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. Disclosure No significant relationships.

Keywords

• Covid-19
• Telepsychotherapy
• attitudes
• machine learning