Allgemeinen Depressionsskala

Maksimović, Saša; Ziegenbein, Marc; Machleidt, Wielant; Sieberer, Marcel

doi:10.1037/t63700-000

Cited by 1 publication

(3 citation statements)

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“…The CES-D and the German version of it (Allgemeine Depressionsskala) are brief self-report measures, designed to assess symptoms of depression in the general population in epidemiological studies among nine signs and symptoms of depression defined by the American Psychiatric Association Diagnostic and Statistical Manual, fourth edition [11]. Several studies have assessed the validity of the CES-D in different populations [24,25]. We used the short form of the German version of the CES-D in our study (allgemeine Depressionsskala Kurzform (ADS-K)) [25].…”

Section: Main Outcome -Assessment Of Depression Ces-dmentioning

confidence: 99%

“…Several studies have assessed the validity of the CES-D in different populations [24,25]. We used the short form of the German version of the CES-D in our study (allgemeine Depressionsskala Kurzform (ADS-K)) [25]. The instrument comprises 15 statements regarding depression.…”

Section: Main Outcome -Assessment Of Depression Ces-dmentioning

confidence: 99%

“…A score that can range from 0 to 45 is built by adding up the points from each statement. We used a cut-off value of ≥ 17 to define clinically meaningful depressive symptoms as suggested by validation studies [25].…”

Section: Main Outcome -Assessment Of Depression Ces-dmentioning

confidence: 99%

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

Linnenkamp

Gontscharuk

Ogurtsova

et al. 2023

Diabetol Metab Syndr

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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.

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