Aims: To clarify the role of self-monitoring of blood glucose (SMBG) in the self-management of Type 2 diabetes from the patient's perspective, using in-depth interviews with non-insulin-treated adults to investigate how they learned to manage their diabetes effectively and whether SMBG played a significant role in this process.
Methods: Individual interviews were conducted with 14 non-insulin-treated adults with Type 2 diabetes who had significantly improved their glycaemic control [64% women; 50% black; 21% Hispanic; mean age 60 years; mean HbA(1c) concentration 43 mmol/mol (6.1%)]. Interviews were transcribed and analysed by a coding team, applying the concept of illness coherence from the Common Sense Model of Self-Regulation.
Results: The majority of participants relied on SMBG to evaluate their self-management efforts. Key themes included: adopting an experimental approach; experiencing 'a-ha' moments; provider-assisted problem-solving; using SMBG and other feedback to evaluate when their efforts were working; and normalizing diabetes-specific behaviour changes as being healthy for everyone.
Conclusions: Our qualitative data are consistent with the argument that SMBG, if implemented appropriately with enough education and provider access, can be a powerful tool for non-insulin-treated adults with Type 2 diabetes to monitor their self-management. Establishing sufficient conditions for illness coherence to develop while individuals are learning to use SMBG could increase their sense of personal control in managing a complex and demanding illness.
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http://dx.doi.org/10.1111/dme.12745 | DOI Listing |
Pol Przegl Chir
July 2024
East Center of Burns Treatment and Reconstructive Surgery, Medical University of Lublin, Leczna, Poland, Department of Plastic Surgery, Reconstructive Surgery and Burn Treatment, Medical University of Lublin, Polish Students' Scientific Association of Medical Simulation, Poland.
Sci Rep
September 2024
Center for Health Systems Research, Sutter Health, Santa Barbara, CA, USA.
The discrepancy between estimated glycemia from HbA values and actual average glucose (AG) levels has significant implications for treatment decisions and patient understanding. Factors contributing to the gap include red blood cell (RBC) lifespan and glucose uptake into the RBC. Personalized models have been proposed to enhance AG prediction accuracy by considering interpersonal variation.
View Article and Find Full Text PDFDiabetes Obes Metab
October 2024
Department of Medical Psychology and Behavioural Neurobiology, University of Tübingen, Tübingen, Germany.
Aim: To assess oxytocin's acute glucoregulatory impact in men with type 2 diabetes in the context of our previous findings that oxytocin improves β-cell responsivity in healthy men.
Methods: In a double-blind, crossover comparison, intranasal oxytocin (24 IU) and placebo, respectively, were administered to 25 fasted men with non-insulin-treated type 2 diabetes (age ± standard error of the mean, 63.40 ± 1.
Diabet Med
September 2024
Translational Health Sciences, Diabetes and Metabolism, Bristol Medical School, University of Bristol, Bristol, UK.
Aim: This study aimed to evaluate characteristics of autoimmunity in individuals who have a type 2 diagnosis and are relatives of children with type 1 diabetes.
Methods: Pre-diagnosis samples (median 17 months before onset) from relatives who were later diagnosed with type 2 diabetes were measured for autoantibodies to glutamate decarboxylase 65 (GADA), islet antigen-2 (IA-2A), zinc transporter 8 (ZnT8A) and insulin (IAA) as well as the type 1 diabetes genetic risk score (GRS2). Associations between islet autoantibodies, insulin treatment and GRS2 were analysed using Fisher's exact and t-tests.
Digital phenotyping refers to characterizing human bio-behavior through wearables, personal devices, and digital health technologies. Digital phenotyping in populations facing a disproportionate burden of type 2 diabetes (T2D) and health disparities continues to lag compared to other populations. Here, we report our study demonstrating the application of multimodal digital phenotyping, i.
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