According to the validation literature on items of Young’s Internet Addiction Test (IAT), this study rephrased disputable items to improve the psychometric properties of this Chinese version of IAT and identify the presence of differential item function (DIF) among demographic and Internet use factors; detect the effect of demographic and Internet use factors on IAT after adjusting for DIF. An online questionnaire was distributed to college students in Zhe Jiang province in two stage. The 1st phase study collected 384 valid responses to examine the quality of IAT items by using Rasch Model analysis and exploring factor analysis (EFA). The online questionnaire was modified according to the 1st phase study and distributed online for the 2nd phase study which collected a total of 1131 valid responses. The 2nd phase study applied confirmatory factor analysis (CFA) and a multiple indicator multiple causes (MIMIC) model to verify the construct of IAT, potential effect of covariates on
Background: Globally, diabetes brought an enormous burden to public health resources and the situation of disease burden caused by diabetes in China is especially severe. China is currently facing the dual threat of aging and diabetes, and wearable activity trackers could promote elderly diabetic patients’ physical activity levels and help them to manage blood glucose control. Therefore, examining the influencing factors of elderly patients’ adoption intention is critical as wearing adoption determines actual wearing behaviors. Objective: This study aims to explore the predicting factors of Chinese elderly type 2 diabetic patients’ adoption intention to wearable activity trackers and their actual wearing behavior, using Diffusion of Innovation Theory as the theoretical framework. We hope to provide insights to future interventions using wearable activity trackers as tools to improve patients’ outcome. Methods: Wearable activity trackers were freely distributed to type 2 diabeti