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. 2023 Apr 7;18(4):e0284091.
doi: 10.1371/journal.pone.0284091. eCollection 2023.

Increasing digitalization is associated with anxiety and depression: A Google Ngram analysis

Gisbert Wilhelm Teepe  1 , Edda Magareta Glase  2 , Ulf-Dietrich Reips  3
Affiliations

Increasing digitalization is associated with anxiety and depression: A Google Ngram analysis

Gisbert Wilhelm Teepe et al. PLoS One. .

Abstract

The prevalence of anxiety disorders and depression are rising worldwide. Studies investigating risk factors on a societal level leading to these rises are so far limited to social-economic status, social capital, and unemployment, while most such studies rely on self-reports to investigate these factors. Therefore, our study aims to evaluate the impact of an additional factor on a societal level, namely digitalization, by using a linguistic big data approach. We extend related work by using the Google Books Ngram Viewer (Google Ngram) to retrieve and adjust word frequencies from a large corpus of books (8 million books or 6 percent of all books ever published) and to subsequently investigate word changes in terms of anxiety disorders, depression, and digitalization. Our analyses comprise and compare data from six languages, British English, German, Spanish, Russian, French, and Italian. We also retrieved word frequencies for the control construct "religion". Our results show an increase in word frequency for anxiety, depression, and digitalization over the last 50 years (r = .79 to .89, p < .001), a significant correlation between the frequency of anxiety and depression words (r = .98, p < .001), a significant correlation between the frequency of anxiety and digitalization words (r = .81, p < .001), and a significant correlation between the frequency of depression and anxiety words (r = .81, p < .001). For the control construct religion, we found no significant correlations for word frequency over the last 50 years and no significant correlation between the frequency of anxiety and depression words. Our results showed a negative correlation between the frequency of depression and religion words (r = -.25, p < .05). We also improved the method by excluding terms with double meanings detected by 73 independent native speakers. Implications for future research and professional and clinical implications of these findings are discussed.

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Conflict of interest statement

I have read the journal’s policy and the authors of this manuscript have the following competing interests: GWT is affiliated with the Centre for Digital Health Interventions (www.c4dhi.org), a joint initiative of the Department of Management, Technology, and Economics at ETH Zurich and the Institute of Technology Management at the University of St. Gallen, which is funded in part by the Swiss health insurer CSS. EMG and UDR do not declare any conflicts of interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. List-averaged word frequencies from 1970 until 2019 for each category and language.
Frequencies (in percent) are z-transformed, most common word controlled, and summed over all words.
Fig 2
Fig 2. Rolling mean word frequencies from 1970 until 2019 for each word by each category and language, considering five years.
See this image and copyright information in PMC

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