ArticleJMIR formative research2025
Public Understanding and Expectations of Digital Health Evidence Generation: Focus Group Study.
Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The rapid proliferation of health apps has not been matched by a comparable growth in scientific evaluations of their effectiveness, particularly for apps available to the public. This gap has prompted ongoing debate about the types of evidence necessary to validate health apps, especially as the perceived risk level varies from wellness tools to diagnostic aids. The perspectives of the general public, who are direct stakeholders, are notably underrepresented in discussions on digital health evidence generation. Objective: This study aimed to explore public understanding and expectations regarding the evidence required to demonstrate health apps' effectiveness, including at varying levels of health risk. Methods: A total of 4 focus group discussions were held with UK residents aged 18 years and older, recruited through targeted advertisements to ensure demographic diversity. Participants discussed their views on evidence requirements for 5 hypothetical health apps, ranging from low-risk wellness apps to high-risk diagnostic tools. Focus groups were moderated using a structured guide, and data were analyzed using reflexive thematic analysis to extract common themes. Results: A total of 5 key themes were established: personal needs, app functionality, social approval, expectations of testing, and authority. Participants relied on personal experiences and social endorsements when judging the effectiveness of low-risk digital health interventions, while making minimal reference to traditional scientific evidence. However, as the perceived risk of an app increased, there was a noticeable shift toward preferring evidence from authoritative sources, such as government or National Health Service endorsements. Conclusions: The public have a preference for evidence that resonates on a personal level, but also show a heightened demand for authoritative guidance as the potential risk of digital health interventions increases. These perspectives should guide developers, regulators, and policy makers as they balance how to achieve innovation, safety, and public trust in the digital health landscape. Engaging the public in evidence-generation processes and ensuring transparency in app functionality and testing can bridge the gap between public expectations and regulatory standards, fostering trust in digital health technologies.
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.