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A Fresh Perspective on Examining Population Emotional Well-Being Trends by Internet Search Engine: An Emerging Composite Anxiety and Depression Index

Author

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  • Yu Wang

    (Center for Applied Statistics, Renmin University of China, Beijing 100872, China
    School of Statistics, Renmin University of China, Beijing 100872, China
    These authors contributed equally to this work.)

  • Heming Deng

    (School of Statistics, Renmin University of China, Beijing 100872, China
    These authors contributed equally to this work.)

  • Sunan Gao

    (School of Statistics, Renmin University of China, Beijing 100872, China)

  • Tongxu Li

    (School of Statistics, Renmin University of China, Beijing 100872, China)

  • Feifei Wang

    (Center for Applied Statistics, Renmin University of China, Beijing 100872, China
    School of Statistics, Renmin University of China, Beijing 100872, China)

Abstract

Traditional assessments of anxiety and depression face challenges and difficulties when it comes to understanding trends in-group psychological characteristics. As people become more accustomed to expressing their opinions online, location-based online media and cutting-edge algorithms offer new opportunities to identify associations between group sentiment and economic- or healthcare-related variables. Our research provides a novel approach to analyzing emotional well-being trends in a population by focusing on retrieving online information. We used emotionally enriched texts on social media to build the Public Opinion Dictionary (POD). Then, combining POD with the word vector model and search trend, we developed the Composite Anxiety and Depression Index (CADI), which can reflect the mental health level of a region during a specific time period. We utilized the representative external data by CHARLS to validate the effectiveness of CADI, indicating that CADI can serve as a representative indicator of the prevalence of mental disorders. Regression and subgroup analysis are employed to further elucidate the association between public mental health (measured by CADI) with economic development and medical burden. The results of comprehensive regression analysis show that the Import–Export index (−16.272, p < 0.001) and average cost of patients (4.412, p < 0.001) were significantly negatively associated with the CADI, and the sub-models stratificated by GDP showed the same situation. Disposable income (−28.389, p < 0.001) became significant in the subgroup with lower GDP, while the rate of unemployment (2.399, p < 0.001) became significant in the higher subgroup. Our findings suggest that an unfavorable economic development or unbearable medical burden will increase the negative mental health of the public, which was consistent across both the full and subgroup models.

Suggested Citation

  • Yu Wang & Heming Deng & Sunan Gao & Tongxu Li & Feifei Wang, 2024. "A Fresh Perspective on Examining Population Emotional Well-Being Trends by Internet Search Engine: An Emerging Composite Anxiety and Depression Index," IJERPH, MDPI, vol. 21(2), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:21:y:2024:i:2:p:202-:d:1336514
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    References listed on IDEAS

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