Background Low back pain (LBP) is the leading cause of worldwide years lost because of disability, with a tremendous economic burden for health care systems. Digital therapeutic care (DTC) programs provide a scalable, universally accessible, and low-cost approach to the multidisciplinary treatment of LBP. Moreover, novel decision support interventions such as personalized feedback messages, push notifications, and data-driven activity recommendations amplify DTC by guiding the user through the program while aiming to increase overall engagement and sustainable behavior change. Objective This systematic review aims to synthesize recent scientific literature on the impact of DTC apps for people with LBP and outline the implementation of add-on decision support interventions, including their effect on user retention and attrition rates. Methods We searched bibliographic databases, including MEDLINE, Cochrane Library, Web of Science, and the Physiotherapy Evidence Database, from March 1, 2016, to October 15, 2020, in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted this review based on related previously published systematic reviews. Besides randomized controlled trials (RCTs), we also included study designs with the evidence level of at least a retrospective comparative study. This enables the consideration of real-world user-generated data and provides information regarding the adoption and effectiveness of DTC apps in a real-life setting. For the appraisal of the risk of bias, we used the Risk of Bias 2 Tool and the Risk of Bias in Non-Randomized Studies of Interventions Tool for the RCTs and nonrandomized trials, respectively. The included studies were narratively synthesized regarding primary and secondary outcome measures, DTC components, applied decision support interventions, user retention, and attrition rates. Results We retrieved 1388 citations, of which 12 studies are included in this review. Of the 12 studies, 6 (50%) were RCTs and 6 (50%) were nonrandomized trials. In all included studies, lower pain levels and increased functionality compared with baseline values were observed in the DTC intervention group. A between-group comparison revealed significant improvements in pain and functionality levels in 67% (4/6) of the RCTs. The study population was mostly homogeneous, with predominantly female, young to middle-aged participants of normal to moderate weight. The methodological quality assessment revealed moderate to high risks of biases, especially in the nonrandomized trials. Conclusions This systematic review demonstrates the benefits of DTC for people with LBP. There is also evidence that decision support interventions benefit overall engagement with the app and increase participants’ ability to self-manage their recovery process. Finally, including retrospective evaluation studies of real-world user-generated data in future systematic reviews of digital health intervention trials can reveal new insights into the benefits, challenges, and real-life adoption of DTC programs.

N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available. Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app. With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials. The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health. Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner. We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice.

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The Smart4Health (S4H) software application will enable European Union (EU) citizens to manage, analyse, and exchange their aggregated electronic health data. This citizen-centred EU electronic health record (EHR) exchange approach for personalised health services will be the first step for the provision of citizen-centred solutions and services in a digital single market for wellbeing and healthcare. Establishing interoperability between the diverse EU EHR data and citizen-generated health data is mandatory to guarantee adequate usability, reliability, and trust of the service. The Connecting Europe Facility (CEF) building blocks address/fulfil such aspects while complying with EU regulations. Here we demonstrate the current status and applicability of the CEF building blocks in the digital health environment for the envisioned S4H software application. The major findings and success stories resulted from the S4H Project are as follows: (1) a secure and user-friendly eID service for the EU-wide Smart4Health community was successfully integrated into the Smart4Health platform, whereby 7 out of the 13 supported EU Member States are already connected, (2) the eTranslation service was compared to other popular alternatives on the market with the result that eTranslation is a secure and valid tool to address multi-language challenges and (3) we identified several use cases for which Smart4Health can benefit from the usage of CEF building blocks, including the improvement of data quality and increase of trust in data sharing.