Abstract
Glycemic control in type 1 diabetes mellitus (T1DM) remains a challenge for many, despite the availability of modern diabetes technology. While technologies have proven glycemic benefits and may reduce excess mortality in some populations, both mortality and complication rates remain significantly higher in T1DM than the general population. Diabetes technology can reduce some burdens of diabetes self-management, however, it may also increase anxiety, stress, and diabetes-related distress. Additional workload associated with diabetes technologies and the dominant focus on metabolic control may be at the expense of quality-of-life. Diabetes is associated with significantly increased risk of suicidal ideation, self-harm, and suicide. The risk increases for those with diabetes and comorbid mood disorder. For example, the prevalence of depression is significantly higher in people with diabetes than the general population, and thus, people with diabetes are at even higher risk of suicide. The Center for Disease Control and Prevention reported a 24% rise in US national suicide rates between 1999 and 2014, the highest in 30 years. In the United Kingdom, 6000 suicides occur annually. Rates of preventable self-injury mortality stand at 29.1 per 100 000 population. Individuals with diabetes have an increased risk of suicide, being three to four times more likely to attempt suicide than the general population. Furthermore, adolescents aged 15 to 19 are most likely to present at emergency departments for self-inflicted injuries (9.6 per 1000 visits), with accidents, alcohol-related injuries, and self-harm being the strongest risk factors for suicide, the second leading cause of death among 10 to 24 year olds. While we have developed tools to improve glycemic control, we must be cognizant that the psychological burden of chronic disease is a significant problem for this vulnerable population. It is crucial to determine the psychosocial and behavioral predictors to uptake and continued use of technology in order to aid the identification of those individuals most likely to realize benefits of any intervention as well as those individuals who may require more support to succeed with technology.