In one paragraphArticle in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from itWhat 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.
2 · The registryThe 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.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
19 authors.
Xavier TadeoInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0003-0356-826X Gyula SeresInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0003-4254-0198 Peter WangInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0002-4925-1738 Yoann SapanelInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0001-6797-7850 Alexandria RemusInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0001-9002-7933 Jasmine L EyalInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0009-0000-6100-5938 Jason Kai-Wei LeeInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.
Simon ChestermanFaculty of Law, National University of Singapore, Singapore.
Christopher L AsplundInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.
Benjamin C K TeeThe N.1 Institute for Health (N.1), National University of Singapore, Singapore, Singapore.
Reza ShokriDepartment of Computer Science, School of Computing, National University of Singapore, Singapore.
Marlena RaczkowskaInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0003-1208-8751 Li Ming ChongInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0002-3742-2704 Siong Peng KwekInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0009-0000-0206-2246 Agata BlasiakInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.
Dean HoInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR, Singapore, SG.01, 117456, Singapore, 65 66017766.ORCID http://orcid.org/0000-0002-7337-296X Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
Unlabelled: Incentivization in clinical trial participation can be challenging, with many studies failing to meet recruitment or retention goals despite traditional compensation strategies. Digital health evolves, and with it, new approaches can emerge to engage participants meaningfully. We propose unique digital images as a novel, symbolic incentive for clinical trials. Digital images combine qualities such as personalization, ownership, and digital visibility, which may drive engagement more effectively than monetary rewards alone. In our illustrative study, participants complete artificial intelligence-personalized digital therapeutics training using CURATE.DTx, generating individualized learning trajectories. These are transformed into digital artworks and minted as nonfungible tokens given as a reward upon trial completion. This concept integrates gamification, personalization, and blockchain technology to support both intrinsic and extrinsic motivation. We explore the implications for decentralized health care, long-term behavior change, and participant recognition in the context of preventive medicine and longevity science. Our aim is to encourage research into the use of digital incentives to transform the trial participant experience and promote sustained engagement in health interventions.
Indexed as
Clinical Trials as TopicMotivationArtificial IntelligenceDigital HealthDigital MediaHumansAIartificial intelligencebehavior changeclinical trial engagementdecentralized health caredigital healthNFTnonfungible tokensparticipant incentives
Identifiers
PMID42258364
PMCPMC13245546
What OpenQuestion holds
Textmetadata
LicenceCC BY
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