The Contribution of “Individual Participant Data” Meta-Analyses of Psychotherapies for Depression to the Development of Personalized Treatments: A Systematic Review

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.

Motivational Variables as Moderating Effects of a Web-Based Mental Health Program for University Students: Secondary Analysis of a Randomized Controlled Trial

BACKGROUND

Self-guided web-based interventions have the potential of addressing help-seeking barriers and symptoms common among university students, such as depression and anxiety. Unfortunately, self-guided interventions are also associated with less adherence, implicating motivation as a potential moderator for adherence and improvement for such interventions. Previous studies examining motivation as a moderator or predictor of improvement on web-based interventions have defined and measured motivation variably, producing conflicting results.

OBJECTIVE

This secondary analysis of data from a randomized controlled trial aimed to examine constructs of motivation as moderators of improvement for a self-guided 8-week web-based intervention in university students (N=1607).

METHODS

Tested moderators included internal motivation, external motivation, and confidence in treatment derived from the Treatment Motivation Questionnaire. The primary outcome was an improvement in depression and anxiety measured by the Depression Anxiety Stress Scale-21.

RESULTS

Piecewise linear mixed effects models showed that internal motivation significantly moderated symptom change for the intervention group (t1504=-2.94; P=.003) at average and high (+1 SD) motivation levels (t1507=-2.28; P=.02 and t1507=-4.05; P<.001, respectively). Significant results remained even after controlling for baseline severity. The results showed that confidence in treatment did not significantly moderate symptom change for the intervention group (t1504=1.44; P=.15). In this sample, only internal motivation was positively correlated with service initiation, intervention adherence, and intervention satisfaction.

CONCLUSIONS

The combination of a web-based intervention and high or moderate internal motivation resulted in greater improvement in the total Depression Anxiety Stress Scale-21 score. These findings highlight the importance of conceptually differentiating motivation-related constructs when examining moderators of improvement. The results suggest that the combination of a web-based intervention and high or moderate internal motivation results in greater improvement. These findings highlight the importance of conceptually differentiating motivation-related constructs when examining moderators of improvement. To better understand the moderating role of internal motivation, future research is encouraged to replicate these findings in diverse samples as well as to examine related constructs such as baseline severity and adherence. Understanding these characteristics informs treatment strategies to maximize adherence and improvement when developing web-based interventions as well as allows services to be targeted to individuals likely to benefit from such interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04361045; https://clinicaltrials.gov/study/NCT04361045.

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.

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 (β̂ = 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 (β̂ = -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.

Editorial Perspective: Extending IPDMA methodology to drive treatment personalisation in child mental health

To improve outcomes for youth who do not respond optimally to existing treatments, we need to identify robust predictors, moderators, and mediators that are ideal targets for personalisation in mental health care. We propose a solution to leverage the Individual Patient Data Meta-analysis (IPDMA) approach to allow broader access to individual-level data while maintaining methodological rigour. Such a resource has the potential to answer questions that are unable to be addressed by single studies, reduce researcher burden, and enable the application of newer statistical techniques, all to provide data-driven strategies for clinical decision-making. Using childhood anxiety as the worked example, the editorial perspective outlines the rationale for leveraging IPDMA methodology to build a data repository, the Platform for Anxiety Disorder Data in Youth. We also include recommendations to address the methods and challenges inherent in this endeavour.

Use of Machine Learning Algorithms Based on Text, Audio, and Video Data in the Prediction of Anxiety and Posttraumatic 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 who 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 that assessed the predictive power of ML algorithms using text, audio, and/or video data in the prediction of anxiety and posttraumatic stress disorder. Most studies (n = 87) were aimed at predicting anxiety, while the remainder (n = 41) focused on posttraumatic stress disorder. They were mostly published since 2019 in computer science journals and tested algorithms using text (n = 72) as opposed to audio or video. Studies focused mainly on general populations (n = 92) and 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, which focused on both disorders, reported acceptable to very good predictive power (including high-quality studies only). The 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 posttraumatic stress disorder, in the future if standardization of methods, reporting of results, and research in clinical populations are improved.

Predicting treatment response using machine learning: A registered report

OBJECTIVE

Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively screening for patients at risk of low treatment response, gain more knowledge about risk factors and to evaluate treatments, accurate insights about predictors of treatment response in naturalistic inpatient samples are needed.

METHODS

We compared the performance of different machine learning algorithms in predicting treatment response, operationalized as a substantial reduction in symptom severity as expressed in the Patient Health Questionnaire Anxiety and Depression Scale. To achieve this goal, we used different sets of variables-(a) demographics, (b) physical indicators, (c) psychological indicators and (d) treatment-related variables-in a naturalistic inpatient sample (N = 723) to specify their joint and unique contribution to treatment success.

RESULTS

There was a strong link between symptom severity at baseline and post-treatment (R2 = .32). When using all available variables, both machine learning algorithms outperformed the linear regressions and led to an increment in predictive performance of R2 = .12. Treatment-related variables were the most predictive, followed psychological indicators. Physical indicators and demographics were negligible.

CONCLUSIONS

Treatment response in naturalistic inpatient settings can be predicted to a considerable degree by using baseline indicators. Regularization via machine learning algorithms leads to higher predictive performances as opposed to including nonlinear and interaction effects. Heterogenous aspects of mental health have incremental predictive value and should be considered as prognostic markers when modelling treatment processes.

Social Skills Interventions for Adolescents with Level 1 Autism Spectrum Disorder: A Systematic Review with Meta-Analysis of Randomized Controlled Trials

Objective

Evidence on the efficacy of social skills training for adolescents with Level 1 Autism Spectrum Disorder (ASD) is unclear.

Method

We searched Pubmed, Scopus, and Web of Science until July 27th, 2023, for randomized controlled trials (RCTs) of social skills training for pre-adolescents and adolescents (aged 9-18) with Level 1 ASD. We then pooled data on efficacy from individual RCTs by conducting multivariate mixed-effects meta-analyses in R. We estimated possible bias in the retained RCTs using the RoB2 tool.

Results

We retained 36 RCTs (encompassing 2796 participants), including 18 RCTs comparing an experimental treatment to a waiting list, and 18 RCTs comparing it to standard care/control treatment. Meta-analyses showed that experimental treatments were significantly more efficacious than waiting list or standard care/ control treatments in improving social skills (SMD = 0.3745; 95%CI = [0.2396; 0.5093]), as well as reducing behavioral symptoms (0.3154;0.1783, 0.4525) and anxious/depressive symptoms (0.2780; 0.0432, 0.5128). However, for some outcomes there was significant heterogeneity across studies and evidence of publication bias. Subgroup analyses and meta-regressions did not identify any specific clinical or demographic factors as significant predictors of outcome. The most common risk of bias across studies was related to deviations from intended interventions and measurement of the outcomes.

Conclusions

At the group level, social skills training for adolescents with Level 1 ASD is efficacious, with small-to-moderate effect size. Future research should focus on personalized medicine approaches, aimed at tailoring interventions to specific characteristics of adolescents with Level 1 ASD.

Treatment effect heterogeneity of cognitive behavioral therapy for insomnia - A meta-analysis

Investigation of the heterogeneity of the treatment effect (HTE) might guide the optimization of cognitive behavioral therapy for insomnia (CBT-I). This study examined HTE in CBT-I thereby analyzing if treatment setting, control group, different CBT-I components, and patient characteristics drive HTE. Randomized controlled trials investigating CBT-I were included. Bayesian random effect meta-regressions were specified to examine variances between the intervention and control groups regarding post-treatment symptom severity. Subgroup analyses analyzing treatment setting and control groups and covariate analysis analyzing treatment components and patient characteristics were specified. No significant HTE in CBT-I was found for the overall data set, settings and control groups. The covariate analyses yielded significant results for baseline severity and the treatment component relaxation therapy. Thus, this study identified potential causes for HTE in CBT-I for the first time, showing that it might be worthwhile to further examine possibilities for precision medicine in CBT-I.

Leveraging Novel Technologies and Artificial Intelligence to Advance Practice-Oriented Research

Mental health services are experiencing notable transformations as innovative technologies and artificial intelligence (AI) are increasingly utilized in a growing number of studies and services.These cutting-edge technologies carry the promise of substantial improvements in the field of mental health. Nevertheless, questions emerge about the alignment of novel technologies and AI systems with human needs, especially in the context of vulnerable populations receiving mental healthcare. The practice-oriented research (POR) model is pivotal in seamlessly integrating these emerging technologies into clinical research and practice. It underscores the importance of tight collaboration between clinicians and researchers, all driven by the central goal of ensuring and elevating client well-being. This paper focuses on how novel technologies can enhance the POR model and highlights its pivotal role in integrating these technologies into clinical research and practice. We discuss two key phases: pre-treatment, and during treatment. For each phase, we describe the challenges, present the major technological innovations, describe recent studies exemplifying technology use, and suggest future directions. Ethical concerns and the importance of aligning humans and technology are also considered, in addition to implications for practice and training.

Moderators of short- and long-term outcomes in panic control treatment and panic-focused psychodynamic psychotherapy

OBJECTIVE

The objective was to test the hypothesis that externalizing and internalizing helpfulness beliefs and learning styles at baseline moderate panic severity and overall mental illness as short-term and long-term outcomes of two panic-focused psychotherapies, Panic Control Treatment (PCT) and Panic-Focused Psychodynamic Psychotherapy (PFPP).

METHOD

Participants were 108 adults with DSM-IV Panic Disorder with or without Agoraphobia (PD/A) who were randomized to treatment in a trial of PCT and PFPP. Piece-wise/segmented multilevel modeling was used to test three-way interactions (Treatments × Moderator × Time), with participants and therapists as random factors. Outcome variables were clinician-rated panic severity and self-rated mental illness post-treatment and during follow-up.

RESULTS

Patients' externalizing (but not internalizing) helpfulness beliefs moderated mental illness outcomes during follow-up (but not during treatment); low levels of Externalization were facilitative for PFPP but not PCT. Internalizing and externalizing helpfulness beliefs and learning style did not moderate clinician-rated panic severity, whether short- or long-term.

CONCLUSIONS

These results suggest that helpfulness beliefs and learning style have limited use in assignment to either PCT or PFPP for PD/A. Although further research is needed, low levels of helpfulness beliefs about externalizing coping may play a role in mental illness outcomes for PFPP.

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.

Primary-level and community worker interventions for the prevention of mental disorders and the promotion of well-being in low- and middle-income countries

BACKGROUND

There is a significant research gap in the field of universal, selective, and indicated prevention interventions for mental health promotion and the prevention of mental disorders. Barriers to closing the research gap include scarcity of skilled human resources, large inequities in resource distribution and utilization, and stigma.

OBJECTIVES

To assess the effectiveness of delivery by primary workers of interventions for the promotion of mental health and universal prevention, and for the selective and indicated prevention of mental disorders or symptoms of mental illness in low- and middle-income countries (LMICs). To examine the impact of intervention delivery by primary workers on resource use and costs.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, CINAHL, Global Index Medicus, PsycInfo, WHO ICTRP, and ClinicalTrials.gov from inception to 29 November 2021.

SELECTION CRITERIA

Randomized controlled trials (RCTs) of primary-level and/or community health worker interventions for promoting mental health and/or preventing mental disorders versus any control conditions in adults and children in LMICs.

DATA COLLECTION AND ANALYSIS

Standardized mean differences (SMD) or mean differences (MD) were used for continuous outcomes, and risk ratios (RR) for dichotomous data, using a random-effects model. We analyzed data at 0 to 1, 1 to 6, and 7 to 24 months post-intervention. For SMDs, 0.20 to 0.49 represented small, 0.50 to 0.79 moderate, and ≥ 0.80 large clinical effects. We evaluated the risk of bias (RoB) using Cochrane RoB2.

MAIN RESULTS

Description of studies We identified 113 studies with 32,992 participants (97 RCTs, 19,570 participants in meta-analyses) for inclusion. Nineteen RCTs were conducted in low-income countries, 27 in low-middle-income countries, 2 in middle-income countries, 58 in upper-middle-income countries and 7 in mixed settings. Eighty-three RCTs included adults and 30 RCTs included children. Cadres of primary-level workers employed primary care health workers (38 studies), community workers (71 studies), both (2 studies), and not reported (2 studies). Interventions were universal prevention/promotion in 22 studies, selective in 36, and indicated prevention in 55 RCTs. Risk of bias The most common concerns over risk of bias were performance bias, attrition bias, and reporting bias. Intervention effects 'Probably', 'may', or 'uncertain' indicates 'moderate-', 'low-', or 'very low-'certainty evidence. *Certainty of the evidence (using GRADE) was assessed at 0 to 1 month post-intervention as specified in the review protocol. In the abstract, we did not report results for outcomes for which evidence was missing or very uncertain. Adults Promotion/universal prevention, compared to usual care: - probably slightly reduced anxiety symptoms (MD -0.14, 95% confidence interval (CI) -0.27 to -0.01; 1 trial, 158 participants) - may slightly reduce distress/PTSD symptoms (SMD -0.24, 95% CI -0.41 to -0.08; 4 trials, 722 participants) Selective prevention, compared to usual care: - probably slightly reduced depressive symptoms (SMD -0.69, 95% CI -1.08 to -0.30; 4 trials, 223 participants) Indicated prevention, compared to usual care: - may reduce adverse events (1 trial, 547 participants) - probably slightly reduced functional impairment (SMD -0.12, 95% CI -0.39 to -0.15; 4 trials, 663 participants) Children Promotion/universal prevention, compared to usual care: - may improve the quality of life (SMD -0.25, 95% CI -0.39 to -0.11; 2 trials, 803 participants) - may reduce adverse events (1 trial, 694 participants) - may slightly reduce depressive symptoms (MD -3.04, 95% CI -6 to -0.08; 1 trial, 160 participants) - may slightly reduce anxiety symptoms (MD -2.27, 95% CI -3.13 to -1.41; 1 trial, 183 participants) Selective prevention, compared to usual care: - probably slightly reduced depressive symptoms (SMD 0, 95% CI -0.16 to -0.15; 2 trials, 638 participants) - may slightly reduce anxiety symptoms (MD 4.50, 95% CI -12.05 to 21.05; 1 trial, 28 participants) - probably slightly reduced distress/PTSD symptoms (MD -2.14, 95% CI -3.77 to -0.51; 1 trial, 159 participants) Indicated prevention, compared to usual care: - decreased slightly functional impairment (SMD -0.29, 95% CI -0.47 to -0.10; 2 trials, 448 participants) - decreased slightly depressive symptoms (SMD -0.18, 95% CI -0.32 to -0.04; 4 trials, 771 participants) - may slightly reduce distress/PTSD symptoms (SMD 0.24, 95% CI -1.28 to 1.76; 2 trials, 448 participants).

AUTHORS' CONCLUSIONS

The evidence indicated that prevention interventions delivered through primary workers - a form of task-shifting - may improve mental health outcomes. Certainty in the evidence was influenced by the risk of bias and by substantial levels of heterogeneity. A supportive network of infrastructure and research would enhance and reinforce this delivery modality across LMICs.

Editorial: Primum non nocere - are adverse events accurately reported in studies on psychological interventions for children?

Adverse Events (AEs) are defined as any unfavorable and unintended sign or symptom, that may occur during or after receipt of any intervention. The principle of non-maleficence requires careful consideration to ensure that existing or new psychological interventions are not harmful before they can be considered beneficial. In this context, the safety of psychological interventions, including the possible occurrence of AEs, is increasingly important for patients, families, and clinicians. The evaluation of AEs is crucial to obtain a complete understanding of the risk/benefit balance of psychological interventions. There is a need for researchers and clinicians to assess and report AEs comprehensively and in a coordinated manner. It is necessary to have more accurate data on the recording of AEs in protocols to enhance transparency and consistency, as well as to improve practice. Finally, and to facilitate this process, there is a need for standards for data collection.

Predicting heterogeneous treatment effects of an Internet-based depression intervention for patients with chronic back pain: Secondary analysis of two randomized controlled trials

Background

Depression is highly prevalent among individuals with chronic back pain. Internet-based interventions can be effective in treating and preventing depression in this patient group, but it is unclear who benefits most from this intervention format.

Method

In an analysis of two randomized trials (N = 504), we explored ways to predict heterogeneous treatment effects of an Internet-based depression intervention for patients with chronic back pain. Univariate treatment-moderator interactions were explored in a first step. Multilevel model-based recursive partitioning was then applied to develop a decision tree model predicting individualized treatment benefits.

Results

The average effect on depressive symptoms was d = -0.43 (95 % CI: -0.68 to -0.17; 9 weeks; PHQ-9). Using univariate models, only back pain medication intake was detected as an effect moderator, predicting higher effects. More complex interactions were found using recursive partitioning, resulting in a final decision tree with six terminal nodes. The model explained a large amount of variation (bootstrap-bias-corrected R2 = 45 %), with predicted subgroup-conditional effects ranging from di = 0.24 to -1.31. External validation in a pilot trial among patients on sick leave (N = 76; R2 = 33 %) pointed to the transportability of the model.

Conclusions

The studied intervention is effective in reducing depressive symptoms, but not among all chronic back pain patients. Predictions of the multivariate tree learning model suggest a pattern in which patients with moderate depression and relatively low pain self-efficacy benefit most, while no benefits arise when patients' self-efficacy is already high. If corroborated in further studies, the developed tree algorithm could serve as a practical decision-making tool.

Evaluation of randomized controlled trials: a primer and tutorial for mental health researchers

BACKGROUND

Considered one of the highest levels of evidence, results of randomized controlled trials (RCTs) remain an essential building block in mental health research. They are frequently used to confirm that an intervention "works" and to guide treatment decisions. Given their importance in the field, it is concerning that the quality of many RCT evaluations in mental health research remains poor. Common errors range from inadequate missing data handling and inappropriate analyses (e.g., baseline randomization tests or analyses of within-group changes) to unduly interpretations of trial results and insufficient reporting. These deficiencies pose a threat to the robustness of mental health research and its impact on patient care. Many of these issues may be avoided in the future if mental health researchers are provided with a better understanding of what constitutes a high-quality RCT evaluation.

METHODS

In this primer article, we give an introduction to core concepts and caveats of clinical trial evaluations in mental health research. We also show how to implement current best practices using open-source statistical software.

RESULTS

Drawing on Rubin's potential outcome framework, we describe that RCTs put us in a privileged position to study causality by ensuring that the potential outcomes of the randomized groups become exchangeable. We discuss how missing data can threaten the validity of our results if dropouts systematically differ from non-dropouts, introduce trial estimands as a way to co-align analyses with the goals of the evaluation, and explain how to set up an appropriate analysis model to test the treatment effect at one or several assessment points. A novice-friendly tutorial is provided alongside this primer. It lays out concepts in greater detail and showcases how to implement techniques using the statistical software R, based on a real-world RCT dataset.

DISCUSSION

Many problems of RCTs already arise at the design stage, and we examine some avoidable and unavoidable "weak spots" of this design in mental health research. For instance, we discuss how lack of prospective registration can give way to issues like outcome switching and selective reporting, how allegiance biases can inflate effect estimates, review recommendations and challenges in blinding patients in mental health RCTs, and describe problems arising from underpowered trials. Lastly, we discuss why not all randomized trials necessarily have a limited external validity and examine how RCTs relate to ongoing efforts to personalize mental health care.

To sleep or not to sleep, that is the question: A systematic review and meta-analysis on the effect of post-trauma sleep on intrusive memories of analog trauma

Distressing intrusive memories of a traumatic event are one of the hallmark symptoms of posttraumatic stress disorder. Thus, it is crucial to identify early interventions that prevent the occurrence of intrusive memories. Both, sleep and sleep deprivation have been discussed as such interventions, yet previous studies yielded contradicting effects. Our systematic review aims at evaluating existing evidence by means of traditional and individual participant data (IPD) meta-analyses to overcome power issues of sleep research. Until May 16th, 2022, six databases were searched for experimental analog studies examining the effect of post-trauma sleep versus wakefulness on intrusive memories. Nine studies were included in our traditional meta-analysis (8 in the IPD meta-analysis). Our analysis provided evidence for a small effect favoring sleep over wakefulness, log-ROM = 0.25, p < .001, suggesting that sleep is associated with a lower number of intrusions but unrelated to the occurrence of any versus no intrusions. We found no evidence for an effect of sleep on intrusion distress. Heterogeneity was low and certainty of evidence for our primary analysis was moderate. Our findings suggest that post-trauma sleep has the potential to be protective by reducing intrusion frequency. More research is needed to determine the impact following real-world trauma and the potential clinical significance.

A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students: A Secondary Analysis of a Randomized Clinical Trial

Importance

Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT.

Objective

To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors.

Design, Setting, and Participants

This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022.

Interventions

Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435).

Main Outcomes and Measures

Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline.

Results

The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P = .003) or treatment as usual (40.0% [2.7%]; P = .001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P = .007; self-guided i-CBT: 25.4% [8.8%]; P = .004; treatment as usual: 31.0% [9.4%]; P = .001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P = .14; treatment as usual: 53.0% [6.0%]; P = .25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P = .001; treatment as usual: 41.8% [3.2%]; P < .001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P = .07).

Conclusions and Relevance

Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings.

Trial Registration

ClinicalTrials.gov Identifier: NCT04780542.

Efficacy of high-intensity versus low-intensity psychoanalytically oriented long-term treatments and determinants of outcome: individual participant data Meta-analysis of Long-term Analytic treatment Studies (MeLAS)

INTRODUCTION

Long-term psychodynamic/psychoanalytic psychotherapy (LTPP) is a prevalent treatment option for complex mental disorders. Yet, little is known about the role of treatment intensity in LTPP. We present a study protocol for a systematic review and individual participant data (IPD) meta-analysis aggregating and analysing individual data from randomised and quasi-experimental trials by meta-analysis. The purpose is to (1) determine the treatment effectiveness of LTPP with low versus high intensity (up to 2 weekly sessions vs three or more), (2) compare their joint effectiveness to shorter therapies and treatments as usual, (3) identify predictors and moderators of treatment outcomes and (4) determine reciprocal relationships between different outcome domains (symptomatic and structural/personality change) over the courses of LTPP.

METHODS AND ANALYSIS

We include studies from (randomised controlled trial, RCT) and quasi-experimental trials, where at least one condition was LTPP of high or low frequency. Long-term treatment is defined as ≥1 year or ≥50 sessions. To be eligible studies must include a standardised outcome measure of symptoms (global or disorder specific) with at least one proof of reliability. The primary outcome is symptom reduction (global or specific), secondary outcome criteria are reliable change, remission, functional capacities, personality, personality functioning and interpersonal pathology. Relevant studies will mainly be identified by searching relevant databases: PubMed, PsycINFO (via EBSCO), Web of Science (via Elsevier), Chochrane's Central Register of Controlled Trials (via Wiley). Risk of bias will be evaluated in line with the Cochrane assessments tools for quasi-experimental trials and RCTs, respectively.

ETHICS AND DISSEMINATION

Aggregation of data from primary trials collected based on ethics votes. Dissemination into clinical practice via open access publications of findings.

PROSPERO REGISTRATION NUMBER

CRD42022304982; Pre-results.

Interventions Involving Caregivers for Children and Adolescents Following Traumatic Events: A Systematic Review and Meta-Analysis

Although treatment guidelines recommend interventions entailing caregiver involvement for children and adolescents following traumatic experiences, evidence on their effectiveness is inconsistent. The present systematic review and meta-analysis considered possible moderators of their effectiveness.

METHOD

Eligible studies were (quasi-)randomized controlled trials and efficacy trials published in English or German with participants up to the age of 21 years presenting symptoms of mental disorders due to traumatic experiences. The effectiveness of interventions entailing any kind and extent of caregiver involvement had to be investigated by applying evaluated instruments. PubMed, PsycINFO, ERIC, COCHRANE and PSYNDEX were searched.

RESULTS

A total of 33 studies with 36 independent samples were retrieved. Child- and parent-reports on PTSD, depression, anxiety, ADHD, internalizing, externalizing symptoms and behavior problems were analyzed where available. The pooled effect size is significant and robust at post-treatment for child-reported PTSD, g = - 0.34 (95% CI = - 0.53; - 0.14), parent-reported PTSD, g = - 0.41 (95% CI = - 0.71; - 0.11), child-reported depression, g = - 0.29 (95% CI = - 0.46; - 0.11), child-reported anxiety, g = - 0.25 (95% CI = - 0.42; - 0.08), and parent-reported internalizing symptoms, g = - 0.27 (95% CI = - 0.47; - 0.07). Female sex and fulfilling diagnostic criteria appeared as potential moderators. The only significant effect size at follow-up is found for child-reported PTSD symptoms 12 months post-treatment, g = - 0.37 (95% CI = - 0.67; - 0.07).

CONCLUSIONS

Interventions entailing caregiver involvement revealed greater symptom reductions than control conditions. Determinants of their effectiveness should be examined further.

Seeing the past in a new light: change in reports of childhood abuse and neglect before and after inpatient psychotherapy and its relevance for change in depression symptoms

OBJECTIVE

As changes in mental representations have been discussed as mechanisms of change in psychotherapy, the question arises whether recollections of childhood abuse and neglect are altered as well and how they relate to symptom changes.

METHOD

Individuals in psychosomatic inpatient treatment (N = 488, 60.5% women) filled out the Childhood Trauma Questionnaire (CTQ) and Patient Health Questionnaire (PHQ-9). Changes in both were investigated with correlations and t-tests. Linear regression analysis was used to test whether CTQ changes predicted symptom changes. Network analysis was performed to ascertain structural connections between somatic and emotional-cognitive depression symptoms and CTQ subscales before and after treatment.

RESULTS

After treatment (duration in days: M = 52.83, SD = 20.94), patients reported fewer depression symptoms (d = 0.84), while CTQ scores increased slightly (d = 0.11). Changes in the CTQ predicted recovery from depression symptoms in a statistically significant way (β = .133, p = .001). We did not observe changes in the overall network structure between baseline assessment and discharge.

CONCLUSION

The findings suggest that the evaluation of past experiences can change over multiple weeks of psychotherapy. Further, these updated mental representations, indicating a greater recognition of past adversity, may contribute to symptom relief.

Psychological interventions for symptoms of depression among informal caregivers of older adult populations: A systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Symptoms of depression are commonly experienced by informal caregivers of older adults, however there is uncertainty concerning effectiveness of psychological interventions targeting symptoms of depression in this population. Further, there is uncertainty concerning important clinical moderators, including intervention type and care recipient health condition. This review examined the effectiveness of psychological interventions targeting symptoms of depression in informal caregivers of older adults.

METHODS

PubMed, CINAHL, Embase, PsycINFO, Cochrane Library and Web of Science were searched. Risk of bias was assessed using the Cochrane Risk of Bias tool version 2.

RESULTS

Fifteen studies were identified and twelve (1270 participants) provided data for the meta-analysis. Interventions included cognitive behavioral therapy (4 studies), problem-solving therapy (4 studies); non-directive supportive therapy (4 studies) and behavioral activation (3 studies). A small effect size favouring the intervention was found for symptoms of depression (g = -0.49, CI = -0.79, -0.19, I² = 83.42 %) and interventions were effective in reducing incidence of major depression (OR = 0.177, CI = 0.08, 0.38), caregiver burden (g = -0.35, CI = -0.55, -0.15) and psychological distress (g = -0.49, CI = -0.70, -0.28). Given high heterogeneity, findings should be interpreted with caution. Overall risk of bias was high.

LIMITATIONS

Studies were limited to those in English or Swedish.

CONCLUSION

Psychological interventions may be effective in reducing symptoms of depression among informal caregivers of older adults. However, evidence is inconclusive due to heterogeneity, high risk of bias, and indirectness of evidence.

Associations between Depression and Self-Reported COVID-19 Symptoms among Adults: Results from Two Population-Based Seroprevalence Studies in Switzerland

(1) Mental health may modulate the perceived risk of SARS-CoV-2 infection. However, it is unclear how psychological symptoms may distort symptom perception of COVID-19 and SARS-CoV-2 infection. We assessed whether depressive symptoms predicted self-reported COVID-19 symptoms, independently of serologically confirmed SARS-CoV-2 infection. (2) Participants (aged 20-64) in the Geneva (N = 576) and Ticino (N = 581) Swiss regions completed the Patient Health Questionnaire before being tested for anti-SARS-CoV-2 IgG antibodies and recalled COVID-19-compatible symptoms on two occasions: April-July 2020 (baseline), and January-February 2021 (follow-up). We estimated prevalence ratios for COVID-19 symptoms by depression scores in interaction with serological status. (3) At baseline, in Geneva, higher depression predicted higher probability of reporting systemic, upper airways, and gastro-intestinal symptoms, and fever and/or cough; in Ticino, higher depression predicted systemic, upper airways, and gastro-intestinal symptoms, fever and/or cough, dyspnea, and headache. At follow-up, in Geneva, higher depression predicted higher probability of reporting systemic symptoms and dyspnea; in Ticino, higher depression predicted higher probability of reporting systemic and upper airways symptoms, dyspnea and headache (all p values < 0.05). (4) We found positive associations between depressive symptoms and COVID-19-compatible symptoms, independently of seropositivity. Mental wellbeing has relevant public health implications because it modulates self-reported infection symptoms that inform testing, self-medication, and containment measures, including quarantine and isolation.

Digital cognitive-behavioural therapy to reduce suicidal ideation and behaviours: a systematic review and meta-analysis of individual participant data

QUESTION

Digital interventions based on cognitive-behavioural therapy (iCBT) is associated with reductions in suicidal ideation. However, fine-grained analyses of effects and potential effect-moderating variables are missing. This study aimed to investigate the effectiveness of iCBT on suicidal ideation, effect moderators, effects on suicide attempts and predictors of adherence.

STUDY SELECTION AND ANALYSIS

We systematically searched CENTRAL, PsycINFO, Embase and PubMed for randomised controlled trials that investigated iCBT for suicidal ideation or behaviours. Participants reporting baseline suicidal ideation were eligible. We conducted a one-stage individual participant data (IPD) meta-analysis. Suicidal ideation was the primary outcome, analysed as three indices: severity of suicidal ideation, reliable changes and treatment response.

FINDINGS

We included IPD from nine out of ten eligible trials (2037 participants). iCBT showed significant reductions of suicidal ideation compared with control conditions across all indices (severity: b=-0.247, 95% CI -0.322 to -0.173; reliable changes: b=0.633, 95% CI 0.408 to 0.859; treatment response: b=0.606, 95% CI 0.410 to 0.801). In iCBT, the rate of reliable improvement was 40.5% (controls: 27.3%); the deterioration rate was 2.8% (controls: 5.1%). No participant-level moderator effects were identified. The effects on treatment response were higher for trials with waitlist-controls compared with active controls. There were insufficient data on suicide attempts. Human support and female gender predicted treatment adherence. The main source of potential bias was missing outcome data.

CONCLUSIONS

The current evidence indicates that iCBT is effective in reducing suicidal ideation irrespective of age, gender and previous suicide attempts. Future studies should rigorously assess suicidal behaviour and drop-out reasons.

Psychotherapy and change in mental health-related work disability: a prospective Finnish population-level register-based study with a quasi-experimental design

BACKGROUND

Mental disorders are a major cause of work disability among the working-age population. Psychotherapy has shown to be an effective treatment for mental disorders, but the evidence is mainly based on small-scale randomised trials with relatively short follow-ups. We used population-based register data to examine the association between statutory rehabilitative psychotherapy and change in depression or anxiety-related work disability.

METHODS

We drew a nationally representative sample of the working-age population (aged 18-55 in 2010). The study group comprised all those who started rehabilitative psychotherapy in 2011-2014. A total of 10 436 participants who were followed from 3 years prior to 4 years after the onset of rehabilitative psychotherapy. This resulted in 83 488 observations. The annual total number of mental health-related work disability months (0 to 12) was calculated from the total number of annual compensated sickness absence and disability pension days. A quasi-experimental interrupted time series analysis was applied.

RESULTS

The onset of rehabilitative psychotherapy marked a decline in work disability in comparison to the counterfactual trend. Specifically, a 20% decrease in the level (incidence rate ratio, IRR 0.80; 95% CI 0.76 to 0.85) and a 48% decrease in the slope (IRR 0.52; 95% CI 0.50 to 0.54) of work disability were detected in comparison to the counterfactual scenario. No significant gender differences were observed. The decline in work disability was the steepest in the oldest age group.

CONCLUSIONS

This study suggests that statutory psychotherapy may decrease work disability at the population level. However, further evidence of causal inference and the potential heterogeneity of the association is required.

A systematic review of digital and face-to-face cognitive behavioral therapy for depression

Cognitive behavioral therapy (CBT) represents one of the major treatment options for depressive disorders besides pharmacological interventions. While newly developed digital CBT approaches hold important advantages due to higher accessibility, their relative effectiveness compared to traditional CBT remains unclear. We conducted a systematic literature search to identify all studies that conducted a CBT-based intervention (face-to-face or digital) in patients with major depression. Random-effects meta-analytic models of the standardized mean change using raw score standardization (SMCR) were computed. In 106 studies including n = 11854 patients face-to-face CBT shows superior clinical effectiveness compared to digital CBT when investigating depressive symptoms (p < 0.001, face-to-face CBT: SMCR = 1.97, 95%-CI: 1.74–2.13, digital CBT: SMCR = 1.20, 95%-CI: 1.08–1.32) and adherence (p = 0.014, face-to-face CBT: 82.4%, digital CBT: 72.9%). However, after accounting for differences between face-to-face and digital CBT studies, both approaches indicate similar effectiveness. Important variables with significant moderation effects include duration of the intervention, baseline severity, adherence and the level of human guidance in digital CBT interventions. After accounting for potential confounders our analysis indicates comparable effectiveness of face-to-face and digital CBT approaches. These findings underline the importance of moderators of clinical effects and provide a basis for the future personalization of CBT treatment in depression.

Unveiling mechanisms of change in digital interventions for depression: Study protocol for a systematic review and individual participant data meta-analysis

INTRODUCTION

The efficacy and effectiveness of digital interventions for depression are both well-established. However, precise effect size estimates for mediators transmitting the effects of digital interventions are not available; and integrative insights on the specific mechanisms of change in internet- and mobile-based interventions (IMIs)-as related to key features like delivery type, accompanying support and theoretical foundation-are largely pending.

OBJECTIVE

We will conduct a systematic review and individual participant data meta-analysis (IPD-MA) evaluating the mediators associated with therapeutic change in various IMIs for depression in adults.

METHODS

We will use three electronic databases (i.e., Embase, Medline/PubMed, PsycINFO) as well as an already established database of IPD to identify relevant published and unpublished studies. We will include (1) randomized controlled trials that examine (2) mediators of (3) guided and unguided (4) IMIs with (5) various theoretical orientations for (6) adults with (7) clinically relevant symptoms of depression (8) compared to an active or passive control condition (9) with depression symptom severity as primary outcome. Study selection, data extraction, as well as quality and risk of bias (RoB) assessment will be done independently by two reviewers. Corresponding authors of eligible primary studies will be invited to share their IPD for this meta-analytic study. In a 1-stage IPD-MA, mediation analyses (e.g., on potential mediators like self-efficacy, emotion regulation or problem solving) will be performed using a multilevel structural equation modeling approach within a random-effects framework. Indirect effects will be estimated, with multiple imputation for missing data; the overall model fit will be evaluated and statistical heterogeneity will be assessed. Furthermore, we will investigate if indirect effects are moderated by different variables on participant- (e.g., age, sex/gender, symptom severity), study- (e.g., quality, studies evaluating the temporal ordering of changes in mediators and outcomes), and intervention-level (e.g., theoretical foundation, delivery type, guidance).

DISCUSSION

This systematic review and IPD-MA will generate comprehensive information on the differential strength of mediators and associated therapeutic processes in digital interventions for depression. The findings might contribute to the empirically-informed advancement of psychotherapeutic interventions, leading to more effective interventions and improved treatment outcomes in digital mental health. Besides, with our novel approach to mediation analyses with IPD-MA, we might also add to a methodological progression of evidence-synthesis in psychotherapy process research.

STUDY REGISTRATION WITH OPEN SCIENCE FRAMEWORK OSF

https://osf.io/md7pq/.