The comparability between self-reports and clinician-rated scales for measuring depression following treatment has been a long-standing debate, with studies finding mixed results. While the use of self-reports in psychotherapy trials is very common, it has been widely assumed that these tools pose a validity threat when masking of participants is not possible. We conducted a meta-analysis across randomized controlled trials (RCTs) of psychotherapy for depression to examine if treatment effect estimates obtained via self-reports differ from clinician-rated outcomes.

We identified studies from a living database of psychotherapies for depression (updated to 1 January 2023). We included RCTs measuring depression at post-treatment with both a self-report and a clinician-rated scale. As our main model, we ran a multilevel hierarchical meta-analysis, resulting in a pooled differential effect size (Δg) between self-reports and clinician ratings. Moderators of this difference were explored through multimodel inference analyses.

A total of 91 trials (283 effect sizes) were included. In our main model, we found that self-reports produced smaller effect size estimates compared to clinician-rated instruments (Δg = 0.12; 95% CI: 0.03–0.21). This difference was very similar when only including trials with masked clinicians (Δg = 0.10; 95% CI: 0.00–0.20). However, it was more pronounced for unmasked clinical ratings (Δg = 0.20; 95% CI: −0.03 to 0.43) and when trials targeted specific population groups (e.g., perinatal depression) (Δg = 0.20; 95% CI: 0.08–0.32). Effect sizes between self-reports and clinicians were identical in trials targeting general adults (Δg = 0.00; 95% CI: −0.14 to 0.14).

Self-report instruments did not overestimate the effects of psychotherapy for depression and were generally more conservative than clinician assessments. Patients’ perception of improvement should not be considered less valid by default, despite the inherent challenge of masking in psychotherapy.

There is considerable evidence that waiting list (WL) control groups overestimate the effect sizes of psychotherapies for depression. It is not clear, however, what are the exact causes for this overestimation. We decided to conduct a meta-analytic study to compare trials on psychotherapy for depression with a WL control group against trials with a care-as-usual (CAU) control group.

We used an existing meta-analytic database of randomized trials comparing psychological treatments of adult depression with control groups and selected trials using a WL or a CAU control group. We used subgroup and meta-regression analyses to examine differences in effect sizes between WL and CAU controlled trials.

We included 333 randomized controlled trials (472 comparisons; total number participants: 41,480), 141 with a WL and 195 with a CAU control group (3 included both). We found several significant differences between WL and CAU controlled trials (in type of therapy examined, treatment format, recency, target group, recruitment strategy, number of treatment arms and number of depression outcome measures). The overall effect size indicating the difference between treatment and control at post-test for all comparisons was g = 0.77 (95% confidence interval [CI]: 0.71; 0.84) with high heterogeneity (I2 = 84; 95% CI: 82; 85). A highly significant difference was observed between studies with a CAU control group (g = 0.63; 95% CI: 0.55; 0.71; I2 = 85; 95% CI: 83; 86) and studies with a WL (g = 0.95; 95% CI: 0.85; 1.04; I2 = 80; 95% CI: 78; 82; p for difference < 0.001). This difference remained significant in all sensitivity analyses, including a meta-regression analysis in which we adjusted for all differences in characteristics of studies with a WL versus CAU control group. We also found that pre-post effect sizes in WL control conditions (g = 0.37; 95% CI: 0.28; 0.46) were significantly smaller than change within CAU conditions (g = 0.64; 95% CI: 0.50; 0.78). We found few indications that pre-post effect sizes within therapy conditions differed between WL and CAU controlled trials.

WL control conditions considerably overestimate the effect sizes of psychological treatments, compared to trials using CAU control conditions. This overestimation is probably caused by a smaller improvement within the WL condition compared to the improvement in the CAU condition. WL control conditions should be avoided in randomized trials examining psychological treatments of adult depression.

Problem Management Plus (PM+) has been effective in reducing mental health problems among refugees at three-month follow-up, but there is a lack of research on its long-term effectiveness. This study examined the effectiveness of PM+ in reducing symptoms of common mental disorders at 12-month follow-up among Syrian refugees in the Netherlands.

This single-blind, parallel, controlled trial randomised 206 adult Syrians who screened positive for psychological distress and impaired functioning to either PM+ in addition to care as usual (PM+/CAU) or CAU alone. Assessments were at baseline, 1 week and 3 months after the intervention and 12 months after baseline. Outcomes were psychological distress (Hopkins Symptom Checklist [HSCL-25]), depression (HSCL-25 subscale), anxiety (HSCL-25 subscale), posttraumatic stress disorder symptoms (PCL-5), functional impairment (WHODAS 2.0) and self-identified problems (PSYCHLOPS).

In March 2019–December 2022, 103 participants were assigned to PM+/CAU and 103 to CAU of which 169 (82.0%) were retained at 12 months. Intention-to-treat analyses showed greater reductions in psychological distress at 12 months for PM+/CAU compared to CAU (adjusted mean difference −0.17, 95% CI −0.310 to −0.027; p = 0.01, Cohen’s d = 0.28). Relative to CAU, PM+/CAU participants also showed significant reductions on anxiety (−0.19, 95% CI −0.344 to −0.047; p = 0.01, d = 0.31) but not on any of the other outcomes.

PM+ is effective in reducing psychological distress and symptoms of anxiety over a period up to 1 year. Additional support such as booster sessions or additional (trauma-focused) modules may be required to prolong and consolidate benefits gained through PM+ on other mental health and psychosocial outcomes.

Although numerous studies have examined the effects of psychological treatments for obsessive-compulsive disorder (OCD), their overall effectiveness remains unclear. We aimed to estimate their overall effect by combining all available randomized controlled trials (RCTs) comparing psychological treatments to control groups for OCD.

We conducted a meta-analysis of 48 RCTs with 55 comparisons published between 1992 and 1 January 2023. The primary outcome was OCD symptom severity, with Hedges' g calculated at post-treatment and follow-up. Random-effects models were employed for all analyses, and the risk of bias was assessed.

In general, psychological treatments demonstrated a significantly large effect (g = −1.14; 95% CI [−1.31 to −0.97]; I2 = 72.23%) on reducing OCD symptom severity post-treatment, this finding remained consistent across measures and after excluding outliers, but lost significance in the sensitivity analysis for only studies with low risk of bias. Type of treatment, control group and treatment format were associated with treatment effects. Moreover, more severe baseline OCD symptom severity predicted higher degree of treatment efficacy. No significant differences were observed in dropout rates between the treatment and control groups. Treatment effects lost significance at 3–6 and 6–12 month follow-ups. 87% of RCTs were rated at high risk of bias.

Psychological treatments are effective in reducing OCD symptom severity. However, caution should be exercised when interpreting these results due to the high heterogeneity and risk of bias across RCTs. Future studies with more rigorous methodology are required, as well as studies examining their long-term effectiveness.

Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics.

Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree.

IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-assessment (d = −0.71 [95% CI−0.92 to −0.51]) and at follow-up (d = −0.84 [95% CI −1.11 to −0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d = −0.48 and −0.87 (post) and d = − 0.66 to −0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators.

An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

This systematic review and individual participant data meta-analysis (IPDMA) examined the overall effectiveness of eye movement desensitization and reprocessing (EMDR) in reducing posttraumatic stress disorder (PTSD) symptoms, achieving response and remission, and reducing treatment dropout among adults with PTSD compared to other psychological treatments. Additionally, we examined available participant-level moderators of the efficacy of EMDR.

This study included randomized controlled trials. Eligible studies were identified by a systematic search in PubMed, Embase, PsyclNFO, PTSDpubs, and CENTRAL. The target population was adults with above-threshold baseline PTSD symptoms. Trials were eligible if at least 70% of study participants had been diagnosed with PTSD using a structured clinical interview. Primary outcomes included PTSD symptom severity, treatment response, and PTSD remission. Treatment dropout was a secondary outcome. The systematic search retrieved 15 eligible randomized controlled trials (RCTs); 8 of these 15 were able to be included in this IPDMA (346 patients). Comparator treatments included relaxation therapy, emotional freedom technique, trauma-focused cognitive behavioral psychotherapies, and REM-desensitization.

One-stage IPDMA found no significant difference between EMDR and other psychological treatments in reducing PTSD symptom severity (β = −0.24), achieving response (β = 0.86), attaining remission (β = 1.05), or reducing treatment dropout rates (β = −0.25). Moderator analyses found unemployed participants receiving EMDR had higher PTSD symptom severity at the post-test, and males were more likely to drop out of EMDR treatment than females.

The current study found no significant difference between EMDR and other psychological treatments. We found some indication of the moderating effects of gender and employment status.

Cost-effective treatments are needed to reduce the burden of depression. One way to improve the cost-effectiveness of psychotherapy might be to increase session frequency, but keep the total number of sessions constant.

To evaluate the cost-effectiveness of twice-weekly compared with once-weekly psychotherapy sessions after 12 months, from a societal perspective.

An economic evaluation was conducted alongside a randomised controlled trial comparing twice-weekly versus once-weekly sessions of psychotherapy (cognitive–behavioural therapy or interpersonal psychotherapy) for depression. Missing data were handled by multiple imputation. Statistical uncertainty was estimated with bootstrapping and presented with cost-effectiveness acceptability curves.

Differences between the two groups in depressive symptoms, physical and social functioning, and quality-adjusted life-years (QALY) at 12-month follow-up were small and not statistically significant. Total societal costs in the twice-weekly session group were higher, albeit not statistically significantly so, than in the once-weekly session group (mean difference €2065, 95% CI −686 to 5146). The probability that twice-weekly sessions are cost-effective compared with once-weekly sessions was 0.40 at a ceiling ratio of €1000 per point improvement in Beck Depression Inventory-II score, 0.32 at a ceiling ratio of €50 000 per QALY gained, 0.23 at a ceiling ratio of €1000 per point improvement in physical functioning score and 0.62 at a ceiling ratio of €1000 per point improvement in social functioning score.

Based on the current results, twice-weekly sessions of psychotherapy for depression are not cost-effective over the long term compared with once-weekly sessions.

In low-resource settings, e-mental health may substantially increase access to evidence-based interventions for common mental disorders. We conducted a systematic literature search to identify randomised trials examining the effects of digital interventions with or without therapeutic guidance compared to control conditions in individuals with anxiety and/or depression symptoms in low- and middle-income countries (LMICs).

The main outcome was the reduction in symptoms at the post-test. Secondary outcomes included improvements in quality of life and longer-term effects (≥20 weeks post-randomisation). The effect size Hedges’ g was calculated using the random effects model.

A total of 21 studies (23 comparisons) with 5.296 participants were included. Digital interventions were more effective than controls in reducing symptoms of common mental disorders at the post-test (g = −0.89, 95% confidence interval [CI] −1.26 to −0.52, p < 0.001; NNT = 2.91). These significant effects were confirmed when examining depressive (g = −0.77, 95% CI −1.11; −0.44) and anxiety symptoms separately (g = −1.02, 95% CI −1.53 to −0.52) and across all other sensitivity analyses. Digital interventions also resulted in a small but significant effect in improving quality of life (g = 0.32, 95% CI 0.19 to 0.45) at the post-test. Over the longer term, the effects were smaller but remained significant for all examined outcomes. Heterogeneity was moderate to high in all analyses. Subgroup and meta-regression analyses did not result in significant outcomes in any of the examined variables (e.g., guided vs. unguided interventions).

Digital interventions, with or without guidance, may effectively bridge the gap between treatment supply and demand in LMICs. Nevertheless, more studies are needed to draw firm conclusions regarding the magnitude of the effects of digital interventions.

Twice weekly sessions of cognitive behavioral therapy (CBT) and interpersonal psychotherapy (IPT) for major depressive disorder (MDD) lead to less drop-out and quicker and better response compared to once weekly sessions at posttreatment, but it is unclear whether these effects hold over the long run.

Compare the effects of twice weekly v. weekly sessions of CBT and IPT for depression up to 24 months since the start of treatment.

Using a 2 × 2 factorial design, this multicentre study randomized 200 adults with MDD to once or twice weekly sessions of CBT or IPT over 16–24 weeks, up to a maximum of 20 sessions. Main outcome measures were depression severity, measured with the Beck Depression Inventory-II and the Longitudinal Interval Follow-up Evaluation. Intention-to-treat analyses were conducted.

Compared with patients who received once weekly sessions, patients who received twice weekly sessions showed a significant decrease in depressive symptoms up through month 9, but this effect was no longer apparent at month 24. Patients who received CBT showed a significantly larger decrease in depressive symptoms up to month 24 compared to patients who received IPT, but the between-group effect size at month 24 was small. No differential effects between session frequencies or treatment modalities were found in response or relapse rates.

Although a higher session frequency leads to better outcomes in the acute phase of treatment, the difference in depression severity dissipated over time and there was no significant difference in relapse.

Modern psychometric methods make it possible to eliminate nonperforming items and reduce measurement error. Application of these methods to existing outcome measures can reduce variability in scores, and may increase treatment effect sizes in depression treatment trials.

We aim to determine whether using confirmatory factor analysis techniques can provide better estimates of the true effects of treatments, by conducting secondary analyses of individual patient data from randomised trials of antidepressant therapies.

We will access individual patient data from antidepressant treatment trials through Clinicalstudydatarequest.com and Vivli.org, specifically targeting studies that used the Hamilton Rating Scale for Depression (HRSD) as the outcome measure. Exploratory and confirmatory factor analytic approaches will be used to determine pre-treatment (baseline) and post-treatment models of depression, in terms of the number of factors and weighted scores of each item. Differences in the derived factor scores between baseline and outcome measurements will yield an effect size for factor-informed depression change. The difference between the factor-informed effect size and each original trial effect size, calculated with total HRSD-17 scores, will be determined, and the differences modelled with meta-analytic approaches. Risk differences for proportions of patients who achieved remission will also be evaluated. Furthermore, measurement invariance methods will be used to assess potential gender differences.

Our approach will determine whether adopting advanced psychometric analyses can improve precision and better estimate effect sizes in antidepressant treatment trials. The proposed methods could have implications for future trials and other types of studies that use patient-reported outcome measures.

It is not clear if there is an interaction between psychotherapy and pharmacotherapy. First, there may be no interaction at all, meaning that the effects of both are independent of each other. Second, antidepressants may reduce the effects of psychotherapy, and third, antidepressants may increase the effects of psychotherapy. We examined which of the three is correct.

We conducted random effects meta-analyses of randomized trials comparing psychotherapies for adult depression with control conditions. The proportion of users of antidepressants was used as a predictor of the effect size in a series of meta-regression analyses, while adjusting for relevant moderators, such as type of control group and baseline severity.

We included 300 randomized controlled trials (353 comparisons between treatment and control; 32,852 participants). The main effect size of psychotherapy was g = 0.71 (95% CI: 0.64; 0.79) with high heterogeneity (I2 = 82; 95% CI: 80; 84). We found no significant association between the proportion of antidepressants users and effect size (p = .07). We did find a significant association with some other predictors, including the type of control group and risk of bias. The use of antidepressants was associated with higher response rates within the control conditions, but not with the relative effects of the treatments compared to the control groups.

We found support for the independent effects of psychotherapy and pharmacotherapy, which is good news from a clinical perspective. Apparently, patients can start with psychotherapy and do not have to be afraid that this will reduce the effects of the therapy.