ArticleJMIR mHealth and uHealth2018
Implementing Systematically Collected User Feedback to Increase User Retention in a Mobile App for Self-Management of Low Back Pain: Retrospective Cohort Study.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis.JMIR mHealth and uHealth · 2022Pooled it
- Article
- User Experience and Extended Technology Acceptance Model in Commercial Health Care App Usage Among Patients With Cancer: Mixed Methods Study.Journal of medical Internet research · 2024Article
- Mobile Health Fitness Interventions: Impact of Features on Routine Use and Data Sharing Acceptability.JACC. Advances · 2023Article
- mHealth Apps for Low Back Pain Self-management: Scoping Review.JMIR mHealth and uHealth · 2022Article
- Digitally Delivered Exercise and Education Treatment Program for Low Back Pain: Longitudinal Observational Cohort Study.JMIR rehabilitation and assistive technologies · 2022Article
- A Yoga Exercise App Designed for Patients With Axial Spondylarthritis: Development and User Experience Study.JMIR formative research · 2022Article
- The burden of incontinence in a real-world data environment-insights from a digital patient companion.International urogynecology journal · 2022Article
- Smartphone applications are used for self-management, telerehabilitation, evaluation and data collection in low back pain healthcare: a scoping review.F1000Research · 2022Article
- Digital Therapeutic Care and Decision Support Interventions for People With Low Back Pain: Systematic Review.JMIR rehabilitation and assistive technologies · 2021Review
- Digital therapeutics in pain medicine.The Korean journal of pain · 2021Article
- Assessing User Retention of a Mobile App: Survival Analysis.JMIR mHealth and uHealth · 2020Article
- Mobile Application-Based Interventions for Chronic Pain Patients: A Systematic Review and Meta-Analysis of Effectiveness.Journal of clinical medicine · 2020Review
- Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2020Review
- Less Pain, Better Sleep? The Effect of a Multidisciplinary Back Pain App on Sleep Quality in Individuals Suffering from Back Pain - a Secondary Analysis of App User Data.Journal of pain research · 2020Article
- App-based multidisciplinary back pain treatment versus combined physiotherapy plus online education: a randomized controlled trial.NPJ digital medicine · 2019Article
- Digital therapeutics-based lumbar core exercise for patients with low back pain: A prospective exploratory pilot study.Digital healthArticle
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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