How Idiographic Methodologies Can Move the Clinical-Science Field Forward to Integrate Personalized Treatment Into Everyday Clinical Care and Improve Treatment Outcomes

Abstract

The research–practice gap refers to the fact that most evidence-based treatments created by researchers are not used in routine clinical care, which affects real-world treatment outcomes negatively. One key reason that evidence-based care is not used more frequently is its nonpersonalized format. For example, most evidence-based treatments are based on averages and are limited in addressing comorbidity, heterogeneity, and the needs of clients with minoritized identities. These limitations reduce therapist uptake of evidence-based treatment at large. As a result, most patients seeking treatment in community settings do not receive evidence-based care, which could more quickly and effectively reduce mental-health suffering. Furthermore, even clinicians who want to engage in evidence-based practice must still rely on their clinical judgment in decision-making when treatments fail to address client-specific needs. This reliance on decision-making can influence outcomes negatively. We propose that idiographic (i.e., one-person; N = 1) methodologies (data analysis of one person’s data) combined with digital mental-health technology could help reduce the research–practice gap and improve treatment outcomes. In this article, we outline the many issues contributing to these problems and how idiographic methods of personalization can address these issues. We provide an overview of idiographic methodologies and examples of how to use these methods to personalize existing evidence-based treatments with patients. Finally, we conclude with recommendations for future research and movement within the field that is needed to propel this type of personalization into routine clinical care to reduce the research–practice gap and improve treatment outcomes broadly.