Association of glucose control and stages of change for multiple self-management behaviors in patients with diabetes: A latent profile analysis. Issue 1 (January 2020) - Shen, Ying; Wang, Taotao; Gao, Min; Wang, Fengbin; Zhu, Xiaorou; Zhang, Xing; Li, Dongmei; Gan, Yadi; Zhang, Yong; Gao, Yanqing; Sun, Xinying
Highlights: We combined the use of latent profile analysis and transtheoretical model. The above two methods could be used jointly to understand diabetic patients' characteristics. LPA classified patients into four groups based on their self-management behavior. Abstract: Objective: To determine whether the joint use of the transtheoretical model and latent profile analysis could help us better understand the shared characteristics of patients with diabetes and explore the association of patients' latent classes and glucose control. Methods: Five hundred twenty-three (523) patients with diabetes were included in the study. The questionnaire evaluated patients' stages of change for medication-taking, diet control, exercise, and glucose-monitoring. Latent profile analysis was performed based on the four indicators. Results: Patients were classified into four latent groups and defined as follows: good medication-taking/good lifestyle (GM/GL, 41.7%), poor medication-taking/poor lifestyle (PM/PL, 27.7%), good medication-taking/poor lifestyle (GM/PL, 21.6%), and poor medication-taking/good lifestyle (PM/GL, 9.0%). Patients in the PM/PL group were generally younger and better educated while those in the GM/GL group exhibited the opposite pattern. Compared with patients in the PM/PL group, those in the PM/GL and GM/GL groups had significantly lower HbA1c values (PM/GL: standardized β = -0.694, P  =  0.007; GM/GL: standardized β = -0.499, P  =  0.003). Conclusion: With the help of the transtheoretical model and latent profile analysis, future study could cluster homogeneous patients before the initiation of intervention and provide tailored instructions to different types of patients accordingly. Practice implications: A combination of the transtheoretical model and latent profile analysis could shed some light into future diabetic interventions.