Background Although lifestyle interventions are useful in the prevention and management of diabetes, they can be expensive and time-consuming. There is some evidence on the effectiveness of automated mobile technology for health self-monitoring; however, few studies have used such devices in the occupational health field. Objective We aimed to examine the effectiveness of a digital self-monitoring device on glucose levels and activity of workers with diabetes in Japan. The primary outcomes were changes in blood glucose levels, and the secondary outcomes were changes in weight and BMI. Methods A 2-arm randomized controlled pilot trial was conducted with workers from 23 organizations. The intervention group (n=50) wore an armband activity monitor, a body composition monitor, and a blood pressure monitor for 3 months and received semiautomated weekly email messages tailored to their device data. The control group (n=53) engaged in no self-monitoring. Messages were developed by a physician and a dietician. Postintervention changes in blood glucose levels, weight, and BMI were compared between the intervention and control groups, using blood tests and questionnaires. Results At the end of 3 months, the intervention group showed significantly lower blood glucose levels (HbA1c: intervention group mean 6.4% (SD 0.3%) vs control group mean 6.6% (SD 0.3%); Cohen d=0.7, 95% CI 0.2-1.1; P=.009). There were no significant between-group differences in weight and BMI. Conclusions Mobile digital self-monitoring was effective in improving blood glucose levels in workers with diabetes. The use of digital health devices is a cost-effective way of implementing health self-monitoring for large numbers of individuals in the workplace. However, due to the large volume of missing values in this study, we need to be careful in interpreting the results, and well-designed intervention studies need to be conducted. Trial Registration University Hospital Medical Information Network UMIN000023651; https://upload.umin.ac.jp/cgi-open-bin/icdr/ctr_view_cb.cgi?recptno=R000027244&flwp_key=1008PYbOcXKmk7CAg4Th1FWS

BACKGROUND Although lifestyle interventions are useful in prevention and management of diabetes, they can be expensive and time-consuming. There is some evidence for the effectiveness of automated mobile technology for health self-monitoring, however, no studies have used such devices with prediabetes workers. OBJECTIVE We aimed to examine the effectiveness of a 3-month digital self-monitoring device on glucose levels and health behaviors of prediabetes workers in Japan. The primary outcome was blood glucose levels and the secondary outcomes were changes in health behaviors and BMI. METHODS A two-arm randomized controlled trial was conducted with workers from 23 organizations. The intervention group (n=50, data analyzed for n=46) wore an armband activity monitor, a body composition monitor, and a blood pressure monitor for 3 months and received semi-automated weekly email messages tailored to their device data. The control group (n=53, data analyzed for n=48) engaged in no self-monitoring. Messages were developed by a physician and a dietician. Post-intervention changes in blood glucose levels, BMI, and health behaviors were compared between the intervention and control groups using blood tests and device data. RESULTS At the end of 3 months, the intervention group showed significantly lower blood glucose levels (HbA1c [%]: intervention mean 6.4 vs. control mean 6.6; Cohen d=0.7; 95% CI 0.2-1.1; P=.009) and significantly greater motivation to increase their daily exercise than the control group. There were no significant between-group differences in BMI or health behaviors. CONCLUSIONS Mobile digital self-monitoring was effective in improving blood glucose levels and motivation to increase daily exercise in prediabetes workers. The use of digital health devices is a cost-effective way of implementing health self-monitoring for large numbers of individuals in the workplace. CLINICALTRIAL This study is registered with the University Hospital Medical Information Network (UMIN000023651).