Efficacy of an internet-based self-management intervention for depression or dysthymia - a study protocol of an RCT using an active control condition

Active Components in Internet-Based Cognitive-Behavioral Therapy for Social Anxiety Disorder: A Randomized Full Factorial Trial

INTRODUCTION

Many studies have demonstrated that social anxiety disorder (SAD) can be effectively treated with psychotherapy, particularly cognitive-behavioral therapy (CBT), including internet-based CBT (ICBT). Despite evidence-based treatments, many individuals do not sufficiently benefit from them. Identifying the active components could help improve the effectiveness of SAD treatment. This study tested the effects of four treatment components (psychoeducation, cognitive restructuring, attention training, and exposure) within ICBT for SAD to investigate its active components.

METHODS

This randomized full factorial trial consisted of four factors (i.e., treatment components) and 16 conditions. A total of 464 adults with a diagnosed SAD were recruited from the community. The primary outcome was SAD symptoms at 8 weeks (post-assessment). Secondary outcomes included SAD diagnosis, SAD symptoms at follow-up (4 months after post), depression and anxiety symptoms, quality of life, client satisfaction, and adverse effects.

RESULTS

Conditions including psychoeducation and exposure were significantly more effective in reducing SAD symptoms at post compared to conditions without these components. Conditions including cognitive restructuring and attention training did not show superiority over conditions without them at post. However, all treatment conditions significantly reduced symptoms compared to the condition without a treatment component. At follow-up, the superiority of psychoeducation and exposure was not significant anymore due to the version without the respective components catching up.

CONCLUSION

The findings suggest that while all treatment components of ICBT for SAD are beneficial compared to no treatment, psychoeducation and exposure include specific active components that significantly improve treatment outcomes more quickly in ICBT for SAD.

INTRODUCTION

Many studies have demonstrated that social anxiety disorder (SAD) can be effectively treated with psychotherapy, particularly cognitive-behavioral therapy (CBT), including internet-based CBT (ICBT). Despite evidence-based treatments, many individuals do not sufficiently benefit from them. Identifying the active components could help improve the effectiveness of SAD treatment. This study tested the effects of four treatment components (psychoeducation, cognitive restructuring, attention training, and exposure) within ICBT for SAD to investigate its active components.

METHODS

This randomized full factorial trial consisted of four factors (i.e., treatment components) and 16 conditions. A total of 464 adults with a diagnosed SAD were recruited from the community. The primary outcome was SAD symptoms at 8 weeks (post-assessment). Secondary outcomes included SAD diagnosis, SAD symptoms at follow-up (4 months after post), depression and anxiety symptoms, quality of life, client satisfaction, and adverse effects.

RESULTS

Conditions including psychoeducation and exposure were significantly more effective in reducing SAD symptoms at post compared to conditions without these components. Conditions including cognitive restructuring and attention training did not show superiority over conditions without them at post. However, all treatment conditions significantly reduced symptoms compared to the condition without a treatment component. At follow-up, the superiority of psychoeducation and exposure was not significant anymore due to the version without the respective components catching up.

CONCLUSION

The findings suggest that while all treatment components of ICBT for SAD are beneficial compared to no treatment, psychoeducation and exposure include specific active components that significantly improve treatment outcomes more quickly in ICBT for SAD.

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.

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.

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).

Newly diagnosed with inflammatory arthritis (NISMA)-development of a complex self-management intervention

BACKGROUND

Patients newly diagnosed with inflammatory arthritis (IA) request regular consultations and support from health professionals to manage physiological, emotional, and social challenges. Evidence suggests that providing a tailored multi-component self-management program may benefit disease management. However, there is a lack of evidence of effective interventions with multiple components targeting the needs of this group. Therefore, the aim of this study was to develop a self-management intervention targeting newly diagnosed patients with IA, following the Medical Research Council (MRC) framework for developing complex interventions.

METHODS

The development of the complex self-management intervention covered three steps. First, the evidence base was identified through literature reviews, in which we described a preliminary nurse-led intervention. Secondly, we chose Social Cognitive Theory as the underlying theory along with Acceptance and Commitment Theory to support our communication strategy. Thirdly, the preliminary intervention was discussed and further developed in workshops to ensure that the intervention was in accordance with patients' needs and feasible in clinical practice.

RESULTS

The developed intervention comprises a 9-month nurse-led intervention (four individual and two group sessions). A physiotherapist and an occupational therapist will attend the group sessions along with the nurse. All sessions should target IA-specific self-management with a particular focus on medical, role, and emotional management.

CONCLUSION

Through the workshops, we involved all levels of the organization to optimize the intervention, but also to create ownership and commitment, and to identify barriers and shortcomings of the preliminary intervention. As a result, from the existing evidence, we believe that we have identified effective mechanisms to increase self-management in people newly diagnosed with IA. Further, we believe that the involvement of various stakeholders has contributed significantly to developing a relevant and feasible intervention. The intervention is a nurse-led complex self-management intervention embedded in a multidisciplinary team (named NISMA). The intervention is currently being tested in a feasibility study.

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.

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

BACKGROUND

An increasing number of studies suggest that web-based interventions for patients with depression can reduce their symptoms and are expected to fill currently existing treatment gaps. However, evidence for their efficacy has mainly been derived from comparisons with wait-list or treatment as usual controls. In particular, designs using wait-list controls are unlikely to induce hope and may even have nocebo effects, making it difficult to draw conclusions about the intervention's efficacy. Studies using active controls are rare and have not yielded conclusive results.

OBJECTIVE

The main objective of this study is to assess the acute and long-term antidepressant efficacy of a 6-week, guided, web-based self-management intervention building on the principles of cognitive behavioral therapy (iFightDepression tool) for patients with depression compared with web-based progressive muscle relaxation as an active control condition.

METHODS

A total of 348 patients with mild-to-moderate depressive symptoms or dysthymia (according to the Mini International Neuropsychiatric Interview) were recruited online and randomly assigned to 1 of the 2 intervention arms. Acute antidepressant effects after 6 weeks and long-term effects at 3-, 6-, and 12-month follow-up were studied using the Inventory of Depressive Symptomatology-self-rating as a primary outcome parameter and change in quality of life (Short Form 12) and user satisfaction (client satisfaction questionnaire) as secondary outcome parameters. Treatment effects were assessed using mixed model analyses.

RESULTS

Over the entire observation period, a greater reduction in symptoms of depression (P=.01) and a greater improvement of life quality (P<.001) was found in the intervention group compared with the active control group. Separate tests for each time point revealed significant effects on depressive symptoms at the 3-month follow-up (d=0.281; 95% CI 0.069 to 0.493), but not after 6 weeks (main outcome:d=0.192; 95% CI -0.020 to 0.404) and 6 and 12 months. The intervention was significantly superior to the control condition with respect to user satisfaction (25.31 vs 21.97; t₂₅₉=5.804; P<.01).

CONCLUSIONS

The fact that antidepressant effects have been found for a guided self-management tool in comparison with an active control strengthens the evidence base for the efficacy of web-based interventions. The antidepressant effect became most prominent at the 3-month follow-up. After 6 weeks of intervention, significant positive effects were observed on life quality but not on depressive symptoms. Although the effect size of such web-based interventions on symptoms of depression might be smaller than that suggested by earlier studies using wait-list control conditions, they can be a cost-effective addition to antidepressants and face-to-face psychotherapy.

TRIAL REGISTRATION

International Clinical Trials Registry Platform ICTRP080-15-09032015; https://apps.who.int/trialsearch/Trial2.aspx?TrialID=DRKS00009323.