algorithms; patient reported outcome measures; patient-centered care; population health; Humans; Europe; Middle East/epidemiology; North America; Machine Learning; Diabetes Mellitus/epidemiology; Diabetes Mellitus/therapy; Diabetes Mellitus; Middle East; Endocrinology, Diabetes and Metabolism
Résumé :
[en] [en] INTRODUCTION: The current evaluation processes of the burden of diabetes are incomplete and subject to bias. This study aimed to identify regional differences in the diabetes burden on a universal level from the perspective of people with diabetes.
RESEARCH DESIGN AND METHODS: We developed a worldwide online diabetes observatory based on 34 million diabetes-related tweets from 172 countries covering 41 languages, spanning from 2017 to 2021. After translating all tweets to English, we used machine learning algorithms to remove institutional tweets and jokes, geolocate users, identify topics of interest and quantify associated sentiments and emotions across the seven World Bank regions.
RESULTS: We identified four topics of interest for people with diabetes (PWD) in the Middle East and North Africa and another 18 topics in North America. Topics related to glycemic control and food are shared among six regions of the world. These topics were mainly associated with sadness (35% and 39% on average compared with levels of sadness in other topics). We also revealed several region-specific concerns (eg, insulin pricing in North America or the burden of daily diabetes management in Europe and Central Asia).
CONCLUSIONS: The needs and concerns of PWD vary significantly worldwide, and the burden of diabetes is perceived differently. Our results will support better integration of these regional differences into diabetes programs to improve patient-centric diabetes research and care, focused on the most relevant concerns to enhance personalized medicine and self-management of PWD.
Disciplines :
Santé publique, services médicaux & soins de santé
Auteur, co-auteur :
BOUR, Charline Gaëlle Louise Adua ; University of Luxembourg ; Department of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg
Ahne, Adrian; Center for Research in Epidemiology and Population Health (CESP), INSERM, Villejuif (Paris), Île-de-France, France
Aguayo, Gloria ; Department of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg
Fischer, Aurélie; Department of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg
Marcic, David; Department of Precision Health, Data Integration and Analysis Unit, Luxembourg Institute of Health, Strassen, Luxembourg
Kayser, Philippe; Department of Precision Health, Data Integration and Analysis Unit, Luxembourg Institute of Health, Strassen, Luxembourg
FAGHERAZZI, Guy ; University of Luxembourg ; Department of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg Guy.Fagherazzi@lih.lu
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Global diabetes burden: analysis of regional differences to improve diabetes care.
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