Mathias Harrer

Objective: Single-session interventions (SSIs) have been proposed as a scalable approach to reduce anxiety and depressive symptoms; however, evidence for adults remains limited. This systematic review and meta-analysis synthesized randomized controlled trials (RCTs) evaluating SSIs relative to inactive or minimal-control conditions.Method: A systematic search identified adult RCTs. Outcomes were analyzed separately for anxiety and depression using three-level random-effects meta-analytic models. Effects were pooled across 1–13 weeks and within short-term (1–3 weeks) and medium-term (4–13 weeks) follow-up windows.Results: Twenty-one RCTs (N = 7,035) contributed 53 outcome-level effect sizes. Across 1–13 weeks, SSIs were associated with significant reductions in anxiety symptoms (g = −0.66, 95% CI [−0.98, −0.34]) and depressive symptoms (g = −0.49, 95% CI [−0.84, −0.13]). At 1–3 weeks, effects were significant for anxiety symptoms (g = −0.80, 95% CI [−1.24, −0.36]), but not depressive symptoms (g = −0.78, 95% CI [−1.78, 0.22]). At 4–13 weeks, effects were significant for both depressive symptoms (g = −0.29, 95% CI [−0.55, −0.02]) and anxiety symptoms (g = −0.48, 95% CI [−0.93, −0.02]). Heterogeneity was high, prediction intervals were wide, publication bias was detected for anxiety outcomes at 1–13 and 1–3 weeks and for depression at 1–13 weeks, and most studies had some concerns or high risk of bias.Conclusions: SSIs may reduce anxiety and depressive symptoms over the short-to-medium term in adults. Substantial heterogeneity, limited trial availability, publication bias, and risk of bias constrain confidence in the magnitude and generalizability of these effects. Rigorous trials with extended follow-up are needed to clarify effect durability and further inform the role within routine care.Keywords: anxiety, depression, meta-analysis, single-session interventions, systematic review

Background: Emotional disorders—primarily anxiety and unipolar depressive disorders—are highly prevalent, disabling, and frequently comorbid. Disorder‑specific cognitive behavioral therapy (DS‑CBT) is considered a gold standard treatment, yet it can be inefficient in the context of high comorbidity and service constraints. Transdiagnostic psychotherapies that target shared maintaining mechanisms (eg, emotion dysregulation and neuroticism) have been developed, including the Unified Protocol, transdiagnostic behavior therapy, emotion regulation therapy, and various transdiagnostic internet-delivered cognitive behavioral therapy protocols. Recent meta-analyses suggest that transdiagnostic interventions are effective or likely effective, but a comprehensive comparative evaluation across different transdiagnostic protocols, DS‑CBT, other evidence‑based psychotherapies, and control conditions is lacking. Objective: This study aims to conduct a network meta-analysis (NMA) to compare the efficacy and acceptability of various transdiagnostic therapies (eg, the Unified Protocol, transdiagnostic behavior therapy, and emotion regulation therapy), DS-CBT, other evidence-based active therapies (eg, acceptance and commitment therapy, behavioral activation, and mindfulness-based cognitive therapy), and control conditions (waitlist or care as usual) in improving symptoms in adults with anxiety and/or depressive disorders and generate a probabilistic ranking of their efficacy. Methods: This meta-analysis will include randomized controlled trials from PubMed, Embase, PsycInfo, and the Cochrane Library, complemented by existing meta‑analytic research domain databases for depression and anxiety. Eligible participants are adults (≥18 years) with a principal diagnosis of anxiety and/or unipolar depressive disorder according to established diagnostic classification systems (eg, any version of the Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases, 10th or 11th revisions) or scoring above a validated cutoff on anxiety or depression scales. Primary outcomes are continuous measures of anxiety and depressive symptom severity at the posttreatment time point; secondary outcomes include study dropout (acceptability) and response or remission where available. We will perform random-effects network meta-analyses within a frequentist framework using the netmeta package in R to estimate relative treatment effects and P scores for treatment rankings and examine transitivity and consistency. We will conduct additional Bayesian NMAs as sensitivity analyses using the surface under the cumulative ranking curve for ranking. Results: As of September 2026, the literature search has been completed, and title and abstract screening is ongoing. Data analysis will be conducted in late 2026. We expect the meta-analysis to be completed and submitted for publication by the end of 2026, with results expected to be published in early 2027. Conclusions: This NMA will provide comprehensive comparative evidence on the efficacy and acceptability of transdiagnostic psychotherapies for emotional disorders, which can inform clinical decision-making and guideline development. Trial Registration: OSF Registries osf.io/p8957; https://osf.io/p8957/overview International Registered Report Identifier (IRRID): DERR1-10.2196/104791

We have learned several lessons from our meta-analytic work in the past decades, and we discuss a few important ones. (a) Publication bias is still a major issue, seriously affecting outcomes of meta-analyses. (b) Preregistration of trials can still be improved because only 50% of trials comparing psychotherapy for depression with control conditions was prospective registered since 2021. (c) A considerable number of trials (at least 28% in published “individual participant data” meta-analyses of psychological interventions for mental-health problems) do not provide their primary data for such meta-analyses. (d) Manuals of treatments are often not open at all. (e) Open access of meta-analytic data sets will considerably increase efficiency, reduce waste of resources, and speed up clinical research.

Introduction: Social functioning is a key component of recovery in depression, yet most research on first-line treatments focuses on symptom reduction, and comparative evidence on social functioning is limited. We aimed to evaluate the comparative effects of psychotherapy, antidepressant medication, and their combination on social functioning in adults with major depression. Methods: We conducted a systematic review and network meta-analysis of randomised controlled trials up to May 1, 2025. Eligible trials compared psychotherapy, antidepressant medication, combined treatment, and control conditions (placebo, care as usual, waitlist, or no/minimal treatment) in adults with major depression. Effects were calculated as standardised mean differences (SMD) in social functioning instruments (e.g., Sheehan Disability Scale) at post-treatment (mean 12 weeks) and follow-up (mean 32 weeks). Random-effects models were used. We assessed risk of bias and conducted sensitivity analyses. Certainty of evidence was evaluated using CINeMA. Results: Of 490 identified trials, 94 (19%; 23,874 participants) reported social functioning and were included. All active treatments outperformed control conditions. Effects varied substantially by control condition type, with waitlist comparisons yielding the largest estimates and comparisons against placebo or care as usual yielding more conservative effects. Combined psychotherapy and pharmacotherapy showed the largest effects versus placebo at post-treatment (SMD 0.75, 95% CI 0.57–0.94) and follow-up (1.08, 0.62–1.54). Psychotherapy and pharmacotherapy did not differ at post-treatment (SMD 0.10, 95% CI −0.05 to 0.25) or follow-up (0.27, 95% CI 0.00–0.54). Certainty of the evidence ranged from moderate to low. Conclusion: First-line depression treatments support not only symptom reduction but also meaningful participation in daily life. However, only one fifth of trials assessed this outcome, highlighting the need to better integrate patient-valued outcomes into future trials.

BACKGROUND Emotional disorders—primarily anxiety and unipolar depressive disorders—are highly prevalent, disabling, and frequently comorbid. Disorder‑specific cognitive behavioral therapy (DS‑CBT) is considered a gold standard treatment, yet it can be inefficient in the context of high comorbidity and service constraints. Transdiagnostic psychotherapies that target shared maintaining mechanisms (eg, emotion dysregulation and neuroticism) have been developed, including the Unified Protocol, transdiagnostic behavior therapy, emotion regulation therapy, and various transdiagnostic internet-delivered cognitive behavioral therapy protocols. Recent meta-analyses suggest that transdiagnostic interventions are effective or likely effective, but a comprehensive comparative evaluation across different transdiagnostic protocols, DS‑CBT, other evidence‑based psychotherapies, and control conditions is lacking. OBJECTIVE This study aims to conduct a network meta-analysis (NMA) to compare the efficacy and acceptability of various transdiagnostic therapies (eg, the Unified Protocol, transdiagnostic behavior therapy, and emotion regulation therapy), DS-CBT, other evidence-based active therapies (eg, acceptance and commitment therapy, behavioral activation, and mindfulness-based cognitive therapy), and control conditions (waitlist or care as usual) in improving symptoms in adults with anxiety and/or depressive disorders and generate a probabilistic ranking of their efficacy. METHODS This meta-analysis will include randomized controlled trials from PubMed, Embase, PsycInfo, and the Cochrane Library, complemented by existing meta‑analytic research domain databases for depression and anxiety. Eligible participants are adults (≥18 years) with a principal diagnosis of anxiety and/or unipolar depressive disorder according to established diagnostic classification systems (eg, any version of the Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases, 10th or 11th revisions) or scoring above a validated cutoff on anxiety or depression scales. Primary outcomes are continuous measures of anxiety and depressive symptom severity at the posttreatment time point; secondary outcomes include study dropout (acceptability) and response or remission where available. We will perform random-effects network meta-analyses within a frequentist framework using the netmeta package in R to estimate relative treatment effects and P scores for treatment rankings and examine transitivity and consistency. We will conduct additional Bayesian NMAs as sensitivity analyses using the surface under the cumulative ranking curve for ranking. RESULTS As of September 2026, the literature search has been completed, and title and abstract screening is ongoing. Data analysis will be conducted in late 2026. We expect the meta-analysis to be completed and submitted for publication by the end of 2026, with results expected to be published in early 2027. CONCLUSIONS This NMA will provide comprehensive comparative evidence on the efficacy and acceptability of transdiagnostic psychotherapies for emotional disorders, which can inform clinical decision-making and guideline development. CLINICALTRIAL OSF Registries osf.io/p8957; https://osf.io/p8957/overview INTERNATIONAL REGISTERED REPORT DERR1-10.2196/104791

Introduction: Around a third of patients with major depressive disorder experience persistent symptoms despite usual treatments. Identifying scalable, psychological treatment options is critical to reduce the burden associated with difficult-to-treat depression (DTD). We examined the efficacy of mindfulness-based cognitive therapy (MBCT) compared with treatment as usual (TAU) and other active psychosocial controls in current DTD, and explored potential moderators. Methods: We conducted an individual patient data (IPD) meta-analysis of randomised controlled trials comparing MBCT with TAU or other active psychosocial controls in currently depressed adults meeting criteria for treatment non-response, treatment resistance, or chronic course. Seven studies (N = 777) contributed data. Bayesian one-stage models were used as primary approach to estimate pooled effects on depressive symptom severity. Results: MBCT was likely superior to TAU at post-treatment (standardised mean difference = −0.40; 95% credible interval [CrI] = −0.64 to −0.16) and medium-term follow-up (−0.41; 95% CrI = −0.76 to −0.02), with posterior probabilities of 92% and 85% of surpassing a minimal important difference (d = −0.24), respectively. In contrast, comparative effects relative to other psychosocial interventions were uncertain, with no evidence of superiority. Moderator analyses did not identify robust predictors of outcome, suggesting broadly consistent effects across baseline severity, chronicity, and comorbidity. Conclusions: MBCT appears to be an effective and safe option for DTD, superior to TAU, with benefits maintained at medium-term follow-up, although no evidence of superiority over other active psychosocial interventions was observed. These findings support the integration of MBCT into comprehensive treatment models for DTD.

This report synthesizes experimental evidence on the effects of generative artificial intelligence (GenAI) misinformation on individuals’ ability to evaluate information and the effectiveness of interventions designed to mitigate its influence. It draws on a meta-analysis of experimental studies (60 effects from 24 publications and 33,801 participants) published between 2018 and 2025. The findings indicate a divergence in public responses to different modalities of GenAI-produced misinformation (referred to in the report as GenAI misinformation), alongside substantial heterogeneity across studies. More recent research tends to report higher perceived accuracy and credibility of textual GenAI misinformation, whereas individuals’ perceptions of visual GenAI misinformation—primarily deepfakes—have become more skeptical over time. These patterns are associated with the time of data collection rather than model capacity and are accompanied by wide variation in effect sizes across contexts. The report also evaluates two countermeasures: preventive corrective information and content labeling. In studies conducted after 2020, corrective information yields small-to-moderate (0.17 to 0.43 standard deviation units) reductions in the perceived accuracy or credibility of GenAI misinformation. Pooled estimates in this subset are significant and comparatively stable, though prediction intervals show substantial variation, especially when outcomes focus on detection rather than evaluative judgment. Content labeling interventions vary more than corrective information. Althoughlabels are associated with modest average reductions in perceived credibility, effect sizes vary widely across modalities, designs, presentations, and contexts,and prediction intervals often include null effects. Key conclusions from the synthesis are as follows: Textual GenAI misinformation may currently pose greater persuasive risks than visual GenAI misinformation. Preventive corrective information appears to be more a consistently effective countermeasure. Content labeling policies yield highly variable outcomes and require careful design and evaluation. The available evidence base is geographically narrow and methodologically constrained, with most studies focusing on populations in Western Europe and North America Based on these findings, policy responses should consider the following: Prioritize addressing text-based GenAI misinformation. Treat preventive corrections as a core intervention. Approach content labeling cautiously

Generative artificial intelligence (GenAI) can now rapidly produce large volumes of misleading text, images, audio, and video with readily accessible tools. This matters for policymakers because false or misleading content can be tailored to specific audiences. Such content can spread quickly and mimic authentic communication, making it difficult for people to judge what is true. This Summary for Policymakers distills the main findings of the IPIE Synthesis Report (SR2026.2) on the effects of misinformation produced with GenAI and the measures most likely to reduce its influence. The assessment draws on a large-scale meta-analysis of experimental scientific evidence. It is based on 60 randomized controlled trial effect estimates from 24 peer-reviewed publications involving 33,801 participants, published between 2018 and 2025. The report reaches four main conclusions: Text-based GenAI misinformation currently poses greater persuasive risks than visual misinformation. The current evidence base excludes most of the world. Research is concentrated in English-language and high-income countries, leaving significant gaps in our knowledge. The most consistently effective intervention is to provide users with corrective information, preventively, so they can evaluate accuracy and credibility themselves. Labeling is effective when it is consistent. Content labeling generally decreases perceived credibility, but its impact varies greatly depending on how the firms create and apply labels. The policy implications are clear. Policymakers should prioritize addressing misinformation from text-based GenAI and support preventive and corrective information as a fundamental strategy. Labeling should be treated as a measure that requires careful design and testing. We must expand independent research well beyond English-language and high-income contexts. Researcher access to platform and model data is crucial for enhancing public understanding of GenAI misinformation and for testing which safeguards are effective in practice.

3,4-methylenedioxymethamphetamine (MDMA) has emerged as a potential treatment for post-traumatic stress disorder (PTSD), generating considerable enthusiasm in the field. However, rapidly changing evidence in a fast-moving field can be challenging to integrate. Here, we present a living systematic review and open-data meta-analytic resource on MDMA treatment for PTSD. In this initial release, six randomized controlled trials comprising 286 participants are included in the database. Our primary model uses inverse-variance random-effects meta-analysis of standardized mean differences on primary outcomes of PTSD. Compared to control conditions, MDMA showed a greater reduction in PTSD symptoms (Hedges’ g = -0.71). Meta-regression on both the number of dosing sessions and cumulative dose showed that a higher number of dosing sessions and a higher cumulative dose was related to larger effects of MDMA. Treatment with MDMA as compared to placebo also resulted in higher response (risk ratio ( RR ) = 1.35) and remission ( RR = 2.25) rates. Most studies included in the database had a low risk of bias according to Cochrane guidelines, though these fail to capture pertinent challenges in the field such as expectancy, functional unblinding, potential issues with study conduct, and safety. The current findings were assigned an overall low certainty rating using the GRADE approach. Together, this systematic review and meta-analysis suggests that MDMA-assisted therapy results in short-term decreases in PTSD symptoms across studies to date, though more trials are needed. This living systematic review, meta-analysis, database, and online dashboard ( sypres.io ) will continue to be updated as evidence emerges, providing a valuable, open, and transparent resource for researchers in a rapidly evolving field.