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Linnenkamp, Ute; Gontscharuk, Veronika; Ogurtsova, Katherine; Brüne, Manuela; Chernyak, Nadezda; Kvitkina, Tatjana; Arend, Werner; Schmitz-Losem, Imke; Kruse, Johannes; Hermanns, Norbert; Kulzer, Bernd; Evers, Silvia M. A. A.; Hiligsmann, Mickaël; Hoffmann, Barbara; Icks, Andrea; Andrich, Silke

PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes

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  • Medientyp: E-Artikel
  • Titel: PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes
  • Beteiligte: Linnenkamp, Ute; Gontscharuk, Veronika; Ogurtsova, Katherine; Brüne, Manuela; Chernyak, Nadezda; Kvitkina, Tatjana; Arend, Werner; Schmitz-Losem, Imke; Kruse, Johannes; Hermanns, Norbert; Kulzer, Bernd; Evers, Silvia M. A. A.; Hiligsmann, Mickaël; Hoffmann, Barbara; Icks, Andrea; Andrich, Silke
  • Erschienen: Springer Science and Business Media LLC, 2023
  • Erschienen in: Diabetology & Metabolic Syndrome
  • Sprache: Englisch
  • DOI: 10.1186/s13098-023-01028-7
  • ISSN: 1758-5996
  • Schlagwörter: Endocrinology, Diabetes and Metabolism ; Internal Medicine
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title><jats:sec> <jats:title>Aims</jats:title> <jats:p>Several instruments are used to identify depression among patients with diabetes and have been compared for their test criteria, but, not for the overlaps and differences, for example, in the sociodemographic and clinical characteristics of the individuals identified with different instruments.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>We conducted a cross-sectional survey among a random sample of a statutory health insurance (SHI) (n = 1,579) with diabetes and linked it with longitudinal SHI data. Depression symptoms were identified using either the Centre for Epidemiological Studies Depression (CES-D) scale or the Patient Health Questionnaire-9 (PHQ-9), and a depressive disorder was identified with a diagnosis in SHI data, resulting in 8 possible groups. Groups were compared using a multinomial logistic model.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>In total 33·0% of our analysis sample were identified with depression by at least one method. 5·0% were identified with depression by all methods. Multinomial logistic analysis showed that identification through SHI data only compared to the group with no depression was associated with gender (women). Identification through at least SHI data was associated with taking antidepressants and previous depression. Health related quality of life, especially the mental summary score was associated with depression but not when identified through SHI data only.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusion</jats:title> <jats:p>The methods overlapped less than expected. We did not find a clear pattern between methods used and characteristics of individuals identified. However, we found first indications that the choice of method is related to specific underlying characteristics in the identified population. These findings need to be confirmed by further studies with larger study samples.</jats:p> </jats:sec>
  • Zugangsstatus: Freier Zugang