Statistical process control for real-time monitoring in clinical psychology: State of the art and future research agenda

Mental disorders place a substantial burden on individuals and society, underscoring the need for preventive interventions that can be delivered to the right person at the right time. This, in turn, requires real-time monitoring of person-specific indicators of risk for mental disorders and identifying when risk is increasing. Statistical process control (SPC) procedures, originally developed for monitoring industrial processes, offer a promising framework for addressing this need, allowing for the real-time detection of meaningful person-specific changes. Although SPC has only recently been introduced in clinical psychology, initial empirical applications demonstrate its potential for forecasting changes in mental health. In this perspective, we introduce the main concepts of SPC and describe two prominent SPC procedures (Shewhart and EWMA), outlining when each is most appropriate to use and summarizing current empirical findings in clinical psychology. We also discuss how SPC procedures compare to other change-detection methods. Finally, we discuss recent methodological advances in the use of SPC within clinical psychology and propose a research agenda that identifies key challenges for future work.