A Mixed Methods Process Evaluation of a Clustered-Randomized Controlled Trial to Determine the Effects of Community-Based Dietary Sodium Reduction in Rural China

Purpose: A clustered-randomized controlled trial was conducted to determine the effects of a sodium reduction program in 120 rural villages in Northern China. This mixed-methods process evaluation was used to investigate the implementation and to evaluate the feasibility of the complex intervention to translate the findings from clinical study to the real world. Methods: A convergent mixed-methods process evaluation design was used in this study. Quantitative data were collected from activity logs and routine study records. Qualitative data were collected from 53 project stakeholders and 45 villagers from 10 intervention villages. Thematic analysis of qualitative interviews facilitated integration with the descriptive quantitative data analysis based on theory-informed domains of fidelity, delivery, reach, receipt, and contextual factors of intervention from a process evaluation framework. Results: The intervention was implemented with high fidelity, delivery, reach, and receipt. A total of 5,450 sheets of posters, 31,400 calendars, and 78,000 sheets of stickers were delivered as planned, and 11 promotion activities were conducted in each village. Contextual factors hindering full uptake of the intervention included preference for salty taste, higher cost of low-sodium salt, and low education levels of villagers. Other contextual factors, positive policy support, administrative support, and staff enthusiasm were the facilitators for implementation. Conclusions: This multifaceted intervention was implemented well and effectively in rural China. This process evaluation has indicated that conducting health education interventions in rural areas requires policy and administrative support, enthusiastic staff, easy-to-understand health education materials and activities, and key persons, but tempered expectations as behavior change requires time. This project demonstrates the feasibility and benefits of using mixed-methods process evaluation in large-scale studies.