Psychotherapists’ Acceptance of Telepsychotherapy: A Machine Learning Approach

Abstract

Introduction: Therapists' forced transition to provide psychotherapy remotely during the COVID-19 pandemic offers a unique opportunity to examine therapists' views and challenges with teletherapy. Objectives: We aimed to develop predictive models of three aspects of psychotherapists' acceptance of teletherapy during the COVID-19 pandemic; attitudes towards teletherapy, concerns about using teletherapy, and intention to use it in the future. Methods: In an international survey, therapists (N = 795) completed a survey about their experiences during the pandemic, including quality of therapeutic relationship, professional self-doubt, vicarious trauma, and telepsychotherapy acceptance. Regression decision trees machine learning analyses were used to build prediction models for each aspects of telepsychotherapy acceptance. Results: Attitudes toward telepsychotherapy were most positive for therapists who reported neutral or strong online working alliance, especially if they experienced little professional self-doubt and were younger than 40 years old. Therapists who were most concerned about telepsychotherapy, were those who reported higher levels of professional self-doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance were the least likely to use telepsychotherapy in the future. Conclusions: Therapists' professional self-doubt and the quality of their working alliance with their telepsychotherapy patients appear to be the most pertinent factors associated with therapists' acceptance of telepsychotherapy during COVID-19, and should be addressed in future training and research.