Clinical trial · Interventional
AI-empowered Nudge to Improve Colonoscopy Uptake (AINC)
AI-empowered Nudge to Improve Colonoscopy Uptake (AINC): A Pragmatic Cluster-Randomized Trial
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Colorectal cancer (CRC) ranks third in both incidence and mortality among all malignant tumors in China. Studies have shown that early screening can significantly reduce its incidence and mortality. Colonoscopy is the gold standard for CRC screening; however, compliance with colonoscopy among high-risk groups in China is very low. Artificial intelligence (AI)-assisted tools can provide real-time, personalized health education, and nudge strategies can help translate intent into action. This trial aims to evaluate the effectiveness of AI-empowered nudge for improving colonoscopy uptake among high-risk individuals aged 45 to 74 in China. It's a two-arm, pragmatic cluster randomized controlled trial. The main question it aims to answer is whether the AI-enabled personalized health education and nudge strategies improve colonoscopy adherence. Participants will: 1. Be recruited and allocated into one of two groups according to the assigned clusters. Participants in one group will be invited to receive usual care. In addition to usual care, participants in the other group will receive AI-empowered nudge, featuring an AI chatbot providing real-time personalized responses and a nudge environment with default screening option. 2. Have their colonoscopy status checked at the end of trial.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Colonoscopy | — | UNRESOLVED | — |
| Colorectal Neoplasms | Colorectal Neoplasm | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| AI-empowered nudge (AINC) strategy | Behavioral | — | UNRESOLVED |
| Usual Care | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- AI-empowered nudge group
- description
- This arm implements a multi-component AI-empowered nudge strategy: Default Appointment: On-site pre-scheduling of colonoscopies for high-risk individuals, providing an "opt-out" mechanism. AI Chatbot: Guided on-site use (≥3 mins) of a dedicated chatbot offering personalized responses on CRC questions to facilitate self-learning. LLM-produced SMS Reminders: For non-adherent participants, ChatGPT-5 generates risk-tailored SMS reminders sent bi-weekly to participants and their families (5 times).
- interventionNames
- Behavioral: AI-empowered nudge (AINC) strategy
- type
- ACTIVE_COMPARATOR
- label
- Control Group
- description
- Usual care: Based on the results of the risk assessment questionnaire and FIT test, village doctors will notify the screening results to colorectal cancer high-risk individuals, and instructs recipients to go to the designated hospital for a colonoscopy. Colonoscopy appointments will be scheduled only for residents who are willing to undergo a colonoscopy.
- interventionNames
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 45 Years
- Maximum age
- 74 Years
Show eligibility criteria text
Inclusion Criteria: * Aged 45-74 years; * Test positive on the Colorectal Cancer Risk Assessment Scale and the immunochemical fecal occult blood test; * In good general health, mentally competent; * Provide informed consent. Exclusion Criteria: * History of colorectal resection; * Previous diagnosis of cancer or currently undergoing any cancer-related treatment; * Underwent a colonoscopy or sigmoidoscopy within the past 5 years; * Contraindications to colonoscopy (e.g. severe cardiac, cerebral, lung diseases, or renal dysfunction).
References
Publications (8)
- BACKGROUNDZhang Q, Wong AKC, Bayuo J. The Role of Chatbots in Enhancing Health Care for Older Adults: A Scoping Review. J Am Med Dir Assoc. 2024 Sep;25(9):105108. doi: 10.1016/j.jamda.2024.105108. Epub 2024 Jun 22. PMID 38917965
- BACKGROUNDMaida M, Mori Y, Fuccio L, Sferrazza S, Vitello A, Facciorusso A, Hassan C. Exploring ChatGPT effectiveness in addressing direct patient queries on colorectal cancer screening. Endosc Int Open. 2025 May 12;13:a25689416. doi: 10.1055/a-2568-9416. eCollection 2025. PMID 40376022
- BACKGROUNDHeald B, Keel E, Marquard J, Burke CA, Kalady MF, Church JM, Liska D, Mankaney G, Hurley K, Eng C. Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy. J Med Genet. 2021 Dec;58(12):807-814. doi: 10.1136/jmedgenet-2020-107294. Epub 2020 Nov 9. PMID 33168571
- BACKGROUNDChen D, Avison K, Alnassar S, Huang RS, Raman S. Medical accuracy of artificial intelligence chatbots in oncology: a scoping review. Oncologist. 2025 Apr 4;30(4):oyaf038. doi: 10.1093/oncolo/oyaf038. PMID 40285677
- BACKGROUNDDougherty MK, Brenner AT, Crockett SD, Gupta S, Wheeler SB, Coker-Schwimmer M, Cubillos L, Malo T, Reuland DS. Evaluation of Interventions Intended to Increase Colorectal Cancer Screening Rates in the United States: A Systematic Review and Meta-analysis. JAMA Intern Med. 2018 Dec 1;178(12):1645-1658. doi: 10.1001/jamainternmed.2018.4637. PMID 30326005
- BACKGROUNDYu Z, Li B, Zhao S, Du J, Zhang Y, Liu X, Guo Q, Zhou H, He M. Uptake and detection rate of colorectal cancer screening with colonoscopy in China: A population-based, prospective cohort study. Int J Nurs Stud. 2024 May;153:104728. doi: 10.1016/j.ijnurstu.2024.104728. Epub 2024 Feb 20. PMID 38461798
- BACKGROUNDChen H, Li N, Ren J, Feng X, Lyu Z, Wei L, Li X, Guo L, Zheng Z, Zou S, Zhang Y, Li J, Zhang K, Chen W, Dai M, He J; group of Cancer Screening Program in Urban China (CanSPUC). Participation and yield of a population-based colorectal cancer screening programme in China. Gut. 2019 Aug;68(8):1450-1457. doi: 10.1136/gutjnl-2018-317124. Epub 2018 Oct 30.