European Alliance Against Depression

Internet-based cognitive behavioral therapy (iCBT) for the treatment of depression has proven to be an effective and accessible option. However, iCBTs tend to have low adherence rates, which may negatively impact their effectiveness. One such iCBT program is the browser-based, proven-effective iFightDepression (iFD) tool. An app-based version of the iFD tool is the iFD app, which was developed to improve usability with a smartphone. The iFD app provides enhanced usability and a more optimized user experience on mobile devices. Additionally, it offers more comfortable interaction with worksheets, reduced text with added videos, and quicker access to the program via the smartphone icon. These improved usability on smartphones and could have an impact on adherence. This study investigated (1) whether adherence parameters, that is, the number of worksheets, the number of sessions, and the number of workshops, significantly differed between users of the iFD app and the iFD tool and (2) exploratorily whether symptom reduction (delta Patient Health Questionnaire-9 [PHQ-9] scores) differed after 5 to 9 weeks between the iFD app and the iFD tool, after controlling for covariates. We used t tests to compare data from 56 participants using the iFD app for 8 weeks with data from 172 participants using the iFD tool in a previous 6-week study. Exploratively, symptom reduction was compared between formats. A multiple regression model was calculated with the delta PHQ-9 score as the dependent variable and format, baseline PHQ-9 score, adherence, current psychotherapy, antidepressants, age, and sex as independent variables. There was no significant difference between the iFD tool and the iFD app in terms of the number of sessions per week (t67.393=0.920; P=.36; corrected P=.36), the number of workshops (t76.368=-1.217; P=.30; corrected P=.36), and the number of worksheets per week (t74=0.984; P=.33; corrected P=.36). We found no difference in delta PHQ-9 scores between the iFD app and the iFD tool, and baseline PHQ-9 scores were the only significant predictor (b=-0.61; P<.001). Despite the improved availability of the app version in daily life, there were no significant differences in the use parameters we analyzed and no differences in symptom reduction. This study provides the first evidence that adherence to iCBT content is comparable for browser- and app-based interventions and that symptom reduction is similar for both formats. However, this study used a convenience sample, and therefore, the results must be interpreted with caution. Notably, in the study of the iFD tool, guidance was provided by the study assistants in a standardized manner. In the pilot study on the iFD app, the amount of guidance varied substantially, as it was provided by the participants' health care practitioners. These differences in guidance could also have an influence on adherence.

SummaryBackgroundInformal caregivers of depressed individuals often report extensive psychological distress with detrimental consequences for their own health and for the course of the depressed person's disease. An online self-help programme was developed involving focus groups of caregivers, affected individuals and clinical experts.MethodsIn this randomised, controlled, open-label superiority trial with three parallel groups (prospective registration: DRKS00025241), stratified randomisation allocated caregivers (≥18 years) of depressed individuals in a 2:2:1 ratio to receiving the programme with either individualised (IND, three weekly e-mails by trained psychologists) or automated (AUT) support messages, or to treatment as usual (TAU; information material, no online programme, no messages). The primary outcome was the change from baseline to four weeks after randomisation in the Kessler Psychological Distress Scale (K-10).FindingsThe trial was conducted between 01 March 2020 and 29 February 2024. In 1640 (IND: n = 651; AUT: n = 659; TAU: n = 330) caregivers (mean[SD] age mage = 42·8 [12·89] years; n = 1300 [79%] female; baseline K-10 score mK-10 = 23·4 [6·09]), both IND and AUT reduced psychosocial distress significantly more than TAU at four weeks after randomisation (adjusted difference mIND/TAU [95%-CI] = –1·45 [–2·19,–0·72], p = 0·0001; mAUT/TAU [95%-CI] = –0·89 [–1·63,–0·14], p = 0·0205; dropout rate: 34%, n = 562). No study-related harms were reported.InterpretationPsychological online support for caregivers of depressed individuals with either individualised or automated messages is effective in decreasing their psychosocial distress and could be offered as part of integrated services.FundingGerman Innovation Fund (Federal Joint Committee, 01VSF19054).

Contrary to the cautions of many, suicide rates during the first COVID-19 pandemic lockdown in Germany did not rise, but declined. With the accessibility of the 2021 weekly suicide data, it was possible to analyze suicide rates and the proportion of suicide methods during the lockdown and non-lockdown phases and during the first 21 months of the pandemic compared to the previous ten years. An interrupted time-series analysis based on a linear regression was used. For the comparisons of predicted and observed suicide rates, excess suicide mortality rates (ESMR) were chosen among others. Changes in the choice of method were analyzed by comparing the rates of different methods in lockdown- and non-lockdown phases. Since the start of the COVID-19 pandemic, suicide mortality in 2020/2021 was significantly higher than expected (ESMR = 1.0161; 95% CI: 1.0005; 1.0317). Registered suicide mortality was lower than expected during the lockdown phases in these years (ESMR = 0.9477; 95% CI: 0.9128; 0.9825) and higher during non-lockdown phases (ESMR = 1.0353; 95% CI: 1.0178; 1.0528). A MANOVA revealed a significant difference of the absolute number of suicides between lockdown and non-lockdown periods (factor “lockdown”: F(1,100) = 9.47; p = 0.003). A shift of suicide methods in the comparison of these periods could not be detected. Our results are in line with the rise in yearly absolute numbers of suicides in 2022 in Germany and illustrate that even though suicide rates declined during lockdowns, there was a general rise since the beginning of the COVID-19 pandemic, especially during the non-lockdown periods. This hints towards a “postponement effect”, probably as loosening of the lockdown restrictions makes suicide methods more easily accessible and more suicides than expected are present in the following non-lockdown periods. More research is needed to better understand the mechanisms influencing suicidality during lockdowns and the COVID-19 pandemic in general.

Abstract Stigmatizing attitudes toward individuals with mental disorders represent a major barrier to treatment, recovery, and social inclusion. The present research introduces and psychometrically evaluates the German-language SToP-MD (Stigma Toward People with Mental Disorders) scale across three independent studies with distinct samples.In study 1 (N = 266), an initial item pool was developed and refined based on theoretical frameworks and exploratory factor analysis. In study 2 (N = 488), confirmatory factor analysis supported a two-factor structure comprising prejudiced stigmatization (SToP-MD-PS) and assumption of problems (SToP-MD-AP). The model showed acceptable fit (e.g., CFI = .918, TLI = .892, RMSEA = .078, SRMR = .051) and good internal consistencies (α = .84 and α = .78). In study 3 (N = 266), convergent and discriminant validity were examined via Spearman correlations with established instruments.As hypothesized, the SToP-MD subscales were positively associated with depression stigma (DSS) and social distance (SDI), and negatively correlated with openness and agreeableness (NEO-FFI), supporting convergent validity. Discriminant validity was partially confirmed by low or non-significant correlations with attitudes toward physically disabled individuals (ATDP), suicide-related cognitions (CCSS), and socially desirable responding (BIDR).Across all three studies, the SToP-MD demonstrated robust psychometric properties. It captures both overt prejudices and implicit burden assumptions, offering a nuanced assessment of public stigma toward mental disorders. The scale can serve as a valuable tool in stigma research, public health monitoring, and evaluation of interventions. Future research should extend validation to more diverse samples and test predictive and longitudinal utility.

BackgroundThe community-based, 4-level intervention of the European Alliance Against Depression (EAAD) is simultaneously addressing depression and suicidal behavior. Intervention activities target primary care health professionals (level 1), the general public (level 2), community facilitators (level 3), and patients and their relatives (level 4). Activities comprise the digital iFightDepression tool, a guided self-management tool based on cognitive behavioral therapy.ObjectiveThis study aimed to present the European Union–cofunded EAAD-Best study protocol, aiming at the implementation, dissemination, and evaluation of the 4-level intervention and the iFightDepression tool in several countries across Europe.MethodsThe 4-level intervention has been implemented for the first time in Bulgaria, Estonia, Greece, and Poland. In 3 countries that have already implemented the 4-level intervention (Hungary, Ireland, and Spain), activities have been extended to new regions. In addition, the nationwide uptake of the iFightDepression tool by patients with depression has been promoted in all mentioned countries and Italy.ResultsTo evaluate the implementation of the 4-level intervention and the iFightDepression tool, data related to the process, output, and outcome were collected between 2022 and 2024. Data processing and analyses started in 2023. Analyses are expected to be completed in 2024. Results are expected to be published in 2025.ConclusionsThis paper informs researchers, practitioners, and stakeholders on how to implement best practices in mental health promotion and evaluate their effectiveness.International Registered Report Identifier (IRRID)DERR1-10.2196/64218

Online interventions, such as the iFightDepression (iFD) tool, are increasingly recognized as effective alternatives to traditional face-to-face psychotherapy or pharmacotherapy for treating depression. However, particularly when used outside of study settings, low adherence rates and the resulting diminished benefits of the intervention can limit their effectiveness. Understanding the factors that predict adherence would allow for early, tailored interventions for individuals at risk of nonadherence, thereby enhancing user engagement and optimizing therapeutic outcomes. This study aims to develop and evaluate a random forest model that predicts adherence to the iFD tool to identify users at risk of noncompletion. The model was based on characteristics collected during baseline and the first week of the intervention in patients with depression. Log data from 4187 adult patients who registered for the iFD tool between October 1, 2016, and May 5, 2022, and provided informed consent were statistically analyzed. The resulting data set was divided into training (2932/4187, 70%) and test (1255/4187, 30%) sets using a randomly stratified split. The training data set was utilized to train a random forest model aimed at predicting each user's adherence at baseline, based on the hypothesized predictors: age, self-reported gender, expectations of the intervention, current or previous depression treatments, confirmed diagnosis of depression, baseline 9-item Patient Health Questionnaire (PHQ-9) score, accompanying guide profession, and usage behavior within the first week. After training, the random forest model was evaluated on the test data set to assess its predictive performance. The importance of each variable in predicting adherence was analyzed using mean decrease accuracy, mean decrease Gini, and Shapley Additive Explanations values. Of the 4187 patients evaluated, 1019 (24.34%) were classified as adherent based on our predefined definition. An initial random forest model that relied solely on sociodemographic and clinical predictors collected at baseline did not yield a statistically significant adherence prediction. However, after incorporating each patient's usage behavior during the first week, we achieved a significant prediction of adherence (P<.001). Within this prediction, the model achieved an accuracy of 0.82 (95% CI 0.79-0.84), an F1-score of 0.53, an area under the curve of 0.83, and a specificity of 0.94 for predicting nonadherent users. The key predictors of adherence included logs, word count on the first workshop's worksheet, and time spent on the tool, all measured during the first week. Our results highlight that early engagement, particularly usage behavior during the first week of the online intervention, is a far greater predictor of adherence than any sociodemographic or clinical factors. Therefore, analyzing usage behavior within the first week and identifying nonadherers through the algorithm could be beneficial for tailoring interventions aimed at improving user adherence. This could include follow-up calls or face-to-face discussions, optimizing resource utilization in the process.

Migrants face many barriers to mental health care, such as different cultural concepts of distress, unfamiliar pathways to care, and language. Digital mental health interventions are effective and scalable in multi-language versions. However, their implementation into routine care is in its infancy. Here, we report on the Arabic- and German-language implementation of two digital interventions in Germany: The iFightDepression® website, providing information about depression to the public, and the iFightDepression® tool, offering guided self-management for depression. Our main goal is to gain empirical knowledge about the success of their implementation and provide evidence-based recommendations for improvement. Data for the current analyses stem from convenience samples, utilizing anonymized user logs of the iFightDepression® website and 15.307 user accounts in the iFightDepression® tool. We found that the acceptability (time on page, usage behavior) of both digital interventions was comparable between the two user groups. The website pervasiveness of the target populations was nine times lower among Arab migrants in Germany than Germans (89 vs. 834 unique page views/ 100,000 inhabitants), but the increase in views was superior and sustained over three years. The adoption of the tool was lower among Arabic than German users (conversion rate from invitation to completed registration: 30.8% vs. 59.0%, p < 0.001) and appropriateness was challenged as Arabic users reported higher depression severities upon first registration (p = 0.027). Our results show that the uptake of digital interventions for migrants requires facilitation and further tailoring to the needs of the target group.

BackgroundBrain-derived neurotrophic factor (BDNF) is essential for antidepressant treatment of major depressive disorder (MDD). Our repeated studies suggest that DNA methylation of a specific CpG site in the promoter region of exon IV of the BDNF gene (CpG -87) might be predictive of the efficacy of monoaminergic antidepressants such as selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and others. This trial aims to evaluate whether knowing the biomarker is non-inferior to treatment-as-usual (TAU) regarding remission rates while exhibiting significantly fewer adverse events (AE).MethodsThe BDNF trial is a prospective, randomized, rater-blinded diagnostic study conducted at five university hospitals in Germany. The study’s main hypothesis is that {1} knowing the methylation status of CpG -87 is non-inferior to not knowing it with respect to the remission rate while it significantly reduces the AE rate in patients experiencing at least one AE. The baseline assessment will occur upon hospitalization and a follow-up assessment on day 49 (± 3). A telephone follow-up will be conducted on day 70 (± 3). A total of 256 patients will be recruited, and methylation will be evaluated in all participants. They will be randomly assigned to either the marker or the TAU group. In the marker group, the methylation results will be shared with both the patient and their treating physician. In the TAU group, neither the patients nor their treating physicians will receive the marker status. The primary endpoints include the rate of patients achieving remission on day 49 (± 3), defined as a score of ≤ 10 on the Hamilton Depression Rating Scale (HDRS-24), and the occurrence of AE.Ethics and disseminationThe trial protocol has received approval from the Institutional Review Boards at the five participating universities. This trial holds significance in generating valuable data on a predictive biomarker for antidepressant treatment in patients with MDD. The findings will be shared with study participants, disseminated through professional society meetings, and published in peer-reviewed journals.Trial registrationGerman Clinical Trial Register DRKS00032503. Registered on 17 August 2023.

"The Tourists" is a subversive tourism campaign by the Depression Era collective, reflecting on the simultaneous influx of refugees and global tourism in Southern Europe. Through diverse media, it exposes landscapes marked by hidden violence, portrays individuals in states of flux, and blurs the line between idyllic tourism and harsh reality.