RÉSUMÉ
Lifestyle is a critical aspect of diabetes management. We aimed to define a healthy lifestyle using objectively measured parameters obtained from a wearable activity tracker (Fitbit) in patients with type 2 diabetes. This prospective observational study included 24 patients (mean age, 46.8 years) with type 2 diabetes. Expectation–maximization clustering analysis produced two groups: A (n=9) and B (n=15). Group A had a higher daily step count, lower resting heart rate, longer sleep duration, and lower mean time differences in going to sleep and waking up than group B. A Shapley additive explanation summary analysis indicated that sleep-related factors were key elements for clustering. The mean hemoglobin A1c level was 0.3 percentage points lower at the end of follow-up in group A than in group B. Factors related to regular sleep patterns could be possible determinants of lifestyle clustering in patients with type 2 diabetes.
RÉSUMÉ
Objectives@#This study is designed to extract a representative variable that distinguishes psychiatric patients of North Korean Defectors and a control group by using machine learning based on measured mental health variables and physical activity variables. @*Methods@#The physical and mental activity variables of 17 North Korean defectors that previously were hospitalized or received psychiatric outpatient treatment and a control group were compared. The survey focused on mental health variables that included contents related to depression, suicidal risks, post-traumatic stress disorder, anxiety, insomnia, physical symptoms, quality of life, coping skills, social support, and drinking. Physical activity variables included the number of steps walked per day, sleep time, and sleep efficiency were measured by Fitbit. @*Results@#The 7th question of the Patient Health Questionnaire-9, “Trouble concentrating on things, such as reading the newspaper or watching television over the past two weeks,” showed the highest gain ratio by 84 percent. Based on the result of the decision tree, this single index may distinguish between the clinical and control groups. @*Conclusion@#A clinician may conduct a more effective interview with a North Korean defector by identifying in the early stages whether the patient has been having difficulty concentrating on daily tasks during the past two weeks.
RÉSUMÉ
Objectives@#This study is designed to extract a representative variable that distinguishes psychiatric patients of North Korean Defectors and a control group by using machine learning based on measured mental health variables and physical activity variables. @*Methods@#The physical and mental activity variables of 17 North Korean defectors that previously were hospitalized or received psychiatric outpatient treatment and a control group were compared. The survey focused on mental health variables that included contents related to depression, suicidal risks, post-traumatic stress disorder, anxiety, insomnia, physical symptoms, quality of life, coping skills, social support, and drinking. Physical activity variables included the number of steps walked per day, sleep time, and sleep efficiency were measured by Fitbit. @*Results@#The 7th question of the Patient Health Questionnaire-9, “Trouble concentrating on things, such as reading the newspaper or watching television over the past two weeks,” showed the highest gain ratio by 84 percent. Based on the result of the decision tree, this single index may distinguish between the clinical and control groups. @*Conclusion@#A clinician may conduct a more effective interview with a North Korean defector by identifying in the early stages whether the patient has been having difficulty concentrating on daily tasks during the past two weeks.