ORCID Profile
0000-0001-6029-5101
Current Organisation
Amsterdam UMC Location VUmc
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Publisher: BMJ
Date: 03-2022
DOI: 10.1136/BMJOPEN-2021-056304
Abstract: The Problem Areas of Diabetes (PAID) questionnaire is a frequently used measure to assess diabetes-distress. The aim of this study was to identify clinically meaningful levels of diabetes-distress, using latent class analyses (LCA), and to determine which groups were at increased risk of elevated diabetes-distress in terms of sex, age, type of diabetes and glycaemic control. Data were derived from four studies (total N=2966, 49% female, age range 18–95 years, 43% type 1 diabetes, diabetes duration range 0–79 years). LCAs were performed to examine possible latent groups in the distribution of answers on the in idual PAID items. Demographic and diabetes-related characteristics were added to the model to estimate their effects on latent class membership and receiver operating curves curves to determine cut-offs. Three levels of diabetes distress were distinguished with defined cut-off scores and labelled as: low, moderate and high diabetes distress. Levels of distress did not associate with distinct clusters of items. Older people were more likely to be part of the low distress class women and people with high HbA 1c were more likely to be part of the high distress class. Sensitivity and specificity of the commonly used cut-off of 40 for high distress are 0.95 and 0.97, respectively. To distinguish the moderate distress group, cut-off scores of 17 and 39 are optimal with a sensitivity of 0.93 and a specificity of 0.94. Three levels of diabetes-distress can be distinguished: low, moderate and high diabetes distress. Younger people, women and people with poor glycaemic control are at an increased risk for high levels of distress. A cut-off of 40 is satisfactory to detect people with high levels of diabetes-distress a score of 0–16 indicates low diabetes distress and a score of 17–39 moderate diabetes distress.
Publisher: Springer Science and Business Media LLC
Date: 22-06-2022
DOI: 10.1007/S00125-022-05738-X
Abstract: This narrative review aims to examine the value of addressing mental disorders as part of the care of people with type 1 and type 2 diabetes in terms of four components of precision medicine. First, we review the empirical literature on the role of common mental disorders in the development and outcomes of diabetes (precision prevention and prognostics). We then review interventions that can address mental disorders in in iduals with diabetes or at risk of diabetes (precision treatment) and highlight recent studies that have used novel methods to in idualise interventions, in person and through applications, based on mental disorders. Additionally, we discuss the use of detailed assessment of mental disorders using, for ex le, mobile health technologies (precision monitoring). Finally, we discuss future directions in research and practice and challenges to addressing mental disorders as a factor in precision medicine for diabetes. This review shows that several mental disorders are associated with a higher risk of type 2 diabetes and its complications, while there is suggestive evidence indicating that treating some mental disorders could contribute to the prevention of diabetes and improve diabetes outcomes. Using technologically enabled solutions to identify mental disorders could help in iduals who stand to benefit from particular treatments. However, there are considerable gaps in knowledge and several challenges to be met before we can stratify treatment recommendations based on mental disorders. Overall, this review demonstrates that addressing mental disorders as a facet of precision medicine could have considerable value for routine diabetes care and has the potential to improve diabetes outcomes. Graphical abstract
No related grants have been discovered for Maartje de Wit.