Across five decades, hundreds of randomized trials have tested psychological therapies for youth internalizing (anxiety, depression) and externalizing (misconduct, ADHD) disorders and problems. Since the last broad-based youth meta-analysis, in 1995, the number of trials has almost tripled, and data-analytic methods have been refined. We applied these methods to the expanded study pool (447 studies; 30,431 youths) synthesizing 50 years of findings and identifying implications for research and practice. We assessed overall effect size (ES) and moderator effects, using multilevel modeling to address ES dependency that is common, but typically not modeled in meta-analyses. Mean posttreatment ES was 0.46; the probability that a youth in the treatment condition would fare better than a youth in the control condition was 63%. Effects varied according to multiple moderators, including the problem targeted in treatment: mean ES at posttreatment was strongest for anxiety (0.61), weakest for depression (0.29), and nonsignificant for multi-problem treatment (0.15). ESs differed across control conditions, with "usual care" emerging as a potent comparison condition, and across informants, highlighting the need to obtain, and integrate, multiple perspectives on outcome.Effects of therapy type varied by informant; only youth-focused behavioral therapies (including CBT) showed similar and robust effects across youth, parent, and teacher reports.Therapy effects did not improve over the years. Effects did not differ for Caucasian versus minority samples, but more diverse samples are needed. The findings underscore the benefits of psychological treatments as well as the need for improved therapies and more representative, informative, and rigorous intervention science.Keywords: children, adolescents, youth, psychological therapy, treatment outcome, metaanalysis YOUTH PSYCHOLOGICAL THERAPY: FIVE DECADES OF RESEARCH What Five Decades of Research Tells Us about the Effects of Youth Psychological Therapy:A Multilevel Meta-Analysis and Implications for Science and Practice Mental health problems are both prevalent and disabling in children and adolescents (herein "youths"). At any one time, about one in six will meet criteria for a disorder, and at least one in three will have a disorder by age 16 (Costello, Mustillo, Erkanli, Keeler, & Angold, 2003). A recent Lancet report (Gore et al., 2011) ranked neuropsychiatric disorders as the most prominent cause of the global burden of disease in young people, expressed in "years lost because of disability" (p. 2093). For many of these conditions, psychological therapy has been identified as the primary resource, highlighted as a path to promoting and protecting youth mental health, and advocated in government policy documents (US Department of Health & Human Services, 2003; US Public Health Service, 2000;Weisz, Sandler, Durlak, & Anton, 2005). Indeed, psychological therapy is often recommended as the first-line treatment of choice for young people, even within the practice guidelin...

Objective: To complement standardized measurement of symptoms, we developed and tested an efficient strategy for identifying (before treatment) and repeatedly assessing (during treatment) the problems identified as most important by caregivers and youths in psychotherapy. Method: A total of 178 outpatient-referred youths, 7–13 years of age, and their caregivers separately identified the 3 problems of greatest concern to them at pretreatment and then rated the severity of those problems weekly during treatment. The Top Problems measure thus formed was evaluated for (a) whether it added to the information obtained through empirically derived standardized measures (e.g., the Child Behavior Checklist [CBCL; Achenbach & Rescorla, 2001] and the Youth Self-Report [YSR; Achenbach & Rescorla, 2001]) and (b) whether it met conventional psychometric standards. Results: The problems identified were significant and clinically relevant; most matched CBCL/YSR items while adding specificity. The top problems also complemented the information yield of the CBCL/YSR; for example, for 41% of caregivers and 79% of youths, the identified top problems did not correspond to any items of any narrowband scales in the clinical range. Evidence on test–retest reliability, convergent and discriminant validity, sensitivity to change, slope reliability, and the association of Top Problems slopes with standardized measure slopes supported the psychometric strength of the measure. Conclusions: The Top Problems measure appears to be a psychometrically sound, client-guided approach that complements empirically derived standardized assessment; the approach can help focus attention and treatment planning on the problems that youths and caregivers consider most important and can generate evidence on trajectories of change in those problems during treatment.

Decades of clinical psychological science have produced many evidence-based interventions that are now undergoing dissemination and implementation (DI), but with little guidance from a DI science that is just now taking shape. Charting a future for DI science and practice, and their complex relationship, will be complicated by significant challenges-the implementation cliff(treatment benefit drops when tested practices are taken to scale), low relevance of most clinical research to actual practice, and differing timetables and goals for DI practice versus research. To address the challenges, and prepare the next generation of psychologists, we propose: making intervention research look more like practice, solving the "too many EBPs" problem, addressing mismatches between interventions and their users, broadening our range of intervention delivery systems, sharpening outcome monitoring and feedback, incentivizing high-risk/high-gain innovations, designing new professional tracks for DI science, and synchronizing and linking the often-insular practice and science of DI.Keywords: dissemination, implementation, evidence-based practice Science and Practice of Dissemination and Implementation 3 An emerging challenge in clinical psychological science is the tension between rigorous testing of interventions-an ongoing task that is never really finished-and deploying those interventions within clinical practice settings. Moving too quickly from science to practice can make us marketers with products not yet ready for prime time. Moving too slowly can mean lost opportunities to take our work to scale and improve clinical care for those who need it. In this paper we focus on the tension between science and practice-whether the two are a cute couple or strange bedfellows-in the development and diffusion of interventions, and implications of the science-practice relationship for clinical training. Welcome to COI World.This science-practice tension is highlighted by the annual conflict-of-interest (COI) reports that are now routine for faculty in North American universities. In decades past, intervention science and practice were indeed a cute couple (with rather socialist leanings) in which scientists developed and tested treatment protocols and shared these openly for use by practitioners who wanted them. That openness has now given way to a more capitalist model in which these products are "IP," owned and marketed, often for income beyond the wildest dreams of prior generations in our field. Under these circumstances, a fair study with adverse findings regarding a treatment program can have major consequences-including loss of employment for those in the business of spreading the treatment, loss of income for the IP-holder and partners, and loss of image in the marketplace with concomitant loss of market share. The resulting pressure on scientists who develop marketable products can be significant, and the potential for conflict of interest is real-hence the need for COI reports. While this situation is not new ...

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Background Within the past decade, healthcare service and research priorities have shifted from evidence-based medicine to personalized medicine. In mental healthcare, a similar shift to personalized intervention may boost the effectiveness and clinical utility of empirically supported therapies (ESTs). Aims and Scope The emerging science of personalized intervention will need to encompass evidence-based methods for determining which problems to target and in which order, selecting treatments and deciding whether and how to combine them, and informing ongoing clinical decision-making through monitoring of treatment response throughout episodes of care. We review efforts to develop these methods, drawing primarily from psychotherapy research with youths. Then we propose strategies for building a science of personalized intervention in youth mental health. Findings The growing evidence base for personalizing interventions includes research on therapies adapted for specific subgroups; treatments targeting youths’ environments; modular therapies; sequential, multiple assignment, randomized trials; measurement feedback systems; meta-analyses comparing treatments for specific patient characteristics; data-mining decision trees; and individualized metrics. Conclusion The science of personalized intervention presents questions that can be addressed in several ways. First, to evaluate and organize personalized interventions, we propose modifying the system used to evaluate and organize ESTs. Second, to help personalizing research keep pace with practice needs, we propose exploiting existing randomized trial data to inform personalizing approaches, prioritizing the personalizing approaches likely to have the greatest impact, conducting more idiographic research, and studying tailoring strategies in usual care. Third, to encourage clinicians’ use of personalized intervention research to inform their practice, we propose expanding outlets for research summaries and case studies, developing heuristic frameworks that incorporate personalizing approaches into practice, and integrating personalizing approaches into service delivery systems. Finally, to build a richer understanding of how and why treatments work for particular individuals, we propose accelerating research to identify mediators within and across RCTs, to isolate mechanisms of change, and to inform the shift from diagnoses to psychopathological processes. This ambitious agenda for personalized intervention science, though challenging, could markedly alter the nature of mental health care and the benefit provided to youths and families.

With the development of empirically supported treatments over the decades, have youth psychotherapies grown stronger? To investigate, we examined changes over time in treatment effects for four frequently treated youth mental-health problems: anxiety, depression, attention-deficit hyperactivity disorder (ADHD), and conduct disorders. We used PubMed and PsycINFO to search for randomized controlled trials (RCTs) that were published between January 1960 and May 2017 involving youths between the ages of 4 and 18 years. We also searched reviews and meta-analyses of youth psychotherapy research, followed reference trails in the reports we identified, and obtained additional studies identified by therapy researchers whom we contacted. We identified 453 RCTs (31,933 participants) spanning 53 years (1963–2016). Effect sizes for the problem-relevant outcome measures were synthesized via multilevel meta-analysis. We tracked temporal trends for each problem domain and then examined multiple study characteristics that might moderate those trends. Mean effect size increased nonsignificantly for anxiety, decreased nonsignificantly for ADHD, and decreased significantly for depression and conduct problems. Moderator analyses involving multiple study subgroups showed only a few exceptions to these surprising patterns. The findings suggest that new approaches to treatment design and intervention science may be needed, especially for depression and conduct problems. We suggest intensifying the search for mechanisms of change, making treatments more transdiagnostic and personalizable, embedding treatments within youth ecosystems, adapting treatments to the social and technological changes that alter youth dysfunction and treatment needs, and resisting old habits that can make treatments unduly skeuomorphic.

Objective: Youth depression is a debilitating condition that constitutes a major public health concern. A 2006 meta-analysis found modest benefits for psychotherapy vs. control. Has 13 more years of research improved that picture? We sought to find out. Method:We searched PubMed, PsychINFO, and Dissertation Abstracts International for 1960-2017, identifying 655 randomized, English-language psychotherapy trials for ages 4-18 years. Of these, 55 assessed psychotherapy versus control for youth depression with outcome measures administered to both treatment and control conditions at post (k=53) and/or follow-up (k=32). Twelve study and outcome characteristics were extracted, and effect sizes were calculated for all psychotherapy vs. control comparisons. Using a threelevel random-effects model, we obtained an overall estimate of the psychotherapy vs. control difference while accounting for the dependency among effect sizes. We then fitted a three-level mixed-effects model to identify moderators that might explain variation in effect size within and between studies.Results: Overall effect size (g) was 0.36 at posttreatment, 0.21 at follow-up (averaging 42 weeks after post-treatment). Three moderator effects were identified: effects were significantly larger for Interpersonal Therapy than CBT, for youth self-reported outcomes than parent-reports, and for comparisons with inactive control conditions (e.g., waitlist) than active controls (e.g., usual care). Effects showed specificity, with significantly smaller effects for anxiety and externalizing behavior outcomes than for depression measures. Conclusion:Youth depression psychotherapy effects are modest, with no significant change over the past 13 years. The findings highlight the need for treatment development Running Head: PSYCHOTHERAPY FOR YOUTH DEPRESSION 3 and research to improve both immediate and longer-term benefits.

Most youth psychotherapy research involves conditions quite unlike the clinical practice it is designed to strengthen. Most studies have not tested interventions with clinically referred youths and practicing clinicians in clinical care settings, nor have they tested whether new treatments produce better outcomes than usual practice. Limited exposure to real-world conditions and questions may partially explain why empirically supported treatments show such modest effects when tested under more representative conditions, against usual care. Our deployment-focused model calls for intervention development and testing with the kinds of participants (e.g., clients and clinicians) and in the contexts (e.g., clinics) for which the interventions are ultimately intended, and for randomized comparisons to usual clinical care. Research with the Child STEPs (system and treatment enhancement projects) treatment approach illustrates the methods and potential benefits of the deployment-focused model. Findings supporting Child STEPs are but one part of a rich research matrix needed to shrink the gap between intervention research and clinical practice.