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ERIC Number: EJ1465701
Record Type: Journal
Publication Date: 2024-Jun
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1044-2073
EISSN: EISSN-1538-4802
Available Date: 0000-00-00
Using Data Mining and Time Series to Investigate ME and CFS Naming Preferences
Shaun Bhatia1; Leonard A. Jason1
Journal of Disability Policy Studies, v35 n1 p65-72 2024
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.
SAGE Publications and Hammill Institute on Disabilities. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Authoring Institution: N/A
Grant or Contract Numbers: HD072208
Author Affiliations: 1DePaul University, Chicago, IL, USA