[Accuracy verification of diet recording tool based on WeChat applet]

Area of Science:

• Nutrition Science
• Digital Health Technology
• Dietary Assessment Methods

Context:

• Accurate dietary assessment is crucial for understanding nutritional status and public health.
• Mobile health (mHealth) applications offer potential for efficient and accessible dietary data collection.
• Traditional dietary assessment methods can be resource-intensive and prone to recall bias.

Purpose:

• To evaluate the accuracy and reliability of the "Zhishi AI Dietitian" mobile application for recording dietary intake among university students.
• To compare the data generated by the Zhishi AI Dietitian with a standard 24-hour dietary recall method.

Summary:

• A study involving 109 university students compared the Zhishi AI Dietitian applet with a 24-hour dietary recall over three non-consecutive days.
• Both methods showed reliability in assessing food, energy, and nutrient intake, with enhanced reliability for nutrients after energy correction.
• Correlation analyses revealed moderate to strong coefficients (0.34-0.79) for food groups and (0.34-0.72) for energy and nutrients, indicating good agreement.

Impact:

• The findings suggest that the Zhishi AI Dietitian is a valid and accurate tool for dietary assessment in a student population.
• This technology has the potential to improve the ease and efficiency of dietary data collection in research and clinical settings.
• The study supports the use of mHealth tools for promoting nutritional awareness and facilitating dietary interventions.