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The effectiveness of interventions for internalizing disorders in children and adolescents was studied using a review and meta-analysis of published single-case research. Databases and other resources were searched for quantitative single-case studies in youth with anxiety, depressive, and posttraumatic stress disorders. Raw data from individual cases were aggregated and analyzed by means of multilevel meta-analytic models. Outcome variables were symptom severity assessed across baseline and treatment phases of the studies, and diagnostic status at post- and follow-up treatment. Single-case studies were rated for quality. We identified 71 studies including 321 cases (Mage = 10.66 years; 55% female). The mean quality of the studies was rated as below average, although there were considerable differences between the studies. Overall, positive within-person changes during the treatment phase in comparison to the baseline phase were found. In addition, positive changes in the diagnostic status were observed at post- and follow-up treatment. Yet high variability in treatment effects was found between cases and studies. This meta-analysis harvests the knowledge from published single-case research in youth-internalizing disorders and illustrates how within-person information from single-case studies can be summarized to explore the generalizability of the results from this type of research. The results emphasize the importance of keeping account of individual variability in providing and investigating youth interventions.

Introduction: In randomized trials, mostly group-level treatment effects of repeated cross-sectional measures are analyzed. However, substantial heterogeneity regarding individual symptom profiles and variability of treatment effects are often neglected, particularly over the long-term course.Objective: Ratings of depression severity over 104 weeks of follow-up after yearlong acute and continuation treatment with the Cognitive Behavioral Analysis System of Psychotherapy (CBASP) or Supportive Psychotherapy (SP) were investigated to cluster intraindividual trajectories and identify risk and protective factors. Methods: Longitudinal cluster analysis and multinomial logistic regression analysis were conducted to group intraindividual long-term trajectories from one of the largest psychotherapy trials in early-onset chronic depression.Results: Two-year post-treatment trajectories of N=176 patients with early-onset chronic depression were clustered into four groups. Only 16.5% of patients remitted (Cluster 1), while the majority continued to experience subthreshold (35.8% Cluster 2) or major depressive symptoms (47.7% Cluster 3-4). Patients previously treated with the CBASP had a 45% lower risk of experiencing major depressive symptoms (Cluster 3) than patients in the SP group (RR=0.55, 95% CI=0.31 to 0.97, p=.03). Further treatment in the health care system during follow-up, especially psychological outpatient treatment, reduced depression severity. Comorbid disorders or childhood emotional/physical abuse had detrimental effects.Conclusion: Despite significant effects in favor of acute treatment with CBASP compared to SP, the majority of patients experienced subthreshold or major depressive symptoms over two years of follow-up. This calls for a long-term perspective with innovative treatment approaches such as the sequential model or modular psychotherapy.

Background: The network approach to psychopathology, which assesses associations between individual symptoms, has recently been applied to evaluate treatments for mental disorders. While various options for conducting a network analysis in intervention research exist, no structured guidelines have been established yet. To gain an overview and evaluate the potential of different analytic options, we conducted a systematic review on these studies. Methods: We systematically searched the literature with combining terms on network analysis, mental health problems, and intervention studies. Studies were included if they constructed a symptom network, analysed data that was collected before, during or after a treatment for mental disorders, and yielded information about the treatment effect. Information on sample characteristics, the intervention, the research design, the estimated networks, the statistical analyses, and open science practices were extracted. Results: Across the 56 included studies, network analyses varied widely. About half of the studies estimated cross-sectional networks without a treatment node, e.g., for different treatment groups separately or for a single group before, and after treatment. About 20% of the studies analysed cross-sectional networks including a treatment node and a third of the studies estimated longitudinal networks. Studies differed on how networks were estimated, which network parameters were calculated, and which statistical tests were applied. Conclusion: This review highlighted that many different analytic options exist when applying the network approach to intervention research. As the potential of the network approach depends on the applied methodologies, the analytic choices need to be further investigated and structured guidelines need to be developed.