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Conceptualization, Operationalization, and Measurement of Adherence to Patient-Facing Digital Health Applications: Protocol for a Scoping Review

  • Ludovico Cavallaro
  • , Philipp Graf
  • , Josephine Verona Konrad
  • , Julia Zielke
  • , Jan Zoellick
  • , Danielly de Paula
  • , Ariel Dora Stern

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Medical adherence is traditionally defined as the extent to which a person’s behavior corresponds with agreed recommendations from a healthcare provider. The rapid diffusion of patient-facing digital health applications (DHAs) challenges the direct applicability of this framework to software-mediated interventions. Unlike pharmacological treatments, DHAs automatically generate detailed usage data but lack a broadly accepted standard for which specific data points and usage patterns actually determine ‘adequate’ use across a broad variety of medical indications and population groups. In parallel, DHAs are becoming increasingly embedded in formal regulatory and reimbursement pathways. A notable example is Germany, where recent reforms plan to link at least 20DiGAs), formally regulated and reimbursed DHAs, to performance-related indicators that implicitly operationalize adherence as a determinant of reimbursable performance. Despite this growing policy relevance, adherence in patient-facing DHAs remains conceptually fragmented and methodologically heterogeneous. Objective: This scoping review aims to map how adherence is defined, operationalized, and measured in the context of patient-facing DHAs, and to explore whether these approaches differ between applications embedded within formal regulatory and/or reimbursement frameworks and those operating outside such settings. Methods: This scoping review follows the Joanna Briggs Institute methodology and will be reported in accordance with the PRISMA-ScR guidelines. PubMed (Medline), Scopus, and Web of Science are searched for scientific literature published between 2020 and 2025, inclusive. Machine learning–assisted title and abstract screening will be performed using ASReview, following a sampling-based stopping criterion. Three independent reviewers will conduct screening and data extraction. Relevant grey literature will be identified through targeted searches. Results: Database searches identified 15,403 records (5,469 from PubMed/MEDLINE; 6,198 from Scopus; 3,736 from Web of Science), which were reduced to 7,052 unique records after automated deduplication using Zotero. Title and abstract screening is expected to commence no later than early April 2026. Conclusions: Conducted as part of the DEKODE project funded by the German Federal Joint Committee’s Innovation Fund, this review contributes to the development of a conceptual and empirical adherence framework for patient-facing DHAs. Although DEKODE is primarily oriented toward the German DiGA context, this review applies no geographical restrictions, reflecting the value of establishing a broad evidence base before narrowing the focus to country-specific settings and rendering findings relevant for understanding DHA adherence in all geographies. By clarifying how adherence is currently conceptualized, operationalized, and measured, the review will promote more consistent and context-specific generation and interpretation of adherence-related evidence and support evidence-based policy discussions, international harmonization of evidence standards for DHAs, and health economic evaluations in digital health.
Original languageEnglish
JournalJMIR Research Protocols
Volume15
DOIs
Publication statusPublished - Jul 2026

UCC Futures

  • Artificial Intelligence and Data Analytics

Keywords

  • Digital Innovation

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