Depression, anxiety, and burnout in academia: topic modeling of PubMed abstracts.

ABSTRACT: The problem of mental health in academia is increasingly discussed in literature, and to extract meaningful insights from the growing amount of scientific publications, text mining approaches are used. In this study, BERTopic, an advanced method of topic modeling, was applied to abstracts of 2,846 PubMed articles on depression, anxiety, and burnout in academia published in years 1975-2023. BERTopic is a modular technique comprising a text embedding method, a dimensionality reduction procedure, a clustering algorithm, and a weighing scheme for topic representation. A model was selected based on the proportion of outliers, the topic interpretability considerations, topic coherence and topic diversity metrics, and the inevitable subjectivity of the criteria was discussed. The selected model w

SUBMITTER: Lezhnina O 

PROVIDER: S-EPMC10711630 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature