The effectiveness of self-guided interventions in adults with depressive symptoms: a systematic review and meta-analysis.

BACKGROUND: Despite promising scalability and accessibility, evidence on the efficacy of self-guided interventions for adult depression is inconclusive. This study investigated their effectiveness and acceptability, considering diverse delivery formats and support levels. METHODS: We systematically searched PubMed, PsycINFO, Embase, and Cochrane Library until 1st January 2024. Included were randomised controlled trials comparing self-guided interventions with a control condition for adult depression. Two independent researchers extracted data. Effect sizes were pooled using random-effects models, with post-intervention depressive severity compared with control conditions as the primary outcome. Study validity was evaluated using Cochrane Risk of Bias 2.0. This study was pre-registered with OSF (https://osf.io/rd43v). FINDINGS: We identified 92 studies (111 interventions vs. control comparisons) with 16,706 participants (mean age: 18.78-74.41 years). Compared to controls, self-guided interventions were moderately effective at post-assessment (g = 0.53, 95% CI: 0.45-0.61; I2 = 79.17%) and six to twelve months post-randomisation follow-up (g = 0.32, 95% CI: 0.16-0.48; I2 = 79.19%). Trials with initial human screening (g = 0.59) and interventions delivered in computer programs (g = 1.04) had the significantly largest effect sizes. No differences in treatment effects were observed across support levels, therapy types, commercial availability, or the presence of online discussion forums. Self-guided interventions were less acceptable than control conditions (RR = 0.92, p < 0.001). Most studies showed a moderate to high risk of bias (n = 80). INTERPRETATION: Existing trials on self-guided interventions are at high risk of bias, potentially overestimating treatment effects. Despite lower acceptability compared to controls, self-guided interventions are moderately effective in treating adult depression, regardless of support levels and online discussion features. FUNDING: None.

Comparison of Patient Health Questionnaire-9, Edinburgh Postnatal Depression Scale and Hospital Anxiety and Depression - Depression subscale scores by administration mode: An individual participant data differential item functioning meta-analysis.

Administration mode of patient-reported outcome measures (PROMs) may influence responses. We assessed if Patient Health Questionnaire-9 (PHQ-9), Edinburgh Postnatal Depression Scale (EPDS) and Hospital Anxiety and Depression Scale - Depression subscale (HADS-D) item responses and scores were associated with administration mode. We compared (1) self-administration versus interview-administration; within self-administration (2) research or medical setting versus private; and (3) pen-and-paper versus electronic; and within interview-administration (4) in-person versus phone. We analysed individual participant data meta-analysis datasets with item-level data for the PHQ-9 (N = 34,529), EPDS (N = 16,813), and HADS-D (N = 16,768). We used multiple indicator multiple cause models to assess differential item functioning (DIF) by administration mode. We found statistically significant DIF for most items on all measures due to large samples, but influence on total scores was negligible. In 10 comparisons conducted across the PHQ-9, EPDS, and HADS-D, Pearson's correlations and intraclass correlation coefficients between latent depression symptom scores from models that did or did not account for DIF were between 0.995 and 1.000. Total PHQ-9, EPDS, and HADS-D scores did not differ materially across administration modes. Researcher and clinicians who evaluate depression symptoms with these questionnaires can select administration methods based on patient preferences, feasibility, or cost.

Individual Patient Data Meta-Analysis Estimates the Minimal Detectable Change of the Geriatric Depression Scale-15.

OBJECTIVE: To use individual participant data meta-analysis (IPDMA) to estimate the minimal detectable change (MDC) of the Geriatric Depression Scale-15 (GDS-15) and to examine whether MDC may differ based on participant characteristics and study-level variables. STUDY DESIGN AND SETTING: This was a secondary analysis of data from an IPDMA on the depression screening accuracy of the GDS. Datasets from studies published in any language were eligible for the present study if they included GDS-15 scores for participants aged 60 or older. MDC of the GDS-15 was estimated via random-effects meta-analysis using 2.77 (MDC95) and 1.41 (MDC67) standard errors of measurement (SEM). Subgroup analyses were used to evaluate differences in MDC by participant age and sex. Meta-regression was conducted to assess for differences based on study-level variables, including mean age, proportion male, proportion with major depression, and recruitment setting. RESULTS: 5,876 participants (mean age 76 years, 40% male, 11% with major depression) from 21 studies were included. The MDC95 was 3.81 points (95% confidence interval [CI] 3.59, 4.04), and MDC67 was 1.95 (95% CI 1.83, 2.03). The difference in MDC95 was 0.26 points (95% CI 0.04, 0.48) between ≥ 80-year-olds and < 80-year-olds; MDC95 was similar for females and males (0.05, 95% CI -0.12, 0.22). The MDC95 increased by 0.29 points (95% CI 0.17, 0.41) per 10% increase in proportion of participants with major depression; mean age had a small association (0.04 points, 95% CI 0.00 to 0.09) with MDC95, but sex and recruitment setting were not significantly associated. CONCLUSIONS: The MDC95 was 3.81 points and MDC67 was 1.95 points. MDC95 increased with the proportion of participants with major depression. Results can be used to evaluate individual changes in depression symptoms and as a threshold for assessing minimal clinical important difference estimates.

Web-Based, Human-Guided, or Computer-Guided Transdiagnostic Cognitive Behavioral Therapy in University Students With Anxiety and Depression: Randomized Controlled Trial.

BACKGROUND: Internet-based cognitive behavioral interventions (iCBTs) are efficacious treatments for depression and anxiety. However, it is unknown whether adding human guidance is feasible and beneficial within a large educational setting. OBJECTIVE: This study aims to potentially demonstrate the superiority of 2 variants of a transdiagnostic iCBT program (human-guided and computer-guided iCBT) over care as usual (CAU) in a large sample of university students and the superiority of human-guided iCBT over computer-guided iCBT. METHODS: A total of 801 students with elevated levels of anxiety, depression, or both from a large university in the Netherlands were recruited as participants and randomized to 1 of 3 conditions: human-guided iCBT, computer-guided iCBT, and CAU. The primary outcome measures were depression (Patient Health Questionnaire) and anxiety (Generalized Anxiety Disorder scale). Secondary outcomes included substance use-related problems (Alcohol Use Disorder Identification Test and Drug Abuse Screening Test-10 items). Linear mixed models were used to estimate the effects of time, treatment group, and their interactions (slopes). The primary research question was whether the 3 conditions differed in improvement over 3 time points (baseline, midtreatment, and after treatment) in terms of depression and anxiety symptoms. Results were analyzed according to the intention-to-treat principle using multiple imputation. Patients were followed exploratively from baseline to 6 and 12 months. RESULTS: In both short-term and long-term analyses, the slopes for the 3 conditions did not differ significantly in terms of depression and anxiety, although both web-based interventions were marginally more efficacious than CAU over 6 months (P values between .02 and .03). All groups showed significant improvement over time (P<.001). For the secondary outcomes, only significant improvements over time (across and not between groups) were found for drug use (P<.001). Significant differences were found in terms of adherence, indicating that participants in the human-guided condition did more sessions than those in the computer-guided condition (P=.002). CONCLUSIONS: The transdiagnostic iCBT program offers a practical, feasible, and efficacious alternative to usual care to tackle mental health problems in a large university setting. There is no indication that human guidance should be preferred over technological guidance. The potential preference of human support also depends on the scale of implementation and cost-effectiveness, which need to be addressed in future trials. TRIAL REGISTRATION: International Clinical Trials Registry Platform NL7328/NTR7544; https://trialsearch.who.int/Trial2.aspx?TrialID=NL-OMON26795.

Evaluating the psychometric structure of the Hamilton Rating Scale for Depression pre- and post-treatment in antidepressant randomised trials: Secondary analysis of 6843 individual participants from 20 trials.

BACKGROUND: The 17-item Hamilton Rating Scale for Depression (HRSD-17) is the most popular depression measure in antidepressant clinical trials. Prior evidence indicates poor replicability and inconsistent factorial structure. This has not been studied in pooled randomised trial data, nor has a psychometrically optimal model been developed. AIMS: To examine the psychometric properties of the HRSD-17 for pre-treatment and post-treatment clinical trial data in a large pooled database of antidepressant randomised controlled trial participants, and to determine an optimal abbreviated version. METHOD: Data for 6843 participants were obtained from the data repository Vivli.org and randomly split into groups for exploratory (n = 3421) and confirmatory (n = 3422) factor analysis. Invariance methods were used to assess potential sex differences. RESULTS: The HRSD-17 was psychometrically sub-optimal and non-invariant for all models. High item variances and low variance explained suggested redundancy in each model. EFA failed at baseline and produced four item models for outcome groups (five for placebo-outcome), which were metric but not scalar invariant. CONCLUSIONS: In antidepressant trial data, the HRSD-17 was psychometrically inadequate and scores were not sex invariant. Neither full nor abbreviated HRSD models are suitable for use in clinical trial settings and the HRSD's status as the gold standard should be reconsidered.

Changes in the prevalence of mental health problems during the first year of the pandemic: a systematic review and dose-response meta-analysis.

AIM: To describe the pattern of the prevalence of mental health problems during the first year of the COVID-19 pandemic and examine the impact of containment measures on these trends. METHODS: We identified articles published until 30 August 2021 that reported the prevalence of mental health problems in the general population at two or more time points. A crowd of 114 reviewers extracted data on prevalence, study and participant characteristics. We collected information on the number of days since the first SARS-CoV-2 infection in the study country, the stringency of containment measures and the number of cases and deaths. We synthesised changes in prevalence during the pandemic using a random-effects model. We used dose-response meta-analysis to evaluate the trajectory of the changes in mental health problems. RESULTS: We included 41 studies for 7 mental health conditions. The average odds of symptoms increased during the pandemic (mean OR ranging from 1.23 to 2.08). Heterogeneity was very large and could not be explained by differences in participants or study characteristics. Average odds of psychological distress, depression and anxiety increased during the first 2 months of the pandemic, with increased stringency of the measures, reported infections and deaths. The confidence in the evidence was low to very low. CONCLUSIONS: We observed an initial increase in the average risk of psychological distress, depression-related and anxiety-related problems during the first 2 months of the pandemic. However, large heterogeneity suggests that different populations had different responses to the challenges imposed by the pandemic.

Use of Machine-Learning Algorithms Based on Text, Audio and Video Data in the Prediction of Anxiety and Post-Traumatic Stress in General and Clinical Populations: A Systematic Review.

Research in machine-learning (ML) algorithms using natural behavior (i.e., text, audio, and video data) suggests that these techniques could contribute to personalization in psychology and psychiatry. However, a systematic review of the current state-of-the-art is missing. Moreover, individual studies often target ML experts, and may overlook potential clinical implications of their findings. In a narrative accessible to mental health professionals, we present a systematic review, conducted in 5 psychology and 2 computer-science databases. We included 128 studies assessing the predictive power of ML algorithms using text, audio, and/or video data in the prediction of anxiety and post-traumatic stress (PTSD). Most studies (n = 87) aimed at predicting anxiety, the remainder (n = 41) focused on PTSD. They were mostly published since 2019, in computer science journals, and tested algorithms using text (n = 72), as opposed to audio or video. They focused mainly on general populations (n = 92), less on laboratory experiments (n = 23) or clinical populations (n = 13). Methodological quality varied, as did reported metrics of the predictive power, hampering comparison across studies. Two thirds of studies, focusing on both disorders, reported acceptable to very good predictive power (including high-quality studies only). Results of 33 studies were uninterpretable, mainly due to missing information. Research into ML algorithms using natural behavior is in its infancy, but shows potential to contribute to diagnostics of mental disorders, such as anxiety and PTSD, in the future, if standardization of methods, reporting of results, and research in clinical populations are improved.

Population mental health science: Guiding principles and initial agenda.

A recent American Psychological Association Summit provided an urgent call to transform psychological science and practice away from a solely individual-level focus to become accountable for population-level impact on health and mental health. A population focus ensures the mental health of all children, adolescents, and adults and the elimination of inequities across groups. Science must guide three components of this transformation. First, effective individual-level interventions must be scaled up to the population level using principles from implementation science, investing in novel intervention delivery systems (e.g., online, mobile application, text, interactive voice response, and machine learning-based), harnessing the strength of diverse providers, and forging culturally informed adaptations. Second, policy-driven community-level interventions must be innovated and tested, such as public efforts to promote physical activity, public policies to support families in early life, and regulation of corporal punishment in schools. Third, transformation is needed to create a new system of universal primary care for mental health, based on models such as Family Connects, Triple P, PROmoting School-community-university Partnerships to Enhance Resilience, Communities That Care, and the Early Childhood Collaborative of the Pittsburgh Study. This new system must incorporate valid measurement, universal screening, and a community-based infrastructure for service delivery. Addressing tasks ahead, including scientific creativity and discovery, rigorous evaluation, and community accountability, will lead to a comprehensive strategic plan to shape the emergent field of public mental health. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cost-Effectiveness of Digital Mental Health Versus Usual Care During Humanitarian Crises in Lebanon: Pragmatic Randomized Trial.

BACKGROUND: There is evidence from meta-analyses and systematic reviews that digital mental health interventions for depression, anxiety, and stress-related disorders tend to be cost-effective. However, no such evidence exists for guided digital mental health care in low and middle-income countries (LMICs) facing humanitarian crises, where the needs are highest. Step-by-Step (SbS), a digital mental health intervention for depression, anxiety, and stress-related disorders, proved to be effective for Lebanese citizens and war-affected Syrians residing in Lebanon. Assessing the cost-effectiveness of SbS is crucial because Lebanon's overstretched health care system must prioritize cost-effective treatment options in the face of continuing humanitarian and economic crises. OBJECTIVE: This study aims to assess the cost-effectiveness of SbS in a randomized comparison with enhanced usual care (EUC). METHODS: The cost-effectiveness analysis was conducted alongside a pragmatic randomized controlled trial in 2 parallel groups comparing SbS (n=614) with EUC (n=635). The primary outcome was cost (in US $ for the reference year 2019) per treatment response of depressive symptoms, defined as >50% reduction of depressive symptoms measured using the Patient Health Questionnaire (PHQ). The secondary outcome was cost per remission of depressive symptoms, defined as a PHQ score <5 at last follow-up (5 months post baseline). The evaluation was conducted first from the health care perspective then from the societal perspective. RESULTS: Taking the health care perspective, SbS had an 80% probability to be regarded as cost-effective compared with EUC when there is a willingness to pay US $220 per additional treatment response or US $840 per additional remission. Taking the wider societal perspective, SbS had a >75% probability to be cost-saving while gaining response or remission. CONCLUSIONS: To our knowledge, this study is the first cost-effectiveness analysis based on a large randomized controlled trial (n=1249) of a guided digital mental health intervention in an LMIC. From the principal findings, 2 implications flowed, from the (1) health care perspective and (2) wider societal perspective. First, our findings suggest that SbS is associated with greater health benefits, albeit for higher costs than EUC. It is up to decision makers in health care to decide if they find the balance between additional health gains and additional health care costs acceptable. Second, as seen from the wider societal perspective, there is a substantial likelihood that SbS is not costing more than EUC but is associated with cost-savings as SBS participants become more productive, thus offsetting their health care costs. This finding may suggest to policy makers that it is in the interest of both population health and the wider Lebanese economy to implement SbS on a wide scale. In brief, SbS may offer a scalable, potentially cost-saving response to humanitarian emergencies in an LMIC. TRIAL REGISTRATION: ClinicalTrials.gov NCT03720769; https://clinicaltrials.gov/ct2/show/NCT03720769. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/21585.

Amount and frequency of psychotherapy as predictors of treatment outcome for adult depression: A meta-regression analysis.

BACKGROUND: It is not clear whether the amount and frequency of psychotherapy is associated with treatment effects for adult depression. We investigated whether a number of indicators of the amount and frequency of psychotherapy were related to the treatment effects in randomized controlled trials (RCTs) comparing individual, face-to-face psychotherapy to a control group (e.g., care-as-usual [CAU] or waitlist condition [WL]). METHODS: Four databases were systematically searched, and meta-regression analyses conducted to assess the relationship between the effect size (Hedges' g) of the treatment and number of sessions, duration of psychotherapy, total contact time with the therapist, and number of sessions per week. RESULTS: We included 176 studies (210 comparisons) with 15,158 participants. We did not find a relationship between the effect size, and number of sessions, or total contact time. There was a small negative association between duration of treatment and the effect size, an additional week of treatment was related to a 0.014 decrease in the effect size. In addition, there was a strong association between number of sessions per week and the effect size, an increase from one to two sessions per week was related to an effect size higher by 0.596. Both associations were no longer significant when controlling for characteristics of studies. LIMITATIONS: The current findings are correlational, future research should thus address this question in an RCT. CONCLUSIONS: We should deliver brief therapies, and thus shorten waiting lists. More sessions, if necessary, should be delivered with higher frequency and over a shorter period of time.

The efficacy of psychotherapy for social anxiety disorder, a systematic review and meta-analysis.

BACKGROUND: Given the growth in research examining the effects of psychotherapy on social anxiety disorder (SAD), an up-to-date comprehensive meta-analysis in this field is needed. METHODS: We selected studies from a database of randomized trials (RCTs) on psychotherapies for anxiety disorders (last updated search of PubMed, PsycINFO, Embase, and Cochrane (CENTRAL): 1 January 2024) We included RCTs comparing psychotherapy to a control condition for adults with SAD and conducted random effects meta-analyses to examine the efficacy of psychotherapy compared to control conditions at post-treatment. RESULTS: Sixty-six RCTs were included with 5560 participants and 98 comparisons between psychotherapy and control groups. Psychotherapy was effective in reducing SAD symptoms, with a large effect size (g = 0.88; 95 % CI: 0.76 to 1.0; I2 = 74 %; 95 % CI: 69 to 79, NNT = 3.8). Effects remained robust across sensitivity analyses. However, there was evidence for significant risk of bias in the included trials. The multivariable meta-regression indicated significant differences in treatment delivery formats, type of recruitment strategy, target group, and number of sessions. CONCLUSION: Psychotherapy is an effective treatment for SAD, with moderate to large effect sizes across all treatment types and formats. Future research is needed to determine the long-term effects.

Comparative effectiveness of remote digital gamified and group CBT skills training interventions for anxiety and depression among college students: Results of a three-arm randomised controlled trial.

Digital interventions can enhance access to healthcare in under-resourced settings. However, guided digital interventions may be costly for low- and middle-income countries, despite their effectiveness. In this randomised control trial, we evaluated the effectiveness of two digital interventions designed to address this issue: (1) a Cognitive Behavioral Therapy Skills Training (CST) intervention that increased scalability by using remote online group administration; and (2) the SuperBetter gamified self-guided CBT skills training app, which uses other participants rather than paid staff as guides. The study was implemented among anxious and/or depressed South African undergraduates (n = 371) randomised with equal allocation to Remote Group CST, SuperBetter, or a MoodFlow mood monitoring control. Symptoms were assessed with the Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9). Intention-to-treat analysis found effect sizes at the high end of prior digital intervention trials, including significantly higher adjusted risk differences (ARD; primary outcome) in joint anxiety/depression remission at 3-months and 6-months for Remote Group CST (ARD = 23.3-18.9%, p = 0.001-0.035) and SuperBetter (ARD = 12.7-22.2%, p = 0.047-0.006) than MoodFlow and mean combined PHQ-9/GAD-7 scores (secondary outcome) significantly lower for Remote Group CST and SuperBetter than MoodFlow. These results illustrate how innovative delivery methods can increase the scalability of standard one-on-one guided digital interventions. PREREGISTRATION INTERNATIONAL STANDARD RANDOMISED CONTROLLED TRIAL NUMBER (ISRTCN) SUBMISSION #: 47,089,643.

Combining endpoint and change data did not affect the summary standardised mean difference in pairwise and network meta-analyses: An empirical study in depression.

When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the impact of combining the two types of SMD in meta-analyses of depression severity. We used individual participant data on pharmacological interventions (89 studies, 27,409 participants) and internet-delivered cognitive behavioural therapy (iCBT; 61 studies, 13,687 participants) for depression to compare endpoint and change from baseline SMDs at the study level. Next, we performed pairwise (PWMA) and network meta-analyses (NMA) using endpoint SMDs, change from baseline SMDs, or a mixture of the two. Study-specific SMDs calculated from endpoint and change from baseline data were largely similar, although for iCBT interventions 25% of the studies at 3 months were associated with important differences between study-specific SMDs (median 0.01, IQR -0.10, 0.13) especially in smaller trials with baseline imbalances. However, when pooled, the differences between endpoint and change SMDs were negligible. Pooling only the more favourable of the two SMDs did not materially affect meta-analyses, resulting in differences of pooled SMDs up to 0.05 and 0.13 in the pharmacological and iCBT datasets, respectively. Our findings have implications for meta-analyses in depression, where we showed that the choice between endpoint and change scores for estimating SMDs had immaterial impact on summary meta-analytic estimates. Future studies should replicate and extend our analyses to fields other than depression.

Guided web app intervention for reducing symptoms of depression in postpartum women: Results of a feasibility randomized controlled trial.

Background: Chile faces a significant postpartum depression prevalence and treatment gap, necessitating accessible interventions. While cognitive-behavioral internet-based interventions have proven effective in high-income countries, this field is underdeveloped in Chile. Based on the country's widespread use of digital technology, a guided 8-week cognitive-behavioral web app intervention named "Mamá, te entiendo" was developed. Objective: This study aimed to assess the acceptability and feasibility of "Mamá, te entiendo", for reducing depressive symptomatology in postpartum women. Methods: Sixty-five postpartum women with minor or major depression were randomly assigned to either intervention or waitlist. Primary outcomes centered on study feasibility, intervention feasibility, and acceptability. Semi-structured interviews with a sub-sample enriched the understanding of participants' experiences. Secondary outcomes included mental health variables assessed at baseline, post-intervention, and 1-month follow-up. Results: Chilean women displayed great interest in the intervention. 44.8 % of participants completed the intervention. Participants reported high satisfaction and engagement levels, with interviewees highlighting the value of the intervention's content, exercises, and therapist's feedback. However, preliminary efficacy analysis didn't reveal a significant interaction between group and time for outcome measures. Discussion: This research represents a pioneering effort in Chile to evaluate an internet-based intervention for postpartum depression symptoms. The demonstrated feasibility and acceptability highlight the potential of integrating technology-driven approaches into mental health interventions. However, the intervention did not demonstrate superiority, as both groups exhibited similar positive progress in several outcomes. Therefore, the following research phase should involve a larger and more diverse sample to assess the intervention's effectiveness, identify influencing factors, and determine the individuals who benefit the most.

The outcomes of mental health care for depression over time: A meta-regression analysis of response rates in usual care.

BACKGROUND: Over the past decades dozens of randomized trials have shown that psychological treatments are more effective than care-as-usual (CAU). It could be expected that these treatments are implemented in routine care and that the response rates in usual care improve over time. The aim of the current meta-analysis is to examine if response and remission rates in usual care have improved over time. METHODS: We used an existing meta-analytic database of randomized controlled trials examining the effects of psychological treatments of depression and selected CAU control groups from these trials. We only included CAU conditions in primary care, specialized mental health care, perinatal care and general medical care. The response rate (50 % symptom reduction) was the primary outcome. RESULTS: We included 125 CAU control groups (8542 participants). The response rate for all CAU control groups was 0.22 (95 % CI: 0.19; 0.24) with high heterogeneity (I2 = 83; 95 % CI: 80; 85), with somewhat higher rates in primary care (0.27; 95 % CI: 0.23; 0.31). We found hardly any indications that the outcomes have improved over the years. The meta-regression analysis with publication year as predictor in the full dataset resulted in a coefficient of 0.1 (SE = 0.01; p = 0.0.35). A series of sensitivity analyses supported the main findings. Remission rates and pre-post effect sizes also did not significantly improve over time. CONCLUSIONS: Response and remission rates in usual care are low, with the large majority of patients not responding or remitting, and the outcomes have probably not improved over time.

Absolute and relative outcomes of psychotherapies for eight mental disorders: a systematic review and meta-analysis.

Psychotherapies are first-line treatments for most mental disorders, but their absolute outcomes (i.e., response and remission rates) are not well studied, despite the relevance of such information for health care users, providers and policy makers. We aimed to examine absolute and relative outcomes of psychotherapies across eight mental disorders: major depressive disorder (MDD), social anxiety disorder, panic disorder, generalized anxiety disorder (GAD), specific phobia, post-traumatic stress disorder (PTSD), obsessive-compulsive disorder (OCD), and borderline personality disorder (BPD). We used a series of living systematic reviews included in the Metapsy initiative (www.metapsy.org), with a common strategy for literature search, inclusion of studies and extraction of data, and a common format for the analyses. Literature search was conducted in major bibliographical databases (PubMed, PsycINFO, Embase, and the Cochrane Register of Controlled Trials) up to January 1, 2023. We included randomized controlled trials comparing psychotherapies for any of the eight mental disorders, established by a diagnostic interview, with a control group (waitlist, care-as-usual, or pill placebo). We conducted random-effects model pairwise meta-analyses. The main outcome was the absolute rate of response (at least 50% symptom reduction between baseline and post-test) in the treatment and control conditions. Secondary outcomes included the relative risk (RR) of response, and the number needed to treat (NNT). Random-effects meta-analyses of the included 441 trials (33,881 patients) indicated modest response rates for psychotherapies: 0.42 (95% CI: 0.39-0.45) for MDD; 0.38 (95% CI: 0.33-0.43) for PTSD; 0.38 (95% CI: 0.30-0.47) for OCD; 0.38 (95% CI: 0.33-0.43) for panic disorder; 0.36 (95% CI: 0.30-0.42) for GAD; 0.32 (95% CI: 0.29-0.37) for social anxiety disorder; 0.32 (95% CI: 0.23-0.42) for specific phobia; and 0.24 (95% CI: 0.15-0.36) for BPD. Most sensitivity analyses broadly supported these findings. The RRs were significant for all disorders, except BPD. Our conclusion is that most psychotherapies for the eight mental disorders are effective compared with control conditions, but absolute response rates are modest. More effective treatments and interventions for those not responding to a first-line treatment are needed.

Mental healthcare access among resettled Syrian refugees in Leipzig, Germany.

Our aim was to examine mental health needs and access to mental healthcare services among Syrian refugees in the city of Leipzig, Germany. We conducted a cross-sectional survey with Syrian refugee adults in Leipzig, Germany in 2021/2022. Outcomes included PTSD (PCL-5), depression (PHQ-9), anxiety (GAD-7) and somatic symptom (SSS-8). Descriptive, regression and effect modification analyses assessed associations between selected predictor variables and mental health service access. The sampling strategy means findings are applicable only to Syrian refugees in Leipzig. Of the 513 respondents, 18.3% had moderate/severe anxiety symptoms, 28.7% had moderate/severe depression symptoms, and 25.3% had PTSD symptoms. A total of 52.8% reported past year mental health problems, and 48.9% of those participants sought care for these problems. The most common reasons for not accessing mental healthcare services were wanting to handle the problem themselves and uncertainty about where to access services. Adjusted Poisson regression models (n = 259) found significant associations between current mental health symptoms and mental healthcare service access (RR: 1.47, 95% CI: 1.02-2.15, p = 0.041) but significance levels were not reached between somatization and trust in physicians with mental healthcare service access. Syrian refugees in Leipzig likely experience high unmet mental health needs. Community-based interventions for refugee mental health and de-stigmatization activities are needed to address these unmet needs in Leipzig.

Understanding priorities and needs for child and adolescent mental health in Greece from multiple informants: an open resource dataset.

The Child and Adolescent Mental Health Initiative (CAMHI) aims to enhance mental health care capacity for children and adolescents across Greece. Considering the need for evidence-based policy, the program developed an open-resource dataset for researching the field within the country. A comprehensive, mixed-method, community-based research was conducted in 2022/2023 assessing the current state, needs, barriers, and opportunities according to multiple viewpoints. We surveyed geographically distributed samples of 1,756 caregivers, 1,201 children/adolescents, 404 schoolteachers, and 475 health professionals using validated instruments to assess mental health symptoms, mental health needs, literacy and stigma, service use and access, professional practices, training background, and training needs and preferences. Fourteen focus groups were conducted with informants from diverse populations (including underrepresented minorities) to reach an in-depth understanding of those topics. A dataset with quantitative and qualitative findings is now available for researchers, policymakers, and society [ https://osf.io/crz6h/ and https://rpubs.com/camhi/sdashboard ]. This resource offers valuable data for assessing the needs and priorities for child and adolescent mental health care in Greece. It is now freely available to consult, and is expected to inform upcoming research and evidence-based professional training. This initiative may inspire similar ones in other countries, informing methodological strategies for researching mental health needs.

Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia? Results from an individual-participant data meta-analysis.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.