JMIR Publications

ABSTRACT

In traditional human psychotherapy, the therapeutic alliance is a fundamental factor describing the client-therapist relationship, mainly due to the strong evidence of its impact on treatment outcomes regardless of the theoretical orientation. More recently, advances in artificial intelligence and other technologies have led to the emergence of the concept of the digital therapeutic alliance, used to characterize the relationship between clients and AI-based therapeutic systems. Nonetheless, this approach replicates human dynamics and overlooks key differences between human therapists and digital agents. Prematurely translating the concept of alliance into the digital context fails to address issues such as the sycophantic tendencies in current systems and the inherent limitations of algorithmic interaction. We propose the Digital Therapeutic Nexus, a framework that recognizes these differences and provides a set of structured criteria for categorizing digital interactions into three progressive levels. This viewpoint argues that only at the highest level can parallels be drawn with the human therapeutic alliance, and stratifies the main risks associated with each nexus level. Transitioning from alliance to nexus offers a more precise conceptual basis for describing and evaluating digital therapeutic relationships, with implications for research, design, and the ethical development of AI-based mental health interventions.