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Our study examined whether potentially critical indications from depression questionnaires, interviews, and single items on suicidal ideation among partici-pants in a large prospective population-based study are related to short-term sui-cides within one year. For this purpose, we studied the association between (a) the severity of depressive symptoms according to the M-CIDI and the PHQ-9, BDI-II, and CID-S depression screening and (b) elevated scores on single sui-cidal ideation items and mortality according to claims databases.
In the baseline cohort, the frequency of depressive symptoms measured by CID-S was 12.90% (SHIP-START-0). The frequency for “Moderate” to “Severe de-pression” measured by the PHQ-9 (≥ 10 points) and BDI-II (≥ 20 points) ques-tionnaires ranged from 5.40% (SHIP-LEGENDE) to 8.80% (SHIP-TREND Morbid-ity follow-up). The 1-month prevalence of unipolar depression, measured by the M-CIDI in SHIP LEGENDE, was 2.31%.
Between 5.90% (SHIP-TREND Morbidity follow-up) and 6.60% (SHIP-LEGENDE) of respondents showed a certain degree of suicidal ideation in the two weeks preceding the assessment, according to BDI-II and PHQ-9.
Our results show the high frequency of depressive symptoms in the study region, with women being affected more frequently than men, especially in the higher categories. Furthermore, women were more frequently affected by suicidal idea-tion, although this difference was not evident in the highest categories.
There was one potential suicide in the year after a SHIP examination.
From our results, we cannot conclude that severe self-reported symptoms from depression questionnaires should be reported back to participants of an obser-vational population-based study to prevent suicide deaths within one year.
Background: Only approximately a third of people with depressive symptoms seek professional health care. Furthermore, people labelled as mentally ill may experience stigmatisation, which can impede help-seeking behaviour.
Aim: To examine the effects of three vignette-based interventions endorsing biopsychosocial causal beliefs and strengthening self-efficacy on help-seeking intention and behaviour, as well as the predictive values of these variables and previous treatment experience.
Method: A quasi-experimental online study utilising a fractioned factorial design was carried out. People were screened for depressive symptoms and their current treatment status. After baseline assessment, they were randomly allocated into one of 24 groups receiving a combination of interventional messages. Actual help-seeking behaviour was measured at follow-ups 3 and 6 months after baseline.
Results: Altogether, N = 1,368 participants were included in the final analyses and N = 983 provided data on their help-seeking behaviour within 3 to 6 months after the baseline assessment. The intention to seek help from a general practitioner or a mental health professional was significantly influenced by the interventions. However, help-seeking behaviour was not influenced by the interventions. On a conceptual level, biopsychosocial causal beliefs (β = 0.09–0.23) and self-efficacy to seek help (β = 0.16–0.25) predicted help-seeking intention. There was a negative interaction effect of both self-efficacy beliefs on intention and behaviour, which changed depending on depression severity. In all models, the intention was the main predictor of actual behaviour. Treatment experience predicted both help-seeking intention and behaviour.
Conclusion: Biopsychosocial causal beliefs and self-efficacy have a direct effect on help-seeking intention. Interventions should include information on how to actually seek help as a means to strengthen self-efficacy beliefs and simulate previous treatment experience. Further research is needed to investigate the respective interaction effects on intention and behaviour.
Clinical Trial Registration: https://drks.de/search/de/trial/DRKS00023557, German Clinical Trials Register: DRKS00023557. Registered 11 December 2020. World Health Organization, Universal Trial Number: U1111–1264-9954. Registered 16 February 2021.
Abstract
Background
Comorbidities in mental disorders are often understood by assuming a common cause. The network theory of mental disorders offers an alternative to this assumption by understanding comorbidities as mutually reinforced problems. In this study, we used network analysis to examine bridge symptoms between anxiety and depression in a large sample.
Method
Using data from a sample of patients diagnosed with both depression and an anxiety disorder before and after inpatient treatment (N = 5,614, mean age: 42.24, 63.59% female, average treatment duration: 48.12 days), network models of depression and anxiety symptoms are estimated. Topology, the centrality of nodes, stability, and changes in network structure are analyzed. Symptoms that drive comorbidity are determined by bridge node analysis. As an alternative to network communities based on categorical diagnosis, we performed a community analysis and propose empirically derived symptom subsets.
Results
The obtained network models are highly stable. Sad mood and the inability to control worry are the most central. Psychomotor agitation or retardation is the strongest bridge node between anxiety and depression, followed by concentration problems and restlessness. Changes in appetite and suicidality were unique to depression. Community analysis revealed four symptom groups.
Conclusion
The estimated network structure of depression and anxiety symptoms proves to be highly accurate. Results indicate that some symptoms are considerably more influential than others and that only a small number of predominantly physical symptoms are strong candidates for explaining comorbidity. Future studies should include physiological measures in network models to provide a more accurate understanding.
Zur Messqualität des Beck-Depressionsinventars (BDI-II) in
unterschiedlichen klinischen Stichproben
(2022)
Theoretischer Hintergrund: Das BDI-II ist ein Selbstbeurteilungsinstrument zur Erfassung des Schweregrads einer Depression. Es liegen kaum Analysen mit Modellen aus der Item-Response-Theorie (IRT) vor. Fragestellung: Wie hoch ist die Messgenauigkeit des BDI-II über die unterschiedlichen Ausprägungen des latenten Traits (Depressivität) hinweg und sind die Kategorien der Items jeweils aufsteigend geordnet? Methode: Anhand von sechs großen Datensätzen aus verschiedenen klinischen Bereichen wurden psychometrische Analysen mit dem Graded Response Model durchgeführt. Ergebnisse: In allen Stichproben fand sich eine hohe interne Konsistenz. Die Schwellenwerte waren mit Ausnahme von Item 6 („Bestrafungsgefühle“) geordnet. Gemäß Testinformationsfunktion misst das BDI-II im mittleren bis hohen Depressionsbereich sehr gut (Reliabilität > .90) und im unteren Bereich gut. Schlussfolgerung: Für das BDI-II ergibt sich eine hohe und relativ gleichbleibende Messpräzision über einen weiten Bereich des latenten Traits, weshalb es insbesondere im klinischen, aber auch im nicht klinisch relevanten Wertebereich zur Erhebung des Schweregrades einer Depression gut geeignet ist.