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Mendeley readers
Attention Score in Context
| Title |
PHQ-9, CES-D, health insurance data—who is identified with depression? A Population-based study in persons with diabetes
|
|---|---|
| Published in |
Diabetology & Metabolic Syndrome, March 2023
|
| DOI | 10.1186/s13098-023-01028-7 |
| Pubmed ID | |
| Authors |
Ute Linnenkamp, Veronika Gontscharuk, Katherine Ogurtsova, Manuela Brüne, Nadezda Chernyak, Tatjana Kvitkina, Werner Arend, Imke Schmitz-Losem, Johannes Kruse, Norbert Hermanns, Bernd Kulzer, Silvia M. A. A. Evers, Mickaël Hiligsmann, Barbara Hoffmann, Andrea Icks, Silke Andrich |
| Abstract |
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. 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. 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. 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 22% |
| Student > Ph. D. Student | 1 | 11% |
| Unspecified | 1 | 11% |
| Unknown | 5 | 56% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 1 | 11% |
| Environmental Science | 1 | 11% |
| Medicine and Dentistry | 1 | 11% |
| Unknown | 6 | 67% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 March 2023.
All research outputs
#20,941,352
of 23,572,509 outputs
Outputs from Diabetology & Metabolic Syndrome
#597
of 710 outputs
Outputs of similar age
#259,273
of 330,359 outputs
Outputs of similar age from Diabetology & Metabolic Syndrome
#22
of 32 outputs
Altmetric has tracked 23,572,509 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 710 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,359 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.