Jacopo Ciaffi1, Riccardo Meliconi1,2, Maria Paola Landini3, Luana Mancarella1, Veronica Brusi1, Cesare Faldini2,4, Francesco Ursini1,2. 1. Medicine and Rheumatology Unit, IRCCS Istituto Ortopedico Rizzoli (IOR), 40136 Bologna, Italy. 2. Department of Biomedical and Neuromotor Science (DIBINEM), University of Bologna, 40125 Bologna, Italy. 3. Scientific Direction, IRCCS Istituto Ortopedico Rizzoli (IOR), 40136 Bologna, Italy. 4. 1st Orthopaedic and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli (IOR), 40136 Bologna, Italy.
Abstract
BACKGROUND: E-health tools have been used to assess the temporal variations of different health problems. The aim of our infodemiology study was to investigate the seasonal pattern of search volumes for back pain in Italy. METHODS: In Italian, back pain is indicated by the medical word "lombalgia". Using Google Trends, we selected the three search terms related to "lombalgia" with higher relative search volumes (RSV), (namely, "mal di schiena", "dolore alla schiena" and "dolore lombare"), representing the semantic preferences of users when performing web queries for back pain in Italy. Wikipedia page view statistics were used to identify the number of visits to the page "lombalgia". Strength and direction of secular trends were assessed using the Mann-Kendall test. Cosinor analysis was used to evaluate the potential seasonality of back pain-related RSV. RESULTS: We found a significant upward secular trend from 2005 to 2020 for search terms "mal di schiena" (τ = 0.734, p < 0.0001), "dolore alla schiena" (τ = 0.713, p < 0.0001) and "dolore lombare" (τ = 0.628, p < 0.0001). Cosinor analysis on Google Trends RSV showed a significant seasonality for the terms "mal di schiena" (pcos < 0.001), "dolore alla schiena" (pcos < 0.0001), "dolore lombare" (pcos < 0.0001) and "lombalgia" (pcos = 0.017). Cosinor analysis performed on views for the page "lombalgia" in Wikipedia confirmed a significant seasonality (pcos < 0.0001). Both analyses demonstrated a peak of interest in winter months and decrease in spring/summer. CONCLUSIONS: Our infodemiology approach revealed significant seasonal fluctuations in search queries for back pain in Italy, with peaking volumes during the coldest months of the year.
BACKGROUND: E-health tools have been used to assess the temporal variations of different health problems. The aim of our infodemiology study was to investigate the seasonal pattern of search volumes for back pain in Italy. METHODS: In Italian, back pain is indicated by the medical word "lombalgia". Using Google Trends, we selected the three search terms related to "lombalgia" with higher relative search volumes (RSV), (namely, "mal di schiena", "dolore alla schiena" and "dolore lombare"), representing the semantic preferences of users when performing web queries for back pain in Italy. Wikipedia page view statistics were used to identify the number of visits to the page "lombalgia". Strength and direction of secular trends were assessed using the Mann-Kendall test. Cosinor analysis was used to evaluate the potential seasonality of back pain-related RSV. RESULTS: We found a significant upward secular trend from 2005 to 2020 for search terms "mal di schiena" (τ = 0.734, p < 0.0001), "dolore alla schiena" (τ = 0.713, p < 0.0001) and "dolore lombare" (τ = 0.628, p < 0.0001). Cosinor analysis on Google Trends RSV showed a significant seasonality for the terms "mal di schiena" (pcos < 0.001), "dolore alla schiena" (pcos < 0.0001), "dolore lombare" (pcos < 0.0001) and "lombalgia" (pcos = 0.017). Cosinor analysis performed on views for the page "lombalgia" in Wikipedia confirmed a significant seasonality (pcos < 0.0001). Both analyses demonstrated a peak of interest in winter months and decrease in spring/summer. CONCLUSIONS: Our infodemiology approach revealed significant seasonal fluctuations in search queries for back pain in Italy, with peaking volumes during the coldest months of the year.
Entities:
Keywords:
Google Trends; Wikipedia; back pain; infodemiology; seasonality
Authors: Frank J Penedo; Laura B Oswald; Joshua P Kronenfeld; Sofia F Garcia; David Cella; Betina Yanez Journal: Lancet Oncol Date: 2020-05 Impact factor: 41.316