A Randomized Controlled Trial to Increase Breast Cancer Screening Uptake

NCT ID: NCT06722469

Last Updated: 2024-12-09

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 470 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-07-01
• Study Completion Date: 2027-12-31

Brief Summary

Breast cancer (BC) is the fifth leading cause of cancer deaths in women worldwide. In Hong Kong (HK), BC is the most common cancer, ranking third in cancer deaths among females. International guidelines advocate regular mammographic screening for women aged 40-50 to 69-74, reducing BC mortality by 20%.

The success and effectiveness of an organized cancer screening program are largely dependent on high adherence or uptake rates. However, nonadherence to BC screening is common and the suboptimal uptake rate remains a challenge, particularly in Asian countries.

Conventional interventions are effective in increasing mammographic screening uptake but are time-consuming, labor-dependent, and expensive. Mobile messenger chatbots are a potential cost-saving tool for enhancing BC screening uptake because they involve only a one-off development cost and a small maintenance cost . Currently, most studies evaluating the effectiveness of mobile health interventions in improving mammography screening uptake have been conducted in Western populations . Health-seeking behaviors for cancer screening in the Chinese population differ from those of Caucasians because of differences in culture, health beliefs, and education, especially regarding breast-related diseases. Chinese women often feel embarrassed when talking with healthcare workers in person about breast health. Communicating with a fully automated chatbot can minimize embarrassment. Additionally, linguistically and culturally tailored interventions are effective in increasing cancer screening rates in the Chinese population.

However, studies evaluating combined theory-based mHealth interventions to enhance BC screening uptake are scarce. Two theory-based WhatsApp chatbots were developed to promote CRC screening, and the longitudinal repeat fecal immunochemical test (FIT) adherence rate of a population-based CRC screening program in HK. These two chatbots used in investigator's previous studies had designs similar to that of the proposed chatbot, except for the health education materials. The chatbot design can be adopted directly with minor modifications to the workflow, replacement of content from CRC screening-related to BC screening-related, and culturally modified education materials. Consequently, the investigators can develop a new chatbot for this study at a lower cost and in a shorter time.

Detailed Description

In the past two decades, internet and mobile phone usage has increased due to affordability. The COVID-19 pandemic has further necessitated online and phone-based healthcare, paving the way for less labor-intensive, cost-effective mHealth interventions. These include short message service (SMS) text messages, telephone calls, email, social media, and mobile apps, which have significantly boosted BC screening uptake by 1.2%-50.9%. Among them, manual calls and SMS are prevalent methods. Manual calls facilitate interactions with subjects, aiding informed decision-making and participation but require high manpower. Although SMS offers automatic communication and chatbot features, each message costs approximately HKD$0.2, posing long-term economic challenges, especially for population-based interventions. Conversely, chatbots based on mobile messengers, like WhatsApp are less expensive due to unlimited free text and multimedia messaging across different mHealth operating systems. WhatsApp is globally prevalent, including in HK and has been successfully implemented in various clinical settings. Given these promising results, the investigators believe that mobile messenger-initiated chatbots have an extended role in the BC screening uptake rate because of the ubiquity, acceptability, and effectiveness of mHealth interventions. However, studies evaluating combined theory-based mHealth interventions to enhance BC screening uptake are scarce.

Conditions

Breast Cancer Prevention; Breast Cancer Risk

Keywords

breast cancer; automated chatbot; breast cancer screening; health belief model

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: SINGLE

Study Groups

WCI

The WCI group will receive automated messages based on the Health Belief Model (HBM) and Protection Motivation Theory (PMT), including personalized risk assessments, educational videos featuring medical professionals and relatable scenarios, and tailored prompts to encourage mammographic screening.

Group Type: EXPERIMENTAL

WCI

Intervention Type: OTHER

The WCI group will receive automated messages based on the Health Belief Model (HBM) and Protection Motivation Theory (PMT), including personalized risk assessments, educational videos featuring medical professionals and relatable scenarios, and tailored prompts to encourage mammographic screening.

STR

A standard tet reminder will be sent regarding the breast cancer screening program

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

WCI

The WCI group will receive automated messages based on the Health Belief Model (HBM) and Protection Motivation Theory (PMT), including personalized risk assessments, educational videos featuring medical professionals and relatable scenarios, and tailored prompts to encourage mammographic screening.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

1. asymptomatic Chinese Women

2. 44-69 years old

3. eligible to enroll in a government-subsidized risk-stratified BC screening program

4. ability to read Chinese

Exclusion Criteria

1. moderate- or high-risk women as defined by the local risk-stratified BC screening program

2. inability to provide informed consent

3. incomplete conversation with the chatbot.

• Minimum Eligible Age: 44 Years
• Maximum Eligible Age: 69 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

Chinese University of Hong Kong

OTHER

Sponsor Role: lead

Responsible Party

Thomas Yuen Tung Lam

Assistant Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Central Contacts

Thomas Lam, PhD in Medical Science

Role: CONTACT

Phone: 852-26370428

Email: thomaslam@cuhk.edu.hk

Felix Sia, Master of Science

Role: CONTACT

Phone: 26370428

Email: felixsia@cuhk.edu.hk

Other Identifiers

2024.527

Identifier Type: -

Identifier Source: org_study_id