Talking about Health: A Topic Analysis of Narratives from Individuals with Schizophrenia and Other Serious Mental Illnesses

Abstract

Individuals with schizophrenia have higher mortality and shorter lifespans. There are a multitude of factors which create these conditions, but one aspect is worse physical health, particularly cardiovascular and metabolic health. Many interventions to improve the health of individuals with schizophrenia have been created, but on the whole, there has been limited effectiveness in improving quality of life or lifespan. One potential new avenue for inquiry involves a more patient-centric perspective; understanding aspects of physical health most important, and potentially most amenable to change, for individuals based on their life narratives. This study used topic modeling, a type of Natural Language Processing (NLP) on unstructured speech samples from individuals (n = 366) with serious mental illness, primarily schizophrenia, in order to extract topics. Speech samples were drawn from three studies collected over a decade in two geographically distinct regions of the United States. Several health-related topics emerged, primarily centered around food, living situation, and lifestyle (e.g., routine, hobbies). The implications of these findings for how individuals with serious mental illness and schizophrenia think about their health, and what may be most effective for future health promotion policies and interventions, are discussed.

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

“…This method was applied in medicine (Oveh et al, 2022 ), quality management (Sánchez-Franco et al, 2023 ), environmental, social, and governance research (Lee et al, 2023 ), and other areas. In mental health research, BERTopic was applied, for instance, by Cowan et al ( 2022 ) to analyse unstructured speech samples from individuals with serious mental illness, primarily schizophrenia. BERTopic compares favorably with LDA (de Groot et al, 2022 ; Kukushkin et al, 2022 ); with Top2Vec and NMF (Egger and Yu, 2022 ); and with Gibbs Sampling Dirichlet Multinomial Mixture Model (Udupa et al, 2022 ).…”