ReviewJournal of medical Internet research2023
A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study.
Review in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis 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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI for IMPACTS Framework for Evaluating the Long-Term Real-World Impacts of AI-Powered Clinician Tools: Systematic Review and Narrative Synthesis.Journal of medical Internet research · 2025Pooled it
- Governance for safe and responsible AI in healthcare organisations: a scoping review of frameworks.NPJ digital medicine · 2026Article
- Exploring Body Image Awareness With a Large Language Model-Based Conversational Agent: Qualitative Study With Young Adults.Journal of medical Internet research · 2025Article
- HTA responsiveness to today's challenges to health systems: a responsible innovation in health perspective.International journal of technology assessment in health care · 2025Article
- To What Extent Can Digital Health Technologies Comply With the Principles of Responsible Innovation? Practice-and Policy-Oriented Research Insights Regarding an Organisational and Systemic Issue.International journal of health policy and management · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundClinicians' scope of responsibilities is being steadily transformed by digital health solutions that operate with or without artificial intelligence (DAI solutions). Most tools developed to foster ethical practices lack rigor and do not concurrently capture the health, social, economic, and environmental issues that such solutions raise.
objectiveTo support clinical leadership in this field, we aimed to develop a comprehensive, valid, and reliable tool that measures the responsibility of DAI solutions by adapting the multidimensional and already validated Responsible Innovation in Health Tool.
methodsWe conducted a 3-phase mixed methods study. Relying on a scoping review of available tools, phase 1 (concept mapping) led to a preliminary version of the Responsible DAI solutions Assessment Tool. In phase 2, an international 2-round e-Delphi expert panel rated on a 5-level scale the importance, clarity, and appropriateness of the tool's components. In phase 3, a total of 2 raters independently applied the revised tool to a sample of DAI solutions (n=25), interrater reliability was measured, and final minor changes were made to the tool.
resultsThe mapping process identified a comprehensive set of responsibility premises, screening criteria, and assessment attributes specific to DAI solutions. e-Delphi experts critically assessed these new components and provided comments to increase content validity (n=293), and after round 2, consensus was reached on 85% (22/26) of the items surveyed. Interrater agreement was substantial for a subcriterion and almost perfect for all other criteria and assessment attributes.
conclusionsThe Responsible DAI solutions Assessment Tool offers a comprehensive, valid, and reliable means of assessing the degree of responsibility of DAI solutions in health. As regulation remains limited, this forward-looking tool has the potential to change practice toward more equitable as well as economically and environmentally sustainable digital health care.
Indexed as
Identifiers
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.