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PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes
AIMS: 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...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031874/ https://www.ncbi.nlm.nih.gov/pubmed/36945050 http://dx.doi.org/10.1186/s13098-023-01028-7 |
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author | 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 |
author_facet | 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 |
author_sort | Linnenkamp, Ute |
collection | PubMed |
description | AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13098-023-01028-7. |
format | Online Article Text |
id | pubmed-10031874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100318742023-03-23 PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes 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 Diabetol Metab Syndr Research AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13098-023-01028-7. BioMed Central 2023-03-22 /pmc/articles/PMC10031874/ /pubmed/36945050 http://dx.doi.org/10.1186/s13098-023-01028-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research 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 |
title | PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes |
title_full | PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes |
title_fullStr | PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes |
title_full_unstemmed | PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes |
title_short | PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes |
title_sort | phq-9, ces-d, health insurance data—who is identified with depression? a population-based study in persons with diabetes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031874/ https://www.ncbi.nlm.nih.gov/pubmed/36945050 http://dx.doi.org/10.1186/s13098-023-01028-7 |
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