ArticleDigital health
Digital health interventions use cases: Classification and taxonomy development, a scoping review.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Use of Waivers of Guardian Permission in the United States for Pediatric Digital Health Intervention Research Since 2020: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Feasibility and preliminary effects of mhealth supportive care interventions in adults with myeloid neoplasms: a systematic review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Exploring complex of digital health interventions (DHI), use cases, and applications in healthcare. Applications include integrated care architectures, mobile health, clinical decision support systems, and risk stratification. Thematic analysis aims to provide context for assurance methodologies aligned to DHIs. Use cases, patient outcomes, stakeholders, digital health technologies utilized, and the relationships will be established as a taxonomy. Methods: Design - Scoping Review using PRISMA methodology, Data Sources from Engineering Village (Compendex and Inspec), PubMed, and OVID Embase (2019-2024). We introduce categories of DHIs and use cases. Records only relevant to the research question were included. We were interested in ontologies recorded in literature; screening was performed by independent reviewer(s). A further review was completed after this initial screening. Results: Studies provide insight into the classification of DHIs, extending from workflow design, relationship analysis between common themes, and behavioural change intervention in mobile applications. The 41 included studies revealed four primary use case categories: diagnosis ( Conclusions: This method of hazard assessment, analysis and use of ontologies (DHI and HSC) improves the justification of safety claims and evidence articulation. DHI's incorporation of AI and other innovative technologies enhances the effectiveness of interventions. The operational aspects of implementing DHIs require consideration of the intended purpose, as well as a lack of experience or understanding of potential complex clinical decision support systems. We provide a classification of DHIs, extended from workflow design and behavioral change intervention, including use cases, resulting in a taxonomy of digital health technologies.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.