Efficacy of a Guided Web-Based Self-Management Intervention for Depression or Dysthymia: Randomized Controlled Trial With a 12-Month Follow-Up Using an Active Control Condition

Community-Based 4-Level Intervention Targeting Depression and Suicidal Behavior in Europe: Protocol for an Implementation Project

BACKGROUND

The 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.

OBJECTIVE

This 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.

METHODS

The 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.

RESULTS

To 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.

CONCLUSIONS

This 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.

Use of Random Forest to Predict Adherence in an Online Intervention for Depression Using Baseline and Early Usage Data: Model Development and Validation on Retrospective Routine Care Log Data

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Effectiveness of Web-Based Cognitive Behavioral Therapy for Depression: A Systematic Review of Randomized Controlled Trials

Evidence-based practices were more effective in managing mental health disorders when compared to traditional, non-evidence-based approaches. Web-based cognitive behavioral therapy (CBT) interventions offer a wide variety of advantages among depressed patients as they offer a sense of anonymity, privacy, and accessibility. This systematic review of randomized controlled trials (RCTs) aims to estimate the efficacy of several types of web-based interventions among patients with depression symptoms. This review was conducted according to the principles of the Cochrane Handbook for Systematic Reviews of Interventions and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched the literature using five databases: PubMed, Medline, Ovid, Cochrane CENTRAL, and Scopus. Key terms for depression and web-based CBT included "Depression", "Cognitive behavioral therapy", "CBT", "Effectiveness", "Internet", and "Web-based". The included studies were published between 2019 and 2024 and assessed the risk of bias (ROB) using the ROB2 tool for RCTs. This search strategy yielded 2902 records, of which 1946 were duplicates and removed. The remaining 956 records underwent screening of their titles and abstracts, and 900 records were excluded. The full texts of the remaining 56 records were retrieved; 45 of them were excluded since 13 had the wrong study design, 10 had inappropriate outcomes, 12 had inappropriate populations, and 10 were out of the date range. All the included studies were 11 RCTs. Most studies assessed the efficacy of internet-based CBT (ICBT) or web-delivered CBT (wCBT). Control groups included the waitlist control (WLC) group and the treatment as usual (TAU) group, and one study included an active control group. Six studies compared the effects of guided or self-guided ICBT with control, three compared wCBT with control, one used internet self-guided intervention, and one employed an internet-based Functional Depression (iFD) program. Interventions were generally self-guided or guided by laypersons, nonspecialists, or automated systems. It can be concluded that despite the significance of most interventions favoring internet-based interventions compared to control groups, many limitations existed in the included studies, making it unclear whether the interventions would prove conclusive and reliable benefits. Therefore, more studies should be conducted on larger sample populations with prolonged duration.

Acceptability of Digital Mental Health Interventions for Depression and Anxiety: Systematic Review

BACKGROUND

Depression and anxiety disorders are common, and treatment often includes psychological interventions. Digital health interventions, delivered through technologies such as web-based programs and mobile apps, are increasingly used in mental health treatment. Acceptability, the extent to which an intervention is viewed positively, has been identified as contributing to patient adherence and engagement with digital health interventions. Acceptability, therefore, impacts the benefit derived from using digital health interventions in treatment. Understanding the acceptability of digital mental health interventions among patients with depression or anxiety disorders is essential to maximize the effectiveness of their treatment.

OBJECTIVE

This review investigated the acceptability of technology-based interventions among patients with depression or anxiety disorders.

METHODS

A systematic review was performed based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PROSPERO (International Prospective Register of Systematic Reviews) guidelines. We searched PubMed, Web of Science, and Ovid in May 2022. Studies were included if they evaluated digital interventions for the treatment of depression or anxiety disorders and investigated their acceptability among adult patients. Studies were excluded if they targeted only specific populations (eg, those with specific physical health conditions), investigated acceptability in healthy individuals or patients under the age of 18 years, involved no direct interaction between patients and technologies, used technology only as a platform for traditional care (eg, videoconferencing), had patients using technologies only in clinical or laboratory settings, or involved virtual reality technologies. Acceptability outcome data were narratively synthesized by the direction of acceptability using vote counting. Included studies were evaluated using levels of evidence from the Oxford Centre for Evidence-Based Medicine. The risk of bias was assessed using a tool designed for this review and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation).

RESULTS

A total of 143 articles met the inclusion criteria, comprising 67 (47%) articles on interventions for depression, 65 (45%) articles on interventions for anxiety disorders, and 11 (8%) articles on interventions for both. Overall, 90 (63%) were randomized controlled trials, 50 (35%) were other quantitative studies, and 3 (2%) were qualitative studies. Interventions used web-based programs, mobile apps, and computer programs. Cognitive behavioral therapy was the basis of 71% (102/143) of the interventions. Digital mental health interventions were generally acceptable among patients with depression or anxiety disorders, with 88% (126/143) indicating positive acceptability, 8% (11/143) mixed results, and 4% (6/143) insufficient information to categorize the direction of acceptability. The available research evidence was of moderate quality.

CONCLUSIONS

Digital mental health interventions seem to be acceptable to patients with depression or anxiety disorders. Consistent use of validated measures for acceptability would enhance the quality of evidence. Careful design of acceptability as an evaluation outcome can further improve the quality of evidence and reduce the risk of bias.

TRIAL REGISTRATION

Open Science Framework Y7MJ4; https://doi.org/10.17605/OSF.IO/SPR8M.

Digital Psychotherapies for Adults Experiencing Depressive Symptoms: Systematic Review and Meta-Analysis

BACKGROUND

Depression affects 5% of adults and it is a major cause of disability worldwide. Digital psychotherapies offer an accessible solution addressing this issue. This systematic review examines a spectrum of digital psychotherapies for depression, considering both their effectiveness and user perspectives.

OBJECTIVE

This review focuses on identifying (1) the most common types of digital psychotherapies, (2) clients' and practitioners' perspectives on helpful and unhelpful aspects, and (3) the effectiveness of digital psychotherapies for adults with depression.

METHODS

A mixed methods protocol was developed using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The search strategy used the Population, Intervention, Comparison, Outcomes, and Study Design (PICOS) framework covering 2010 to 2024 and 7 databases were searched. Overall, 13 authors extracted data, and all aspects of the review were checked by >1 reviewer to minimize biases. Quality appraisal was conducted for all studies. The clients' and therapists' perceptions on helpful and unhelpful factors were identified using qualitative narrative synthesis. Meta-analyses of depression outcomes were conducted using the standardized mean difference (calculated as Hedges g) of the postintervention change between digital psychotherapy and control groups.

RESULTS

Of 3303 initial records, 186 records (5.63%; 160 studies) were included in the review. Quantitative studies (131/160, 81.8%) with a randomized controlled trial design (88/160, 55%) were most common. The overall sample size included 70,720 participants (female: n=51,677, 73.07%; male: n=16,779, 23.73%). Digital interventions included "stand-alone" or non-human contact interventions (58/160, 36.2%), "human contact" interventions (11/160, 6.8%), and "blended" including stand-alone and human contact interventions (91/160, 56.8%). What clients and practitioners perceived as helpful in digital interventions included support with motivation and accessibility, explanation of task reminders, resources, and learning skills to manage symptoms. What was perceived as unhelpful included problems with usability and a lack of direction or explanation. A total of 80 studies with 16,072 participants were included in the meta-analysis, revealing a moderate to large effect in favor of digital psychotherapies for depression (Hedges g=-0.61, 95% CI -0.75 to -0.47; Z=-8.58; P<.001). Subgroup analyses of the studies with different intervention delivery formats and session frequency did not have a statistically significant effect on the results (P=.48 and P=.97, respectively). However, blended approaches revealed a large effect size (Hedges g=-0.793), while interventions involving human contact (Hedges g=-0.42) or no human contact (Hedges g=-0.40) had slightly smaller effect sizes.

CONCLUSIONS

Digital interventions for depression were found to be effective regardless of format and frequency. Blended interventions have larger effect size than those involving human contact or no human contact. Digital interventions were helpful especially for diverse ethnic groups and young women. Future research should focus on understanding the sources of heterogeneity based on intervention and population characteristics.

TRIAL REGISTRATION

PROSPERO CRD42021238462; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=238462.

The SME tool supporting employers of small- and medium-sized enterprises during the return to work of employees on long-term sick leave: study protocol for a randomized controlled trial and for a process evaluation

BACKGROUND

Returning to work after long-term sick leave can be challenging, particularly in small- and medium-sized enterprises (SMEs) where support may be limited. Recognizing the responsibilities and challenges of SME employers, a web-based intervention (hereafter the SME tool) has been developed. The SME tool aims to enhance the employer's intention and ability to support the sick-listed employee. Based on the Self-Determination Theory, it is hypothesized that this intention is enhanced by intervening in the employer's autonomy, competences, and relatedness targeted at, e.g., communication with sick-listed employee, involvement of other stakeholders, and practical support. This is achieved by means of providing templates, communication videos, and information on legislation. This article describes the design of an effect and process evaluation of the SME tool.

METHODS

A randomized controlled trial (RCT) with a 6-month follow-up will be conducted with a parallel-group design with two arms: an intervention group and a control group. Sick-listed employees (≤ 8 weeks) of SMEs (≤ 250 employees) at risk of long-term sick leave and their employers will be recruited and randomly allocated as a dyad (1:1). Employers randomized to the intervention group receive unlimited access to the SME tool, while those in the control group will receive care as usual. The primary outcome is the satisfaction of the employee with the return to work (RTW) support provided by their employer. Secondary outcomes include social support, work performance, and quality of work life at the employee level and self-efficacy in providing RTW support at the employer level. Outcomes will be assessed using questionnaires at baseline and 1, 3, and 6 months of follow-up. Process evaluation measures include, e.g., recruitment and use of and perceived usefulness of the SME tool. Additionally, semi-structured interviews with employers, employees, and occupational physicians will explore the interpretation of the RCT results and strategies for the national implementation of the SME tool.

DISCUSSION

The SME tool is hypothesized to be valuable in addition to usual care helping employers to effectively support the RTW of their long-term sick-listed employees, by improving the employers' intention and ability to support.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT06330415. Registered on February 14, 2024.

Heterogeneity of Treatment Effects in Internet- and Mobile-Based Interventions for Depression: A Systematic Review and Meta-Analysis

Importance

While the effects of internet- and mobile-based interventions (IMIs) for depression have been extensively studied, no systematic evidence is available regarding the heterogeneity of treatment effects (HTEs), indicating to what extent patient-by-treatment interactions exist and personalized treatment models might be necessary.

Objective

To investigate the HTEs in IMIs for depression as well as their efficacy and effectiveness.

Data Sources

A systematic search in Embase, MEDLINE, Central, and PsycINFO for randomized clinical trials and supplementary reference searches was conducted on October 13, 2019, and updated March 25, 2022. The search string included various terms related to digital psychotherapy, depression, and randomized clinical trials.

Study Selection

Titles, abstracts, and full texts were reviewed by 2 independent researchers. Studies of all populations with at least 1 intervention group receiving an IMI for depression and at least 1 control group were eligible, if they assessed depression severity as a primary outcome and followed a randomized clinical trial (RCT) design.

Data Extraction and Synthesis

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias Tool. HTE was investigated using logarithmic variance ratios (lnVR) and effect sizes using Hedges g. Three-level bayesian meta-regressions were conducted.

Main Outcomes and Measures

Heterogeneity of treatment effects was the primary outcome of this study; magnitudes of treatment effect sizes were the secondary outcome. Depression severity was measured by different self-report and clinician-rated scales in the included RCTs.

Results

The systematic review of 102 trials included 19 758 participants (mean [SD] age, 39.9 [10.58] years) with moderate depression severity (mean [SD] in Patient Health Questionnaire-9 score, 12.81 [2.93]). No evidence for HTE in IMIs was found (lnVR = -0.02; 95% credible interval [CrI], -0.07 to 0.03). However, HTE was higher in more severe depression levels (β̂ = 0.04; 95% CrI, 0.01 to 0.07). The effect size of IMI was medium (g = -0.56; 95% CrI, -0.46 to -0.66). An interaction effect between guidance and baseline severity was found (β̂ = -0.24, 95% CrI, -0.03 to -0.46).

Conclusions and Relevance

In this systematic review and meta-analysis of RCTs, no evidence for increased patient-by-treatment interaction in IMIs among patients with subthreshold to mild depression was found. Guidance did not increase effect sizes in this subgroup. However, the association of baseline severity with HTE and its interaction with guidance indicates a more sensitive, guided, digital precision approach would benefit individuals with more severe symptoms. Future research in this population is needed to explore personalization strategies and fully exploit the potential of IMI.

Empowerment of Italian general practitioners in depression and suicide prevention: the iFightDepression tool, a game changer of the EAAD-Best project

General Practitioners (GPs) play a key role in the early detection and management of depression and in preventing suicide risk. They are often the first healthcare professionals that people in crisis contact. However, their effectiveness can be limited by several barriers, including the lack of specific training and appropriate tools.The EAAD-Best project aims to fill these gaps through its iFightDepression tool, an online tool designed to support patients, psychologists, psychiatrists, and GPs in managing depression and preventing suicide. This article examines the implementation of the iFightDepression platform in Italy, assessing its impact on the empowerment of GPs in the fight against depression. Through a qualitative and quantitative analysis of the data collected by the project, the 'unmet need' of GPs' in Italy regarding their specific training in mental health is highlighted.The response of 2,068 Italian GPs in just 7 months after the start of the iFD project is an expression of GPs' engagement to work against depression and for suicide risk prevention.

Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB)

BACKGROUND

The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear.

METHODS

In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB).

RESULTS

We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone.

CONCLUSIONS

Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.

Arabic-language digital interventions for depression in German routine health care are acceptable, but intervention adoption remains a challenge

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.

The clinical effectiveness of a self-management intervention for patients with persistent depressive disorder and their partners/caregivers: results from a multicenter, pragmatic randomized controlled trial

BACKGROUND

Persistent depressive disorder (PDD) is prevalent and debilitating. For patients with PDD, psychiatric rehabilitation using self-management interventions is advised as the next therapeutic step after multiple unsuccessful treatment attempts. The "Patient and Partner Education Program for All Chronic Diseases" (PPEP4All) is a brief, structured self-management program that focuses on functional recovery for patients and their partners/caregivers. In chronic somatic disorder populations, PPEP4All has already been shown to be clinically effective. We examined whether PPEP4All adapted for PDD (PPEP4All-PDD, nine weekly group or individual sessions) is also clinically effective for adults/elderly with PDD and their partners/caregivers compared to care-as-usual (CAU) in specialized mental healthcare.

METHODS

In this mixed-method multicenter pragmatic randomized controlled trial, 70 patients with PDD and 14 partners/caregivers were allocated to either PPEP4All-PDD (patients, n = 37; partners/caregivers, n = 14) or CAU (patients, n = 33; partners/caregivers, not included) and completed questionnaires at 0, 3, 6, and 12 months regarding depressive symptoms, psychopathology, psychosocial burden, mental resilience, and happiness/well-being. Qualitative data were collected regarding treatment satisfaction. Data were analyzed using mixed model analyses and an intention-to-treat (ITT) approach.

RESULTS

There was no statistically significant difference in any outcome regarding clinical effectiveness between PPEP4All-PDD and CAU. Subgroup analysis for depressive symptoms did not show any interaction effect for any subgroup. Although 78% of participants recommended PPEP4All-PDD, there was no difference in treatment satisfaction between PPEP4All-PDD (score = 6.6; SD = 1.7) and CAU (score = 7.6; SD = 1.2), p = 0.06.

CONCLUSION

Although depressive symptoms did not improve relative to CAU, this only confirmed that treatment for patients with treatment-resistant PDD should move from symptom reduction to functional recovery. Also, functional recovery may be reflected in other outcomes than psychosocial burden, such as self-empowerment, in patients with treatment-resistant PDD. Future research on PPEP4All-PDD could focus on a longer-term program and/or online program that may also be offered earlier in the treatment process as an empowerment intervention.  TRIAL REGISTRATION: Netherlands Trial Register Identifier NL5818. Registered on 20 July 2016 https://clinicaltrialregister.nl/nl/trial/20302.

[Efficacy of internet-based interventions for depression available in Germany-A systematic review and meta-analysis]

BACKGROUND

Internet-based interventions (IBIs) for the treatment of depression have been found to have positive effects in international meta-analyses; however, it is unclear whether these effects also extend to IBIs specifically available in Germany. The aim of this meta-analysis was to estimate the immediate effects and the long-term effects of IBIs available in Germany free of charge or available on prescription and covered by the public health insurances as so-called digital health applications (DiGAs) and to compare the efficacy of DiGAs and freely available IBIs.

METHOD

A systematic literature search and random-effects meta-analysis were performed (preregistration: INPLASY202250070). Randomized controlled trials (RCTs) of IBIs freely available in Germany or as DiGA in adults with elevated depressive symptoms were compared with active and inactive controls available at the time of the survey in May 2022.

RESULTS

A total of six interventions were identified: COGITO, deprexis, iFightDepression, moodgym, Novego, and Selfapy. The pooled effect size of a total of 28 studies with 13,413 participants corresponded to an effect of Cohen's d = 0.42, (95% confidence interval, CI: 0.31-0.54, I2 = 81%). The analysis of long-term effects showed a smaller effect size of d = 0.29, (95% CI: 0.21-0.37, I2 = 22%, N = 10). Subgroup analyses indicated a possible superiority of the three interventions listed in the DiGA directory (d = 0.56, 95% CI: 0.38-0.74, I2 = 83%, N = 15) compared to the three freely available IBIs (d = 0.24, 95% CI: 0.14-0.33, I2 = 44%, N = 13, p = 0.002).

CONCLUSION

The IBIs for depressive disorders available in Germany are effective and can therefore be used in the treatment of people with a depressive disorder; however, it is possible that not all interventions are equally effective.

Race, Ethnicity, and Other Cultural Background Factors in Trials of Internet-Based Cognitive Behavioral Therapy for Depression: Systematic Review

BACKGROUND

There is a growing interest in developing scalable interventions, including internet-based cognitive behavioral therapy (iCBT), to meet the increasing demand for mental health services. Given the growth in diversity worldwide, it is essential that the clinical trials of iCBT for depression include diverse samples or, at least, report information on the race, ethnicity, or other background indicators of their samples. Unfortunately, the field lacks data on how well diversity is currently reported and represented in the iCBT literature.

OBJECTIVE

Thus, the main objective of this systematic review was to examine the overall reporting of racial and ethnic identities in published clinical trials of iCBT for depression. We also aimed to review the representation of specific racial and ethnic minoritized groups and the inclusion of alternative background indicators such as migration status or country of residence.

METHODS

Studies were included if they were randomized controlled trials in which iCBT was compared to a waiting list, care-as-usual, active control, or another iCBT. The included papers also had to have a focus on acute treatment (eg, 4 weeks to 6 months) of depression, be delivered via the internet on a website or a smartphone app and use guided or unguided self-help. Studies were initially identified from the METAPSY database (n=59) and then extended to include papers up to 2022, with papers retrieved from Embase, PubMed, PsycINFO, and Cochrane (n=3). Risk of bias assessment suggested that reported studies had at least some risk of bias due to use of self-report outcome measures.

RESULTS

A total of 62 iCBT randomized controlled trials representing 17,210 participants are summarized in this study. Out of those 62 papers, only 17 (27%) of the trials reported race, and only 12 (19%) reported ethnicity. Reporting outside of the United States was very poor, with the United States accounting for 15 (88%) out of 17 of studies that reported race and 9 (75%) out of 12 for ethnicity. Out of 3,623 participants whose race was reported in the systematic review, the racial category reported the most was White (n=2716, 74.9%), followed by Asian (n=209, 5.8%) and Black (n=274, 7.6%). Furthermore, only 25 (54%) out of the 46 papers conducted outside of the United States reported other background demographics.

CONCLUSIONS

It is important to note that the underreporting observed in this study does not necessarily indicate an underrepresentation in the actual study population. However, these findings highlight the poor reporting of race and ethnicity in iCBT trials for depression found in the literature. This lack of diversity reporting may have significant implications for the scalability of these interventions.

Effects of a Self-Guided Transdiagnostic Smartphone App on Patient Empowerment and Mental Health: Randomized Controlled Trial

BACKGROUND

Mental disorders impact both individuals and health systems. Symptoms and syndromes often remain undetected and untreated, resulting in chronification. Besides limited health care resources, within-person barriers such as the lack of trust in professionals, the fear of stigmatization, or the desire to cope with problems without professional help contribute to the treatment gap. Self-guided mental health apps may support treatment seeking by reducing within-person barriers and facilitating mental health literacy. Digital mental health interventions may also improve mental health related self-management skills and contribute to symptom reduction and the improvement of quality of life.

OBJECTIVE

This study aims to investigate the effects of a self-guided transdiagnostic app for mental health on help seeking, reduced stigma, mental health literacy, self-management skills, mental health symptoms, and quality of life using a randomized controlled design.

METHODS

Overall, 1045 participants (recruited via open, blinded, and web-based recruitment) with mild to moderate depression or anxiety-, sleep-, eating-, or somatization-related psychopathology were randomized to receive either access to a self-guided transdiagnostic mental health app (MindDoc) in addition to care as usual or care as usual only. The core features of the app were regular self-monitoring, automated feedback, and psychological courses and exercises. The coprimary outcomes were mental health literacy, mental health-related patient empowerment and self-management skills (MHPSS), attitudes toward help seeking, and actual mental health service use. The secondary outcomes were psychopathological symptom burden and quality of life. Data were collected at baseline and 8 weeks and 6 months after randomization. Treatment effects were investigated using analyses of covariance, including baseline variables as predictors and applying multiple imputation.

RESULTS

We found small but robust between-group effects for MHPSS (Cohen d=0.29), symptoms burden (Cohen d=0.28), and quality of life (Cohen d=0.19) 8 weeks after randomization. The effects on MHPSS were maintained at follow-up. Follow-up assessments also showed robust effects on mental health literacy and preliminary evidence for the improvement of help seeking. Predictors of attrition were lower age and higher personality dysfunction. Among the non-attritors, predictors for deterioration were less outpatient treatment and higher initial symptom severity.

CONCLUSIONS

A self-guided transdiagnostic mental health app can contribute to lasting improvements in patient empowerment. Symptoms of common mental disorders and quality of life improved faster in the intervention group than in the control group. Therefore, such interventions may support individuals with symptoms of 1 or more internalizing disorders, develop health-centered coping skills, prevent chronification, and accelerate symptom improvement. Although the effects for individual users are small and predictors of attrition and deterioration need to be investigated further, the potential public health impact of a self-guided intervention can be large, given its high scalability.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00022531; https://drks.de/search/de/trial/DRKS00022531.

Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing

BACKGROUND

Implementing evidence-based healthcare practices (EBPs) is a complex endeavour and often lags behind research-informed decision processes. Understanding and systematically improving implementation using implementation theory can help bridge the gap between research findings and practice. This study aims to translate, pilot, and validate a German version of the English NoMAD questionnaire (G-NoMAD), an instrument derived from the Normalisation Process Theory, to explore the implementation of EBPs.

METHODS

Survey data has been collected in four German research projects and subsequently combined into a validation data set. Two versions of the G-NoMAD existed, independently translated from the original English version by two research groups. A measurement invariance analysis was conducted, comparing latent scale structures between groups of respondents to both versions. After determining the baseline model, the questionnaire was tested for different degrees of invariance (configural, metric, scalar, and uniqueness) across samples. A confirmatory factor analysis for three models (a four-factor, a unidimensional, and a hierarchical model) was used to examine the theoretical structure of the G-NoMAD. Finally, psychometric results were discussed in a consensus meeting, and the final instructions, items, and scale format were consented to.

RESULTS

A total of 539 health care professionals completed the questionnaire. The results of the measurement invariance analysis showed configural, partial metric, and partial scalar invariance indicating that the questionnaire versions are comparable. Internal consistency ranged from acceptable to good (0.79 ≤ α ≤ 0.85) per subscale. Both the four factor and the hierarchical model achieved a better fit than the unidimensional model, with indices from acceptable (SRMR = 0.08) to good (CFI = 0.97; TLI = 0.96). However, the RMSEA values were only close to acceptable (four-factor model: χ2164 = 1029.84, RMSEA = 0.10; hierarchical model: χ2166 = 1073.43, RMSEA = 0.10).

CONCLUSIONS

The G-NoMAD provides a reliable and promising tool to measure the degree of normalisation among individuals involved in implementation activities. Since the fit was similar in the four-factor and the hierarchical model, priority should be given to the practical relevance of the hierarchical model, including a total score and four subscale scores. The findings of this study support the further usage of the G-NoMAD in German implementation settings.

TRIAL REGISTRATION

Both the AdAM project (No. NCT03430336, 06/02/2018) and the EU-project ImpleMentAll (No. NCT03652883, 29/08/2018) were registered on ClinicalTrials.gov. The ImplementIT study was registered at the German Clinical Trial Registration (No. DRKS00017078, 18/04/2019). The G-NoMAD validation study was registered at the Open Science Framework (No7u9ab, 17/04/2023).

Outcome assessment of a complex mental health intervention in the workplace. Results from the MENTUPP pilot study

OBJECTIVE

Multicomponent interventions are recommendable to achieve the greatest mental health benefits, but are difficult to evaluate due to their complexity. Defining long-term outcomes, arising from a Theory of Change (ToC) and testing them in a pilot phase, is a useful approach to plan a comprehensive and meaningful evaluation later on. This article reports on the pilot results of an outcome evaluation of a complex mental health intervention and examines whether appropriate evaluation measures and indicators have been selected ahead of a clustered randomised control trial (cRCT).

METHODS

The MENTUPP pilot is an evidence-based intervention for Small and Medium Enterprises (SMEs) active in three work sectors and nine countries. Based on our ToC, we selected the MENTUPP long-term outcomes, which are reported in this article, are measured with seven validated scales assessing mental wellbeing, burnout, depression, anxiety, stigma towards depression and anxiety, absenteeism and presenteeism. The pilot MENTUPP intervention assessment took place at baseline and at 6 months follow-up.

RESULTS

In total, 25 SMEs were recruited in the MENTUPP pilot and 346 participants completed the validated scales at baseline and 96 at follow-up. Three long-term outcomes significantly improved at follow-up (p < 0.05): mental wellbeing, symptoms of anxiety, and personal stigmatising attitudes towards depression and anxiety.

CONCLUSIONS

The results of this outcome evaluation suggest that MENTUPP has the potential to strengthen employees' wellbeing and decrease anxiety symptoms and stigmatising attitudes. Additionally, this study demonstrates the utility of conducting pilot workplace interventions to assess whether appropriate measures and indicators have been selected. Based on the results, the intervention and the evaluation strategy have been optimised.

Effects of digital psychotherapy for depression and anxiety: A systematic review and bayesian network meta-analysis

OBJECTIVE

To evaluate the effectiveness of digital psychotherapies for depression and anxiety. We conducted a systematic review and network meta-analyses (NMA) to make comparisons of digital psychotherapies.

METHODS

A bayesian NMA was conducted in this study. The databases including PubMed, Embase, Web of Science, the Cochrane Central Register of Controlled Trials and CINAL were searched for all eligible randomized controlled trials (RCTs) published from Jan 1, 2012 to Oct 1, 2022. We used the Cochrane Collaboration's Risk of bias tool for quality assessment. The primary outcomes were set as a standardized mean difference model in efficacy to describe continuous outcomes. We used STATA and WinBUGS to conduct a bayesian network meta-analysis of all interventions based on a random-effects model. This study was registered with PROSPERO, number CRD42022374558.

RESULTS

From the retrieved 16,750 publications, we included 72 RCTs (13,096 participants) with the overall medium quality and above. In terms of depression scale, cognitive behavioral therapy (CBT) was more effective than TAU (SMDs 0.53) and NT (SMDs 0.98). In terms of anxiety scale, CBT (SMDs 0.68; SMDs 0.72) and exercise therapy (ERT) (SMDs 1.01; SMDs 1.05) were more effective than TAU and NT.

LIMITATIONS

Uneven quality of literature, simple network, and subjective judgment.

CONCLUSION

Based on NMA results, we suggest that CBT, which is the most commonly used digital technology, should be preferred among digital psychotherapy for relieving depression and anxiety symptoms. Digital exercise therapy is an effective strategy to relieve some anxiety problems in the context of COVID-19.

Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review

BACKGROUND

New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness.

OBJECTIVE

This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy.

METHODS

We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study.

RESULTS

This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability.

CONCLUSIONS

Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations.

E-mental health in Germany - what is the current use and what are experiences of different types of health care providers for patients with mental illnesses?

BACKGROUND

As a new and effective support option, e-mental health interventions can be useful in complementing treatment in mental health care. To date, little is known about how health care providers use these programs to treat patients with mental illnesses in Germany. The present study aims to examine the use of and experiences with e-mental health interventions from the point of view of different types of health care providers for patients with mental illnesses.

METHODS

Data from a cross-sectional survey of routine care health care providers in Germany in 2021 were analysed. In this survey, data were collected from n = 107 general practitioners (GPs), n = 114 specialist doctors, n = 102 psychotherapists, and n = 102 inpatient clinicians. Assessments included professional use of digital media, as well as knowledge, use and experiences regarding e-mental health interventions in care of people with mental illness.

RESULTS

In the total sample of n = 425, 65.6% (n = 279) were female. The study participants had an average age of 47.7 years (SD = 11.0) and their average work experience was 20.0 years (SD = 11.1). Overall, the majority (83.8%, n = 353) had heard of e-mental health interventions, but few felt well informed. Only 28.5% (n = 121) had already used e-mental health interventions for treatment support. The most commonly recommended e-mental health interventions in the sample were deprexis (39.7%, n = 48), moodgym (24.8%, n = 30), and iFightDepression (22.3%, n = 27). The use was predominantly considered to be helpful and satisfactory. Insufficient knowledge about e-mental health interventions and lack of informational materials for patients were reported as relevant barriers to the use of e-mental health interventions.

CONCLUSIONS

E-mental health interventions can be a useful support option, but they are rarely used in the treatment of patients with mental illnesses. There is a need to disseminate information specific to the various types of health care providers. Tailored implementation strategies need to be developed in order to capitalize on the potential of effective e-mental health interventions and to improve health care for patients with mental illnesses.

Efficacy of Virtual Care for Depressive Disorders: Systematic Review and Meta-analysis

BACKGROUND

The COVID-19 pandemic has created an epidemic of distress-related mental disorders such as depression, while simultaneously necessitating a shift to virtual domains of mental health care; yet, the evidence to support the use of virtual interventions is unclear.

OBJECTIVE

The purpose of this study was to evaluate the efficacy of virtual interventions for depressive disorders by addressing three key questions: (1) Does virtual intervention provide better outcomes than no treatment or other control conditions (ie, waitlist, treatment as usual [TAU], or attention control)? (2) Does in-person intervention provide better outcomes than virtual intervention? (3) Does one type of virtual intervention provide better outcomes than another?

METHODS

We searched the PubMed, EMBASE, and PsycINFO databases for trials published from January 1, 2010, to October 30, 2021. We included randomized controlled trials of adults with depressive disorders that tested a virtual intervention and used a validated depression measure. Primary outcomes were defined as remission (ie, no longer meeting the clinical cutoff for depression), response (ie, a clinically significant reduction in depressive symptoms), and depression severity at posttreatment. Two researchers independently selected studies and extracted data using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Risk of bias was evaluated based on Agency for Healthcare and Research Quality guidelines. We calculated odds ratios (ORs) for binary outcomes and standardized mean differences (SMDs) for continuous outcomes.

RESULTS

We identified 3797 references, 24 of which were eligible. Compared with waitlist, virtual intervention had higher odds of remission (OR 10.30, 95% CI 5.70-18.60; N=619 patients) and lower posttreatment symptom severity (SMD 0.81, 95% CI 0.52-1.10; N=1071). Compared with TAU and virtual attention control conditions, virtual intervention had higher odds of remission (OR 2.27, 95% CI 1.10-3.35; N=512) and lower posttreatment symptom severity (SMD 0.25, 95% CI 0.09-0.42; N=573). In-person intervention outcomes were not significantly different from virtual intervention outcomes (eg, remission OR 0.84, CI 0.51-1.37; N=789). No eligible studies directly compared one active virtual intervention to another.

CONCLUSIONS

Virtual interventions were efficacious compared with control conditions, including waitlist control, TAU, and attention control. Although the number of studies was relatively small, the strength of evidence was moderate that in-person interventions did not yield significantly better outcomes than virtual interventions for depressive disorders.

Guided Internet-Delivered Treatment for Depression: Scoping Review

BACKGROUND

Studies on guided internet-delivered treatment have demonstrated promising results for patients with depressive disorder.

OBJECTIVE

The aim of this study was to provide an overview of this research area and identify potential gaps in the research.

METHODS

In this scoping review, web-based databases were used to identify research papers published between 2010 and 2022 where guided internet-delivered treatment was administered to participants with depressive disorders, a standardized rating scale of depressive symptoms was used as the primary outcome measure, and the treatment was compared with a control condition.

RESULTS

A total of 111 studies were included, and an overview of the studies was provided. Several gaps in the research were identified regarding the design of the studies, treatments delivered, participant representation, and treatment completion.

CONCLUSIONS

This review provides a comprehensive overview of the research area, and several research gaps were identified. The use of other designs and active control conditions is recommended. Future studies should provide access to treatment manuals, and more replications should be conducted. Researchers should aim to include underrepresented populations and provide reports of comorbidities. Definitions of adequate dosage, reports of completion rates, and reasons for treatment dropout are recommended for future studies.

["iFightDepression" in inpatient treatment : Evaluation of a web-based, therapist-guided self-management program on a specialized ward for affective disorders]

BACKGROUND

E‑mental health mainly plays a role in the outpatient treatment of patients with depressive disorders. The goal of this study was to implement and evaluate the web-based, therapist-guided self-management tool "iFightDepression" (iFD) to clarify if there is a benefit for inpatient use.

MATERIAL AND METHODS

In this study 78 inpatients with affective disorders (ICD-10 F32.0‑3, F33.0-3) or dysthymia (F34) were recruited. The intervention duration with the iFD tool went from admission until discharge, therapeutic support was granted by the ward staff. Symptom severity, intervention expectations and experience with therapy were processed in an online questionnaire before the intervention (T0) while intervention satisfaction was captured after the intervention shortly before discharge (T1) in a paper-pencil questionnaire.

RESULTS

Out of 78 participating inpatients 42 used the iFD tool at least once. Moderate to high levels of expectation regarding the iFD tool and mildly above-average level of satisfaction after the intervention were observed. Of the active users 67% indicated they would continue to use the iFD tool after discharge. The main reasons for not using the iFD tool were short duration of stay, severity of disease and lack of digital literacy.

CONCLUSION

An implementation of the iFD tool is feasible on principle. Active users gave positive feedback concerning the intervention and most participants claimed to continue using the iFD tool after discharge; however, low usage rates among study participants (42/78, 54%) showed barriers of implementation that have to be addressed and underline the importance of adaptations regarding the use of the intervention in a clinical setting.

Lockdown Measures Against the Spread of the COVID-19 Pandemic: Negative Effects for People Living With Depression

The COVID-19 pandemic and associated measures to restrict the spread of the virus correlated with limitations in healthcare and changes in depression-related lifestyle elements (loss of daily structure, lack of exercise, and extended bed and sleep time) for depressed patients, both of which are known to negatively affect the course of depression. This paper examines, (i) the reporting of a worsening state of illness as a result of COVID-19-related measures among individuals with depressive disorders; and (ii) whether this worsening was related to restrictions in healthcare for depression or changes in depression-related lifestyle. The analysis was based on a population-representative survey of the German population aged 18-69 years (N = 5,135 respondents, comprising a subgroup of n = 1,038 persons suffering from depression and n = 598 persons who spent the lockdown primarily in home isolation). The key findings were: 49% (n = 505) of respondents with self-reported diagnosed depression reported that the measures against the pandemic had a negative impact on their depressive illness (new depressive episode, worsening of symptoms, suicidal impulses, suicide attempt, and other negative consequences). Of those who reported impaired access to healthcare for their depressive illness, 70% (n = 276) also reported a worsening of their depressive illness. This was a significantly higher percentage than those who did not experience impaired access to healthcare (36%, n = 229, p < 0.001). Of those who reported changes in depression-related lifestyle (loss of daily structure, lack of exercise, or extended bed and sleep time), 58% (n = 308) reported a worsening of their depressive illness. This was a significantly higher percentage than those who did not exhibit any of the outlined behaviours (28%, n = 19, p < 0.001). Worsening of the depressive illness was most common among those who reported a lack of daily structure or extended bedtimes (67%; n = 230 resp. N = 226). People who mentioned a lack of exercise also reported a worsening of their depressive illness (59%; n = 271). These findings reinforce the need to consider the suffering and possible increased suicide risk to people suffering from depression induced by measures designed to constrain the COVID-19 pandemic; an important consideration in identifying the optimal risk-benefit ratio when setting pandemic measures. Our study highlighted the importance of maintaining healthcare, even in crisis situations, and ensuring access to guideline-based treatment for people who need urgent care. It also showed that political interventions can influence individual behaviours that can have negative effects on depressive illness.

How are guide profession and routine care setting related to adherence and symptom change in iCBT for depression? - an explorative log-data analysis

BACKGROUND

While the antidepressant efficacy of guided digital interventions has been proven in randomized controlled trials, findings from routine care are less clear. Low adherence rates are common and limit the potential effectiveness. Adherence has been linked to sociodemographic variables and the amount of guidance, but the role of the guide's profession and their work setting has not yet been studied for routine care.

METHODS

Routinely collected log data from a digital intervention for depressed patients (iFightDepression tool) were analyzed in an exploratory manner. The sample is a convenience sample from routine care, where guidance is provided by general practitioners (GP), certified psychotherapists (PT) or medical doctors specialized in mental health. Log data from 2184 patients were analyzed and five usage parameters were extracted to measure adherence (first-to-last login, time on tool, number of sessions, workshops completed and minimal dose). Multiple logistic regression was used to analyze relations between the guide's profession and clinical context as well as other covariates and adherence and symptom change on a brief depression questionnaire (PHQ-9).

RESULTS

The analyses showed a significant relation of guide profession and adherence. Guidance by PT was associated to the highest adherence scores (reference category). The odds ratios (ORs) of scoring above the median in each usage parameter for patients guided by GPs were 0.50-0.63 (all ps < 0.002) and 0.61-0.80 (p = .002-0.197) for MH. Higher age, initial PHQ-9 score and self-reported diagnosis of depression were also significantly associated with higher adherence scores. In a subsample providing enough data on the PHQ-9 (n = 347), no association of guide profession with symptom reduction was found. Instead, a greater reduction was observed for patients with a higher baseline PHQ-9 (β = -0. 39, t(341.75) = -8.814, p < .001) and for those who had achieved minimal dose (β = -2.42, t(340.34) = -4.174, P < .001) and those who had achieved minimal dose and scored high on time on tool (β = 0.22, t(341.75) = 1.965, P = .050).

CONCLUSION

Being guided by PT was associated with the highest adherence. The lowest adherence was observed in patients who were guided by GP. While no association of guide profession and symptom reduction was found in a subsample, greater adherence was associated with symptom reduction.

Intervention Use and Symptom Change With Unguided Internet-Based Cognitive Behavioral Therapy for Depression During the COVID-19 Pandemic: Log Data Analysis of a Convenience Sample

BACKGROUND

Internet- and mobile-based interventions are most efficacious in the treatment of depression when they involve some form of guidance, but providing guidance requires resources such as trained personnel, who might not always be available (eg, during lockdowns to contain the COVID-19 pandemic).

OBJECTIVE

The current analysis focuses on changes in symptoms of depression in a guided sample of patients with depression who registered for an internet-based intervention, the iFightDepression tool, as well as the extent of intervention use, compared to an unguided sample. The objective is to further understand the effects of guidance and adherence on the intervention's potential to induce symptom change.

METHODS

Log data from two convenience samples in German routine care were used to assess symptom change after 6-9 weeks of intervention as well as minimal dose (finishing at least two workshops). A linear regression model with changes in Patient Health Questionnaire (PHQ-9) score as a dependent variable and guidance and minimal dose as well as their interaction as independent variables was specified.

RESULTS

Data from 1423 people with symptoms of depression (n=940 unguided, 66.1%) were included in the current analysis. In the linear regression model predicting symptom change, a significant interaction of guidance and minimal dose revealed a specifically greater improvement for patients who received guidance and also worked with the intervention content (β=-1.75, t=-2.37, P=.02), while there was little difference in symptom change due to guidance in the group that did not use the intervention. In this model, the main effect of guidance was only marginally significant (β=-.53, t=-1.78, P=.08).

CONCLUSIONS

Guidance in internet-based interventions for depression is not only an important factor to facilitate adherence, but also seems to further improve results for patients adhering to the intervention compared to those who do the same but without guidance.

Evidence on Technology-Based Psychological Interventions in Diagnosed Depression: Systematic Review

BACKGROUND

Evidence on technology-based psychological interventions (TBIs) for the treatment of depression is rapidly growing and covers a broad scope of research. Despite extensive research in this field, guideline recommendations are still limited to the general effectiveness of TBIs.

OBJECTIVE

This study aims to structure evidence on TBIs by considering different application areas (eg, TBIs for acute treatment and their implementation in health care, such as stand-alone interventions) and treatment characteristics (eg, therapeutic rationale of TBIs) to provide a comprehensive evidence base and to identify research gaps in TBIs for diagnosed depression. Moreover, the reporting of negative events in the included studies is investigated in this review to enable subsequent safety assessment of the TBIs.

METHODS

Randomized controlled trials on adults diagnosed with unipolar depression receiving any kind of psychotherapeutic treatment, which was at least partly delivered by a technical medium, were eligible for inclusion in our preregistered systematic review. We searched for trials in CENTRAL (Cochrane Central Register of Controlled Trials; until August 2020), MEDLINE, PsycINFO, PSYNDEX, CINAHL; until the end of January 2018), clinical trial registers, and sources of gray literature (until the end of January 2019). Study selection and data extraction were conducted by 2 review authors independently.

RESULTS

Database searches resulted in 15,546 records, of which 241 publications were included, representing 83 completed studies and 60 studies awaiting classification (ie, preregistered studies, study protocols). Almost all completed studies (78/83, 94%) addressed the acute treatment phase, being largely either implemented as stand-alone interventions (66/83, 80%) or blended treatment approaches (12/83, 14%). Studies on TBIs for aftercare (4/83, 5%) and for bridging waiting periods (1/83, 1%) were scarce. Most TBI study arms (n=107) were guided (59/107, 55.1%), delivered via the internet (80/107, 74.8%), and based on cognitive behavioral treatment approaches (88/107, 79.4%). Almost all studies (77/83, 93%) reported information on negative events, considering dropouts from treatment as a negative event. However, reports on negative events were heterogeneous and largely unsystematic.

CONCLUSIONS

Research has given little attention to studies evaluating TBIs for aftercare and for bridging waiting periods in people with depression, even though TBIs are seen as highly promising in these application areas; thus, high quality studies are urgently needed. In addition, the variety of therapeutic rationales on TBIs has barely been represented by identified studies hindering the consideration of patient preferences when planning treatment. Finally, future studies should use specific guidelines to systematically assess and report negative events.

TRIAL REGISTRATION

International Prospective Register of Systematic Reviews (PROSPERO) CRD42016050413; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42016050413.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2018-028042.

The 4-Level Approach: Prevention of Suicidal Behaviour Through Community-Based Intervention

Due to the many different factors contributing to diagnostic and therapeutic deficits concerning depression and the risk of suicidal behaviour, community-based interventions combining different measures are considered the most efficient way to address these important areas of public health. The network of the European Alliance Against Depression has implemented in more than 120 regions within and outside of Europe community-based 4-level-interventions that combine activities at four levels: (i) primary care, (ii) general public, (iii) community facilitators and gatekeepers (e.g., police, journalists, caregivers, pharmacists, and teachers), and (iv) patients, individuals at high risk and their relatives. This review will discuss lessons learned from these broad implementation activities. These include targeting depression and suicidal behaviour within one approach; being simultaneously active on the four different levels; promoting bottom-up initiatives; and avoiding any cooperation with the pharmaceutical industry for reasons of credibility.