Digital Health LiteracyNCT07881510
Artificial Intelligence and Digital Health Literacies Among Older Adults: A Mixed-method Pilot Intervention Study
A study testing AI and digital health literacy program (E2NGAGE-Literacy) in people with Digital Health Literacy and AI Chatbot, run by National University of Singapore.
Trial summary
The goal of this pilot study is to determine the feasibility and to learn if a training program called E2NGAGE-Literacy (Empowering Elders in Navigating Generative AI for Greater E-health Literacy) can potentially help older adults in Singapore use generative AI (GenAI) chatbots safely and confidently to find and… Read more about this study
- Who is it for?
- Ages 60 years and olderHealthy volunteers can take part
- Conditions the study is for
- Digital Health Literacy, AI Chatbot, Aged 60 Years or Older
- What is being tested?
- AI and digital health literacy program (E2NGAGE-Literacy)
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 60 participants
- Where
- No sites listed yet
- Study dates
- Oct 2026to Jul 2027
- Phase
- Interventional
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 60 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- aged 60 years and above
- has a smartphone
- has limited knowledge and exposure to GenAI and internet usage for health information
- has no cognitive impairment (e.g., screened using the Mini-Cog Test; a score below 3 will be considered a positive screen for possible cognitive impairment or higher risk of dementia)
- willing to participate and be audio-recorded for qualitative interview
Who cannot join
- diagnosed with dementia or cognitive impairment
- have severe visual or hearing impairments that make it challenging to participate in the intervention group sessions
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
The goal of this pilot study is to determine the feasibility and to learn if a training program called E2NGAGE-Literacy (Empowering Elders in Navigating Generative AI for Greater E-health Literacy) can potentially help older adults in Singapore use generative AI (GenAI) chatbots safely and confidently to find and evaluate health information.
The main questions it aims to answer are:
Read more
- Is the conduct of E2NGAGE-Literacy program to improve older adults' AI literacy and digital health literacy feasible?
- Do older adults find the E2NGAGE-Literacy program acceptable?
- What are the potential changes in AI literacy, digital health literacy and actual use of AI-chatbot apps and web-based apps between older adults who receive E2NGAGE-Literacy program and those who do not receive the program?
- What do participants think about E2NGAGE-Literacy, and how can it be improved?
Researchers will compare two groups:
- E2NGAGE-Literacy group: Participants will join a 6-week program with face-to-face group lessons on using GenAI for health information, supported by online videos, quizzes and short homework tasks.
- Waitlist control group: Participants will continue with their usual activities at the senior centres and receive the same program after the study period.
Participants in the E2NGAGE-Literacy group will:
- Join weekly 1.5-hour face-to-face sessions for 6 weeks during the study period
- Watch short videos and complete online quizzes and practice tasks between sessions during the study period
- Be invited to a focus group discussion after the program to share their experiences
- Complete a questionnaire at the start of the study and again at 7 and 12 weeks later
- Be invited to share AI-chatbot transcripts for analysis
Participants in the waitlist group will:
- Complete a questionnaire at the start of the study and again at 7 and 12 weeks later
- Join weekly 1.5-hour face-to-face sessions for 6 weeks after the study period (after week 8)
- Watch short videos and complete online quizzes and practice tasks between sessions after the study period (after week 12)
- Be invited to share AI-chatbot transcripts for analysis
Read the detailed description
Artificial intelligence (AI) is rapidly reshaping how health information is produced, distributed and consumed worldwide. Across healthcare systems and consumer markets, AI-enabled technologies - including large language modelling (LLMs) embedded in search engines, conversational agents (e.g., chatbots), recommender algorithms on social media and automated translation tools - are increasingly integrated into everyday information ecosystems. These global trends increase access to plain-language health information and can offer fast, dialogic, concise and tailored medical knowledge, with potential to close gaps in digital health disparities.
Strengthening AI literacy and digital health literacy among older adults is essential to ensure effective and safe use of online health information. AI literacy is the set of competencies that allows one to effectively interact with AI systems (e.g., generate appropriate prompts), critically evaluate AI-generated responses and leverage them as tools to accomplish tasks proficiently and ethically. Digital health literacy extends these competencies to engaging with digital technologies, including GenAI and web-based searches, in effective, safe and helpful approaches to achieve health goals. Together, these literacies can help older adults better differentiate credible from misleading information, communicate more effectively with healthcare providers using information found online, use digital health platforms with confidence and safety, and reduce harmful self-care practices.
Current research on AI literacy among older adults has focused on understanding their experiences, motivation and preferences in learning AI. Despite calls to prioritise community-based digital literacy programs in public health policies and implementation research, tailored interventions on generative AI education programs among adults remain limited and exploratory. Moreover, existing programs for older adults focus on AI literacy and digital health literacy skills in silos and lack the integration of empowering older adults to leverage and apply AI-mediated information to their individual health context.
Based on the findings of the PI's ongoing trial on a digital health literacy intervention conducted among lower-educated older adults, participants showed great interest in learning the use of AI generative chatbots and gained skills on how to evaluate the credibility of online health information.
This study will pilot E2NGAGE-Literacy to explore its potential benefits in improving AI literacy and digital health literacy among community-dwelling older adults. A mixed methods design will be adopted. Sixty older adults aged 60 years and above with limited prior exposure to GenAI will be recruited from active ageing centres of the Tzu Chi Foundation.
The E2NGAGE-Literacy program will last 6 weeks and include weekly face-to-face group lessons, including online videos, quizzes and brief homework tasks. Weekly topics include, but are not limited to, the basics of GenAI chatbots, writing health-related prompts, critically evaluating AI-generated responses, and applying online health information.
Participants in the intervention group may receive additional support where needed. Participants in the waitlist control group will receive the same program after the study period. A subset of participants in the intervention group will join focus group discussions after the program to share their experiences and provide feedback.
Data will be collected at three timepoints: baseline (pre-test), post-test (week 7) and post-test (week 12) to monitor changes in AI literacy, digital health literacy, use of AI chatbots and web-based apps, and other pre-specified outcomes. Quantitative analyses will use repeated measures approaches, and qualitative data will be analysed thematically. Participants will also be invited to share their AI-chatbot transcripts with the research team for further analysis and qualitative data triangulation.
This pilot study will provide insights into the feasibility, acceptability and preliminary changes of E2NGAGE-Literacy as a potentially scalable, culturally responsive intervention to help older adults in Singapore engage with AI-generated health information safely and confidently.
- Conditions
- Digital Health Literacy, AI Chatbot, Aged 60 Years or Older
- Being tested
- AI and digital health literacy program (E2NGAGE-Literacy)
- Keywords
- digital health literacy, Artificial intelligence literacy, older adults
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI and digital health literacy program (E2NGAGE-Literacy)Behavioural
A 6-week program delivered through weekly 1.5-hour face-to-face group lessons, supported by online videos, quizzes and homework on using generative AI chatbots for health information. The programme will be delivered in English and Chinese. Additional support may be provided if needed.
| Study group | Role | What they receive |
|---|---|---|
| E2NGAGE-Literacy Intervention | Experimental | Participants in this arm will take part in the E2NGAGE-Literacy program during the study period. Receives: Behavioral: AI and digital health literacy program (E2NGAGE-Literacy) |
| Waitlist Control | No intervention | Participants in this arm will continue with the usual activities provided at their active ageing centres during the study period. They will not receive the E2NGAGE-Literacy program during the study period, and will receive the same program after completing the post-intervention questionnaire. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Artificial intelligence literacy
Competency in artificial intelligence (AI) literacy will be measured using the 12-item Artificial Intelligence Literacy Scale (AILS) on a 7-point Likert scale. The AILS includes four domains: awareness (ability to identify and understand AI technology), usage (ability to apply and use AI technology to accomplish tasks proficiently), evaluation (ability to analyse, select and critically evaluate AI applications and their output) and ethics (ability to be aware of the responsibilities and risks associated with the use of AI technology). Internal consistency for the tool is α=0.88, with domains ranging from α=0.73 to 0.78.
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Digital health literacy
Competency in digital health literacy will be measured using the 24-item Digital Health Literacy Instrument 2.0 (DHLI 2.0). The DHLI 2.0 includes eight domains: operational skills, navigation skills, information searching, evaluating reliability, determining relevance, generating content, using security measures, and protecting privacy. Internal consistency for the tool is α=0.94.
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Secondary outcomes (6)
Actual use of AI chatbot apps and web-based apps
Measured using self-reported frequency of use and time spent on web browsers, social media platforms, generative AI chatbots and mobile health applications on participants' smartphones.
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Health information orientation
The 8-item health information orientation scale will be used to measure health information-seeking behaviour style. This five-point Likert scale comprises two domains: information engagement (α=0.66) and information avoidance (α=0.67).
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Motivated learning behaviour
Measured using an adapted 5-item Motivated Learning Behaviour scale on a 5-point Likert scale, assessing the extent to which participants are willing to work hard and persist in learning AI (α=0.92).
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Perceived usefulness of GenAI chatbots
Measured using a 4-item adapted subscale from the Technology Acceptance Model 3 tool (α=0.92).
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Perceived ease of use of GenAI chatbots
Measured using a 4-item adapted subscale from the Technology Acceptance Model 3 tool (α=0.93)
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Trust in health-related information from AI
Measured using a 3-item adapted trust subscale on a 5-point Likert scale (α=0.91)
Measured: Baseline, week 7 (post-test) and week 12 (post-test)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Oct 2026
- Study startOct 2026 (estimated)
- Primary completionMar 2027 (estimated)
- Study completionJul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Digital Health LiteracyStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Waitlist control: no intervention during the study period. They will receive the E2NGAGE-Literacy program after the post-intervention survey.
- Masking
- None (open label)
- Enrolment
- 60 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National University of Singapore
- Sponsor type
- University, hospital or other
- Collaborators
- Buddhist Compassion Relief Tzu-Chi Foundation (Singapore)
- Responsible party
- Principal investigator, Seah Betsy, National University of Singapore
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07881510
- Sponsor's protocol ID
- DERC Ref: 001455
- Other IDs
- RCA: 2026-00857
- Status last verified
- Oct 2026
- First submitted
- 12 Oct 2026
- Last updated
- 22 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data (IPD) will not be shared because this is a small pilot study involving community-dwelling older adults in Singapore. Sharing of IPD is not planned due to privacy, ethical, and institutional data protection requirements under Singapore's Personal Data Protection Act (PDPA) and the National University of Singapore's research data management policies. Only aggregate results will be reported in publications and presentations.
Publications
Yang K, Hu Y, Qi H. Digital Health Literacy: Bibliometric Analysis. J Med Internet Res. 2022 Jul 6;24(7):e35816. doi: 10.2196/35816.
PubMed 35793141Milanti A, Norman C, Chan DNS, So WKW, Skinner H. eHealth Literacy 3.0: Updating the Norman and Skinner 2006 Model. J Med Internet Res. 2025 Mar 11;27:e70112. doi: 10.2196/70112.
PubMed 40068166van der Vaart R, Drossaert C. Development of the Digital Health Literacy Instrument: Measuring a Broad Spectrum of Health 1.0 and Health 2.0 Skills. J Med Internet Res. 2017 Jan 24;19(1):e27. doi: 10.2196/jmir.6709.
PubMed 28119275Eskinazi N, Zwilling M, Marques A, Tesler R. The Role of AI in Improving Digital Wellness Among Older Adults: Comparative Bibliometric Analysis. JMIR AI. 2026 Jan 14;5:e71248. doi: 10.2196/71248.
PubMed 41540814Dong Q, Liu T, Liu R, Yang H, Liu C. Effectiveness of Digital Health Literacy Interventions in Older Adults: Single-Arm Meta-Analysis. J Med Internet Res. 2023 Jun 28;25:e48166. doi: 10.2196/48166.
PubMed 37379077