GoutGOUTBuddyNCT07004231
Using Gout Buddy to Enhance Gout Management
A study testing GOUT Buddy, an AI chatbot in people with Gout, run by SingHealth Polyclinics at 1 site in Singapore.
Trial summary
Background: Dietary management is crucial for gout, but patients often lack adequate dietary literacy. However, patients often lack adequate dietary literacy and struggle to navigate complex dietary recommendations. Read more about this study
- Who is it for?
- Ages 21 years and older
- Conditions the study is for
- Gout
- What is being tested?
- GOUT Buddy, an AI chatbot
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 110 participants
- Where
- 1 siteSingapore
- Study dates
- 1 Jul 2025to 15 Aug 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 21 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age > 21 years
- At least one serum uric acid > 360 μmol/L or an episode of acute gout attack within the last 18 months
- Able to read and speak English
- Access to an internet-enabled device compatible with Gout Buddy
Who cannot join
- Not a Singapore citizen or permanent resident
- Pregnant
- End-stage kidney disease or on renal replacement therapy
- Known terminal illness
- Visual and/or hearing impairment
- Cognitive impairment or mental illness
- Unable to provide informed consent
- Individuals who do not have a personal mobile device with internet access
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Using Gout Buddy to Enhance Dietary Literacy and Gout Management-A Mixed Method Clinical Trial
Background: Dietary management is crucial for gout, but patients often lack adequate dietary literacy. However, patients often lack adequate dietary literacy and struggle to navigate complex dietary recommendations. Gout Buddy is an autonomous AI agent to offer personalized gout education and awareness tailored to individual needs. This study aims to evaluate the effectiveness and user experience of Gout Buddy, in improving dietary literacy and gout management.
Materials and methods: A two-arm RCT will randomize patients with gout to either the intervention (Gout Buddy) or control (standard care). Two study visits within 3-6 months will assess changes in dietary literacy and gout management behaviours. Qualitative interviews will be conducted with intervention arm participants and multidisciplinary care team members to explore their experiences with Gout Buddy till the point of data saturation.
Read more
Expected Outcomes: The current trial is expected to demonstrate the effectiveness of Gout Buddy in improving dietary literacy and gout management compared to standard care. Qualitative data will provide rich insights into user engagement, perceived benefits, challenges, and the feasibility of integrating the chatbot into routine gout management.
Significance: This study will provide evidence on the potential of AI chatbots to enhance gout self-management. The findings will inform the development and implementation of digital health tools for chronic disease management, potentially improving patient outcomes and reducing the burden of gout.
Read the detailed description
Background and Rationale:
Gout is a chronic and progressive form of inflammatory arthritis characterized by the accumulation of urate crystals in the joints, leading to recurrent episodes of severe pain, redness, and swelling. It is primarily caused by hyperuricemia, a condition in which there is an excess of uric acid in the blood. Gout is more common in men and older adults and is often associated with comorbidities such as hypertension, diabetes, and cardiovascular disease.
A 2015 meta-analysis of global gout studies estimated a pooled prevalence of 0.6%, though with significant variation. [1] In mainland China, the prevalence of gout from 1998 to 2019 was 1.6%, and a local study from Singapore among Chinese individuals found that 4.1% had a history of physician-diagnosed gout. [2,3] Despite the availability of effective treatments, about one-third patients struggle with managing their condition.[4] Poor control can be attributed due to lack of understanding of gout's etiology, progression, and the importance of adherence to prescribed therapies. [5] Poor management of gout can result in frequent flare-ups, joint damage, and decreased quality of life.
Research indicates that patient education significantly impacts the successful management of gout. [6] However, traditional methods of patient education-such as pamphlets, infrequent consultations, and group sessions-often fall short in engaging patients and providing timely information tailored to their individual needs. [7,8] Additionally, these methods do not accommodate the continuous need for information that patients may have outside of clinic hours. Therefore, there is a need for innovative, accessible, and patient-centered educational tools that can bridge these gaps and empower patients to manage their gout more effectively.
Digital health interventions have emerged as a promising solution to these challenges. By leveraging technology, these interventions can provide continuous support, personalized information, and interactive educational content to patients. [9] Chatbots, in particular, have gained attention for their efficacy of health behaviour change among large and diverse population. [10] Chatbots can be particularly beneficial in chronic disease management, where ongoing patient education and engagement are critical. By providing instant access to reliable information and guidance, chatbots can help patients better understand their condition, adhere to treatment plans, and make informed decisions about their health.
Health Expert Language Framework (HELF) is a state-of-the-art AI-powered healthcare platform dedicated to advancing health and wellness education. Tailored for learners, educators, healthcare professionals, and researchers, HELF AI offers an immersive learning environment enriched by direct access to PubMed, a vast repository of the latest health literature. The platform elevates the educational experience by presenting detailed information and resources in a dynamic Question-Answer format, fostering a deeper understanding of health topics.
Building on this foundation, HELF AI can be further developed into a sophisticated, autonomous AI agent ("Gout Buddy") to offer personalized gout education and awareness tailored to individual needs. Given the challenges associated with gout management and the potential of digital health interventions, this study seeks to evaluate the effectiveness of the Gout Buddy as an intelligent patient companion, in improving dietary literacy of gout and adherence to its management, leveraging its AI capabilities to offer tailored educational support.
Study Objective:
- To assess the effectiveness of the Gout Buddy in improving patients' dietary literacy of gout, adherence, and overall health outcomes
- To explore the views, acceptance, and potential challenges associated with using the Gout Buddy among the participants and the multidisciplinary care team, including nurses, dietitians, and pharmacists.
The study will utilize the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance) to comprehensively evaluate the Gout Buddy intervention.
This study will employ a Sequential Explanatory mixed-methods design, incorporating both quantitative and qualitative approaches.
Quantitative phase: Two-arm randomized controlled trial (RCT) Arm 1: Usual care + Gout Buddy Arm 2: Usual care Qualitative phase: In-depth interviews will be conducted with participants who used the Gout Buddy, as well as the multidisciplinary care team (nurses, dietitians, and pharmacists) involved in patient care. These interviews will explore their experiences, views on the effectiveness of the chatbot, and any challenges they encountered. This will provide insights into the user experience and identify any barriers to effective implementation of Gout Buddy in managing patient care.
Recruitment and consent taking Participant recruitment Eligible patient participants will be identified through either screening from electronic medical records (EMR) or referred by the attending physicians to the study team. The study team will contact potential participants in-person or over phone to invite them to participate in the study and arrange a screening visit following which they will be recruited in-person during their regular clinic visits.
The study team will verify eligibility using a screening tool and written informed consent will be obtained in-person at the study site, in a quiet and separate room or space, ensuring privacy. Adequate time will be given to read the documents and questions, emphasizing the voluntary nature of participation and its independence from routine clinical care.
Participant withdrawal Participants may choose to withdraw from the study at any time without providing an explanation and this will not result in any punitive consequences.
Randomization Patient participants from each study site will be randomly allocated in a 1:1 ratio to one of the two arms in an open-label fashion, using computer-generated random numbers for simple randomization of subjects. The nature of the intervention makes impossible to blind patients and research team to participant allocation. The randomization sequence is written and kept in an opaque sealed envelope, which will be labelled with a serial number. The study team will open the sealed envelope once the patient has consented to participate and then will be assigned to the study arms accordingly.
Qualitative: In-depth interviews A semi-structured interview with retrospective probing, using an interview guide will be conducted among the participants who used the Gout Buddy, as well as with members of the multidisciplinary care team (nurses, dietitians, and pharmacists) involved in patient care till point of data saturation. Maximum variation sampling will be employed based on their age, ethnicity, and socioeconomic status. The session will be audio-recorded.
Follow-up Study participants will be followed up at their subsequent clinic visit, scheduled 3-6 months after enrolment, by a second assessor who is blinded to the intervention. If a participant does not return to the clinic within the study period, the follow up survey will be conducted via phone at a time convenient for them.
- Conditions
- Gout
- Being tested
- GOUT Buddy, an AI chatbot
- Keywords
- gout, dietary literacy, Artificial Intelligence, Chatbot, Primary care
- Medical subject headings
- Gout
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
GOUT Buddy, an AI chatbotOther
AI Chatbot ("GOUT Buddy") offers personalized gout education and awareness tailored to individual needs
| Study group | Role | What they receive |
|---|---|---|
| Intervention arm using Gout Buddy | Experimental | Participants in the intervention group will receive usual care, including standard medical management and dietary counselling for gout. In addition, they will use the Gout Buddy chatbot (a prototype mobile application developed by HELF AI). The chatbot will be installed on their mobile phones (iOS or Android, 2020 models or newer) and requires a stable but standard mobile internet connectivity.
Participants will download and enroll in Gout Buddy with the guidance of study team. The chatbot provides interactive support by allowing users to ask questions and receive daily tips and recommendations to help them manage their condition effectively.
Notifications will be sent by Gout Buddy to the users' phones; these happen one to three times every day and mainly consist of daily tips related to better gout literacy and self-efficacy. The notifications are also useful conversation starters with users. Receives: Other: GOUT Buddy, an AI chatbot |
| Standard care | No intervention | Participants in the control group will receive usual care, which includes standard medical management and dietary counselling for gout. They will also receive a pamphlet containing information on dietary management for gout. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Food Frequency Questionnaire
Food Frequency Questionnaire-SF (FFQ-SF) is a limited checklist of foods and beverages with a frequency response section for subjects to report how often each item was consumed over a specified period of time. Changes in the frequency of consuming each food item will be compared to baseline consumption.
Measured: through study completion, an average of 3 to 6 months
Dietary literacy about gout
Change in the scores using Dietary literacy about gout questionnaire; a newly developed questionnaire to assess patients' understanding of gout diet comprising 19 questions scored from a scale of 1-5: 1 (Strongly agree), 2 (agree), 3 (uncertain), 4 (disagree) and 5 (strongly disagree). A higher score indicates better understanding.
Measured: through study completion, an average of 3 to 6 months
Medication adherence report scale- 5 items
Change in the scores using five item Medication Adherence Report Scale (MARS-5); MARS-5 score was calculated by summing the numeric score (range 1-5) from each question for out of 25 (range 5-25). A higher score indicates better adherence.
Measured: through study completion, an average of 3 to 6 months
Health related quality of life (HRQoL)
Change in the scores using EQ-5D-5L questionnaire; The EQ-5D-5L tool comprises five dimensions, each describing a different aspect of health: mobility, self-care, usual activities, pain/ discomfort and anxiety/ depression. Each dimension has five response levels (no problems, slight problems, moderate problems, severe problems, unable to/ extreme problems). The proportion of patients reporting each level of problem on each dimension of the EQ-5D will be determined through study completion and compared. EQ VAS (Visual Analogue Scale) provides a quantitative measure of the patient's perception of their overall health. The EQ VAS records the respondent's overall current health on a vertical scale (0-100), where the endpoints are labelled '0-The worst health you can imagine' and '100-The best health you can imagine'.
Measured: through study completion, an average of 3 to 6 months
Secondary outcomes (1)
exploring the views, acceptance, and potential challenges associated with using the Gout Buddy
in-depth interview with the participants till point of data saturation
Measured: 3-6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Jun 2025
- Study start1 Jul 2025
- Primary completion15 Aug 2026 (estimated)
- Study completion15 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (12)Papers the sponsor has linked to this study.
- Other trials for GoutStudies 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
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 110 participants (actual)
Sponsor and investigators
- Lead sponsor
- SingHealth Polyclinics
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Tan Ngiap Chuan, SingHealth Polyclinics
- Investigators
- Ngiap Chuan Tan, MMed, Principal investigator, SingHealth Polyclinics
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07004231
- Sponsor's protocol ID
- 2024-4476
- Other IDs
- 2024-4476
- Acronym
- GOUTBuddy
- Status last verified
- May 2026
- First submitted
- 26 May 2025
- Last updated
- 12 May 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Harrold LR, Mazor KM, Peterson D, Naz N, Firneno C, Yood RA. Patients' knowledge and beliefs concerning gout and its treatment: a population based study. BMC Musculoskelet Disord. 2012 Sep 21;13:180. doi: 10.1186/1471-2474-13-180.
PubMed 22995041Fields TR, Batterman A. How Can We Improve Disease Education in People with Gout? Curr Rheumatol Rep. 2018 Mar 8;20(3):12. doi: 10.1007/s11926-018-0720-x.
PubMed 29516200Bhattad PB, Pacifico L. Empowering Patients: Promoting Patient Education and Health Literacy. Cureus. 2022 Jul 27;14(7):e27336. doi: 10.7759/cureus.27336. eCollection 2022 Jul.
PubMed 36043002Hoving C, Visser A, Mullen PD, van den Borne B. A history of patient education by health professionals in Europe and North America: from authority to shared decision making education. Patient Educ Couns. 2010 Mar;78(3):275-81. doi: 10.1016/j.pec.2010.01.015. Epub 2010 Mar 1.
PubMed 20189746Kuwabara A, Su S, Krauss J. Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine. Am J Lifestyle Med. 2019 Dec 13;14(2):137-142. doi: 10.1177/1559827619892547. eCollection 2020 Mar-Apr.
PubMed 32231478Aggarwal A, Tam CC, Wu D, Li X, Qiao S. Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review. J Med Internet Res. 2023 Feb 24;25:e40789. doi: 10.2196/40789.
PubMed 36826990Rothenberg E, Strandhagen E, Samuelsson J, Ahlner F, Rydberg Sterner T, Skoog I, Lundberg CE. Relative Validity of a Short 15-Item Food Frequency Questionnaire Measuring Dietary Quality, by the Diet History Method. Nutrients. 2021 Oct 24;13(11):3754. doi: 10.3390/nu13113754.
PubMed 34836011Wijnands JM, Viechtbauer W, Thevissen K, Arts IC, Dagnelie PC, Stehouwer CD, van der Linden S, Boonen A. Determinants of the prevalence of gout in the general population: a systematic review and meta-regression. Eur J Epidemiol. 2015 Jan;30(1):19-33. doi: 10.1007/s10654-014-9927-y. Epub 2014 Jul 27.
PubMed 25064615Huang J, Ma ZF, Zhang Y, Wan Z, Li Y, Zhou H, Chu A, Lee YY. Geographical distribution of hyperuricemia in mainland China: a comprehensive systematic review and meta-analysis. Glob Health Res Policy. 2020 Nov 30;5(1):52. doi: 10.1186/s41256-020-00178-9.
PubMed 33292806Teng GG, Ang LW, Saag KG, Yu MC, Yuan JM, Koh WP. Mortality due to coronary heart disease and kidney disease among middle-aged and elderly men and women with gout in the Singapore Chinese Health Study. Ann Rheum Dis. 2012 Jun;71(6):924-8. doi: 10.1136/ard.2011.200523. Epub 2011 Dec 15.
PubMed 22172492Oka P, Chong WM, Ng DX, Aau WK, Tan NC. Epidemiology and risk factors associated with gout control among adult Asians: a real-world retrospective cohort study. Front Med (Lausanne). 2023 Sep 7;10:1253839. doi: 10.3389/fmed.2023.1253839. eCollection 2023.
PubMed 37746085Serlachius A, Schache K, Kieser A, Arroll B, Petrie K, Dalbeth N. Association Between User Engagement of a Mobile Health App for Gout and Improvements in Self-Care Behaviors: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2019 Aug 13;7(8):e15021. doi: 10.2196/15021.
PubMed 31411147
Study at a glance
From the registry record, last updated by the sponsor on 12 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Gout Buddy to Enhance Dietary Literacy and Gout Management-A Mixed Method Clinical Trial
- ClinicalTrials.gov ID
- NCT07004231
- Acronym / sponsor ID
- GOUTBuddy / 2024-4476
- Conditions
- Gout
- Keywords
- gout, dietary literacy, Artificial Intelligence, Chatbot, Primary care
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 110 participants (actual)
- Lead sponsor
- SingHealth PolyclinicsUniversity, hospital or other
- Study start
- 1 Jul 2025 (actual)
- Primary completion
- 15 Aug 2026 (estimated)
- Study completion
- 15 Aug 2026 (estimated)
- First posted
- 4 Jun 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Background: Dietary management is crucial for gout, but patients often lack adequate dietary literacy. However, patients often lack adequate dietary literacy and struggle to navigate complex dietary recommendations. Gout Buddy is an autonomous AI agent to offer personalized gout education and awareness tailored to individual needs. This study aims to evaluate the effectiveness and user experience of Gout Buddy, in improving dietary literacy and gout management.
Materials and methods: A two-arm RCT will randomize patients with gout to either the intervention (Gout Buddy) or control (standard care). Two study visits within 3-6 months will assess changes in dietary literacy and gout management behaviours. Qualitative interviews will be conducted with intervention arm participants and multidisciplinary care team members to explore their experiences with Gout Buddy till the point of data saturation.
Expected Outcomes: The current trial is expected to demonstrate the effectiveness of Gout Buddy in improving dietary literacy and gout management compared to standard care. Qualitative data will provide rich insights into user engagement, perceived benefits, challenges, and the feasibility of integrating the chatbot into routine gout management.
Significance: This study will provide evidence on the potential of AI chatbots to enhance gout self-management. The findings will inform the development and implementation of digital health tools for chronic disease management, potentially improving patient outcomes and reducing the burden of gout.
Detailed description
Background and Rationale:
Gout is a chronic and progressive form of inflammatory arthritis characterized by the accumulation of urate crystals in the joints, leading to recurrent episodes of severe pain, redness, and swelling. It is primarily caused by hyperuricemia, a condition in which there is an excess of uric acid in the blood. Gout is more common in men and older adults and is often associated with comorbidities such as hypertension, diabetes, and cardiovascular disease.
A 2015 meta-analysis of global gout studies estimated a pooled prevalence of 0.6%, though with significant variation. [1] In mainland China, the prevalence of gout from 1998 to 2019 was 1.6%, and a local study from Singapore among Chinese individuals found that 4.1% had a history of physician-diagnosed gout. [2,3] Despite the availability of effective treatments, about one-third patients struggle with managing their condition.[4] Poor control can be attributed due to lack of understanding of gout's etiology, progression, and the importance of adherence to prescribed therapies. [5] Poor management of gout can result in frequent flare-ups, joint damage, and decreased quality of life.
Research indicates that patient education significantly impacts the successful management of gout. [6] However, traditional methods of patient education-such as pamphlets, infrequent consultations, and group sessions-often fall short in engaging patients and providing timely information tailored to their individual needs. [7,8] Additionally, these methods do not accommodate the continuous need for information that patients may have outside of clinic hours. Therefore, there is a need for innovative, accessible, and patient-centered educational tools that can bridge these gaps and empower patients to manage their gout more effectively.
Digital health interventions have emerged as a promising solution to these challenges. By leveraging technology, these interventions can provide continuous support, personalized information, and interactive educational content to patients. [9] Chatbots, in particular, have gained attention for their efficacy of health behaviour change among large and diverse population. [10] Chatbots can be particularly beneficial in chronic disease management, where ongoing patient education and engagement are critical. By providing instant access to reliable information and guidance, chatbots can help patients better understand their condition, adhere to treatment plans, and make informed decisions about their health.
Health Expert Language Framework (HELF) is a state-of-the-art AI-powered healthcare platform dedicated to advancing health and wellness education. Tailored for learners, educators, healthcare professionals, and researchers, HELF AI offers an immersive learning environment enriched by direct access to PubMed, a vast repository of the latest health literature. The platform elevates the educational experience by presenting detailed information and resources in a dynamic Question-Answer format, fostering a deeper understanding of health topics.
Building on this foundation, HELF AI can be further developed into a sophisticated, autonomous AI agent ("Gout Buddy") to offer personalized gout education and awareness tailored to individual needs. Given the challenges associated with gout management and the potential of digital health interventions, this study seeks to evaluate the effectiveness of the Gout Buddy as an intelligent patient companion, in improving dietary literacy of gout and adherence to its management, leveraging its AI capabilities to offer tailored educational support.
Study Objective:
- To assess the effectiveness of the Gout Buddy in improving patients' dietary literacy of gout, adherence, and overall health outcomes
- To explore the views, acceptance, and potential challenges associated with using the Gout Buddy among the participants and the multidisciplinary care team, including nurses, dietitians, and pharmacists.
The study will utilize the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance) to comprehensively evaluate the Gout Buddy intervention.
This study will employ a Sequential Explanatory mixed-methods design, incorporating both quantitative and qualitative approaches.
Quantitative phase: Two-arm randomized controlled trial (RCT) Arm 1: Usual care + Gout Buddy Arm 2: Usual care Qualitative phase: In-depth interviews will be conducted with participants who used the Gout Buddy, as well as the multidisciplinary care team (nurses, dietitians, and pharmacists) involved in patient care. These interviews will explore their experiences, views on the effectiveness of the chatbot, and any challenges they encountered. This will provide insights into the user experience and identify any barriers to effective implementation of Gout Buddy in managing patient care.
Recruitment and consent taking Participant recruitment Eligible patient participants will be identified through either screening from electronic medical records (EMR) or referred by the attending physicians to the study team. The study team will contact potential participants in-person or over phone to invite them to participate in the study and arrange a screening visit following which they will be recruited in-person during their regular clinic visits.
The study team will verify eligibility using a screening tool and written informed consent will be obtained in-person at the study site, in a quiet and separate room or space, ensuring privacy. Adequate time will be given to read the documents and questions, emphasizing the voluntary nature of participation and its independence from routine clinical care.
Participant withdrawal Participants may choose to withdraw from the study at any time without providing an explanation and this will not result in any punitive consequences.
Randomization Patient participants from each study site will be randomly allocated in a 1:1 ratio to one of the two arms in an open-label fashion, using computer-generated random numbers for simple randomization of subjects. The nature of the intervention makes impossible to blind patients and research team to participant allocation. The randomization sequence is written and kept in an opaque sealed envelope, which will be labelled with a serial number. The study team will open the sealed envelope once the patient has consented to participate and then will be assigned to the study arms accordingly.
Qualitative: In-depth interviews A semi-structured interview with retrospective probing, using an interview guide will be conducted among the participants who used the Gout Buddy, as well as with members of the multidisciplinary care team (nurses, dietitians, and pharmacists) involved in patient care till point of data saturation. Maximum variation sampling will be employed based on their age, ethnicity, and socioeconomic status. The session will be audio-recorded.
Follow-up Study participants will be followed up at their subsequent clinic visit, scheduled 3-6 months after enrolment, by a second assessor who is blinded to the intervention. If a participant does not return to the clinic within the study period, the follow up survey will be conducted via phone at a time convenient for them.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Intervention arm using Gout Buddy | Experimental | Other: GOUT Buddy, an AI chatbotParticipants in the intervention group will receive usual care, including standard medical management and dietary counselling for gout. In addition, they will use the Gout Buddy chatbot (a prototype mobile application developed by HELF AI). The chatbot will be installed on their mobile phones (iOS or Android, 2020 models or newer) and requires a stable but standard mobile internet connectivity. Participants will download and enroll in Gout Buddy with the guidance of study team. The chatbot provides interactive support by allowing users to ask questions and receive daily tips and recommendations to help them manage their condition effectively. Notifications will be sent by Gout Buddy to the users' phones; these happen one to three times every day and mainly consist of daily tips related to better gout literacy and self-efficacy. The notifications are also useful conversation starters with users. |
| Standard care | No intervention | –Participants in the control group will receive usual care, which includes standard medical management and dietary counselling for gout. They will also receive a pamphlet containing information on dietary management for gout. |
Who may qualify
- Ages
- 21 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Age > 21 years
- At least one serum uric acid > 360 μmol/L or an episode of acute gout attack within the last 18 months
- Able to read and speak English
- Access to an internet-enabled device compatible with Gout Buddy
Key exclusion criteria (8 listed)
- Not a Singapore citizen or permanent resident
- Pregnant
- End-stage kidney disease or on renal replacement therapy
- Known terminal illness
- Visual and/or hearing impairment
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| GOUT Buddy, an AI chatbotAI Chatbot ("GOUT Buddy") offers personalized gout education and awareness tailored to individual needs | Other | Intervention arm using Gout Buddy |
Primary outcome
Food Frequency Questionnaire
Time frame: through study completion, an average of 3 to 6 months
Food Frequency Questionnaire-SF (FFQ-SF) is a limited checklist of foods and beverages with a frequency response section for subjects to report how often each item was consumed over a specified period of time. Changes in the frequency of consuming each food item will be compared to baseline consumption.
Dietary literacy about gout
Time frame: through study completion, an average of 3 to 6 months
Change in the scores using Dietary literacy about gout questionnaire; a newly developed questionnaire to assess patients' understanding of gout diet comprising 19 questions scored from a scale of 1-5: 1 (Strongly agree), 2 (agree), 3 (uncertain), 4 (disagree) and 5 (strongly disagree). A higher score indicates better understanding.
Medication adherence report scale- 5 items
Time frame: through study completion, an average of 3 to 6 months
Change in the scores using five item Medication Adherence Report Scale (MARS-5); MARS-5 score was calculated by summing the numeric score (range 1-5) from each question for out of 25 (range 5-25). A higher score indicates better adherence.
Health related quality of life (HRQoL)
Time frame: through study completion, an average of 3 to 6 months
Change in the scores using EQ-5D-5L questionnaire; The EQ-5D-5L tool comprises five dimensions, each describing a different aspect of health: mobility, self-care, usual activities, pain/ discomfort and anxiety/ depression. Each dimension has five response levels (no problems, slight problems, moderate problems, severe problems, unable to/ extreme problems). The proportion of patients reporting each level of problem on each dimension of the EQ-5D will be determined through study completion and compared. EQ VAS (Visual Analogue Scale) provides a quantitative measure of the patient's perception of their overall health. The EQ VAS records the respondent's overall current health on a vertical scale (0-100), where the endpoints are labelled '0-The worst health you can imagine' and '100-The best health you can imagine'.
1 secondary outcome
exploring the views, acceptance, and potential challenges associated with using the Gout Buddy
Time frame: 3-6 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 May 2026.
- Background: PubMed 22995041Harrold LR, Mazor KM, Peterson D, Naz N, Firneno C, Yood RA. Patients' knowledge and beliefs concerning gout and its treatment: a population based study. BMC Musculoskelet Disord. 2012 Sep 21;13:180. doi: 10.1186/1471-2474-13-180.
- Background: PubMed 29516200Fields TR, Batterman A. How Can We Improve Disease Education in People with Gout? Curr Rheumatol Rep. 2018 Mar 8;20(3):12. doi: 10.1007/s11926-018-0720-x.
- Background: PubMed 36043002Bhattad PB, Pacifico L. Empowering Patients: Promoting Patient Education and Health Literacy. Cureus. 2022 Jul 27;14(7):e27336. doi: 10.7759/cureus.27336. eCollection 2022 Jul.
- Background: PubMed 20189746Hoving C, Visser A, Mullen PD, van den Borne B. A history of patient education by health professionals in Europe and North America: from authority to shared decision making education. Patient Educ Couns. 2010 Mar;78(3):275-81. doi: 10.1016/j.pec.2010.01.015. Epub 2010 Mar 1.
- Background: PubMed 32231478Kuwabara A, Su S, Krauss J. Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine. Am J Lifestyle Med. 2019 Dec 13;14(2):137-142. doi: 10.1177/1559827619892547. eCollection 2020 Mar-Apr.
- Background: PubMed 36826990Aggarwal A, Tam CC, Wu D, Li X, Qiao S. Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review. J Med Internet Res. 2023 Feb 24;25:e40789. doi: 10.2196/40789.
- Background: PubMed 34836011Rothenberg E, Strandhagen E, Samuelsson J, Ahlner F, Rydberg Sterner T, Skoog I, Lundberg CE. Relative Validity of a Short 15-Item Food Frequency Questionnaire Measuring Dietary Quality, by the Diet History Method. Nutrients. 2021 Oct 24;13(11):3754. doi: 10.3390/nu13113754.
- Results publication: PubMed 25064615Wijnands JM, Viechtbauer W, Thevissen K, Arts IC, Dagnelie PC, Stehouwer CD, van der Linden S, Boonen A. Determinants of the prevalence of gout in the general population: a systematic review and meta-regression. Eur J Epidemiol. 2015 Jan;30(1):19-33. doi: 10.1007/s10654-014-9927-y. Epub 2014 Jul 27.
- Results publication: PubMed 33292806Huang J, Ma ZF, Zhang Y, Wan Z, Li Y, Zhou H, Chu A, Lee YY. Geographical distribution of hyperuricemia in mainland China: a comprehensive systematic review and meta-analysis. Glob Health Res Policy. 2020 Nov 30;5(1):52. doi: 10.1186/s41256-020-00178-9.
- Results publication: PubMed 22172492Teng GG, Ang LW, Saag KG, Yu MC, Yuan JM, Koh WP. Mortality due to coronary heart disease and kidney disease among middle-aged and elderly men and women with gout in the Singapore Chinese Health Study. Ann Rheum Dis. 2012 Jun;71(6):924-8. doi: 10.1136/ard.2011.200523. Epub 2011 Dec 15.
- Results publication: PubMed 37746085Oka P, Chong WM, Ng DX, Aau WK, Tan NC. Epidemiology and risk factors associated with gout control among adult Asians: a real-world retrospective cohort study. Front Med (Lausanne). 2023 Sep 7;10:1253839. doi: 10.3389/fmed.2023.1253839. eCollection 2023.
- Results publication: PubMed 31411147Serlachius A, Schache K, Kieser A, Arroll B, Petrie K, Dalbeth N. Association Between User Engagement of a Mobile Health App for Gout and Improvements in Self-Care Behaviors: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2019 Aug 13;7(8):e15021. doi: 10.2196/15021.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Ngiap Chuan Tan, MMed principal investigator
SingHealth Polyclinics
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing GOUT Buddy, an AI chatbot in people with Gout, run by SingHealth Polyclinics at 1 site in Singapore.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 12 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Food Frequency Questionnaire (time frame: through study completion, an average of 3 to 6 months). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07004231, which also lists 12 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 May 2026.