This study was designed as a 12-week, nonblinded randomized controlled trial to examine the efficacy of a WeChat-based intervention in patients with T2DM between September 2020 and December 2020. These participants were recruited from 3 community health service centers and followed up on at 12 weeks and 2 years after the intervention. Family physicians followed up on patients with diabetes via telephone to introduce the trial and determine potential participants’ willingness to take part. These participants had established health records and had signed up for contracted family physician services at 3 community health service centers in Chongqing, China. Before the trial started, all the researchers involved were trained in uniform protocols, including trial procedures, questionnaires, and the use of the WeChat mini program and public account. A CONSORT (Consolidated Standards of Reporting Trials) checklist was completed to guide the trial’s design, analysis, and findings (Checklist 1). Before conducting the formal research, we carried out a feasibility study, as shown in Multimedia Appendix 1.

On the basis of the inclusion and exclusion criteria, the family physician teams selected eligible participants for registration. The inclusion criteria for enrollment were as follows: (1) participants who were diagnosed with T2DM and met the 1999 World Health Organization diagnostic criteria; (2) receipt of the contracted family physician service within the validity period; (3) ability of the participants to undergo face-to-face interviews and voluntary participation in the trial; and (4) ownership of a smartphone and familiarity with the WeChat app, including chatting, subscribing to WeChat public accounts, and using WeChat mini programs. The exclusion criteria for this study were as follows: (1) participants with severe complications, such as ketoacidosis or hyperosmolar nonketotic diabetic coma; (2) participants with severe heart disease who would not tolerate moderate-intensity exercise; (3) participants who could not answer the questions clearly; and (4) participants who were taking part in other intervention studies.

A total of 900 eligible patients with T2DM were recruited by family physician teams from 3 communities, of whom 300 (33.3%) were excluded. Of these 300 excluded patients, 196 (65.3%) did not meet the inclusion criteria, 79 (26.3%) refused to participate, and 25 (8.3%) were excluded for other reasons. A total of 600 participants were randomized into the intervention group (n=300, 50%) or the control group (n=300, 50%). Moreover, 556 participants completed the 12-week follow-up visit (intervention: n=278, 50%; control: n=278, 50%), and the retention rate was 92.7% (556/600).

The sample size was calculated based on a completely random design using the tests for 2 proportions. The trial was designed for analysis via 2-tailed tests, with type I and II error rates set at 0.05 and 0.2, respectively. A priori sample size calculations were conducted for the primary outcome of hemoglobin A_1C (HbA_1c) control rate (proportion of <7%). On the basis of national epidemiological data [1], the retention rate in the control group was estimated to be 35.2% in this study. We hypothesized that an 11% absolute risk reduction in the intervention group (24.2% event rate) derived from conservative adaptation of the Finnish Diabetes Prevention Study [21] would account for our digital intervention modality. With these parameters in the PASS software (version 15.0; NCSS, LLC), the total sample size required was 267 in each group. Considering a dropout rate of up to 10%, the final sample size was determined to be 300 patients in each group.

After the willingness of patients to participate in the study was confirmed by the family physician teams, the baseline data of the participants were collected at the community health service centers. Randomization was performed by an independent statistician who generated the allocation sequence through computerized random number generation. The participants were assigned in a 1:1 ratio to the study groups, with allocation concealment ensured via opaque, sealed envelopes that were sequentially numbered.

Our multidisciplinary diabetes health education teams [22] were composed of the following: (1) a total of 18 family physicians from 6 family physician teams at 3 community health centers who were responsible for directly managing patients with diabetes and providing sustainable health education services; (2) an online health assistant who was responsible for functional maintenance and training on the health education platform; and (3) health education experts from the Military Health Education Center, including endocrinologists, rehabilitation therapists, ophthalmologists, dietitians, and coaches.

The WeChat-based health education tool used in our study consisted of the WeWalk mini program, the Bayu Health public account, and the WeChat group. The WeWalk mini program, an interactive mobile health platform, integrates 5 core functional modules designed to promote diabetes self-management through physical activity monitoring and community engagement. This gamified intervention system uses behavioral economics principles and social cognitive theory to enhance users’ health literacy and sustainable behavior change. Participants in the WeChat-based intervention group carried out daily health education activities to promote healthy behaviors. The WeChat public account Bayu Health was used to push diabetes self-management courses for the intervention group. The WeChat group was used mainly to organize and guide patients to participate in intervention activities. Multimedia Appendix 2 presents the functional modules of the WeWalk mini program and shows the QR codes of the WeWalk mini program and the Bayu Health public account.

The participants underwent 2 follow-up assessments: after the intervention (12 weeks) and in the long term (2 years after the intervention). To assess the condition of the patients, the primary outcome measure of the study was the change in fasting blood glucose (FBG) and HbA_1c levels in the 2 groups at baseline and 12 weeks after the intervention began. The secondary outcomes included changes in weight, BMI, waist circumference, hip circumference, systolic blood pressure, diastolic blood pressure, and serum lipid profiles. Baseline assessments included standardized questionnaires capturing demographics, medical and treatment history, comorbidities, and lifestyle factors, alongside fasting-state physical examinations conducted by certified personnel at community health service centers. Longitudinal glycemic control was assessed through triplicate FBG measurements extracted from standardized electronic health records at the 2-year follow-up.

Data were double entered using EpiData (EpiData Association) and analyzed using SPSS (version 26; IBM Corp). Normally distributed variables expressed as means and SDs were compared using independent t tests; nonparametric variables reported as medians and IQRs were analyzed via Mann-Whitney U tests. Demographic (sex, educational level, and annual family income), clinical (hypoglycemic medication use and diabetic complications), and behavioral (smoking and alcohol use) variables were analyzed using the chi-square test at baseline. The chi-square test was used to test the differences in HbA_1c data before and after the intervention. Patients with diabetes were divided into 2 categories according to their HbA_1c levels: HbA_1c<7% (normal) and HbA_1c≥7% (abnormal) according to the guidelines for the prevention and treatment of T2DM in China (2017) [23]. P<.05 was considered statistically significant.

This study was approved by the Army Medical University medical ethics committee (approval 2020-007-02) and registered at the Chinese Clinical Trial Registry (ChiCTR2300071926). Written informed consent was obtained from all participants before enrollment. All data were deidentified for analysis and stored securely to ensure confidentiality. Participants received no financial compensation but were provided with free medical checkups, medication guidance, and healthy lifestyle guidance.

This study evaluated the short-term efficacy of a WeChat-based health education tool in primary care through a 12-week randomized trial with a 2-year follow-up on glycemic control. After 12 weeks, the intervention group had improved HbA_1c and FBG levels compared with those of the control group, especially in patients with diabetes with a disease duration of <10 years, an educational level of junior high school or lower, and a annual family income of <CN ¥50,000 (US $7172.10) . Significant between-group differences were found in waist circumference and triglycerides, but no significant changes were observed in BMI, hip circumference, WHR, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, or diastolic blood pressure. Two years after the intervention, FBG levels were significantly lower in the intervention group. However, the change in FBG from baseline was not significantly different between the groups.

Our study adds to the growing body of international evidence confirming the efficacy of digital health interventions, including smartphone apps and telemedicine, in improving diabetes outcomes [24-26]. This global consensus is strongly supported by a series of studies in China that have demonstrated the effectiveness of telemedicine and app-based interventions for glycemic control [27-29]. Specifically, with respect to the WeChat platform, our results are consistent with and reinforce findings from regional studies in the Jiangsu [19], Jilin [30], and Henan [31] provinces. The convergence of evidence from these diverse settings solidifies the view that WeChat-based health education is a viable and effective strategy for improving blood glucose levels in patients with T2DM. The intervention likely works by first improving disease knowledge through structured education [20]; then increasing self-efficacy via interactive support [32]; and, finally, enhancing adherence to medication and healthy behaviors through regular reminders and self-monitoring [33].

We found that the reduction in the HbA_1c level in the intervention group was lower than that reported in other studies according to a systematic review of self-management among patients with type 2 diabetes via the WeChat app [34]. A similar eHealth intervention in Shanghai demonstrated a greater HbA_1c reduction (7.9% to 7.3%) than our study (7.39% to 7.35%) [28]. This difference may be attributed to regional disparities in health care infrastructure [35-37] and a critical design variation: their single-platform (WeChat public account) intervention likely offered a simpler user experience, whereas our multimodule design incorporating a mini program may have increased operational complexity for participants.

We found that WeChat-based health education improved the HbA_1c level in patients with diabetes with low income, low educational level, and short disease duration who contracted family physicians. Currently, health apps designed to enhance self-management of chronic illnesses require continuous patient involvement as a pivotal factor influencing clinical effectiveness [38-40]. A meta-analysis revealed that the dropout rate in clinical trials for smartphone apps was significantly higher among high-income countries than among lower-middle–income countries [41]. A national web-based survey in China revealed that educational level and family income were associated with diabetes management app use in adult patients [42]. We speculated that patients with diabetes with shorter disease durations would have better acceptance of the WeChat-based health education tool, those with low educational levels would have higher expectations for our intervention, and our free program would be more attractive to low-income patients with diabetes.

Moreover, we found that the waist circumference and WHR in the intervention group were significantly lower than those in the control group. Indeed, sex was a confounding factor, with the waist circumference and WHR of female patients being out of balance in the 2 groups before the intervention. We observed that the BMI values increased in both groups after the intervention, presumably related to the end of the intervention in the winter. People are more likely to eat more food during the Spring Festival in China [43,44]. However, WeChat-based health education was effective in helping patients with diabetes control their body shape in the winter, which was similar to the findings of other studies [45].

The intervention was constructed based on the WeChat mini program and public account, which enhances communication between family physicians and patients [46]. The family physicians’ online virtual clinics were set up on the WeWalk mini program to help patients easily contact their contracted family physicians. Compared with other diabetes management mobile apps, the WeWalk mini program is free to download and use and easy to operate, reducing the likelihood of users discontinuing use [42]. Furthermore, subgroup analysis revealed that WeChat-based health education was effective for glucose control based on evidence from 3 communities. The WeChat mini program provides remote supervision and ongoing support for patients and physicians, which makes it easy to achieve continuous efficacy in the long term [47]. We suggest integrating effective, low-cost digital solutions such as this WeChat mini program into national chronic disease management strategies. Further validation is needed to assess its efficacy in rural settings with different health care infrastructures.

Our study has several limitations. First, due to the impact of COVID-19, formal follow-up was only conducted at 12 weeks, and only the short-term effects of WeChat-based health education were observed in our study. Regarding the long-term effects of WeChat-based health education, only FBG was evaluated in this study. However, this result still needs to be further evaluated through other indicators. Second, this study was based on 3 community health service centers but was not a cluster randomized controlled trial, which may lead to insufficient accuracy of the study results. Although the authorized supervisor prevented information contamination, they may have unintentionally disclosed intervention details while managing both groups. Third, no implementation fidelity data such as user engagement and use frequency of the intervention group were collected and analyzed. Finally, a future cost-effectiveness analysis and continuous real-world optimization are crucial next steps to definitively inform policy. We could explore incorporating artificial intelligence to provide more personalized, patient-specific educational content and support, thereby enhancing the scalability and integration of this WeChat-based intervention.

We conducted a randomized controlled trial in community-dwelling patients with T2DM to examine the efficacy of a WeChat-based health education intervention in Chongqing, China. By strategically integrating social media platforms with primary care services, this WeChat-based health education intervention achieved significant results in improving glycemic control in patients with T2DM. Future investigations should use longitudinal designs to evaluate the sustained efficacy and feasibility of implementing WeChat-based health education.