Purpose: The purpose of this systematic review was to determine if the use of gaming (gamification) among persons with type 2 diabetes improves diabetes self-management behaviors and diabetes outcomes. Methods: A systematic review was conducted using electronic databases including MEDLINE, Embase, Web of Science, and CINAHL. Studies reporting on the impact of gaming on at least 1 of the Association of Diabetes Care and Education Specialists self-care behaviors (ADCES7) were included. Results: The review included 9 studies, 8 of which were of strong/high quality. Five of the self-care behaviors were addressed in at least 1 of the included studies. However, taking medications and problem solving were not reported in any of the studies. Physical activity and self-efficacy or quality of life (healthy coping) were the most frequently reported ADCES7 behaviors. Six of the studies used A1C as an outcome measure, with a reduction reported in all the studies except 1. Conclusion: Type 2 diabetes affects a person holistically, necessitating a range of self-care behaviors to effectively manage the chronic condition. Novel gaming interventions may improve coping mechanisms, lifestyle behaviors, medication engagement, and monitoring of risks and problems, all of which are essential in facilitating optimal diabetes self-management.

Purpose: The purpose was to determine if negative or stigmatizing language and messaging have an impact on diabetes distress, outcomes, or care behaviors in people with diabetes. Since 2012, when the first language position statement was published, the way health care professionals talk to people with diabetes has been an ongoing topic of discussion. However, there have been no recent literature reviews evaluating the impact of problem language on outcomes among people with type 1 and type 2 diabetes. Methods: An integrative review was conducted using 4 electronic databases: CINAHL, Embase, Web of Science, and Medline (Ovid). Studies reporting on diabetes, language, stigma, diabetes distress, glycemic outcomes, and self-care behaviors were included. Results: The review included 9 studies, all of which were of high quality. The impact of negative or stigmatizing language on self-care behaviors was the most commonly addressed outcome. Whereas some studies revealed no change, others reported a decrease in self-care behaviors by people with diabetes who had negative perceptions of provider messages. Actual or perceived use of negative or stigmatizing language is linked to higher A1C. Four studies reported an association between messages and diabetes distress. Conclusions: Negative/stigmatizing language has both an immediate and long-term effect on people with diabetes. The inconsistent approaches to studying language in diabetes makes it challenging to compare outcomes and identify themes. Future research is needed to identify effective interventions to change the messages in diabetes.

OBJECTIVE: The aim of this review was to describe how the coronavirus disease 2019 (COVID-19) lockdown affected the self-care behaviors of people living with type 2 diabetes. Methods: A systematic rapid review was conducted using four electronic databases. Studies reporting on the lockdown’s impact on at least one of the self-care behaviors that were published from January 2020 through October 2021 were included. Findings were synthesized narratively, using the Association of Diabetes Care & Education Specialists ADCES7 Self-Care Behaviors as a framework. The methodological level of evidence and quality ratings of the articles were assessed using the Joanna Briggs Institute Appraisal Checklist. Results: Fifteen articles were included. Most studies reported on at least five of the self-care behaviors. There were reported increases in diabetes-related stress, as well as in increases in dietary intake and changes in the timing of meals. Physical activity was reported to decrease. Overall, taking medications and glycemic self-monitoring of blood glucose (SMBG) were unaffected by the lockdown. Of the studies reporting glycemic outcomes, the lockdown appeared to have little negative effect. None of the articles assessed all the self-care behaviors. The self-care behavior of SMBG was the least assessed. Most articles had a medium level of evidence and a medium to high quality rating (scores >60%). Conclusion: The findings from this review found the COVID-19 lockdown had a variable impact on diabetes self-care behaviors. Because the potential for future COVID-19 surges and/or other virulent transmissible diseases remains a concern, health care providers should continue to address the importance of self-care behaviors to mitigate the risk of poor health outcomes in people with diabetes.

A panel of experts in the use of continuous glucose monitoring (CGM) data in the treatment of diabetes met in Burlingame, California on October 27, 2025 to discuss the utility of the glycemia risk index (GRI) for clinical care research and population health management. The GRI composite metric is a single number (on a 0-100 percentile scale—lower is better) based on an expert-determined weighting of the seven individual components in the existing ambulatory glucose profile (AGP). The GRI describes the quality of glycemia based on glucose values collected in a 14-day CGM tracing, thus providing additional insights into CGM profiles beyond the AGP. During the meeting, the mathematical derivation of the GRI metric was presented along with its use for adult and pediatric individuals with diabetes and cancer who require medications that can adversely affect the glucose concentration. Examples where the GRI provided useful insights into the quality of CGM tracings were also discussed by the expert panel. In addition, a new smartphone application, the GRI Calculator, was presented. This app calculates the GRI of a CGM tracing and provides visualization of sequential CGM tracings for a specific individual. The GRI provides a reference measurement for the accuracy of artificial intelligence (AI) models assigning levels of glycemic quality to CGM tracings intended to match the assessments of clinicians. The GRI is now part of the data visualization panel for the Integration of Connected Diabetes Device Data into the Electronic Health Record (iCoDE-2) project, which standardizes both CGM and insulin dosing data. Further exploration of the potential value of the GRI for non-insulin users needs to be undertaken. The panel unanimously recommended that CGM manufacturers and developers of data visualization software for CGMs add the GRI to their data platforms for insulin users.