A WeChat-Based Decision Aid Intervention to Promote Informed Decision-Making for Family Members Regarding the Genetic Testing of Patients With Colorectal Cancer: Randomized Controlled Trial

Background: Identifying patients with inherited colorectal cancer (CRC) syndromes offers many potential benefits. However, individuals often experience decisional conflict regarding genetic testing for CRC, and the uptake rate remains low. Given the growing popularity of genetic testing and the increasing demands on genetic service providers, strategies are needed to promote informed decision-making, increase genetic testing uptake among at-risk individuals, and ensure the rational use of genetic service resources. Objective: This study aims to determine whether a decision aid (DA) tool could promote informed decision-making among family members regarding the genetic testing of a patient with CRC. Methods: A single-center, parallel-group, randomized controlled trial was conducted. We randomized 82 family members of patients with CRC, who were involved in major medical decision-making for the patient, to either a DA intervention or usual care. The primary outcome was informed decision-making, assessed through measures of knowledge, decisional conflict, decision self-efficacy, and preparation for decision-making. Secondary outcomes included patients’ uptake of genetic counseling and testing, participants’ CRC screening behavior, healthy lifestyle scores, anxiety and depression levels, quality of life, and satisfaction with the intervention. Data were collected at baseline (T0), after the intervention (T1), and 3 months after the baseline survey (T2). The DA intervention and outcome assessments at T1 and T2 were delivered via WeChat. The effects of the intervention were analyzed using generalized estimating equation models. Results: Statistically significant improvements were observed in knowledge (T1: β=2.049, P<.001; T2: β=3.317, P<.001), decisional conflict (T1: β=–11.660, P<.001; T2: β=–17.587, P<.001), and decision self-efficacy (T1: β=15.353, P<.001; T2: β=22.337, P<.001) in the DA group compared with the usual care group at both T1 and T2. Additionally, the DA group showed significantly greater improvement in processed and red meat intake (β=–1.494, P<.001) at T1 and in healthy lifestyle scores (β=1.073, P=.03) at T2. No differences were found between the groups for other outcomes. Conclusions: A DA tool may be a safe, effective, and resource-efficient approach to facilitate informed decision-making about genetic testing. However, the current DA tool requires optimization and further evaluation—for example, by leveraging more advanced technology than WeChat to develop a simpler and more intelligent DA system.