To Örebro University

With the objective of increasing the magnitude of treatment effects in behavioral health, there is steadily growing interest in tailoring assessments and interventions to better match individual needs. This aligns with the central idea that behavior can be adequately understood by considering the unique characteristics of the individual and context. Thus, data collected at an individual level provides critical evidence that can be used to inform health care decisions, improve treatment, or refine theories. Yet, the majority of research in behavioral health is based on group-level analyses. Recent developments in the field of single-case experimental design (SCED) has provided new opportunities to utilize individual data. The present article provides a state-of-the art overview regarding key aspects of SCED, including a historical background to why and how SCED emerged, declined, and recently reemerged as well as methodological aspects such as design issues, challenges related to reliability and validity of repeated observations, innovations in visual and statistical analyses of individual data, strategies to deal with missing values, methodology to examine effect size, and approaches to summarize data from a large number of SCEDs using multilevel models and meta-analyses of replication data. Finally, the article discusses key concerns and actions needed to move the field forward.