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Trial no.:
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PACTR202607470386334 |
Date of Registration:
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20/07/2026 |
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Trial Status:
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Registered in accordance with WHO and ICMJE standards |
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| TRIAL DESCRIPTION |
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Public title
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Catalyzing AI4SkinNTDs: Accelerating equitable Artificial Intelligence use through participatory co-design of SelfCareQA dataset by persons affected by Skin-NTDs (AI4SkinSelfCare) |
| Official scientific title |
Catalyzing AI4SkinNTDs: Accelerating equitable Artificial Intelligence use through participatory co-design of SelfCareQA dataset by persons affected by Skin-NTDs (AI4SkinSelfCare) |
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Brief summary describing the background
and objectives of the trial
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About half of neglected tropical diseases (NTDs) present with cutaneous manifestations, so-called skin-NTDs thus, share similar selfcare morbidity management approaches enabling cost-effective, integrated care as espoused by the WHO. Yet, despite existing guidelines and technical documents for NTDs self-care, their accessibility and adaptability remain limited. Artificial Intelligence (AI) holds huge potential for expanding access to health information and self-care interventions; however, existing AI models are disproportionately trained on data from high-income, western populations rendering current digital health tools less effective and culturally discordant for under-represented groups like people living with skin-NTDs in resource-limited settings.
This study aims to develop and validate an evidence-based, culturally competent skin self-care Q&A dataset through participatory co-creation with persons affected by skin-NTDs. The goal is to facilitate equitable, contextually relevant AI health interventions that address their specific lived experience. |
| Type of trial |
Non-Randomised |
| Acronym (If the trial has an acronym then please provide) |
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| Disease(s) or condition(s) being studied |
Buruli Ulcer, Leprosy, Lymphatic Filariasis,Skin and Connective Tissue Diseases |
| Sub-Disease(s) or condition(s) being studied |
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| Purpose of the trial |
Psychosocial |
| Anticipated trial start date |
27/07/2026 |
| Actual trial start date |
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| Anticipated date of last follow up |
27/01/2027 |
| Actual Last follow-up date |
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| Anticipated target sample size (number of participants) |
30 |
| Actual target sample size (number of participants) |
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| Recruitment status |
Not yet recruiting |
| Publication URL |
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