| Literature DB >> 34920710 |
Romain Lan1, Fabrice Campana2, Delphine Tardivo3, Jean-Hugues Catherine4, Jean-Noel Vergnes5,6, Mehdi Hadj-Saïd7.
Abstract
BACKGROUND: Tobacco and alcohol are the main risk factors for oral squamous cell carcinoma, the low survival rate of which is a public health problem. European-wide health policies (a prevention campaign, tobacco packaging) have been put in place to inform the population of the risks associated with consumption. Due to the increase in smoking among women, the incidence of this disease remains high. The identification of internet research data on the population could help to measure the impact of and better position these preventive measures. The objective was to analyze a potential temporal association between public health programs and interest in oral cancers on the internet in the European Union (EU).Entities:
Keywords: Bibliometrics; Epidemiology; Head and neck neoplasms; Health communication; Internet; Mass media; Mass screening; Oral cancer; Prevention and control
Mesh:
Year: 2021 PMID: 34920710 PMCID: PMC8679572 DOI: 10.1186/s12903-021-02022-z
Source DB: PubMed Journal: BMC Oral Health ISSN: 1472-6831 Impact factor: 2.757
Fig. 1Evolution of RSV over time (2004–2018) for search terms in the countries included. The linear regression curves have the equation: lip cancer (y = 0.0074x + 11.007; R2 = 0.0112), tongue cancer (y = 0.0223x + 15.012; R2 = 0.1011), cancer gums (y = 0.0109x + 11.362; R2 = 0.0127) and oral cancer (y = 0.0225x + 12.795; R2 = 0.08
Visits of the Wikipedia pages on oral cancers in different languages, Descriptive statistics (July 2015–September 2018)
| Language | Page visits (2015–2018) | Monthly mean | Monthly median | Standard deviation | Variance | Range | Minimum | Maximum | |
|---|---|---|---|---|---|---|---|---|---|
| 1 | English | 966,625 | 24,785.25 | 24,120 | 3111 | 9,678,349.72 | 12,161 | 18,894 | 31,055 |
| 2 | German | 333,502 | 8551.33 | 8694 | 1851.90 | 3,429,543.54 | 3769 | 5206 | 12,739 |
| 3 | Italian | 147,616 | 3785.02 | 3767 | 981.37 | 963,085.39 | 3769 | 2145 | 5914 |
| 4 | French | 77,300 | 1982.05 | 1628 | 1170.44 | 1,369,946.89 | 6098 | 936 | 7034 |
| 5 | Dutch | 55,216 | 1415.79 | 1349 | 280.36 | 78,601.69 | 1140 | 838 | 1978 |
| 6 | Polish | 50,757 | 1301.46 | 1298 | 274.76 | 75,493.20 | 1295 | 799 | 2094 |
| 7 | Portuguese | 39,018 | 1000.46 | 1001 | 297.19 | 88,323.83 | 1380 | 477 | 1857 |
| 8 | Slovenian | 14,180 | 363.59 | 367 | 67.99 | 4622.62 | 307 | 257 | 564 |
| 9 | Finnish | 11,080 | 284.10 | 279 | 74.65 | 5572.30 | 316 | 167 | 483 |
Fig. 2Evolution of the number of consultations of the 9 Wikipedia pages concerning oral cancers included according to time (2015–2018). The equation for the linear regression curve is: y = − 0.0216x + 994.45; R2 = 0.5083
Fig. 3Evolution of the number of visits to Wikipedia pages over time (2015–2018) for search terms in the countries included. The linear regression curves have the following equation: English (y = − 4.167x + 202,988; R2 = 0.2161), German (y = − 3.8263x + 172,186; R2 = 0.5141), Italian (y = − 1, 9807x + 88,489; R2 = 0.4906)
Fig. 4Evolution of the monthly number of articles published in the written press and the media in Europe as a function of time (2004–2018). The linear regression curves have the following equation: English (y = 0.0325x + 1.5496; R2 = 0.1793), French (y = − 0.0006x + 4.2038; R2 = 0.0002), German ( y = 0.0047x + 1.7921; R2 = 0.0239)
Influence of public health policies on Google © and Wikipedia searches for oral cancers and in press articles on the subject in Europe
| Country or language | Monthly mean | Mean before the 2014/40/EU directive | Mean before health warnings (countries having adopted them before the 2014/40/EU directive) | Mean before the introduction of a national campaign | Mean after the 2014/40/EU directive | Mean after health warnings (countries having adopted them before the 2014/40/EU directive) | Mean during MSC | Mean during a national campaign | |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Germany | 25.45 | 24.80 | – | – | 28.21 | – | 26.38 | – |
| 1bis | Germany (for the isolated term “Mundkrebs”) | 23.21 | 21.68 | – | – | – | 28.3 | – | |
| 2 | Austria | 15.40 | 15.49 | – | – | 15.06 | – | 12.21 | – |
| 3 | Bulgaria | 9.35 | 9.19 | – | – | 9.99 | – | 9.33 | – |
| 3bis | Bulgaria (for the isolated term “Paк Ha Гъpдaтa”) | 0.98 | 0.85 | – | – | – | 1.66 | – | |
| 4 | Croatia | 11.50 | 12.03 | – | – | 9.26 | – | 7.25 | – |
| 5 | Denmark | 21.08 | 18.24 | – | – | – | 32.50 | – | |
| 6 | Estonia | 3.00 | 3.09 | – | – | 2.62 | – | 0.00 | – |
| 7 | Finland | 10.01 | 7.28 | – | – | – | 12.33 | – | |
| 8 | Ireland | 9.12 | 8.48 | – | 6.87 | 11.82 | – | 10.4 p = 0.03 | |
| 9 | Latvia | 3.60 | 3.24 | – | – | 5.10 | – | 3.50 | – |
| 10 | Lithuania | 4.66 | 3.92 | – | – | 7.79 | – | 8.33 | – |
| 11 | Luxembourg | 15.34 | 14.82 | – | – | 17.55 | – | 15.44 | – |
| 12 | Netherlands | 16.52 | 16.89 | – | – | 14.94 | – | 10.50 | – |
| 13 | Poland | 12.51 | 12.43 | – | – | 12.84 | – | 8.00 | – |
| 14 | Czech Republic | 4.16 | 4.15 | – | 4.20 | – | 2.54 | ||
| 14bis | Czech Republic (for the isolated term “Rakovina Úst”) | 0.37 | 0.27 | – | – | 0.79 | – | 0.16 | – |
| 15 | Slovakia | 10.07 | 9.48 | – | – | 12.59 | – | 9.83 | – |
| 16 | Slovenia | 1.63 | 1.60 | – | – | 1.79 | – | 2.67 | – |
| 17 | Belgium | 15.84 | 15.57 | 9.99 | – | 17.00 | 16.73 | 15.33 | – |
| 17bis | Wallonia (keywords in French isolated) | 27.5 | 26.95 | 12.25 | – | 29.82 | 27.83 | – | |
| 18 | Spain | 30.66 | 30.17 | 27.57 | – | 32.74 | 30.67 | – | |
| 19 | France | 16.03 | 15.32 | 14.51 | – | 17.28 | – | ||
| 20 | United Kingdom | 24.82 | 23.79 | 26.1 | 24.82 | 24.35 | 27.33 | ||
| 1 | English | 24,785 | 25,109 | – | – | 24,726 | – | 21,836 | – |
| 2 | German | 8551 | 10,269 | – | – | 42,874 | – | 7352 | – |
| 3 | Italian | 9785 | 3799 | – | – | – | 3612 | – | |
| 4 | French | 1982 | 2972 | – | – | – | 1661 | – | |
| 5 | Dutch | 1416 | 1864 | – | – | 1285 | – | 1211 | – |
| 6 | Polish | 1301 | 1390 | – | – | 1285 | – | 1096 | – |
| 7 | Portuguese | 1000 | 682 | – | – | – | 1067 | – | |
| 8 | Slovenia | 363 | 331 | – | – | 369 | – | 341 | – |
| 9 | Finnish | 284 | 321 | – | – | 277 | – | 235 | – |
| 1 | English | 4.44 | 3.86 | – | – | 6.3 | – | 8.83 p = 0.007 | |
| 2 | French | 4.15 | 4.17 | – | – | 2.51 | – | – | |
| 3 | German | 2.21 | 2.02 | – | – | 3.78 | – | – |
When one of the search terms studied isolated produced a significant result, it was highlighted (bis). When a research term studied produced an insignificant result due to Bonferroni's correction (to eliminate the cumulative effect of the different measures), it was noted in red italics
Fig. 5Evolution of the number of Tweets worldwide (2013–2018). The equation for the linear regression curve is: y = − 0.4316x + 20,081; R2 = 0.04
Measurement of the Spearman correlation (ρ – rho) between the results obtained after ANOVA analysis
| Google Trends© | Wikipedia | Twitter© | Europresse | Bibliometrics | |
|---|---|---|---|---|---|
| Google Trends© | – | ρ = 0.09 | ρ = 0.013 | ρ = 0.18 | ρ = 0.24 |
| Wikipedia | – | – | ρ = 0.09 | ρ = − 0.14 | Insufficient data |
| Twitter© | – | – | – | ρ = 0.89 | ρ = 0.98 |
| Europresse | – | – | – | – | ρ = 0.2 |
| Bibliometrics | – | – | – | – | – |