Using Data Mining and Time Series to Investigate ME and CFS Naming Preferences

Abstract:

There have been numerous iterations of naming convention specified for Myalgic Encephalomyelitis (ME) and Chronic Fatigue Syndrome (CFS). As health care turns to “big data” analytics to gain insights, the Google Trends database was mined to ascertain worldwide trends of public interest in several ME- and CFS-related search categories between 2004 and 2019.
Time series analysis revealed that though “Chronic Fatigue Syndrome” remains the predominant search category in the ME and CFS field, the interest index declined at a rate of 2.77 per month during the 15-year study period. In the same time period, the interest index in “ME/CFS Hybrid” terms increased at a rate of 3.20 per month. Potential causal mechanisms for these trends and implications for patient sentiment analysis are discussed.
Source: Bhatia, S., & Jason, L. A. (2023). Using Data Mining and Time Series to Investigate ME and CFS Naming Preferences. Journal of Disability Policy Studies0(0). https://doi.org/10.1177/10442073231154027

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