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How to identify clinically significant diabetes distress using the Problem Areas in Diabetes (PAID) scale in adults with diabetes treated in primary or secondary care? Evidence for new cut points based on latent class analyses

Maartje de Wit, Frans Pouwer, Frank J. Snoek

2022BMJ Open53 citationsDOIOpen Access PDF

Abstract

INTRODUCTION: 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. METHODS: 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 individual 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. RESULTS: 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. CONCLUSION: 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.

Topics & Concepts

MedicineDiabetes mellitusPrimary careScale (ratio)DistressEpidemiologyGerontologyMEDLINEFamily medicineInternal medicineEndocrinologyClinical psychologyQuantum mechanicsLawPolitical sciencePhysicsDiabetes Management and EducationChronic Disease Management StrategiesCancer survivorship and care