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:  O  bjective : To determine the characteristics of members of online diabetes communities as well as those factors affecting the provision and acceptance of social support. M  ethods : A cross-sectional STAR questionnaire survey was conducted among patients with diabetes who were members of online diabetes groups. Univariate and multivariate binary logistic regression analysis were adopted to explore the relative analysis of providing and accepting social support compared with the characteristics of members in virtual diabetics' groups. R  esults : A total of 1297 respondents were collected. The map distribution of patients in China was mainly located in the Guangdong, Jiangsu, Shandong, Henan, and Hebei provinces. As for their demographic characteristics, respondents had diabetes or prediabetes and were between the ages of 21 and 50 years (Median age was 35.0 (interquartile range from 28.0 to 44.0)). Most respondents were married and lived in cities. The education level of patients was mainly distributed throughout junior high, technical secondary, high school, junior college, and undergraduate levels. Age, marital status, and education level varied by gender, and the total score of the patients aged 41 to 50 for social support had a statistical significance between male and female. In addition, when group members were in junior high school or below, or were undergraduate students, their total social support scores varied by gender. Binary logistic regression showed that in 21 independent variables the total score and the total score grade of relationship intensity in the online group and reorganize of age were significant. The patients' social support acceptance of the map of respondents score grading of relationship intensity in the online group was 5.420 times higher than that of the lower score grading of relationship intensity in the group. At the same time, the patients' social support acceptance of the patients at the age of less than or equal to 31 years old was 19.608 times higher than that of group members aged more than 31 years old. Conclusion: Age and education background of the patients affects scores of social supports between males and females. The higher the total score and the score grade of relationship intensity in the online group, the higher the patients' social support acceptance. The younger patients had a better utilization of social support.

Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population