Clinical trial · Interventional
AI-assisted Integrated Care to Promote Colonoscopy Uptake
Artificial Intelligence-assisted Integrated Care to Promote Colonoscopy Uptake in China: a Cluster Randomized Controlled 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 the second most common cancer and the fourth leading cause of cancer-related deaths in China. Early screening of CRC has been proven to reduce the incidence and mortality, with colonoscopy as the gold standard for CRC screening. This trial aims to evaluate the effectiveness of artificial intelligence-assistant integrated care for improving uptake rate of colonoscopy among high-risk individuals aged 40 to 64 in China. It's a two-arm, parallel cluster randomized controlled trial. The main question it aims to answer is whether the AI-assisted integrated care influence participants' screening-related knowledge, health beliefs, behavioral intention, and uptake of colonoscopy. 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 specialty care. In addition to usual specialty care, participants in the other group will receive AI-assisted integrated care provided by specialist and general practitioners collaboratively. 2. Complete a questionnaire survey on their knowledge, health beliefs, behavioral intention on CRC screening. 3. Have their colonoscopy status checked at the middle and 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 (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| AI-assisted integrated care | Behavioral | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- AICC intervention group
- description
- Participants in the intervention group will receive AICC. This includes a colonoscopy recommendation from a county specialist for both participants and their families, followed by an introduction to and guided registration for a CRC education chatbot with an initial 5-minute tutorial. Subsequently, general practitioners will conduct three monthly face-by-face follow-ups, each comprising a brief reminder of colonoscopy and a guided usage of CRC education chatbot.
- interventionNames
- Behavioral: AI-assisted integrated care
- type
- NO_INTERVENTION
- label
- Control group
- description
- Participants in this group will receive usual specialty care, only a colonoscopy recommendation from a county specialists. For ethical considerations, participants in this arm will be offered access to the chatbot after the end of the study.
Primary outcomes (2)
- measure
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 40 Years
- Maximum age
- 64 Years
Show eligibility criteria text
Inclusion Criteria: * Individuals who test positive on either the Colorectal Cancer Risk Assessment Scale or the fecal immunochemical test (FIT); * Aged 40 \~ 64 years; * Proficient in smartphone use and able to engage with the intervention; * Provided informed consent . Exclusion Criteria: * History of colorectal cancer; * Contraindications to colonoscopy,(e.g. severe cardiac, cerebral, lung diseases, or renal dysfunction).
References
Publications (21)
- BACKGROUNDHan B, Zheng R, Zeng H, Wang S, Sun K, Chen R, Li L, Wei W, He J. Cancer incidence and mortality in China, 2022. J Natl Cancer Cent. 2024 Feb 2;4(1):47-53. doi: 10.1016/j.jncc.2024.01.006. eCollection 2024 Mar. PMID 39036382
- 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
- BACKGROUNDZeng A, Steinke J, Bocse HF, De Pastena M. Dr. LLM Will See You Now: The Ability of ChatGPT to Provide Geographically Tailored Colorectal Cancer Screening and Surveillance Recommendations. J Clin Med. 2025 Jul 18;14(14):5101. doi: 10.3390/jcm14145101. PMID 40725794
- BACKGROUNDKerbage A, Kassab J, El Dahdah J, Burke CA, Achkar JP, Rouphael C. Accuracy of ChatGPT in Common Gastrointestinal Diseases: Impact for Patients and Providers. Clin Gastroenterol Hepatol. 2024 Jun;22(6):1323-1325.e3. doi: 10.1016/j.cgh.2023.11.008. Epub 2023 Nov 19. PMID 37984563
- 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.