ABSTRACT
Psychotherapy has been proven to be effective on average, though patients respond very differently to treatment. Understanding which characteristics are associated with treatment effect heterogeneity can help to customize therapy to the individual patient. In this tutorial, we describe different meta-learners, which are flexible algorithms that can be used to estimate personalized treatment effects. More specifically, meta-learners decompose treatment effect estimation into multiple prediction tasks, each of which can be solved by any machine learning model. We begin by reviewing necessary assumptions for interpreting the estimated treatment effects as causal, and then give an overview over key concepts of machine learning. Throughout the article, we use an illustrative data example to show how the different meta-learners can be implemented in R. We also point out how current popular practices in psychotherapy research fit into the meta-learning framework. Finally, we show how heterogeneous treatment effects can be analyzed, and point out some challenges in the implementation of meta-learners.
ABSTRACT
BACKGROUND: Many studies display promising results for interventions that are based on Applied Behavior Analysis (ABA) in the treatment of autism spectrum disorder (ASD). METHODS: This meta-analysis assessed the effects of such treatments on developmental outcomes in children with ASD and on parental stress based on 11 studies with 632 participants. RESULTS: Compared to treatment as usual, minimal or no treatment, comprehensive ABA-based interventions showed medium effects for intellectual functioning (standardized mean difference SMD = 0.51, 95% CI [0.09; 0.92]) and adaptive behavior (SMD = 0.37, 95% CI [0.03; 0.70]). Language abilities, symptom severity or parental stress did not improve beyond the improvement in control groups. Moderator analyses indicate that language abilities at intake could influence the effect sizes and the influence of treatment intensity might decrease with older age. CONCLUSIONS: Practical implications and limitations are discussed.
