基于“AI + 行为科学”的体重管理微信小程序开发

Development of a WeChat Mini Program for Weight Management Based on “AI + Behavioral Science”

摘要: 传统体重管理存在数据采集繁琐、干预方案落地难的情况，用户长期依从性不足。为响应《健康中国行动》和《“十四五”国民健康规划》的要求，本研究设计了一款体重管理小程序。小程序以微信原生框架结合Python Flask为技术基础，搭配Vant Weapp组件库构建三层轻量化架构，实现多模态数据采集、个性化健康建议生成，通过目标梯度拆解与社群打卡强化行为激励；同时采用HTTPS加密存储用户敏感数据，超6个月的历史数据自动匿名化处理，保障数据安全。经检验，小程序实现了轻量化加载与高效数据采集，契合18~35岁目标用户便捷、精准的使用需求，为体重管理数字化工具开发提供可复用方案，助力健康管理从粗放式向精准化转型。

Abstract: Traditional weight management faces challenges of tedious data collection processes, difficulty in implementing intervention plans, and low long-term user adherence. To implement the obesity prevention and control orientation of the “Healthy China Initiative” and the digitalization deployment for chronic disease prevention and control in the “‘14th Five-Year’ Plan for National Health”, this study developed a WeChat mini program for weight management. Built on the technical core of the WeChat native framework and Python Flask, integrated with the Vant Weapp component library and common data tools, the development process conducted demand analysis, system design, and function implementation, constructing a three-tier lightweight architecture. The mini program can complete multimodal data collection and generate personalized health recommendations, and also enhances behavioral incentives through goal gradient decomposition and community check-in interactions. Meanwhile, it adopts HTTPS encryption to store users’ sensitive data and automatically anonymizes historical data older than 6 months, building a solid data security barrier. After technical verification, the mini program has achieved the design goals of lightweight loading and efficient data collection, which well meets the core needs of convenience and accuracy for target users aged 18~35. It provides a reusable practical solution for the development of digital weight management tools and helps promote the transformation of health management from extensive to precise.