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Background: Depression and panic disorders have high prevalence rates in primary care. Given the crucial role of general practitioners in diagnosing and treating mental disorders, the two-arm cluster-randomized, controlled PREMA trial was designed. PREMA was aimed at investigating a new intervention combining cognitive behavioral therapy, case management and eHealth components for patients with depression and/or panic disorder with or without agoraphobia in primary care practices in Germany. This qualitative study, embedded in the PREMA trial, explores primary healthcare professionals' lived experiences in using the new treatment program. Using a qualitative design, we conducted eleven interviews with general practitioners and medical assistants from Hesse, Germany, between July 2021 and March 2022. For both groups we relied on a semi-structured interview guide covering the following subjects: study procedures, implementation, practicality, and individual components of the treatment program. Interviews were audio-recorded, transcribed verbatim and analyzed by two researchers using content analysis. A deductive-inductive approach was used for the analysis according to Kuckartz. Results: We narratively summarized the facilitators and barriers from two different stakeholders across five key themes regarding experiences of feasibility and practicability of the new treatment program: study instruction materials, individual components of the treatment program, practicality, target population, and benefits of the treatment program. Facilitators to become familiar with the study include study instruction materials that are easy to understand and not too complex, considering the limited time resources available; barriers included text-heavy instruction materials, lack of collegial exchange, and issues especially with digital materials also involved access and log-in difficulties on the online platform. Facilitators for using the treatment program include the combination of face-to-face consultations and the use of an online platform, enabling a structured approach and regularity; barriers included patients feeling unsupported in performing anxiety exercises independently at home. For practicality, the professional skills of medical assistants and their central role as points of contact for patients facilitated the implementation; barriers included time-intensive organization and planning of monitoring phone calls and consultations. Regarding the target population, general practitioners and medical assistants state that the treatment program would be most appropriate for patients with mild to moderate depression and for those waiting for psychotherapeutic treatment; it would be less suitable for older patients, and those with negative attitudes towards technological tools. For benefits of the program, facilitating factors included free and low-threshold access to the online platform and strengthening the relationship between medical assistants and patients; barriers included a preference for in-person conversations and the inability of some people to use online applications. Conclusions: The complexity of the new treatment program and the associated high workload underline the need for further adjustments to the treatment approach. Team-based care and the expanded responsibilities of medical assistants demonstrated promising results. Trial registration: The study was registered in the German Clinical Trials Register (DRKS00016622) on February 22, 2019. [ABSTRACT FROM AUTHOR]

Unipolar depression is a prevalent and disabling condition, often left untreated. In the outpatient setting, general practitioners fail to recognize depression in about 50% of cases mainly due to somatic comorbidities. Given the significant economic, social, and interpersonal impact of depression and its increasing prevalence, there is a need to improve its diagnosis and treatment in outpatient care. Various efforts have been made to isolate individual biological markers for depression to streamline diagnostic and therapeutic approaches. However, the intricate and dynamic interplay between neuroinflammation, metabolic abnormalities, and relevant neurobiological correlates of depression is not yet fully understood. To address this issue, we propose a naturalistic prospective study involving outpatients with unipolar depression, individuals without depression or comorbidities, and healthy controls. In addition to clinical assessments, cardiovascular parameters, metabolic factors, and inflammatory parameters are collected. For analysis we will use conventional statistics as well as machine learning algorithms. We aim to detect relevant participant subgroups by data-driven cluster algorithms and their impact on the subjects' long-term prognosis. The POKAL-PSY study is a subproject of the research network POKAL (Predictors and Clinical Outcomes in Depressive Disorders; GRK 2621). [ABSTRACT FROM AUTHOR]

Background: Depression is a common mental health disorder and the second leading cause of disability worldwide. In people with depression, low depression literacy, which could be characterized by a poor recognition of depressive symptoms and less knowledge about the availability of treatment options, can hinder adequate therapy for depression. Nevertheless, questionnaires measuring depression literacy in Germany are rare. Consequently, for the present study, the German Depression Literacy Scale (D-Lit) has been revised and evaluated. Methods: First, a team of clinical psychologists revised the D-Lit German scale. Next, cognitive interviews were conducted with patients with depression to improve the comprehensibility of the scale items. Our revision of the D-Lit-R German scale was then subjected to an anonymous online study. Finally, the data went through an exploratory factor analysis, and sociodemographic subgroup analyses were performed. Results: N = 524 individuals (age 18–80) completed the D-Lit-R German scale and a questionnaire on their sociodemographic data. Cronbach´s alpha was estimated as α =.72, and McDonald's Omega (categorical) was estimated as ω =.77. The mean Item difficulty was M =.75 (SD =.15). An EFA was performed for a unidimensional model, a 5-factor-model and at last a 3-factor-model. The 5-factorial model showed a good model fit (χ2emp,WLSMV(131) = 92.424, p >.05; CFI = 1, RMSEA = 0, SRMR =.07) but was rejected since the content of the potential 5 factors could not be determined. The 3-factor model showed an arguable model fit. The Chi2 test was significant (χ2emp,WLSMV(168) = 199.912, p <.05), but the CFI and the RMSEA met an acceptable model fit (CFI =.990, RMSEA of.019, 90% CI[.003,.029]). Substantively, the three factors were defined as (1) Distractors and other symptoms, (2) Depressive symptoms, and (3) Pharmacological and psychotherapeutic depression treatment. Furthermore, there were significant differences in sum scores regarding the subgroup's gender, treatment for mental health problems, depression treatment, experience with depression, and different career fields. Conclusions: The D-Lit-R German scale is a time-efficient scale to assess some aspects of the depression literacy construct that can be easily applied. Since there was no perfect model fit, it is recommended to continue to revise the scale. Further evaluation studies could ask for knowledge of the etiological factors of depression. Future studies could then use this instrument to convey depression literacy. This instrument could assess the growth of knowledge after psychoeducational interventions in different settings. Trial registration: This trial was preregistered at the platform osf.io (https://osf.io/49xdh). Registration number: https://doi.org/10.17605/OSF.IO/49XDH Date of registration: 28 April 2022. [ABSTRACT FROM AUTHOR]

Vaccinations against COVID-19 are of the utmost importance in long-term care facilities. During the pandemic, mental health issues increased significantly. This cross-sectional analysis aimed to assess the associations of depression and anxiety with health literacy in people in need of care and the association of depression and burnout with vaccination readiness against COVID-19 in health care workers (HCWs). Within our cross-sectional study, people in need of care were assessed for symptoms of depression (PHQ-9), anxiety (GAD-7), and health literacy (HLS-EU-Q16). Among HCWs, we assessed symptoms of depression (PHQ-9) and burnout (MBI-HSS), as well as psychological antecedents of vaccination (5C) to measure vaccination readiness against COVID-19. A multivariate regression analysis was performed. Symptoms of a major depression were significantly associated with reduced health literacy (p = 0.010) in people in need of care. Among HCWs, symptoms of depression and burnout reduced vaccination readiness against COVID-19 significantly. In particular, collective responsibility was reduced in HCWs suffering from burnout symptoms (p = 0.001). People in need of care and their HCWs could benefit from intensified target group-specific vaccination counseling. Additionally, more attention should be paid to the protection of mental health in long-term care facilities. [ABSTRACT FROM AUTHOR]

The strength of evidence for specific ambulatory care prescribing cascades, in which a marker drug is used to treat an adverse event caused by an index drug, has not been well characterized. To perform a structured, systematic, and transparent review of the evidence supporting ambulatory care prescribing cascades. Ninety‐four potential prescribing cascades identified through a previously published systematic review. Systematic search of the literature to further characterize prescribing cascades. (1) Grading of evidence based on observational studies investigating associations between index and marker drugs, including: Level I—strong evidence [i.e. multiple high‐quality studies]; Level II—moderate evidence [i.e. single high‐quality study]; Level III—fair evidence [no high‐quality studies but one or more moderate‐quality studies]; and Level IV—poor evidence [other]. (2) Listing of the adverse event associated with the index drug in the product's United States Food and Drug Administration (FDA) label. (3) Synthesis of the evidence supporting mechanisms linking index drugs and associated adverse events. Of 99 potential cascades, 94 were supported by one or more confirmatory observational studies and were therefore included in this review. The 94 cascades related to 30 types of adverse drug reactions affecting 10 different anatomic/physiologic systems and were investigated by a total of 88 confirmatory studies, including prescription sequential symmetry analysis (n = 51), cohort (n = 30), and case–control (n = 7) studies. Overall, the evidence from observational studies was strong for 18 (19.1%) prescribing cascades, moderate for 61 (64.9%), fair for 13 (13.8%), and poor for 2 (2.1%). Although the evidence supporting mechanisms that link index drugs and associated adverse events was variable, FDA labels included information about the adverse event associated with the index drug for most (n = 86) but not all of the 94 prescribing cascades. Although we identified 18 of 94 prescribing cascades supported by strong clinical evidence and most adverse events associated with index drugs are included in FDA label, the evidentiary basis for prescribing cascades varies, with many requiring further evidence of clinical relevance. [ABSTRACT FROM AUTHOR]

Vaccines against COVID-19 and influenza are highly recommended for the chronically ill. They often suffer from co-morbid mental health issues. This cross-sectional observational study analyzes the associations between depression (PHQ-9) and anxiety (OASIS) with vaccination readiness (5C) against COVID-19 and influenza in chronically ill adults in primary care in Germany. Sociodemographic data, social activity (LSNS), patient activation measure (PAM), and the doctor/patient relationship (PRA) are examined as well. Descriptive statistics and linear mixed-effects regression models are calculated. We compare data from n = 795 study participants. The symptoms of depression are negatively associated with confidence in COVID-19 vaccines (p = 0.010) and positively associated with constraints to get vaccinated against COVID-19 (p = 0.041). There are no significant associations between symptoms of depression and vaccination readiness against influenza. Self-reported symptoms of a generalized anxiety disorder seem not to be associated with vaccination readiness. To address confidence in COVID-19 vaccines among the chronically ill, targeted educational interventions should be elaborated to consider mental health issues like depression. As general practitioners play a key role in the development of a good doctor/patient relationship, they should be trained in patient-centered communication. Furthermore, a standardized implementation of digital vaccination management systems might improve immunization rates in primary care. [ABSTRACT FROM AUTHOR]

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A practice team-based exercise programme with elements of cognitive behavioural therapy (CBT) and case management for patients with panic disorder with or without agoraphobia in primary care showed significant positive effects. Here, we analyse the long-term effects (>5 years) of this intervention in the stressful context of the Covid-19 pandemic. All participants of the original PARADIES cluster randomized controlled trial (cRCT; 2012–2016) were invited to participate in a follow-up during the Covid-19 pandemic. Clinical outcomes were anxiety symptoms, number and severity of panic attacks, agoraphobic avoidance behaviour, Covid-specific anxiety symptom severity, depression, and patient assessment of chronic illness care. Data were analysed cross-sectionally for group differences (intervention, control) and longitudinally (T0: baseline, T1: 6 months and TCorona: >60 months). Of the original 419 participants, 100 participated in the 60 months follow-up (October 2020-May 2021). In the cross-sectional analysis, the anxiety symptom severity in the intervention group was lower than in the control group (p =.011, Cohen's d =.517). In the longitudinal analysis, both groups showed an increase of anxiety and depression symptoms compared to pre-pandemic level. The intervention may have had a lasting impact regarding anxiety severity despite the challenging context of the Covid-19 pandemic. However, we cannot say to what extend the intervention still played a role in participants' lives; other factors may also have helped with coping. The increase of anxiety and depression symptoms in both groups over time could be attributed to external circumstances. [ABSTRACT FROM AUTHOR]

The detection and prevention of medication-related health risks, such as medication-associated adverse events (AEs), is a major challenge in patient care. A systematic review on the incidence and nature of in-hospital AEs found that 9.2% of hospitalised patients suffer an AE, and approximately 43% of these AEs are considered to be preventable. Adverse events can be identified using algorithms that operate on electronic medical records (EMRs) and research databases. Such algorithms normally consist of structured filter criteria and rules to identify individuals with certain phenotypic traits, thus are referred to as phenotype algorithms. Many attempts have been made to create tools that support the development of algorithms and their application to EMRs. However, there are still gaps in terms of functionalities of such tools, such as standardised representation of algorithms and complex Boolean and temporal logic. In this work, we focus on the AE delirium, an acute brain disorder affecting mental status and attention, thus not trivial to operationalise in EMR data. We use this AE as an example to demonstrate the modelling process in our ontology-based framework (TOP Framework) for modelling and executing phenotype algorithms. The resulting semantically modelled delirium phenotype algorithm is independent of data structure, query languages and other technical aspects, and can be run on a variety of source systems in different institutions. [ABSTRACT FROM AUTHOR]