Efficacy of computer- and/or internet-based cognitive-behavioral guided self-management for depression in adults: a systematic review and meta-analysis of randomized controlled trials

Digital mental health interventions for the treatment of depression: A multiverse meta-analysis

BACKGROUND

The varying sizes of effects in published meta-analyses on digital interventions for depression prompt questions about their efficacy.

METHODS

A systematic search in Embase, PsycINFO, and PubMed identified 125 randomised controlled trials up to February 2023, comparing digital interventions for depression against inactive controls. The stability of results was evaluated with a multiverse meta-analysis, thousands of meta-analyses were conducted based on different combinations of analytical choices, like target populations, intervention characteristics, and study designs.

RESULTS

A total of 3638 meta-analyses were performed based on 125 randomised controlled trials and 263 effect sizes, with a total of 32,733 participants. The average effect size was Hedges' g = 0.43, remaining positive at both the 10th (g = 0.16) and 90th percentiles (g = 0.74). Most meta-analyses indicated a statistically significant benefit of digital interventions. Larger effects were observed in meta-analyses focusing on adults, low- and middle-income countries, guided interventions, comparing interventions with waitlist controls, and patients with major depressive or unipolar mood disorders. Smaller effects appeared when adjusting for publication bias and in assessments after 24 weeks.

LIMITATIONS

While multiverse meta-analysis aims to exhaustively investigate various analytical decisions, some subjectivity remains due to the necessity of making choices that affect the methodology. Additionally, the quality of the included primary studies was low.

CONCLUSIONS

The analytical decisions made during performing pairwise meta-analyses result in vibrations from small to medium effect sizes. Our study provides robust evidence for the effectiveness of digital interventions for depression while highlighting important factors associated with treatment outcomes.

Predicting CBT modality, treatment participation, and reliable improvements for individuals with anxiety and depression in a specialized mental health centre: a retrospective population-based cohort study

BACKGROUND

Cognitive Behaviour Therapy (CBT) is one of the most successful therapeutic approaches for treating anxiety and depression. Clinical trials show that for some clients, internet-based CBT (eCBT) is as effective as other CBT delivery modes. However, the fidelity of these effects may be weakened in real-world settings where clients and providers have the freedom to choose a CBT delivery mode and switch treatments at any time. The purpose of this study is to measure the CBT attendance rate and identify client-level characteristics associated with delivery mode selection and having reliable and clinically significant improvement (RCSI) of treatment in each delivery mode in a real-world CBT outpatient program.

METHODS

This is a retrospective cohort analysis of electronic medical records collected between May 1, 2019, and March 31, 2022, at Ontario Shores Centre for Mental Health Sciences. Regression models were used to investigate the impact of individual client characteristics on participation and achieving RCSI of different CBT delivery modes.

RESULTS

Our data show a high attendance rate for two and more CBT sessions across all modalities (98% of electronic, 94% of group, 100% of individual, and 99% of mixed CBT). Individuals were more likely to enter mixed and group CBT modality if they were younger, reported being employed, and reported higher depression severity at the baseline. Among the four modalities of CBT delivery, group CBT clients were least likely to have RCSI. Of those who started sessions, clients were significantly more likely to experience RCSI on the Patient Health Questionnaire (PHQ)-9 and the Generalized Anxiety Disorder (GAD)-7 if they were employed, reported more severe symptoms at baseline, and were living in the most deprived neighborhoods.

CONCLUSIONS

This study will contribute to the body of knowledge about the implementation and treatment planning of different CBT delivery modes in real-world settings. With the changing clinical environment, it is possible to advocate for the adoption of the eCBT intervention to improve therapy practices and achieve better treatment success. The findings can help guide future CBT program planning based on client socio-demographic characteristics, allowing the optimal therapy type to be targeted to the right client at the right time.

Predictors of Use and Drop Out From a Web-Based Cognitive Behavioral Therapy Program and Health Community for Depression and Anxiety in Primary Care Patients: Secondary Analysis of a Randomized Controlled Trial

BACKGROUND

A previously reported study examined the treatment of primary care patients with at least moderate severity depressive or anxiety symptoms via an evidence-based computerized cognitive behavioral therapy (CCBT) program (Beating the Blues) and an online health community (OHC) that included a moderated internet support group. The 2 treatment arms proved to be equally successful at 6-month follow-up.

OBJECTIVE

Although highly promising, e-mental health treatment programs have encountered high rates of noninitiation, poor adherence, and discontinuation. Identifying ways to counter these tendencies is critical for their success. To further explore these issues, this study identified the primary care patient characteristics that increased the chances patients would not initiate the use of an intervention, (ie, not try it even once), initiate use, and go on to discontinue or continue to use an intervention.

METHODS

The study had 3 arms: one received access to CCBT (n=301); another received CCBT plus OHC (n=302), which included a moderated internet support group; and the third received usual care (n=101). Participants in the 2 active intervention arms of the study were grouped together for analyses of CCBT use (n=603) because both arms had access to CCBT, and there were no differences in outcomes between the 2 arms. Analyses of OHC use were based on 302 participants who were randomized to that arm.

RESULTS

Several baseline patient characteristics were associated with failure to initiate the use of CCBT, including having worse physical health (measured by the Short Form Health Survey Physical Components Score, P=.01), more interference from pain (by the Patient-Reported Outcomes Measurement Information System Pain Interference score, P=.048), less formal education (P=.02), and being African American or another US minority group (P=.006). Characteristics associated with failure to initiate use of the OHC were better mental health (by the Short Form Health Survey Mental Components Score, P=.04), lower use of the internet (P=.005), and less formal education (P=.001). Those who initiated the use of the CCBT program but went on to complete less of the program had less formal education (P=.01) and lower severity of anxiety symptoms (P=.03).

CONCLUSIONS

This study found that several patient characteristics predicted whether a patient was likely to not initiate use or discontinue the use of CCBT or OHC. These findings have clear implications for actionable areas that can be targeted during initial and ongoing engagement activities designed to increase patient buy-in, as well as increase subsequent use and the resulting success of eHealth programs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01482806; https://clinicaltrials.gov/study/NCT01482806.

Digital Therapeutics for Improving Effectiveness of Pharmaceutical Drugs and Biological Products: Preclinical and Clinical Studies Supporting Development of Drug + Digital Combination Therapies for Chronic Diseases

Limitations of pharmaceutical drugs and biologics for chronic diseases (e.g., medication non-adherence, adverse effects, toxicity, or inadequate efficacy) can be mitigated by mobile medical apps, known as digital therapeutics (DTx). Authorization of adjunct DTx by the US Food and Drug Administration and draft guidelines on "prescription drug use-related software" illustrate opportunities to create drug + digital combination therapies, ultimately leading towards drug-device combination products (DTx has a status of medical devices). Digital interventions (mobile, web-based, virtual reality, and video game applications) demonstrate clinically meaningful benefits for people living with Alzheimer's disease, dementia, rheumatoid arthritis, cancer, chronic pain, epilepsy, depression, and anxiety. In the respective animal disease models, preclinical studies on environmental enrichment and other non-pharmacological modalities (physical activity, social interactions, learning, and music) as surrogates for DTx "active ingredients" also show improved outcomes. In this narrative review, we discuss how drug + digital combination therapies can impact translational research, drug discovery and development, generic drug repurposing, and gene therapies. Market-driven incentives to create drug-device combination products are illustrated by Humira® (adalimumab) facing a "patent-cliff" competition with cheaper and more effective biosimilars seamlessly integrated with DTx. In conclusion, pharma and biotech companies, patients, and healthcare professionals will benefit from accelerating integration of digital interventions with pharmacotherapies.

Therapeutic alliance in two forms of guided self-help for binge eating

The role of therapeutic alliance within psychological treatments for eating disorders (EDs), including those delivered remotely, is well established. However, few studies have investigated alliance in guided self-help, a widely recommended first-line treatment for EDs characterised by regular binge eating. Using data from a randomised controlled trial, the current study examined both facilitator and patient assessments of alliance within e-mail-assisted and face-to-face guided self-help and looked at associations between alliance, ED symptoms and ED-related impairment. One hundred thirteen patients and 11 facilitators completed measures of alliance during and following a course of guided self-help. Whilst ratings were reliable across patients and facilitators, alliance scores were higher both in the patient sample and in the face-to-face condition. Ratings of alliance showed no correlations with ED symptoms at post-treatment, and early alliance was not significantly associated with outcome, which could inform how early symptom change is encouraged in guided self-help.

Internet-delivered therapist-assisted cognitive behavioral therapy for gambling disorder: a randomized controlled trial

Objectives

Cognitive behavioral therapy (CBT) is the most promising treatment for gambling disorder (GD) but only 21% of those with problematic gambling seek treatment. CBT over the Internet might be one way to reach a larger population. The aim of this study was to assess the effectiveness of Internet-delivered CBT with therapist guidance compared to an active control treatment.

Methods

Using a single-blinded design, 71 treatment-seeking gamblers (18-75 years) diagnosed with GD were randomized to 8 weeks of Internet-delivered CBT guided by telephone support, or 8 weeks of Internet-delivered motivational enhancement paired with motivational interviewing via telephone (IMI). The primary outcome was gambling symptoms measured at a first face-to-face assessment, baseline (treatment start), every 2 weeks, post-treatment, and 6-month follow-up. Gambling expenditures, time spent gambling, depression, anxiety, cognitive distortions, and quality of life were assessed as secondary outcomes. Analysis was performed on the full analysis sample (n = 60), with intention-to-treat sensitivity analyses (n = 69).

Results

In the CBT group, 80% stayed in treatment until the final week, compared to 67% in IMI. Post-treatment and at 6-month follow-up, no differences were found between CBT and IMI for any outcome measure. An exploratory analysis of the total sample (n = 60) showed a significant effect of time during treatment on gambling symptoms (d, [95% CI] 0.52, [-1.15, 2.02]) and all secondary outcomes except the gambling diary (depression (0.89, [-1.07-2.65]); anxiety (0.69, [-1.20-2.38])); cognitive distortions (0.84, [-0.73-2.29]); quality of life (0.60, [-0.61-1.70])). Post-treatment, there were no clinical gambling symptoms in either group. Some deterioration was seen between post-treatment and 6-month follow-up on gambling symptoms (0.42, [-1.74-2.43]), depression (0.59, [-0.82-1.86]), and anxiety (0.30, [-0.99-1.48]). Additionally, it was observed that the largest reduction in gambling symptoms was between the first assessment and baseline.

Conclusion

Both treatments offered in this study were effective at reducing gambling symptoms. It is also possible that the process of change started before treatment, which gives promise to low-intensity interventions for GD. Additional research is needed as this approach could be both cost-effective and has the potential to reach more patients in need of treatment than is currently possible.

Clinical trial registration

https://www.isrctn.com/, identifier ISRCTN38692394.

Digital Health Applications in the Area of Mental Health

BACKGROUND

The introduction of digital health applications (DiGA) is a fundamental innovation in Germany. In the field of mental health, numerous applications are already available whose efficacy has been tested in clinical trials. We investigated whether, and to what extent, the use of DiGA can be recommended on the basis of the available evidence.

METHODS

In this scoping review, we summarize the evidence supporting the use of DiGA in the mental health field through an examination of relevant publications that were retrieved by a systematic literature search. We provide an annotated tabular listing and discuss the current advantages of, and obstacles to, the care of mentally ill patients with the aid of DiGA.

RESULTS

We identified 17 DiGA for use in depression, anxiety disorders, addiction disorders, sleep disorders, stress/burnout, vaginismus, and chronic pain. These DiGA have been evaluated to date in 3 meta-analyses, 39 randomized controlled trials (RCTs), and two single-armed intervention trials. 23 of the 36 published trials were carried out with the direct participation of the manufacturers. 29 of the 39 RCTs were not blinded or contained no information regarding blinding. Active controls were used in 6 of the 39 RCTs. The reported effect sizes, with the exclusion of pre-post analyses, ranged from 0.16 to 1.79.

CONCLUSION

Most of the published studies display a high risk of bias, both because of the manufacturers' participation and because of methodological deficiencies. DiGA are an increasingly important therapeutic modality in psychiatry. The available evidence indicates that treatment effects are indeed present, but prospective comparisons with established treatments are still entirely lacking.

Long-Term Efficacy of Internet-Based Cognitive Behavioral Therapy Self-Help Programs for Adults With Depression: Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Depression is a worldwide mental disorder and a leading cause of disability. Many people with depression do not want to take medication or have the motivation to seek psychotherapy treatment for many reasons. Guided internet-based self-help programs may be a promising solution for addressing these issues. This kind of intervention has proven to be effective in reducing depression symptoms on a short-term scale. However, as treatment often is a long-term rehabilitation process, it is important to examine not only the short-term effects of internet-based cognitive behavioral therapy (iCBT) self-help treatment but also the follow-up or long-term efficacy of this kind of intervention.

OBJECTIVE

This systematic review and meta-analysis aimed to identify studies that examined follow-up data ≥8 weeks after posttreatment measurements and thereby examined the long-term efficacy of iCBT self-help programs with minimal weekly guidance for people with depression. It aimed to analyze the long-term efficacy of iCBT treatments compared to control conditions as well as long-term efficacy within the iCBT treatment conditions. Additionally, it aimed to conduct subgroup analyses according to the follow-up time points for each outcome. Finally, it examined long-term improvements in quality of life.

METHODS

The Cochrane Collaboration Depression, Anxiety, and Neurosis Controlled Trials Register (CCDANCTR), grey literature, reference lists, and correspondence were used to search for published and unpublished randomized controlled trials (RCTs) that reported the long-term or follow-up efficacy of computer-based or iCBT self-help treatments for depression with minimal guidance of up to 10 min/wk. The search took place between 2015 and 2022 (October).

RESULTS

The search resulted in a total of 2809 study abstracts, of which 15 studies (with 17 samples) met all inclusion criteria and were included in the long-term analysis. The results showed that the depression outcomes of all follow-up time points together in the treatment conditions were favored over the control conditions with a medium effect size of 0.43 (n=1689 participants; 9 RCTs; standardized mean difference [SMD] -0.43, 95% CI -0.67 to -0.20; P<.001). The analysis of long-term efficacy within the iCBT treatment conditions showed that the follow-up outcomes of the treatment groups were favored over the posttreatment outcomes with a small effect size of 0.20 (n=2196 participants; 17 RCTs; SMD 0.20, 95% CI 0.07-0.49; P=.003). Findings for improving quality of life also showed that the iCBT conditions were favored over the control conditions with a small effect size of 0.19 (n=1345 participants; 3 RCTs; SMD 0.19, 95% CI 0.08-0.30; P<.001).

CONCLUSIONS

This systematic review and meta-analysis found that iCBT self-help interventions had a superior long-term efficacy for individuals with depressive symptoms compared to control groups. The within-group analysis of iCBT treatment conditions also showed statistically significant improvements in reducing depressive symptoms at follow-up compared to posttreatment measurements.