Effectiveness of Chat-based Mobile Application for Consultation (Zalo) in Improving Compliance With Follow-up Tests After Abnormal Chest X-ray Findings Interpret by Artificial Intelligent

Summary

The study titled "Effectiveness of Chat-based Mobile Application for Consultation (Zalo) in Improving Compliance with Follow-up Tests after Abnormal Chest X-ray Findings Interpreted by Artificial Intelligence" aims to evaluate whether digital communication can enhance patient adherence to follow-up evaluations after lung disease screening in Vietnam.

Lung cancer and tuberculosis (TB) remain leading causes of morbidity and mortality in Vietnam. Despite advances in screening technologies, including low-dose CT and AI-assisted chest X-rays, many patients fail to follow up after receiving abnormal results, resulting in delayed diagnosis and treatment. Communication barriers, low health literacy, and limited consultation time are key factors behind this gap. Digital health tools such as chat-based mobile applications offer potential to strengthen post-screening engagement and improve health outcomes.

This randomized controlled trial will be conducted at Nhan Dan Gia Dinh Hospital in Ho Chi Minh City between October 2025 and October 2026. Participants aged 40-62 years, who undergo routine chest X-ray screening interpreted by AI software (qXR by QURE.AI), will be randomly assigned to either the intervention or control group. All participants must have an active Zalo account.

In the intervention group, participants will receive their AI-interpreted results and educational guidelines for lung cancer or TB through the research team's Zalo account. The guideline covers disease overview, diagnostic methods, follow-up recommendations, and lifestyle guidance. Participants may ask questions directly to doctors specializing in nutrition, respiratory medicine, and pulmonary pathology, with guaranteed responses within 4 hours during working hours and 10 hours after hours. Messages are also sent via email as backup. The hospital's IT department oversees the Zalo platform to ensure data security.

In the control group, participants will receive only the doctor's conclusion and brief advice via Zalo and email. They will be invited to connect with the hospital's official Zalo account for general inquiries but will not receive further digital consultation.

Follow-up calls will assess compliance. For positive or suspected cases, research staff will call one month after result notification to confirm whether participants completed follow-up tests. For negative cases, calls will occur at six months to check for new symptoms or additional imaging. Structured questionnaires will document reasons for compliance or noncompliance. The study does not provide additional diagnostic services; all follow-up costs are covered by participants or their health insurance.

The primary outcome is the rate of compliance with recommended follow-up tests. The secondary outcome measures participants' responsiveness to follow-up phone calls. Statistical analyses will compare compliance rates between groups using chi-square or Fisher's exact tests and risk ratios with 95% confidence intervals.

Sample size calculations estimate that 2,692 participants are required to detect a 10% improvement in follow-up compliance (from 85% to 95%) with 80% power and 5% significance. Randomization will use REDCap software with block sizes of 2-8. Interviewers conducting follow-up calls will be blinded to group allocation.

Ethical approval will be obtained from the Nhan Dan Gia Dinh Hospital Ethics Committee, and the study will be registered at ClinicalTrials.gov. Data confidentiality will be strictly maintained, with all digital records password-protected and accessible only to authorized research members.

This project is the first randomized controlled trial in Vietnam to evaluate the effectiveness of chat-based mobile consultation in improving post-screening compliance for lung diseases. It leverages Vietnam's high mobile phone penetration and the popularity of Zalo to create a scalable model for patient engagement. Expected benefits include improved communication, increased awareness of lung cancer and TB, reduced loss to follow-up, and faster diagnostic confirmation.

The findings will provide scientific evidence for integrating digital communication into screening programs and contribute to national efforts to improve early detection and management of lung diseases.

Conditions

• Lung Cancer
• Tuberculosis (TB)
• Chat-based Mobile Application
• Compliance Behavior
• Artificial Intelligence in Radiology

Interventions

OTHER

chat-based mobile application (Zalo)

this intervention are chat-based activities (including providing illness guidelines and chat-based environment) to encourage participants to compliance doctor's recommendation to do early further tests if they have positive lung disease screening result or they develop lung disease symptoms which suspected to lung cancer or TB

Sponsors & Collaborators

• Prince of Songkla University

  collaborator OTHER

• AstraZeneca

  collaborator INDUSTRY

• Gia Dinh People Hospital

  lead OTHER

Principal Investigators

• Kiet Anh Vu, MPH · Nhan dan Gia Dinh Hospital

Study Design

Allocation

RANDOMIZED

Purpose

SUPPORTIVE_CARE

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

40 Years

Max Age

62 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2025-11-15

Primary Completion

2026-12-30

Completion

2027-12-30

Countries

• Vietnam

Study Locations