals. Prior opioid users filled significantly more pain medication prescriptions in the year after the index date than did opioid-naïve individuals. Prior opioid users were significantly more likely to be taking opioids at 1year after the index date, regardless of disability level. In patients presenting with LBP, prior opioid exposure appears to be related to increased analgesic use (opioid and non-opioid) and longitudinal analgesic utilization at 1year after the index date.

A Decision Support System to Enhance Self-Management of Low Back Pain: Protocol for the selfBACK Project.

BackgroundLow back pain (LBP) is a leading cause of disability worldwide. Most patients with LBP encountered in primary care settings have nonspecific LBP, that is, pain with an unknown pathoanatomical cause. Self-management in the form of physical activity and strength and flexibility exercises along with patient education constitute the core components of the management of nonspecific LBP. However, the adherence to a self-management program is challenging for most patients, especially without feedback and reinforcement. Here we outline a protocol for the design and implementation of a decision support system (DSS), selfBACK, to be used by patients themselves to promote self-management of LBP.ObjectiveThe main objective of the selfBACK project is to improve self-management of nonspecific LBP to prevent chronicity, recurrence and pain-related disability. This is achieved by utilizing computer technology to develop personalized self-management plans based on individual patient data.MethodsThe decision support is conveyed to patients via a mobile phone app in the form of advice for self-management. Case-based reasoning (CBR), a technology that utilizes knowledge about previous cases along with data about the current patient case, is used to tailor the advice to the current patient, enabling a patient-centered intervention based on what has and has not been successful in previous patient cases. The data source for the CBR system comprises initial patient data collected by a Web-based questionnaire, weekly patient reports (eg, symptom progression), and a physical activity-detecting wristband. The effectiveness of the selfBACK DSS will be evaluated in a multinational, randomized controlled trial (RCT), targeting care-seeking patients with nonspecific LBP. A process evaluation will be carried out as an integral part of the RCT to document the implementation and patient experiences with selfBACK.ResultsThe selfBACK project was launched in January 2016 and will run until the end of 2020. The final version of the selfBACK DSS will be completed in 2018. The RCT will commence in February 2019 with pain-related disability at 3 months as the primary outcome. The trial results will be reported according to the CONSORT statement and the extended CONSORT-EHEALTH checklist. Exploitation of the results will be ongoing throughout the project period based on a business plan developed by the selfBACK consortium. Tailored digital support has been proposed as a promising approach to improve self-management of chronic disease. However, tailoring self-management advice according to the needs, motivation, symptoms, and progress of individual patients is a challenging task. Here we outline a protocol for the design and implementation of a stand-alone DSS based on the CBR technology with the potential to improve self-management of nonspecific LBP.ConclusionsThe selfBACK project will provide learning regarding the implementation and effectiveness of an app-based DSS for patients with nonspecific LBP.Registered Report IdentifierRR1-10.2196/9379

Implementing Systematically Collected User Feedback to Increase User Retention in a Mobile App for Self-Management of Low Back Pain: Retrospective Cohort Study.

BackgroundPromising first results for Kaia, a mobile app digitalizing multidisciplinary rehabilitation for low back pain, were recently published. It remains unclear whether the implementation of user feedback in an updated version of this app leads to desired effects in terms of increased app usage and clinical outcomes.ObjectiveThe aim is to elucidate the effect on user retention and clinical outcomes of an updated version of the Kaia app where user feedback was included during development.MethodsUser feedback of the initial app versions (0.x) was collected in a quality management system and systematically analyzed to define requirements of a new version. For this study, the anonymized data of Kaia users was analyzed retrospectively and users were grouped depending on the available version at the time of the sign-up (0.x vs 1.x). The effect on the duration of activity of users in the app, the number of completed exercises of each type, and user-reported pain levels were compared.ResultsOverall, data of 1251 users fulfilled the inclusion criteria, of which 196 users signed up using version 0.x and 1055 users signed up with version 1.x. There were significant differences in the demographic parameters for both groups. A log-rank test showed no significant differences for the duration of activity in the app between groups (P=.31). Users signing up during availability of the 1.x version completed significantly more exercises of each type in the app (physical exercises: 0.x mean 1.99, SD 1.61 units/week vs 1.x mean 3.15, SD1.72 units/week; P<.001; mindfulness exercises: 0.x mean 1.36, SD 1.43 units/week vs 1.x mean 2.42, SD 1.82 units/week; P<.001; educational content: 0.x mean 1.51, SD 1.42 units/week vs 1.x mean 2.71, SD 1.89 units/week; P<.001). This translated into a stronger decrease in user-reported pain levels in versions 1.x (F1,1233=7.084, P=.008).ConclusionsDespite the limitations of retrospective cohort studies, this study indicates that the implementation of systematically collected user feedback during development of updated versions can contribute to improvements in terms of frequency of use and potentially even clinical endpoints such as pain level. The clinical efficiency of the Kaia app needs to be validated in prospective controlled trials to exclude bias.

Discontinuation of the PACE Plus trial: problems in patient recruitment in general practice

BackgroundThe PACE Plus trial was a multi-center, double-blinded, superiority randomized controlled trial (RCT) conducted in patients from Dutch general practice to investigate the efficacy of paracetamol and NSAIDs in acute non-specific low back pain (LBP). Because insufficient numbers of patients could be recruited (only four out of the required 800 patients could be recruited over a period of 6 months), the trial was prematurely terminated in February 2017, 6 months after the start of recruitment. This article aims to transparently communicate the discontinuation of PACE Plus and to make recommendations for future studies.MethodsGeneral Practitioners (GPs) from 36 participating practices received a one-question survey in which they were asked to give the three most important factors that in their opinion contributed to failure of patient recruitment.ResultsGPs of 33 out of 36 (92%) participating practices sent a response. A total of 81 factors were reported. These have been categorized into patient factors (26 out of 81 comments, 32%), GP factors (39 out of 81 comments, 48%) and research factors (16 out of 81 comments, 20%).DiscussionPatient recruitment in the PACE Plus trial may have failed due to inefficient medication distribution, recruitment of incident rather than prevalent cases, a design that was too complicated, adequate self-management of LBP, patient expectations different from the trial’s scope and lack of time of participating GPs. Substantial differences in design may explain why the preceding PACE trial did manage to successfully complete patient recruitment.ConclusionAlthough the PACE Plus trial was terminated as a result of insufficient patient inclusion, the research questions addressed in this trial remain relevant but unanswered. We hope that lessons learned from the discontinuation of PACE Plus and corresponding recommendations may be helpful in the design of upcoming research projects in LBP in general practice.Trial registrationDutch Trial Registration NTR6089, registered September 14th 2016.

Using an internet intervention to support self-management of low back pain in primary care: findings from a randomised controlled feasibility trial (SupportBack)

ObjectiveTo determine the feasibility of a randomised controlled trial of an internet intervention for low back pain (LBP) using three arms: (1) usual care, (2) usual care plus an internet...

Reducing sedentary behaviour to decrease chronic low back pain: the stand back randomised trial

ObjectiveThe Stand Back study evaluated the feasibility and effects of a multicomponent intervention targeting reduced prolonged sitting and pain self-management in desk workers with chronic low back pain (LBP).MethodsThis randomised...

Treatment of Low Back Pain with a Digital Multidisciplinary Pain Treatment App: Short-Term Results.

BackgroundEven though modern concepts of disease management of unspecific low back pain (LBP) postulate active participation of patients, this strategy is difficult to adapt unless multidisciplinary pain therapy is applied. Recently, mobile health solutions have proven to be effective aides to foster self-management of many diseases.ObjectiveThe objective of this paper was to report on the retrospective short-term results of a digital multidisciplinary pain app for the treatment of LBP.MethodsKaia is a mobile app that digitalizes multidisciplinary pain treatment and is in the market as a medical product class I. For the current study, the data of anonymized Kaia users was retrospectively analyzed. User data were evaluated for 12 weeks regarding duration of use and effect on in-app user reported pain levels, using the numerical rating scale (NRS), depending on whether LBP was classified as acute, subacute, or chronic back pain according to current guidelines.ResultsData of 180 users were available. The mean age of the users was 33.9 years (SD 10.9). Pain levels decreased from baseline NRS 4.8 to 3.75 for all users at the end of the observation period. Users who completed 4, 8, or 12 weeks showed an even more pronounced decrease in pain level NRS (baseline 4.9 [SD 1.7] versus 3.6 [SD 1.5] at 4 weeks; baseline 4.7 [SD 1.8] versus 3.2 [SD [2.0] at 8 weeks; baseline 4.6 [SD 2.2] versus 2.6 [SD 2.0] at 12 weeks). In addition, subgroup analysis of acute, subacute, or chronic classification revealed no significant main effect of group (P>.30) on the reduction of pain. Conclusions: This retrospective study showed that in a pre-selected population of app users, an app digitalizing multidisciplinary rehabilitation for the self-management of LBP reduced user-reported pain levels significantly. The observed effect size was clinically relevant. Ongoing prospective randomized controlled trials (RCTs) will adjust for potential bias and selection effects.ConclusionsThis retrospective study showed that in a pre-selected population of app users, an app digitalizing multidisciplinary rehabilitation for the self-management of LBP reduced user-reported pain levels significantly. The observed effect size was clinically relevant. Ongoing prospective RCTs will adjust for potential bias and selection effects.

SelfBACK, A decision support system for self-management of low back pain, HORIZON2020

selfBACK, A decision support system for self-management of low back pain, HORIZON2020