Depression in times of a pandemic – the impact of COVID-19 on the lay discourses of e-mental health communities

ABSTRACT

The article aims at exploring the impact of the COVID-19 pandemic on the lay discourses of depression emerging in online mental health forums. The narrative framing of depression plays a central role not only because it affects the instrumental strategies of depressed people (e.g., preferred therapy), but also because it is a constitutive element of the identity of depressed people, thus affects the process of recovery itself. COVID-19 had a serious impact on people living with mental disorders (especially depression and anxiety), thus our research aimed at mapping the consequences of these transformations on a discursive level. A textual dataset of English language online health forums was collected (n = 339,550 publicly available entries posted between 15 February 2016 and 31 December 2020). Structural topic modelling was used to explore the various discursive patterns characterizing the pre-pandemic and pandemic era. Our results show that the pandemic did not take over the discursive space of depression forums, yet it transformed many aspects of it: a new horizon of critique opened up; the biomedical authority was reinforced; the ego-centric perspectives were refined; the previously unquestionable discursive frames become fragmented; and the horizon of emergency overshadowed the previous risk perspective.

KEYWORDS:

• COVID-19
• e-mental health
• depression
• online forum
• structural topic model
• natural language processing

Acknowledgements

The authors would like to thank Fanni Máté for her contribution to data collection.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

The data are not publicly available due to confidentiality reasons but the preprocessed data are available from the corresponding author on reasonable request.

Notes

1 FREX score is a weighted average between word frequency in a given topic and the degree to which the word appears only in the given topic (i.e. exclusivity) (Bischof & Airoldi, 2012). We used STM’s sageLabels function to obtain the score.

Additional information

Funding

This publication has been supported by the Ministry of Innovation and Technology, and the National Research, Development and Innovation Office through the project NLP-08, titled "National Laboratory for Social Innovation”. The founder had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Notes on contributors

Renáta Németh

Renáta Németh is professor of Sociology at ELTE Eötvös Loránd University, Budapest. She is co-founder and co-leader of ELTE Research Center for Computational Social Science. Her research focuses on social research methods, natural language processing and causality in social siences.

Domonkos Sik

Domonkos Sik is associate professor of Sociology at ELTE Eötvös Loránd University (Budapest), alumni of CEU-IAS (Budapest-Vienna). His research deals with various topics in critical theory including political culture and mental disorders in late modernity. His work has appeared in such venues as The Sociological Review, European Journal of Social Theory, Journal of Mental Health, Thesis Eleven, Continental Philosophy Review and Culture, Medicine, and Psychiatry. He has written several monographs including Radicalism and indifference (Peter Lang 2016) and Empty suffering (Routledge 2021).

Bendegúz Zaboretzky

Bendegúz Zaboretzky holds a Master’s degree in Survey Statistics and Data Analytics. He is a visiting researcher at ELTE Research Center for Computational Social Science (RC2S2). He takes part in different projects using natural language processing and topic modelling where his general responsibility is building a sound methodological background while experimenting with new processes and ideas.

Eszter Katona

Eszter Katona is an assistant lecturer at ELTE Eötvös Loránd University, Budapest. She is a researcher at ELTE Research Center for Computational Social Science. Her research interests include Natural Language Processing, Data Visualization and Research Methodology.