Computational Methods in Psychotherapy: A Scoping Review.

Area of Science:

• Psychology
• Computational Science
• Psychotherapy Research

Background:

• Psychotherapeutic encounters are complex systems requiring methods beyond traditional linear approaches.
• Probabilistic and unpredictable phenomena in therapy necessitate advanced analytical tools.

Purpose of the Study:

• To conduct a scoping review of computational methods in psychotherapy research.
• To identify new developments and enhance understanding of psychotherapeutic and human interactions.
• To systematize empirical literature on computational methods in psychotherapy.

Main Methods:

• Scoping review of online databases for papers published between 2011 and 2022.
• Selection of 18 publications based on predefined criteria.
• Categorization of studies by computational methods used, with a focus on combined computational and experimental approaches.

Main Results:

• The majority of studies (44.4%) utilized combined computational and experimental methods.
• All studies confirmed the utility of predictive and learning models for complex psychological and psychotherapeutic variables.
• Measured data was collected in all but one of the reviewed studies.

Conclusions:

• Computational methods, particularly predictive and learning models, are highly useful in psychotherapy research.
• A careful selection of reference methods and standards is crucial for advancing research in this field.
• This review provides clinicians with an overview of the utility and applications of computational methods in psychotherapy, identifying future research opportunities.