Scoping review on natural language processing applications in counselling and psychotherapy

Area of Science:

• Psychology
• Computer Science
• Computational Linguistics

Background:

• Natural Language Processing (NLP) has advanced significantly, enabling sophisticated text analysis.
• Applications of NLP in counselling and psychotherapy have emerged as a growing research area.
• Understanding the trends, advancements, and limitations of NLP in this field is crucial.

Purpose of the Study:

• To conduct a scoping review of NLP applications in counselling and psychotherapy from 1990 to 2021.
• To identify key trends, technological advancements, and challenges in the field.
• To assess the extent to which studies address critical issues like bias and generalizability.

Main Methods:

• Systematic literature search for NLP applications in counselling and psychotherapy.
• Scoping review methodology to synthesize findings from 41 included papers.
• Categorization of studies based on primary purposes: automated coding, outcome prediction, session monitoring, and language pattern investigation.

Main Results:

• A notable increase in NLP applications within psychotherapy research over the review period.
• A significant trend towards employing advanced machine learning methods, especially neural networks.
• A concerning finding: only one-third of the reviewed studies addressed bias and generalizability concerns.

Conclusions:

• NLP offers powerful tools for analysing therapeutic discourse, with increasing adoption of advanced AI.
• There is a critical need for greater attention to bias, generalizability, and validity in NLP research for mental health.
• Future research should prioritize robust methodologies that ensure equitable and reliable NLP applications in counselling and psychotherapy.