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      Adhärenz digitaler Interventionen im Gesundheitswesen: Definitionen, Methoden und offene Fragen Translated title: Adherence to digital health interventions: definitions, methods, and open questions

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          Abstract

          Viele digitale Interventionen sind auf die Mitwirkung ihrer Nutzer*innen angewiesen, damit sie eine positive Wirkung erzielen können. In verschiedenen Bereichen ist zu beobachten, dass die Anwendung digitaler Interventionen durch Nutzer*innen oftmals nach einer kurzen Zeit reduziert oder in Gänze eingestellt wird. Dies wird als einer der wesentlichen Faktoren angesehen, der die Wirksamkeit digitaler Interventionen einschränken kann. In diesem Zusammenhang gewinnt das Konzept der Adhärenz (Einhalten therapeutischer Vorgaben) bei digitalen Interventionen zunehmend an Bedeutung. Definiert wird Adhärenz bei digitalen Interventionen etwa als „the degree to which the user followed the program as it was designed“ („Ausmaß, in dem die Nutzer*innen die Software so verwenden, wie sie konzipiert wurde“). Dies wird auch oftmals mit „intended use“ oder „use as it is designed“ umschrieben („bestimmungsgemäße Verwendung“ bzw. „Verwendung, wie es konzipiert wurde“). Jedoch finden sowohl die theoretisch-konzeptionelle als auch die praktische Auseinandersetzung hinsichtlich der Adhärenz bei digitalen Interventionen noch eine zu geringe Berücksichtigung in der Forschung.

          Ziel dieses narrativen Übersichtsartikels ist es, das Konzept der Adhärenz bei digitalen Interventionen näher zu beleuchten und von verwandten Konzepten abzugrenzen. Zudem wird diskutiert, mit welchen Methoden und Messgrößen die Adhärenz operationalisiert werden kann und welche Prädiktoren die Adhärenz positiv beeinflussen. Weiterhin wird auf die Dosis-Wirkungs-Beziehung bei der Anwendung digitaler Interventionen eingegangen und auf Faktoren, die die Adhärenz positiv beeinflussen können. Abgeschlossen wird mit einer ethischen Betrachtung der Thematik.

          Translated abstract

          Many digital interventions rely on the participation of their users to have a positive impact. In various areas it can be observed that the use of digital interventions is often reduced or fully discontinued by the users after a short period of time. This is seen as one of the main factors that can limit the effectiveness of digital interventions. In this context, the concept of adherence to digital interventions is becoming increasingly important. Adherence to digital interventions is roughly defined as “the degree to which the user followed the program as it was designed,” which can also be paraphrased as “intended use” or “use as it is designed.” However, both the theoretical–conceptual and practical discussions regarding adherence to digital interventions still receive too little attention.

          The aim of this narrative review article is to shed more light on the concept of adherence to digital interventions and to distinguish it from related concepts. It also discusses the methods and metrics that can be used to operationalize adherence and the predictors that positively influence adherence. Finally, needs for action to better address adherence are considered critically.

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          Persuasive System Design Does Matter: A Systematic Review of Adherence to Web-Based Interventions

          Background Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed. Technology as a means to communicate the content in web-based interventions has been neglected in research. Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content. In this paper we examine technology from a holistic perspective. We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence. Objective This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention. Methods We conducted a systematic review of studies into web-based health interventions. Per intervention, intervention characteristics, persuasive technology elements and adherence were coded. We performed a multiple regression analysis to investigate whether these variables could predict adherence. Results We included 101 articles on 83 interventions. The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention. Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 2.9 out of a possible 7.0). Dialogue support and social support are less commonly employed (mean 1.5 and 1.2 out of a possible 7.0, respectively). When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = .004), setup (p < .001), updates (p < .001), frequency of interaction with a counselor (p < .001), the system (p = .003) and peers (p = .017), duration (F = 6.068, p = .004), adherence (F = 4.833, p = .010) and the number of primary task support elements (F = 5.631, p = .005). Our final regression model explained 55% of the variance in adherence. In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence. Conclusions Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained. Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence. Rather, the differences in technology and interaction predict adherence. The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adhere.
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            The Law of Attrition

            In an ongoing effort of this Journal to develop and further the theories, models, and best practices around eHealth research, this paper argues for the need for a “science of attrition”, that is, a need to develop models for discontinuation of eHealth applications and the related phenomenon of participants dropping out of eHealth trials. What I call “law of attrition” here is the observation that in any eHealth trial a substantial proportion of users drop out before completion or stop using the appplication. This feature of eHealth trials is a distinct characteristic compared to, for example, drug trials. The traditional clinical trial and evidence-based medicine paradigm stipulates that high dropout rates make trials less believable. Consequently eHealth researchers tend to gloss over high dropout rates, or not to publish their study results at all, as they see their studies as failures. However, for many eHealth trials, in particular those conducted on the Internet and in particular with self-help applications, high dropout rates may be a natural and typical feature. Usage metrics and determinants of attrition should be highlighted, measured, analyzed, and discussed. This also includes analyzing and reporting the characteristics of the subpopulation for which the application eventually “works”, ie, those who stay in the trial and use it. For the question of what works and what does not, such attrition measures are as important to report as pure efficacy measures from intention-to-treat (ITT) analyses. In cases of high dropout rates efficacy measures underestimate the impact of an application on a population which continues to use it. Methods of analyzing attrition curves can be drawn from survival analysis methods, eg, the Kaplan-Meier analysis and proportional hazards regression analysis (Cox model). Measures to be reported include the relative risk of dropping out or of stopping the use of an application, as well as a “usage half-life”, and models reporting demographic and other factors predicting usage discontinuation in a population. Differential dropout or usage rates between two interventions could be a standard metric for the “usability efficacy” of a system. A “run-in and withdrawal” trial design is suggested as a methodological innovation for Internet-based trials with a high number of initial dropouts/nonusers and a stable group of hardcore users.
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              Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis

              “Engagement” with digital behaviour change interventions (DBCIs) is considered important for their effectiveness. Evaluating engagement is therefore a priority; however, a shared understanding of how to usefully conceptualise engagement is lacking. This review aimed to synthesise literature on engagement to identify key conceptualisations and to develop an integrative conceptual framework involving potential direct and indirect influences on engagement and relationships between engagement and intervention effectiveness. Four electronic databases (Ovid MEDLINE, PsycINFO, ISI Web of Knowledge, ScienceDirect) were searched in November 2015. We identified 117 articles that met the inclusion criteria: studies employing experimental or non-experimental designs with adult participants explicitly or implicitly referring to engagement with DBCIs, digital games or technology. Data were synthesised using principles from critical interpretive synthesis. Engagement with DBCIs is conceptualised in terms of both experiential and behavioural aspects. A conceptual framework is proposed in which engagement with a DBCI is influenced by the DBCI itself (content and delivery), the context (the setting in which the DBCI is used and the population using it) and the behaviour that the DBCI is targeting. The context and “mechanisms of action” may moderate the influence of the DBCI on engagement. Engagement, in turn, moderates the influence of the DBCI on those mechanisms of action. In the research literature, engagement with DBCIs has been conceptualised in terms of both experience and behaviour and sits within a complex system involving the DBCI, the context of use, the mechanisms of action of the DBCI and the target behaviour. Electronic supplementary material The online version of this article (doi:10.1007/s13142-016-0453-1) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                sven.kernebeck@uni-wh.de
                Journal
                Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
                Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
                Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1436-9990
                1437-1588
                24 September 2021
                24 September 2021
                2021
                : 64
                : 10
                : 1278-1284
                Affiliations
                [1 ]GRID grid.412581.b, ISNI 0000 0000 9024 6397, Lehrstuhl für Didaktik und Bildungsforschung im Gesundheitswesen, Fakultät für Gesundheit, , Universität Witten/Herdecke, ; Pferdebachstraße 11, 58448 Witten, Deutschland
                [2 ]GRID grid.5570.7, ISNI 0000 0004 0490 981X, Medizinische Fakultät, Abteilung für Allgemeinmedizin, , Ruhr-Universität Bochum, ; Bochum, Deutschland
                Article
                3415
                10.1007/s00103-021-03415-9
                8492574
                34559252
                167d7c60-2569-438d-9ac8-279593d4c6a1
                © The Author(s) 2021

                Open Access Dieser Artikel wird unter der Creative Commons Namensnennung 4.0 International Lizenz veröffentlicht, welche die Nutzung, Vervielfältigung, Bearbeitung, Verbreitung und Wiedergabe in jeglichem Medium und Format erlaubt, sofern Sie den/die ursprünglichen Autor(en) und die Quelle ordnungsgemäß nennen, einen Link zur Creative Commons Lizenz beifügen und angeben, ob Änderungen vorgenommen wurden.

                Die in diesem Artikel enthaltenen Bilder und sonstiges Drittmaterial unterliegen ebenfalls der genannten Creative Commons Lizenz, sofern sich aus der Abbildungslegende nichts anderes ergibt. Sofern das betreffende Material nicht unter der genannten Creative Commons Lizenz steht und die betreffende Handlung nicht nach gesetzlichen Vorschriften erlaubt ist, ist für die oben aufgeführten Weiterverwendungen des Materials die Einwilligung des jeweiligen Rechteinhabers einzuholen.

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                History
                : 16 December 2020
                : 23 August 2021
                Funding
                Funded by: Private Universität Witten/Herdecke gGmbH (3128)
                Categories
                Leitthema
                Custom metadata
                © Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2021

                adhärenz,digitale interventionen,wirksamkeit,m‑health,e‑health,digitale gesundheitsanwendungen,adherence,digital interventions,effectiveness,digital health apps

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