{
  "abstract": "Introduction First-degree relatives of colorectal cancer (CRC) patients have a twofold to fourfold increased risk of CRC. Tailored communication interventions have shown efficacy in improving their risk awareness and screening participation. While computer-based tailoring systems offer convenience, they often overlook the integration of healthcare professionals’ verbal input, potentially limiting effectiveness and long-term impact. To address this gap, we developed ScreenTalk, an intelligent voice-interactive tailored communication system that employs intelligent speech interaction to automate the tailoring process, enhance message credibility and improve scalability within CRC screening workflows.Methods and analysis This study is a two-arm, cluster-randomised controlled trial with a hybrid type I design involving 314 participants across three tertiary general hospitals in Guangzhou, China. Participants in both groups will receive usual care. Additionally, the intervention group will receive a 1-month tailored intelligent voice-interactive intervention, whereas the control group will receive unrelated health education to control for attention. Screening uptake (primary outcomes) and health beliefs (secondary outcomes) are measured at baseline and at 3 months, 6 months, 9 months and 12 month post the intervention. Implementation outcomes including reach, implementation, adoption and maintenance will be assessed through questionnaire, qualitative interviews and tailored system record.Ethics and dissemination The trial has been approved by the Ethics Committee of the Sun Yat-sen University (IRB No. L2024SYSU-HL-054). Information on the purpose and process of this study will be provided to the participants before recruitment, and written signatures will be collected from all participants to ensure their voluntary participation and protection of their rights and privacy.Trial registration NCT06710860 on ClinicalTrials.gov. Registered 26 November 2024. Date and version: 3.0, 14 July 2025.",
  "authors": [
    {
      "affiliations": [
        "School of Nursing, Sun Yat-sen University, Guangzhou, China"
      ],
      "name": "Shuya Lin"
    },
    {
      "affiliations": [
        "Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China"
      ],
      "name": "Baojia Luo"
    },
    {
      "affiliations": [
        "Department of Gastrointestinal Surgery, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China"
      ],
      "name": "Lei Cai"
    },
    {
      "affiliations": [
        "Department of Nursing, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China",
        "Department of Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China"
      ],
      "name": "Liangzhi Qiu"
    },
    {
      "affiliations": [
        "Department of Gastrointestinal Surgery, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China"
      ],
      "name": "Haixia Li"
    },
    {
      "affiliations": [
        "Department of Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China"
      ],
      "name": "Weiyan Liu"
    },
    {
      "affiliations": [
        "School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"
      ],
      "name": "Yichao Luo"
    },
    {
      "affiliations": [
        "School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"
      ],
      "name": "Yiwei Yuan"
    },
    {
      "affiliations": [
        "School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"
      ],
      "name": "Zhenhui Peng"
    },
    {
      "affiliations": [
        "School of Nursing, Sun Yat-sen University, Guangzhou, China"
      ],
      "name": "Yang Bai"
    }
  ],
  "title": "Intelligent voice-interactive tailored communication system (ScreenTalk) to improve colorectal cancer screening uptake among first-degree relatives of colorectal cancer patients: study protocol for a cluster-randomised type I hybrid effectiveness-implementation trial",
  "uid": "6efb76fa-5d69-5d5c-98bb-cb5311df84d1"
}