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NFTs are blockchain-based digital and physical assets traded on digital marketplaces. Current and exploratory NFT use cases include art, collectibles, in-game items, real estate, ticketing, events, fintech, licenses, IDs, and healthcare. NFT marketplaces, online games, virtual worlds, and open-source coding platforms use NFTs to incentivize participation. In trials, where the effectiveness of financial remuneration to increase trial participation is unclear, NFTs could encourage involvement. Considering the increasing opportunities for blockchain technology and NFT use in both the economy and society, we present a pilot study protocol to gauge the interest and feasibility of using NFTs as payment for trial participants, the first of its kind to our knowledge. Additionally, as the global population ages and chronic diseases become more prevalent, innovative solutions to sustain engagement in longevity-focused interventions are needed. Harnessing CURATE.AI, an indication-agnostic artificial intelligence (AI) platform that modulates the intensity of interventions to generate truly personalized profiles - or digital avatars, we will develop N-of-1 learning trajectory profiles for fifteen healthy volunteers trained on the CURATE.DTx, a digital therapeutic (DTx) platform. The profiles will be artistically modified and minted for the participants in the Ethereum blockchain, whereafter the recipient can choose to keep, display, or trade their NFT. Through interviews, we will evaluate the interest and acceptability of NFTs as an incentive for trial participation. This pioneering exploration connects AI-driven personalized medicine with inventive blockchain solutions. Our research aims to advance the field of digital therapeutics and pave the way for novel approaches to patient-centered care and incentivization strategies in clinical trials.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Avatar.DTx | Experimental | DTx sessions: participants will interact with the DTx twelve minutes per day, three days per week, for ten weeks. We will obtain a personalized profile for each participant (relationship between training intensity and participant's performance). A digital artist will receive the profiles without personal or medical data and create fifteen unique artworks. The team, who will mint the artworks as NFTs on Ethereum and send them to the participants' digital wallets (or help them to set one up). The NFTs will be displayed on OpenSea. If the Ethereum blockchain stops its activity within two years of the NFT minting, the team will mint a new NFT for each participant in an alternative blockchain and compensate them with SGD150. After the last DTx session (regardless of study completion by the participant), a 60-minute interview will be conducted. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| CURATE.DTx sessions | Device | Participants will interact with CURATE.DTx twelve minutes per day, three days a week, for ten weeks. CURATE.DTx is a cognitive training DTx developed by our research team in The N.1 Institute for Health (N.1) and The Institute for Digital Medicine (WisDM). CURATE.DTx is comprised of CURATE.AI and a modified version of the Multi-Attribute Task Battery (MATB), Online MATB. CURATE.AI is a small data AI-derived platform that can dynamically personalize treatment by modulating drug dose or therapy intensity. We previously implemented CURATE.AI into Online MATB - the modernized, online version of MATB, a flight deck simulator program developed by NASA and the United States Air Force. |
| Measure | Description | Time Frame |
|---|---|---|
| Interest and Acceptability of Personalized NFTs as Incentives | Evaluated through semi-structured interviews conducted at the end of the study. | At week 11 into the trial (after the participant's last completed DTx session). |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xavier Tadeo, PhD | Contact | +65 6601 7766 | lsixtc@nus.edu.sg | |
| Peter Wang, PhD | Contact | +65 6601 7766 | lsipww@nus.edu.sg |
| Name | Affiliation | Role |
|---|---|---|
| Dean Ho, PhD | The Institute for Digital Medicine (WisDM) | Principal Investigator |
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| ID | Term |
|---|---|
| D010358 | Patient Participation |
| ID | Term |
|---|---|
| D010342 | Patient Acceptance of Health Care |
| D000074822 | Treatment Adherence and Compliance |
| D015438 | Health Behavior |
| D001519 | Behavior |
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| ID | Term |
|---|---|
| D007407 | Interviews as Topic |
| ID | Term |
|---|---|
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D017531 | Health Care Evaluation Mechanisms |
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| Interview | Behavioral | After the last DTx session (regardless of study completion by the participant), a 60-minute interview session will be conducted by a team member, either at the Institute for Digital Medicine (WisDM) in person or via Zoom. All responses will be audio-recorded and transcribed verbatim. We will use thematic analysis of anonymized transcripts to identify emerging or recurring themes. Data will be analyzed using NVivo. The analysis will begin with open/primary coding, where we will descriptively label data. Subsequently, we will group the labels into categories based on literature (i.e., secondary coding). These categories will then help create broader themes/assertions. |
|
| D011787 | Quality of Health Care |
| D017530 | Health Care Quality, Access, and Evaluation |
| D011634 | Public Health |
| D004778 | Environment and Public Health |