Artificial intelligence-based psychotherapy: focusing on common psychotherapeutic factors

Abstract

Artificial intelligence-based psychotherapy applications have been evolving rapidly in recent years. They seem to offer solutions to a complex world with enormous mental health needs. Easy access, immediacy and low cost are their enduring advantages, while anonymity attracts people who are isolated by the stigma of mental illness. Artificial intelligence-based psychotherapy applications borrow and incorporate elements of the already proven common psychotherapeutic factors, as described in the so-called ‘contextual model’. As decades of practice have shown, these ‘common factors’ seem to prevail in every type of in-person psychotherapy. They are the key elements of their successful outcome and the main reason for the lack of superiority of one type of psychotherapy over another. A key area here is therapeutic alliance, characterized by the therapist's empathy, the patient's expectations, and the shared therapeutic goals. Could artificial intelligence design opportunities so that these factors become even more useful in AI psychotherapy? Improvement in the development of an empathetic therapeutic relationship environment, based on the ‘theory of common factors’, are expected to facilitate the adaptation of interventions and further increase the reliability and effectiveness of AI psychotherapy.