부산대학교 도서관

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. Key points: Patients with diabetes often have comorbid depression. Those patients are struggling to meet their treatment goals. Thus, they have a higher risk of getting diabetes related complications as for example coronary heart diseases. A lot of different tools and instruments are available to diagnose depression, to screen for depression among patients with diabetes or to identify depression symptoms or depressive disorder in clinical or epidemiological studies, including interview, questionnaires or claims data. It would be helpful to know if the tools that are used identify the same people or, if this is not the case, whether people identified by different tools have different characteristics or health outcomes. We found that different methods do not identify the same people with depression. There was no clear pattern of differences between the identified groups, however, we found some initial indications that the method chosen is related to particular underlying characteristics in the population identified. Further research with larger data sets is necessary to see if there are differences among the persons that are identified by different tools to give recommendations which screening tool to use for what purpose. [ABSTRACT FROM AUTHOR]