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      Medical App Treatment of Non-Specific Low Back Pain in the 12-month Cluster-Randomized Controlled Trial Rise-uP: Where Clinical Superiority Meets Cost Savings

      case-report

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          Abstract

          Purpose

          Non-specific low back pain (NLBP) exerts a profound impact on global health and economics. In the era of Web 3.0, digital therapeutics offer the potential to improve NLBP management. The Rise-uP trial introduces a digitally anchored, general practitioner (GP)-focused back pain management approach with the Kaia back pain app as the key intervention. Here, we present the 12-months evaluation of the Rise-uP trial including clinical and economic outcomes, patient satisfaction and behavioral tracking analysis.

          Methods

          The cluster-randomized controlled study (registration number: DRKS00015048) enrolled 1237 patients, with 930 receiving treatment according to the Rise-uP approach and 307 subjected to standard of care treatment. Assessments of pain, psychological state, functional capacity, and well-being (patient-reported outcome measures; PROMs) were collected at baseline, and at 3-, 6-, and 12-months follow-up intervals. Health insurance partners AOK, DAK, and BARMER provided individual healthcare cost data. An artificial intelligence (AI)-driven behavioral tracking analysis identified distinct app usage clusters that presented all with about the same clinical outcome. Patient satisfaction (patient-reported experience measures; PREMs) was captured at the end of the trial.

          Results

          Intention-to-treat (ITT) analysis demonstrated that the Rise-uP group experienced significantly greater pain reduction at 12 months compared to the control group (IG: −46% vs CG: −24%; p < 0.001) with only the Rise-uP group achieving a pain reduction that was clinically meaningful. Improvements in all other PROMs were notably superior in patients of the Rise-uP group. The AI analysis of app usage discerned four usage clusters. Short- to long-term usage, all produced about the same level of pain reduction. Cost-effectiveness analysis indicated a substantial economic benefit for Rise-uP.

          Conclusion

          The Rise-uP approach with a medical multimodal back pain app as the central element of digital treatment demonstrates both, clinical and economic superiority compared to standard of care in the management of NLBP.

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          Most cited references52

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          User Acceptance of Information Technology: Toward a Unified View

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            The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories

            The psychometric properties of the Depression Anxiety Stress Scales (DASS) were evaluated in a normal sample of N = 717 who were also administered the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI). The DASS was shown to possess satisfactory psychometric properties, and the factor structure was substantiated both by exploratory and confirmatory factor analysis. In comparison to the BDI and BAI, the DASS scales showed greater separation in factor loadings. The DASS Anxiety scale correlated 0.81 with the BAI, and the DASS Depression scale correlated 0.74 with the BDI. Factor analyses suggested that the BDI differs from the DASS Depression scale primarily in that the BDI includes items such as weight loss, insomnia, somatic preoccupation and irritability, which fail to discriminate between depression and other affective states. The factor structure of the combined BDI and BAI items was virtually identical to that reported by Beck for a sample of diagnosed depressed and anxious patients, supporting the view that these clinical states are more severe expressions of the same states that may be discerned in normals. Implications of the results for the conceptualisation of depression, anxiety and tension/stress are considered, and the utility of the DASS scales in discriminating between these constructs is discussed.
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              A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies

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                Author and article information

                Journal
                J Pain Res
                J Pain Res
                jpr
                Journal of Pain Research
                Dove
                1178-7090
                26 June 2024
                2024
                : 17
                : 2239-2255
                Affiliations
                [1 ]Center of Interdisciplinary Pain Medicine, Department of Neurology, Klinikum Rechts der Isar, Technical University of Munich (TUM) , Munich, Germany
                [2 ]Institute for Applied Health Services Research, Inav GmbH , Berlin, Germany
                [3 ]Bayerische TelemedAllianz, Ingolstadt , Baar-Ebenhausen, Germany
                [4 ]Pain Clinic, Algesiologikum Pain Center , Munich, Germany
                [5 ]StatConsult GmbH Magdeburg , Magdeburg, Germany
                [6 ]Department of Health Economics, Faculty of Sports and Health Sciences, Technical University of Munich (TUM) , Munich, Germany
                Author notes
                Correspondence: Thomas R Toelle, Center of Interdisciplinary Pain Medicine, Department of Neurology, Klinikum rechts der Isar, Technical University of Munich (TUM) , Ismaninger Str. 22, Munich, 81675, Germany, Tel +49-89-4140-4613, Email thomas.toelle@tum.de
                Author information
                http://orcid.org/0009-0001-5943-0596
                Article
                473250
                10.2147/JPR.S473250
                11215667
                38952994
                3cf56474-c152-4934-b655-b77d163a2c1e
                © 2024 Priebe et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 17 April 2024
                : 19 June 2024
                Page count
                Figures: 6, Tables: 7, References: 52, Pages: 17
                Categories
                Clinical Trial Report

                Anesthesiology & Pain management
                digital medicine,medical apps,non-specific low back pain,multimodal pain therapy,healthcare costs,behavioral tracking analysis

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