Keywords: Telepsychology, telemental health, NLP, NER, Topic Modeling, Text Mining, Covid-19, NMF
The Coronavirus pandemic has had a tremendous effect on all areas of life, perhaps the most salient being the rapid transition to remote life. This paper aims to understand how that shift has impacted academic work produced in the field of telepsychology. We used a variety of Natural Language Processing (NLP) techniques to explore keywords, named entities, topics, and more across articles published between 2016 and 2021. Furthermore, we compared the results for those articles published before 2020 and the outbreak of the COVID-19 Pandemic with those published during the pandemic in order to find the changes that have occurred as a result. We identified three major groups in the literature: 1. Implementation, barriers, and evidence-based treatment; 2. Training and ethics; and 3. Covid-19 and Stress related disorders. We also identified major shifts during the pandemic towards discussing stress and stress-related disorders and away from discussing depression and self-help technologies. This paper summarizes some of the existing research on telemental health and provides a model for systematically applying NLP to identify trends in literature.