RESUMEN
Objective: To investigate the current status of diabetes self-care behavior and the association between depression, self-efficacy and self-care in a sample of Chinese elderly type 2 diabetes mellitus (T2DM) patients. Methods: A cross-sectional study with a convenient sample including 240 elderly T2DM patients collected the data of demographic characteristics, diabetes self-care behavior, self-efficacy and depression status. The difference of self-care behavior in different sample characteristics was compared by independent t-test. The Personal correlation analysis was employed to examine the correlation of study variables. The method of bootstrap was used to analyze mediating role of depression. Results: Only 22.5% of patients reported better diabetes self-care behavior and depression partly mediated the association between self-efficacy and self-care behavior. The significant coefficient of path a (B = -0.052, p < 0.001) and path b (B = -0.423, p < 0.05) indicated negative associations of self-efficacy on depression, and depression on self-care behavior. The indirect effect (Path a × b) between self-efficacy and self-care behavior through depression was significant (B = 0.022, p < 0.05), the 95% bias-corrected bootstrap confidence interval was 0.004 to 0.006. Meanwhile, the mediating role of depression was not found significant among the participants reported 60-74 years old (B = 0.104, p < 0.001). But depression completely mediated this association among the participants reported 75-89 years old (B = 0.034, p > 0.05). Conclusion: The level of diabetes self-care behavior among the elderly T2DM patients in Dahu community of Anqing city was hardly optimistic. The self-efficacy focused intervention could be encouraged for community and clinicians to improve diabetes self-care behavior. Moreover, the prevalence of depression and T2DM is increasing in younger population. More work is needed to confirm these findings, especially conducting cohort studies on different populations.
RESUMEN
Freehand exercises help improve physical fitness without any requirements for devices or places. Existing fitness assistant systems are typically restricted to wearable devices or exercising at specific positions, compromising the ubiquitous availability of freehand exercises. In this paper, we develop MobiFit, a contactless freehand exercise assistant using just one cellular signal receiver placed on the ground. MobiFit passively monitors the ubiquitous cellular signals sent by the base station, which frees users from the space constraints and deployment overheads and provides accurate repetition counting, exercise type recognition and workout quality assessment without any attachments to the human body. The design of MobiFit faces new challenges of the uncertainties not only on cellular signal payloads but also on signal propagations because the sender (base station) is beyond the control of MobiFit and located far away. To tackle these challenges, we conducted experimental studies to observe the received cellular signal sequence during freehand exercises. Based on the observations, we constructed the analytic model of the received signals. Guided by the insights derived from the analytic model, MobiFit segments out every repetition and rest interval from one exercise session through spectrogram analysis and extracts low-frequency features from each repetition for type recognition. Extensive experiments were conducted in both indoor and outdoor environments, which collected 22,960 exercise repetitions performed by ten volunteers over six months. The results confirm that MobiFit achieves high counting accuracy of 98.6%, high recognition accuracy of 94.1% and low repetition duration estimation error within 0.3 s. Besides, the experiments show that MobiFit works both indoors and outdoors and supports multiple users exercising together.
