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.

EMDR v. other psychological therapies for PTSD: a systematic review and individual participant data meta-analysis.

BACKGROUND: 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. METHODS: 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. RESULTS: One-stage IPDMA found no significant difference between EMDR and other psychological treatments in reducing PTSD symptom severity (ß = -0.24), achieving response (ß = 0.86), attaining remission (ß = 1.05), or reducing treatment dropout rates (ß = -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. CONCLUSION: 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.

The effectiveness of unguided self-help psychological interventions for obsessive-compulsive disorder: A meta-analysis of randomized controlled trials.

BACKGROUND: Evidence-based psychological interventions exist for individuals with obsessive-compulsive disorder (OCD), but many individuals with OCD are unable to access them because of barriers, such as geographical isolation, treatment cost, and stigma etc. Unguided self-help psychological intervention has emerged as a potential solution to this problem. However, there is limited research on its overall effectiveness. This study aimed to address this gap. METHODS: Comprehensive searches from inception to 1st Jan 2023 were conducted in both international (PubMed, Embase, PsycINFO, International clinical trials registry platform of WHO) and Chinese (China National Knowledge Infrastructure, WeiPu, WanFang, Chinese Clinical Trial Registry) databases. The registered protocol is accessible at https://doi.org/10.17605/OSF.IO/FKB5W. We included randomized controlled trials (RCTs) comparing unguided self-help psychological interventions to control groups for individuals with OCD. The primary outcome was OCD symptom severity, with Hedges' g calculated post-intervention. Heterogeneity was deemed to be low, moderate, and high if the I2 value was quantified 25%, 50%, and 75% respectively. Relative Risks (RRs) was calculated for dropout rates post-intervention. Random-effects models were used for all analyses. RESULTS: 12 RCTs comparing unguided self-help psychological interventions to control groups were identified, with a total of 20 comparisons and 769 OCD patients. Overall, unguided self-help psychological interventions demonstrated a significant moderate effect on reducing OCD symptom severity (g = -0.42; 95% CI [-0.69; -0.14]) compared to control groups, with a moderate heterogeneity (I2 = 59%; 95% CI [22.73; 78.38]). This finding remained significant in sensitivity analyses for the self-rated Yale-Brown Obsessive-Compulsive Scale (Y-BOCS; k = 7, g = -0.46; 95% CI [-0.71; -0.2]) and after removing an outlier (g = -0.37; 95% CI [-0.55; -0.19]), but not for the clinician-rated Y-BOCS (k = 4, g = -0.78; 95% CI [-2.75; 1.19]) and Obsessive Compulsive Inventory-Revised (k = 6, g = -0.26; 95% CI [-0.53; 0]). Subgroup analyses revealed a significant difference in effect size between studies conducting intention-to-treat and completers-only analyses (p = .01). The completers-only analyses demonstrated a moderate significant effect (g = -0.65; 95% CI [-1.08; -0.21]), whereas the effect of the intention-to-treat analyses was not significant (g = -0.18; 95% CI [-0.36; 0]). Participants in the unguided self-help groups exhibited a significantly higher dropout rate (RR = 2.08; 95% CI [1.53; 2.81]) compared to control groups. Furthermore, participants recruited from the community had a higher likelihood of dropping out compared to those recruited from clinical settings (p < .001). Additionally, participants who received cognitive-behavioural therapy intervention were more likely to drop out than those who received other types of intervention (p < .001). Most trials (92%) were rated at a high risk of bias. CONCLUSION: Unguided self-help psychological interventions demonstrate potential effectiveness in alleviating OCD symptom severity post-intervention. However, caution should be exercised when interpreting the results due to high risk of bias across trials and the relatively small sample size. And the considerable dropout rate might hinder treatment effects. Future studies with strict methodology should investigate the long-term effectiveness of unguided self-help psychological interventions for OCD, explore the reasons for high dropout rates, and improve intervention adherence.

The associations of hair cortisol and DHEA with posttraumatic stress disorder symptoms in refugees.

BACKGROUND: Exposure to traumatic events, ongoing adversity, and posttraumatic stress disorder (PTSD) are associated with altered activity of the hypothalamic-pituitary-adrenal (HPA) axis, but findings are mixed. This may be explained in part by heterogeneity in PTSD symptom profiles. AIM: The aim of this study was to investigate the complex relationships between the number of traumatic events and post-displacement stressors, individual symptoms of PTSD, and HPA-axis hormones cortisol and dehydroepiandrosterone (DHEA) in refugees. METHODS: Adult (18+ years) Syrian refugees with increased levels of distress participating in a randomized controlled trial completed baseline measures to assess traumatic events (trauma checklist), post-displacement stressors (Post-Migration Living Difficulties checklist), symptoms of PTSD (PTSD Checklist for DSM-5; PCL-5), and provided a hair sample for additional stress hormone analyses. We used R-packages qgraph and bootnet to perform network analysis on the number of traumatic events and post-displacement stressors, individual symptoms of PTSD, and HPA-axis hormones cortisol and DHEA. The final network model was corrected for depression severity. RESULTS: 115 (53% male, M age = 36.9, SD = 12.7) of 206 participants provided a hair sample. A higher number of traumatic events was directly associated with three symptoms of the PTSD cluster arousal and reactivity, i.e., sleep disturbance, hypervigilance and physiological reactivity, and with three other PTSD symptoms, namely flashbacks, avoidance of reminders, and self-destructive behavior. A higher number of post-displacement stressors was associated with four symptoms of the PTSD cluster cognition and mood, i.e., trauma-related amnesia, negative beliefs, blaming of self/others, and detachment, as well as with intrusive thoughts, sleep disturbance, hypervigilance, and exaggerated startle response. The number of traumatic events and post-displacement stressors were not associated with cortisol or DHEA. Cortisol was positively associated with two symptoms of the PTSD cluster cognition and mood, i.e., negative beliefs and negative trauma-related emotions, and negatively associated with avoidance of reminders. DHEA was positively associated with restricted affect and with three symptoms of the PTSD symptom cluster arousal and reactivity, i.e., irritability/anger, sleep disturbance, and self-destructive behavior, and negatively associated with avoidance of thoughts. CONCLUSIONS: This study demonstrated that exposure to traumatic events and post-displacement stressors is not related to cortisol and DHEA, but that cortisol and DHEA are differentially related to individual symptoms of PTSD. While lower levels of both cortisol and DHEA were associated with increased avoidance, higher levels of cortisol were mostly associated with symptoms of the PTSD cluster cognition and mood and higher levels of DHEA were mostly associated with symptoms of the PTSD cluster arousal and reactivity. These findings contribute to explaining the variability of findings in the literature on HPA-axis activity in PTSD. ETHICS: The study was approved by the Research Ethics Review Committee at VU Medical Center, the Netherlands (Protocol ID: NL61361.029.17, 7 September 2017) and prospectively registered online (https://www.trialregister.nl/trial/6665).

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

BACKGROUND: Evidence shows that online interventions could prevent depression. However, to improve the effectiveness of preventive online interventions in individuals with subthreshold depression, it is worthwhile to study factors influencing intervention outcomes. Outcome expectancy has been shown to predict treatment outcomes in psychotherapy for depression. However, little is known about whether this also applies to depression prevention. The aim of this study was to investigate the role of participants' outcome expectancy in an online depression prevention intervention. METHODS: A secondary data analysis was conducted using data from two randomised-controlled trials (N = 304). Multilevel modelling was used to explore the effect of outcome expectancy on depressive symptoms and close-to-symptom-free status postintervention (6-7 weeks) and at follow-up (3-6 months). In a subsample (n = 102), Cox regression was applied to assess the effect on depression onset within 12 months. Explorative analyses included baseline characteristics as possible moderators. Outcome expectancy did not predict posttreatment outcomes or the onset of depression. RESULTS: Small effects were observed at follow-up for depressive symptoms (ß = -.39, 95% confidence interval [CI]: [-0.75, -0.03], p = .032, padjusted = .130) and close-to-symptom-free status (relative risk = 1.06, 95% CI: [1.01, 1.11], p = .013, padjusted = 0.064), but statistical significance was not maintained when controlling for multiple testing. Moderator analyses indicated that expectancy could be more influential for females and individuals with higher initial symptom severity. CONCLUSION: More thoroughly designed, predictive studies targeting outcome expectancy are necessary to assess the full impact of the construct for effective depression prevention. PATIENT OR PUBLIC CONTRIBUTION: This secondary analysis did not involve patients, service users, care-givers, people with lived experience or members of the public. However, the findings incorporate the expectations of participants using the preventive online intervention, and these exploratory findings may inform the future involvement of participants in the design of indicated depression prevention interventions for adults. CLINICAL TRIAL REGISTRATION: Original studies: DRKS00004709, DRKS00005973; secondary analysis: osf.io/9xj6a.

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.

Planetary Health and Mental Health Nexus: Least Understood and Embraced in Policy Decisions.

Planetary health influences mental health and a better management of climate, biodiversity and pollution has co-benefits of improving mental health outcomes. The recognition and treatment of mental health, however, has been marginalized within environmental and climate change sciences and a greater understanding of the complex underlying processes and societal costs is required to appropriately manage and motivate policy responses. The paper provides seven recommendations underscoring that public policy developers and implementors need to be aware of the combined costs of inaction - that might accrue from neglecting mental health and environmental sciences- two areas that have been historically marginalized. Improved methodologies in conducting studies on the nature and mental health nexus are needed. The trajectories and models of adaptation and mitigation of climate change and environmental damage can be strengthened through adoption of mental and behavioral sciences approach.

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.

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.

Non-directive supportive therapy for depression: A meta-analytic review.

BACKGROUND: Non-directive supportive therapy (NDST) is an important treatment of adult depression, but no recent meta-analysis has integrated the randomized trials examining its effects. METHODS: We conducted a meta-analysis comparing NDST to control conditions and to other therapies, by using an existing database of randomized trials of psychological treatments of depression in adults. This database was built through searches in PubMed, PsycINFO, Embase and the Cochrane Library. RESULTS: 48 randomized controlled trials (5075 participants), with 20 comparisons between NDST and a control group and 49 comparisons between NDST and another psychotherapy were included. Random effects meta-analyses found an effect size of NDST compared with control conditions of g = 0.53 (95 % CI, 0.34; 0.72) with moderate heterogeneity (I2 = 51; 95 % CI: 18; 71; PI = -0.02 to 1.09). NDST was less effective than other therapies (g = -0.21; 95 % CI: -0.31; -0.11). The difference with other therapies was significantly larger in studies in which NDST was used as a control group (p = .003). There was no significant difference between NDST and other therapies in which NDST was not used as a control group (k = 14; g = -0.05; 95 % CI: -0.17; 0.07). CONCLUSIONS: NDST probably is an effective treatment of depression. The effects may be somewhat smaller than those of other therapies, but that may also be an artefact, because NDST is often used as a control group and may be designed as an "intent-to-fail" intervention in some studies.

What works for whom and why? Treatment effects and their moderators among forcibly displaced people receiving psychological and psychosocial interventions: study protocol for an individual patient data meta-analysis.

INTRODUCTION: Forcibly displaced people (FDP) have a high risk of developing mental disorders such as post-traumatic stress (PTS) disorder. Providing adequate mental healthcare for FDP is crucial but despite overall efficacy of many existing interventions, a large proportion of FDP does not benefit from treatment, highlighting the necessity of further investigating factors contributing to individual differences in treatment outcome. Yet, the few studies that have explored moderators of treatment effects are often insufficiently powered. Therefore, the present Individual Patient Data meta-analysis (IPD-MA) will investigate treatment effects and their moderators-variables related to beneficiaries, providers, intervention and study characteristics in relation to PTS outcomes. METHODS AND ANALYSIS: A systematic literature search will be conducted from database inception in the databases PsycINFO, Cochrane, Embase, PTSDpubs and Web of Science. Only studies published in English, German, French, Spanish, Portuguese, and Dutch will be considered. Retrieved records will be screened for eligibility. Randomised controlled trials on adult FDP receiving psychological and psychosocial interventions aimed at alleviating symptoms such as PTS compared with a control condition without intervention will be included in this IPD-MA. Subsequently, authors of eligible studies will be contacted to request individual patient data (IPD). All datasets obtained will be synthesised into one large dataset which will be analysed using a one-stage approach by conducting mixed-effects linear regression models (ie, primary analysis). Additionally, aggregate data meta-analyes will be run using a two-stage approach by conducting multivariate regression models including all IPD (transformed) and available meta-data from study reports (ie, secondary analysis). PTS will serve as primary outcome measure, while mental health outcomes other than PTS, attendance, attrition, treatment non-response and adverse outcomes will be examined as secondary outcomes. ETHICS AND DISSEMINATION: This IPD-MA does not require ethical approval. The results will be published in international peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42022299510.

Predicting effects of a digital stress intervention for patients with depressive symptoms: Development and validation of meta-analytic prognostic models using individual participant data.

OBJECTIVE: Digital stress interventions could be helpful as an "indirect" treatment for depression, but it remains unclear for whom this is a viable option. In this study, we developed models predicting individualized benefits of a digital stress intervention on depressive symptoms at 6-month follow-up. METHOD: Data of N = 1,525 patients with depressive symptoms (Center for Epidemiological Studies' Depression Scale, CES-D ≥ 16) from k = 6 randomized trials (digital stress intervention vs. waitlist) were collected. Prognostic models were developed using multilevel least absolute shrinkage and selection operator and boosting algorithms, and were validated using bootstrap bias correction and internal-external cross-validation. Subsequently, expected effects among those with and without a treatment recommendation were estimated based on clinically derived treatment assignment cut points. RESULTS: Performances ranged from R² = 21.0%-23.4%, decreasing only slightly after model optimism correction (R² = 17.0%-19.6%). Predictions were greatly improved by including an interim assessment of depressive symptoms (optimism-corrected R2 = 32.6%-35.6%). Using a minimally important difference of d = -0.24 as assignment cut point, approximately 84.6%-93.3% of patients are helped by this type of intervention, while the remaining 6.7%-15.4% would experience clinically negligible benefits (δ^ = -0.02 to -0.19). Using reliable change as cut point, a smaller subset (39.3%-46.2%) with substantial expected benefits (δ^ = -0.68) receives a treatment recommendation. CONCLUSIONS: Meta-analytic prognostic models applied to individual participant data can be used to predict differential benefits of a digital stress intervention as an indirect treatment for depression. While most patients seem to benefit, the developed models could be helpful as a screening tool to identify those for whom a more intensive depression treatment is needed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Baseline depression severity as moderator on depression outcomes in psychotherapy and pharmacotherapy.

BACKGROUND: Evidence-based treatments for adult depression include psychotherapy and pharmacotherapy, yet little is known about how baseline depression severity moderates treatment outcome. OBJECTIVES: We aimed to compare the effects of psychotherapy and pharmacotherapy for adult depression and to examine the association between baseline depression severity and treatment outcome, converting multiple baseline depression measures into the scores of the Beck Depression Inventory, second edition (BDI-II). METHODS: We conducted systematic searches in bibliographical databases up to September 2022 to identify randomized controlled trials (RCTs) in which psychotherapy was compared with pharmacotherapy in the treatment of adult depression. Various meta-regressions using the baseline depression severity as predictor of the relative effects of psychotherapy and pharmacotherapy were performed. RESULTS: We identified 65 RCTs including 7250 participants for the meta-analyses and 56 RCTs including 5548 participants for the meta-regression. We found no significant difference between psychotherapy and pharmacotherapy (g = -0.08, 95 % CI: -0.2 to 0.04, p = 0.193) and baseline depression severity was not significantly associated with the relative effects of psychotherapy and pharmacotherapy (B = 0.0032, SE = 0.0096, p = 0.74). Results were similar in several sensitivity analyses. LIMITATIONS: Limitations included the low quality of the included studies, and the omission of long-term effects and within-study variability. CONCLUSIONS: We found no indication for a moderation effect of baseline depression severity on the relative effects of psychotherapy and pharmacotherapy. Thus, other factors such as availability and patients' preference must be considered when deciding for treatment options.

Current evidence on the efficacy of mental health smartphone apps for symptoms of depression and anxiety. A meta-analysis of 176 randomized controlled trials.

The mental health care available for depression and anxiety has recently undergone a major technological revolution, with growing interest towards the potential of smartphone apps as a scalable tool to treat these conditions. Since the last comprehensive meta-analysis in 2019 established positive yet variable effects of apps on depressive and anxiety symptoms, more than 100 new randomized controlled trials (RCTs) have been carried out. We conducted an updated meta-analysis with the objectives of providing more precise estimates of effects, quantifying generalizability from this evidence base, and understanding whether major app and trial characteristics moderate effect sizes. We included 176 RCTs that aimed to treat depressive or anxiety symptoms. Apps had overall significant although small effects on symptoms of depression (N=33,567, g=0.28, p<0.001; number needed to treat, NNT=11.5) and generalized anxiety (N=22,394, g=0.26, p<0.001, NNT=12.4) as compared to control groups. These effects were robust at different follow-ups and after removing small sample and higher risk of bias trials. There was less variability in outcome scores at post-test in app compared to control conditions (ratio of variance, RoV=-0.14, 95% CI: -0.24 to -0.05 for depressive symptoms; RoV=-0.21, 95% CI: -0.31 to -0.12 for generalized anxiety symptoms). Effect sizes for depression were significantly larger when apps incorporated cognitive behavioral therapy (CBT) features or included chatbot technology. Effect sizes for anxiety were significantly larger when trials had generalized anxiety as a primary target and administered a CBT app or an app with mood monitoring features. We found evidence of moderate effects of apps on social anxiety (g=0.52) and obsessive-compulsive (g=0.51) symptoms, a small effect on post-traumatic stress symptoms (g=0.12), a large effect on acrophobia symptoms (g=0.90), and a non-significant negative effect on panic symptoms (g=-0.12), although these results should be considered with caution, because most trials had high risk of bias and were based on small sample sizes. We conclude that apps have overall small but significant effects on symptoms of depression and generalized anxiety, and that specific features of apps - such as CBT or mood monitoring features and chatbot technology - are associated with larger effect sizes.

A blended intervention for adjustment disorder: Study protocol for a feasibility trial.

Introduction: Adjustment disorder (AjD) is a maladaptive response to one or more psychosocial stressors. In many cases, the symptomatology of this disorder disappears once the stressor or its consequences are no longer present. However, in some cases, if left untreated, the symptoms may worsen and develop into a more severe mental disorder. In this regard, different authors propose that a low-intensity intervention may be suitable for this disorder. Previous studies with other mental disorders and with patients with AjD found that blended interventions can be a viable and effective option. The aim of this study is to analyze the feasibility (the participants' expectations and preferences, the satisfaction and acceptance, the appropriateness of different methods of recruitment and data collection, and the reasons for dropping out) of a blended cognitive-behavioral intervention (CBT) for AjD that combines the use of a self-applied Internet-based program with videoconference sessions with a therapist. As a secondary objective, the potential efficacy of this intervention will be tested. Method and analysis: A feasibility trial with a single-group and open-trial design will be conducted. A total of 41 participants will be assigned to the single treatment group. All the participants will be assessed for eligibility and respond at four measurement points: pre-treatment, post-treatment, and 3- and 12-month follow-ups. The treatment combines the use of an Internet-based intervention through a web platform with videoconference sessions with a therapist every 10-12 days. The intervention contains seven modules and is based on CBT. The main outcome measures are related to the feasibility of the intervention (adherence, treatment satisfaction and expectations, participants' opinions, preferences, therapeutic alliance, and usability). Clinical measures will also be assessed. Discussion: To the best of our knowledge, this is the first study to test a blended intervention for AjD in the Spanish language. We expect this intervention to be feasible, and that a future Randomized Controlled Trial will be able to show its efficacy. Potential limitations include difficulties in recruiting the sample, failures in the computer systems, or a high dropout rate. Measures have been taken to try to reduce the impact of these limitations. This study received the approval of the Ethics committee of Universitat Jaume I in March 2022 (CD/42/2022). Trial registration: ClinicalTrials.gov Identifier: NCT05464121. Registered 19 July 2022, https://clinicaltrials.gov/ct2/show/NCT05464121.

A systematic review of predictors and moderators of treatment outcomes in internet- and mobile-based interventions for depression.

This systematic review aimed to synthesize evidence on predictors and moderators of treatment outcomes in internet- and mobile-based interventions (IMIs) for depression, informing personalized care. A systematic search across PubMed, PsycInfo, and Cochrane yielded 33,002 results. Two reviewers independently performed screening, data extraction, risk of bias assessment, and methodological quality evaluation. Fifty-eight single studies (m = 466 analyses) focusing on baseline-predictors (59.7 %, m = 278), process-predictors (16.5 %, m = 77), and moderators (21.9 %, m = 102), and six individual patient data meta-analyses (m = 93) were included. Only 24.0 % (m = 112/466) of analyses in single studies and 15.1 % (m = 14/93) in individual patient data meta-analyses were significant. Evidence from single studies was rated as insufficient for all variable categories with only 2 out of 40 categories showing >50 % significant results. Baseline depression severity had the strongest predictive value with higher scores linked to better outcomes followed by variables indicative for the course-of-change. Other frequently analyzed and potentially relevant variables with significant results were adherence, age, educational level, ethnicity, relationship status, treatment history, and behavioral variables. More high quality quantitative studies with sufficient power are essential to validate and expand findings, identifying predictors and moderators specifically relevant in IMIs to explain differential treatment effects.

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.

Heterogeneity of Treatment Effects in Internet- and Mobile-Based Interventions for Depression: A Systematic Review and Meta-Analysis.

Importance: While the effects of internet- and mobile-based interventions (IMIs) for depression have been extensively studied, no systematic evidence is available regarding the heterogeneity of treatment effects (HTEs), indicating to what extent patient-by-treatment interactions exist and personalized treatment models might be necessary. Objective: To investigate the HTEs in IMIs for depression as well as their efficacy and effectiveness. Data Sources: A systematic search in Embase, MEDLINE, Central, and PsycINFO for randomized clinical trials and supplementary reference searches was conducted on October 13, 2019, and updated March 25, 2022. The search string included various terms related to digital psychotherapy, depression, and randomized clinical trials. Study Selection: Titles, abstracts, and full texts were reviewed by 2 independent researchers. Studies of all populations with at least 1 intervention group receiving an IMI for depression and at least 1 control group were eligible, if they assessed depression severity as a primary outcome and followed a randomized clinical trial (RCT) design. Data Extraction and Synthesis: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias Tool. HTE was investigated using logarithmic variance ratios (lnVR) and effect sizes using Hedges g. Three-level bayesian meta-regressions were conducted. Main Outcomes and Measures: Heterogeneity of treatment effects was the primary outcome of this study; magnitudes of treatment effect sizes were the secondary outcome. Depression severity was measured by different self-report and clinician-rated scales in the included RCTs. Results: The systematic review of 102 trials included 19 758 participants (mean [SD] age, 39.9 [10.58] years) with moderate depression severity (mean [SD] in Patient Health Questionnaire-9 score, 12.81 [2.93]). No evidence for HTE in IMIs was found (lnVR = -0.02; 95% credible interval [CrI], -0.07 to 0.03). However, HTE was higher in more severe depression levels (ß̂ = 0.04; 95% CrI, 0.01 to 0.07). The effect size of IMI was medium (g = -0.56; 95% CrI, -0.46 to -0.66). An interaction effect between guidance and baseline severity was found (ß̂ = -0.24, 95% CrI, -0.03 to -0.46). Conclusions and Relevance: In this systematic review and meta-analysis of RCTs, no evidence for increased patient-by-treatment interaction in IMIs among patients with subthreshold to mild depression was found. Guidance did not increase effect sizes in this subgroup. However, the association of baseline severity with HTE and its interaction with guidance indicates a more sensitive, guided, digital precision approach would benefit individuals with more severe symptoms. Future research in this population is needed to explore personalization strategies and fully exploit the potential of IMI.

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.