Health information needs regarding diabetes mellitus in China: an internet-based analysis

Abstract

Abstract Background Today,. most people use the Internet to seek online health-related information from general public health-related websites and discussion groups. However, there are no Internet-based analyses of health information needs pertaining to diabetes in China until now. With the development of artificial intelligence,we can analyzed these online health-related information and provide references for health providers to improve their health service. Methods We have done a study of statistically analyzing the questions about diabetes collected from 39 health website, the number of which is 151,589. We have divided these questions into 9 categories using a convolutional neural network. Results The diabetes problems of consumer are presented as follows, diagnosis: 34.95%, treatment: 25.17%, lifestyle: 21.09%, complication: 8.00%, maternity-related:5.00%, prognosis: 2.59%, health provider choosing: 1.40%, prevention: 1.23%, others: 0.58%, The elderly are more concerned about the treatment and complications of diabetes, while the young are more concerned about the maternity-related and prognosis of diabetes. The diabetes drugs most frequently mentioned by consumers are insulin, metformin and Xiaoke pills, The most concerned complication is caidiovascular disease and diabetic eye disease. Conclusion Diabetes health education should focus on how to prevent diabetes and the contents of health education should be different for differernt age groups;on diabetes treatment, the use of insulin and oral hypoglycemic drugs education should be strengthened.

Keywords

• Machine learning
• Diabetes mellitus
• Question classification
• Consumer health information
• Health problem