Evaluation of a brief unguided psychological online intervention for depression: A controlled trial including exploratory moderator analyses

Does outcome expectancy predict outcomes in online depression prevention? Secondary analysis of randomised-controlled trials

BACKGROUND

Evidence shows that online interventions could prevent depression. However, to improve the effectiveness of preventive online interventions in individuals with subthreshold depression, it is worthwhile to study factors influencing intervention outcomes. Outcome expectancy has been shown to predict treatment outcomes in psychotherapy for depression. However, little is known about whether this also applies to depression prevention. The aim of this study was to investigate the role of participants' outcome expectancy in an online depression prevention intervention.

METHODS

A secondary data analysis was conducted using data from two randomised-controlled trials (N = 304). Multilevel modelling was used to explore the effect of outcome expectancy on depressive symptoms and close-to-symptom-free status postintervention (6-7 weeks) and at follow-up (3-6 months). In a subsample (n = 102), Cox regression was applied to assess the effect on depression onset within 12 months. Explorative analyses included baseline characteristics as possible moderators. Outcome expectancy did not predict posttreatment outcomes or the onset of depression.

RESULTS

Small effects were observed at follow-up for depressive symptoms (β = -.39, 95% confidence interval [CI]: [-0.75, -0.03], p = .032, padjusted = .130) and close-to-symptom-free status (relative risk = 1.06, 95% CI: [1.01, 1.11], p = .013, padjusted = 0.064), but statistical significance was not maintained when controlling for multiple testing. Moderator analyses indicated that expectancy could be more influential for females and individuals with higher initial symptom severity.

CONCLUSION

More thoroughly designed, predictive studies targeting outcome expectancy are necessary to assess the full impact of the construct for effective depression prevention.

PATIENT OR PUBLIC CONTRIBUTION

This secondary analysis did not involve patients, service users, care-givers, people with lived experience or members of the public. However, the findings incorporate the expectations of participants using the preventive online intervention, and these exploratory findings may inform the future involvement of participants in the design of indicated depression prevention interventions for adults.

CLINICAL TRIAL REGISTRATION

Original studies: DRKS00004709, DRKS00005973; secondary analysis: osf.io/9xj6a.

Cognitive reappraisal in mHealth interventions to foster mental health in adults: a systematic review and meta-analysis

Background

An increasing number of mHealth interventions aim to contribute to mental healthcare of which interventions that foster cognitive reappraisal may be particularly effective.

Objectives

To evaluate the efficacy of mHealth interventions enhancing cognitive reappraisal to improve mental health in adult populations.

Methods

The literature search (four databases) yielded 30 eligible randomized controlled trials (comprising 3,904 participants). We performed a multi-level meta-analysis to examine differences between intervention and comparator conditions at post-intervention assessment. Moderator analyses were conducted for potential moderator variables (e.g., type of comparators).

Results

Most interventions were CBT-based with other training components in addition to cognitive reappraisal. We found preliminary evidence for a small to medium effect favouring mHealth interventions to enhance cognitive reappraisal over comparators, M(SMD) = 0.34, p = .002. When analysing single symptoms, there was evidence for a small to medium effect of mHealth interventions on anxiety and depressive symptoms, but not for psychological distress and well-being. All analyses showed substantial heterogeneity. Moderator analyses revealed evidence for more favourable effects in studies with passive comparators. There was an overall high risk of bias in most of the studies.

Conclusions

We found preliminary evidence for a small to medium effect of mHealth interventions including a cognitive reappraisal component to improve mental health. However, most of the interventions were complex (i.e., reappraisal was provided alongside other components), which prevents us from examining reappraisal-specific effects beyond general mental health promotion in mHealth. Dismantling studies examining the effects of single intervention components are warranted to corroborate these promising results.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=142149, identifier [CRD42019142149].

Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms

Introduction

Personalization is a much-discussed approach to improve adherence and outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open, such as (1) what personalization is, (2) how prevalent it is in practice, and (3) what benefits it truly has.

Methods

We address this gap by performing a systematic literature review identifying all empirical studies on DMHIs targeting depressive symptoms in adults from 2015 to September 2022. The search in Pubmed, SCOPUS and Psycinfo led to the inclusion of 138 articles, describing 94 distinct DMHIs provided to an overall sample of approximately 24,300 individuals.

Results

Our investigation results in the conceptualization of personalization as purposefully designed variation between individuals in an intervention's therapeutic elements or its structure. We propose to further differentiate personalization by what is personalized (i.e., intervention content, content order, level of guidance or communication) and the underlying mechanism [i.e., user choice, provider choice, decision rules, and machine-learning (ML) based approaches]. Applying this concept, we identified personalization in 66% of the interventions for depressive symptoms, with personalized intervention content (32% of interventions) and communication with the user (30%) being particularly popular. Personalization via decision rules (48%) and user choice (36%) were the most used mechanisms, while the utilization of ML was rare (3%). Two-thirds of personalized interventions only tailored one dimension of the intervention.

Discussion

We conclude that future interventions could provide even more personalized experiences and especially benefit from using ML models. Finally, empirical evidence for personalization was scarce and inconclusive, making further evidence for the benefits of personalization highly needed.

Systematic Review Registration

Identifier: CRD42022357408.

Effectiveness and Minimum Effective Dose of App-Based Mobile Health Interventions for Anxiety and Depression Symptom Reduction: Systematic Review and Meta-Analysis

BACKGROUND

Mobile health (mHealth) apps offer new opportunities to deliver psychological treatments for mental illness in an accessible, private format. The results of several previous systematic reviews support the use of app-based mHealth interventions for anxiety and depression symptom management. However, it remains unclear how much or how long the minimum treatment "dose" is for an mHealth intervention to be effective. Just-in-time adaptive intervention (JITAI) has been introduced in the mHealth domain to facilitate behavior changes and is positioned to guide the design of mHealth interventions with enhanced adherence and effectiveness.

OBJECTIVE

Inspired by the JITAI framework, we conducted a systematic review and meta-analysis to evaluate the dose effectiveness of app-based mHealth interventions for anxiety and depression symptom reduction.

METHODS

We conducted a literature search on 7 databases (ie, Ovid MEDLINE, Embase, PsycInfo, Scopus, Cochrane Library (eg, CENTRAL), ScienceDirect, and ClinicalTrials, for publications from January 2012 to April 2020. We included randomized controlled trials (RCTs) evaluating app-based mHealth interventions for anxiety and depression. The study selection and data extraction process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We estimated the pooled effect size using Hedge g and appraised study quality using the revised Cochrane risk-of-bias tool for RCTs.

RESULTS

We included 15 studies involving 2627 participants for 18 app-based mHealth interventions. Participants in the intervention groups showed a significant effect on anxiety (Hedge g=-.10, 95% CI -0.14 to -0.06, I2=0%) but not on depression (Hedge g=-.08, 95% CI -0.23 to 0.07, I2=4%). Interventions of at least 7 weeks' duration had larger effect sizes on anxiety symptom reduction.

CONCLUSIONS

There is inconclusive evidence for clinical use of app-based mHealth interventions for anxiety and depression at the current stage due to the small to nonsignificant effects of the interventions and study quality concerns. The recommended dose of mHealth interventions and the sustainability of intervention effectiveness remain unclear and require further investigation.

Online micro intervention for mood improvement: The role of confidence, motivation, and activity type

BACKGROUND

Internet interventions provide a unique opportunity to increase widespread accessibility of treatment at reduced and scalable costs (Muñoz, 2010). Previous research has explored the impact of specific types of activities on participant's main depressive symptoms i.e., anhedonia, or enjoyment levels, and mood (Bunge et al., 2017).The aim of the current study is to improve the understanding of the effects of online micro interventions targeting motivation, enjoyment levels, and mood.

METHODS

A total of 838 participants recruited from Amazon Mechanical Turk participated in an online calendar activity to improve mood.

RESULTS

A regression analysis showed that confidence and motivation were significantly associated with mood (R² = 0.467, p < .001). The total number of activities reported in the last two days was associated with participants' current mood (R² = 0.203, p < .001) and enjoyment (R² = 0.156, p < .001). Interestingly, only mastery and meaningful activities improved mood but not pleasant activities. Regarding enjoyment, pleasant and meaningful activities impacted current enjoyment of the day but not mastery activities. Lastly, only individuals who engaged with the calendar showed a significant increase in motivation and confidence.

LIMITATIONS

Depression may moderate engagement and was not analyzed in the present study. Additionally, there were no follow-up analyses that looked at the long-term effects of the intervention or changes in actual activity engagement.

CONCLUSIONS

Online micro interventions have a promising future as an intervention that can impact the mood and motivation for change. Future studies should examine increasing engagement to facilitate confidence and motivation to enact change.

A randomized controlled trial on a self-guided Internet-based intervention for gambling problems

The majority of individuals with problematic and pathological gambling remain untreated, and treatment barriers are high. Internet-based interventions can help to address existing barriers, and first studies suggest their potential for this target group. Within a randomized controlled trial (N = 150) with two assessment times (baseline and post-intervention), we aimed to investigate the feasibility, acceptance, and effectiveness of a self-guided Internet-based intervention targeted at gambling problems. We expected a significant reduction in gambling symptoms (primary outcome) and depressive symptoms as well gambling-specific dysfunctional thoughts (secondary outcomes) in the intervention group (IG) compared to a wait-list control group with access to treatment-as-usual (control group, CG) after the intervention period of 8 weeks. Results of the complete cases, per protocol, intention-to-treat (ITT), and frequent user analyses showed significant improvements in both groups for primary and secondary outcomes but no significant between-group differences (ITT primary outcome, F(1,147) = .11, p = .739, ηp2 < .001). Moderation analyses indicated that individuals in the IG with higher gambling and depressive symptoms, older age, and comorbid anxiety symptoms showed significant improvement relative to the CG. The intervention was positively evaluated (e.g., 96.5% rated the program as useful). Possible reasons for the nonsignificant between-group differences are discussed. Future studies should include follow-up assessments and larger samples to address limitations of the present study.

Trial Registration ClinicalTrials.gov (NCT03372226), http://clinicaltrials.gov/ct2/show/NCT03372226, date of registration (13/12/2017).

Exploring the Role of Persuasive Design in Unguided Internet-Delivered Cognitive Behavioral Therapy for Depression and Anxiety Among Adults: Systematic Review, Meta-analysis, and Meta-regression

BACKGROUND

Internet-delivered cognitive behavioral therapy (ICBT) is an effective treatment that can overcome barriers to mental health care. Various research groups have suggested that unguided ICBT (ie, ICBT without therapist support) and other eHealth interventions can be designed to enhance user engagement and thus outcomes. The persuasive systems design framework captures most design recommendations for eHealth interventions, but there is little empirical evidence that persuasive design is related to clinical outcomes in unguided ICBT.

OBJECTIVE

This study aims to provide an updated meta-analysis of randomized controlled trials of unguided ICBT for depression and anxiety, describe the frequency with which various persuasive design principles are used in such interventions, and use meta-regression to explore whether a greater number of persuasive design elements predicts efficacy in unguided ICBT for depression and anxiety.

METHODS

We conducted a systematic review of 5 databases to identify randomized controlled trials of unguided ICBT for depression and anxiety. We conducted separate random effects meta-analyses and separate meta-regressions for depression and anxiety interventions. Each meta-regression included 2 steps. The first step included, as a predictor, whether each intervention was transdiagnostic. For the meta-regression of ICBT for depression, the first step also included the type of control condition. The number of persuasive design principles identified for each intervention was added as a predictor in the second step to reveal the additional variance in effect sizes explained by persuasive design.

RESULTS

Of the 4471 articles we identified in our search, 46 (1.03%) were eligible for inclusion in our analyses. Our meta-analyses showed effect sizes (Hedges g) ranging from 0.22 to 0.31 for depression interventions, depending on the measures taken to account for bias in the results. We found a mean effect size of 0.45 (95% CI 0.33-0.56) for anxiety interventions, with no evidence that the results were inflated by bias. Included interventions were identified as using between 1 and 13 persuasive design principles, with an average of 4.95 (SD 2.85). The meta-regressions showed that a greater number of persuasive design principles predicted greater efficacy in ICBT for depression (R2 change=0.27; B=0.04; P=.02) but not anxiety (R2 change=0.05; B=0.03; P=.17).

CONCLUSIONS

These findings show wide variability in the use of persuasive design in unguided ICBT for depression and anxiety and provide preliminary support for the proposition that more persuasively designed interventions are more efficacious, at least in the treatment of depression. Further research is needed to clarify the role of persuasive design in ICBT.

Smartphone Apps for the Treatment of Mental Disorders: Systematic Review

BACKGROUND

Smartphone apps are an increasingly popular means for delivering psychological interventions to patients suffering from a mental disorder. In line with this popularity, there is a need to analyze and summarize the state of the art, both from a psychological and technical perspective.

OBJECTIVE

This study aimed to systematically review the literature on the use of smartphones for psychological interventions. Our systematic review has the following objectives: (1) analyze the coverage of mental disorders in research articles per year; (2) study the types of assessment in research articles per mental disorder per year; (3) map the use of advanced technical features, such as sensors, and novel software features, such as personalization and social media, per mental disorder; (4) provide an overview of smartphone apps per mental disorder; and (5) provide an overview of the key characteristics of empirical assessments with rigorous designs (ie, randomized controlled trials [RCTs]).

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews were followed. We performed searches in Scopus, Web of Science, American Psychological Association PsycNET, and Medical Literature Analysis and Retrieval System Online, covering a period of 6 years (2013-2018). We included papers that described the use of smartphone apps to deliver psychological interventions for known mental disorders. We formed multidisciplinary teams, comprising experts in psychology and computer science, to select and classify articles based on psychological and technical features.

RESULTS

We found 158 articles that met the inclusion criteria. We observed an increasing interest in smartphone-based interventions over time. Most research targeted disorders with high prevalence, that is, depressive (31/158,19.6%) and anxiety disorders (18/158, 11.4%). Of the total, 72.7% (115/158) of the papers focused on six mental disorders: depression, anxiety, trauma and stressor-related, substance-related and addiction, schizophrenia spectrum, and other psychotic disorders, or a combination of disorders. More than half of known mental disorders were not or very scarcely (<3%) represented. An increasing number of studies were dedicated to assessing clinical effects, but RCTs were still a minority (25/158, 15.8%). From a technical viewpoint, interventions were leveraging the improved modalities (screen and sound) and interactivity of smartphones but only sparingly leveraged their truly novel capabilities, such as sensors, alternative delivery paradigms, and analytical methods.

CONCLUSIONS

There is a need for designing interventions for the full breadth of mental disorders, rather than primarily focusing on most prevalent disorders. We further contend that an increasingly systematic focus, that is, involving RCTs, is needed to improve the robustness and trustworthiness of assessments. Regarding technical aspects, we argue that further exploration and innovative use of the novel capabilities of smartphones are needed to fully realize their potential for the treatment of mental health disorders.

Brief Web-Based Intervention for Depression: Randomized Controlled Trial on Behavioral Activation

Background

Web-based interventions have been shown to be effective for the treatment of depression. However, interventions are often complex and include a variety of elements, making it difficult to identify the most effective component(s).

Objective

The aim of this pilot study was to shed light on mechanisms in the online treatment of depression by comparing a single-module, fully automated intervention for depression (internet-based behavioral activation [iBA]) to a nonoverlapping active control intervention and a nonactive control group.

Methods

We assessed 104 people with at least mild depressive symptoms (Patient Health Questionnaire-9, >4) via the internet at baseline (t₀) and 2 weeks (t₁) and 4 weeks (t₂) later. After the t₀ assessment, participants were randomly allocated to one of three groups: (1) iBA (n=37), (2) active control using a brief internet-based mindfulness intervention (iMBI, n=32), or (3) care as usual (CAU, n=35). The primary outcome was improvement in depressive symptoms, as measured using the Patient Health Questionnaire-9. Secondary parameters included changes in activity, dysfunctional attitudes, and quality of life

Results

While groups did not differ regarding the change in depression from t₀ to t₁ (η_p²=.007, P=.746) or t₀ to t₂ (η_p²=.008, P=.735), iBA was associated with a larger decrease in dysfunctional attitudes from t₀ to t₂ in comparison to CAU (η_p²=.053, P=.04) and a larger increase in activity from t₀ to t₁ than the pooled control groups (η_p²=.060, P=.02). A change in depression from t₀ to t₂ was mediated by a change in activity from t₀ to t₁. At t₁, 22% (6/27) of the participants in the iBA group and 12% (3/25) of the participants in the iMBI group indicated that they did not use the intervention.

Conclusions

Although we did not find support for the short-term efficacy of the single-module iBA regarding depression, long-term effects are still conceivable, potentially initiated by changes in secondary outcomes. Future studies should use a longer intervention and follow-up interval.

Trial Registration

DKRS (#DRKS00011562)

Diminishing Effects After Recurrent Use of Self-Guided Internet-Based Interventions in Depression: Randomized Controlled Trial

Background

Self-guided internet-based interventions have several advantages over guided interventions and are generally effective in treating psychiatric symptoms.

Objective

We aimed to investigate whether the use of a new self-guided internet-based intervention (MOOD) would lead to a significant reduction in depressive symptoms compared with a care-as-usual (CAU) control group in a sample of individuals with depressive symptoms, most of whom had already used a different self-guided internet-based intervention in a previous trial.

Methods

A total of 125 individuals were randomized to the intervention condition (MOOD) and received access to the intervention for a period of six weeks or a CAU group. After six weeks, all participants were invited to take part in the post assessment. The Beck Depression Inventory-II served as the primary outcome.

Results

Both intention-to-treat as well as per-protocol analyses indicated that the depressive symptomatology decreased in both conditions but showed no advantage for those who had used MOOD. Subsequent moderation analyses suggested that those individuals who had less experience with psychotherapy benefitted to a greater extent compared with those with more experience.

Conclusions

Self-guided internet-based interventions are deemed a suitable first-step approach to the treatment of depression. However, our results indicate that they are more efficacious in those with less psychotherapy experience.

Trial Registration

ClinicalTrials.gov NCT03795480; http://clinicaltrials.gov/ct2/show/NCT03795480