Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner
Abstract
1. Introduction
2. Materials and Methods
2.1. Search Strategy for Data Extraction
2.2. Statistical Analysis
3. Results
3.1. Trends over Time
3.2. Heartburn-Related Keyword Categories
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Patti, M.G. An Evidence-Based Approach to the Treatment of Gastroesophageal Reflux Disease. JAMA Surg. 2016, 151, 73–78. [Google Scholar] [CrossRef]
- De Bortoli, N.; Frazzoni, L.; Savarino, E.V.; Frazzoni, M.; Martinucci, I.; Jania, A.; Tolone, S.; Scagliarini, M.; Bellini, M.; Marabotto, E.; et al. Functional Heartburn Overlaps with Irritable Bowel Syndrome More Often than GERD. Am. J. Gastroenterol. 2016, 111, 1711–1717. [Google Scholar] [CrossRef] [PubMed]
- Richter, J.E.; Rubenstein, J.H. Presentation and Epidemiology of Gastroesophageal Reflux Disease. Gastroenterology 2018, 154, 267–276. [Google Scholar] [CrossRef] [PubMed]
- Eusebi, L.H.; Ratnakumaran, R.; Yuan, Y.; Solaymani-Dodaran, M.; Bazzoli, F.; Ford, A.C. Global prevalence of, and risk factors for, gastro-oesophageal reflux symptoms: A meta-analysis. Gut 2018, 67, 430–440. [Google Scholar] [CrossRef] [PubMed]
- Dent, J.; El-Serag, H.B.; Wallander, M.-A.; Johansson, S. Epidemiology of gastro-oesophageal reflux disease: A systematic review. Gut 2005, 54, 710–717. [Google Scholar] [CrossRef]
- Lødrup, A.; Reimer, C.; Bytzer, P. Use of antacids, alginates and proton pump inhibitors: A survey of the general Danish population using an internet panel. Scand. J. Gastroenterol. 2014, 49, 1044–1050. [Google Scholar] [CrossRef]
- Freedberg, D.E.; Kim, L.S.; Yang, Y.-X. The Risks and Benefits of Long-Term Use of Proton Pump Inhibitors: Expert Review and Best Practice Advice from the American Gastroenterological Association. Gastroenterology 2017, 152, 706–715. [Google Scholar] [CrossRef]
- Trifan, A.; Stanciu, C.; Girleanu, I.; Stoica, O.C.; Singeap, A.M.; Maxim, R.; Chiriac, S.A.; Ciobica, A.; Boiculese, L. Proton pump inhibitors therapy and risk of Clostridium difficile infection: Systematic review and meta-analysis. World J. Gastroenterol. 2017, 23, 6500–6515. [Google Scholar] [CrossRef]
- Wombwell, E.; Chittum, M.E.; Leeser, K.R. Inpatient Proton Pump Inhibitor Administration and Hospital-Acquired Clostridium difficile Infection: Evidence and Possible Mechanism. Am. J. Med. 2018, 131, 244–249. [Google Scholar] [CrossRef]
- Hanna, A.; Hanna, L.-A. What, where and when? Using Google Trends and Google to investigate patient needs and inform pharmacy practice. Int. J. Pharm. Pract. 2019, 27, 80–87. [Google Scholar] [CrossRef]
- Martini, M.; Bragazzi, N. Googling for neurological disorders: From seeking health-related information to patient empowerment, advocacy and open self-disclosure in the Neurology 2.0 era. J. Med. Internet Res. 2019. [Google Scholar] [CrossRef] [PubMed]
- Beck, F.; Richard, J.-B.; Nguyen-Thanh, V.; Montagni, I.; Parizot, I.; Renahy, E. Use of the internet as a health information resource among French young adults: Results from a nationally representative survey. J. Med. Internet Res. 2014, 16, e128. [Google Scholar] [CrossRef] [PubMed]
- McDaid, D.; Park, A.-L. Online Health: Untangling the Web. 2010. Available online: https://www.bupa.com.au/staticfiles/Bupa/HealthAndWellness/MediaFiles/PDF/LSE_Report_Online_Health.pdf (accessed on 26 October 2019).
- Nuti, S.V.; Wayda, B.; Ranasinghe, I.; Wang, S.; Dreyer, R.P.; Chen, S.I.; Murugiah, K. The Use of Google Trends in Health Care Research: A Systematic Review. PLoS ONE 2014, 9, e109583. [Google Scholar] [CrossRef] [PubMed]
- Bernardo, T.M.; Rajic, A.; Young, I.; Robiadek, K.; Pham, M.T.; Funk, J.A. Scoping review on search queries and social media for disease surveillance: A chronology of innovation. J. Med. Internet Res. 2013, 15, e147. [Google Scholar] [CrossRef]
- StatCounter GlobalStats. Search Engine Market Worldwide. 2019. Available online: https://gs.statcounter.com/search-engine-market-share/all (accessed on 26 October 2019).
- Jones, R.B.; Goldsmith, L.; Williams, C.J.; Kamel Boulos, M.N. Accuracy of geographically targeted internet advertisements on Google AdWords for recruitment in a randomized trial. J. Med. Internet Res. 2012, 14, e84. [Google Scholar] [CrossRef]
- Van Gelder, M.M.H.J.; van de Belt, T.H.; Engelen, L.J.L.P.G.; Hooijer, R.; Bredie, S.J.H.; Roeleveld, N. Google AdWords and Facebook Ads for Recruitment of Pregnant Women into a Prospective Cohort Study with Long-Term Follow-Up. Matern. Child Health J. 2019, 23, 1285–1291. [Google Scholar] [CrossRef]
- Jerman, J.; Onda, T.; Jones, R.K. What are people looking for when they Google “self-abortion”? Contraception 2018, 97, 510–514. [Google Scholar] [CrossRef]
- Zink, A.; Schuster, B.; Rüth, M.; Pereira, M.P.; Philipp-Dormston, W.G.; Biedermann, T.; Ständer, S. Medical needs and major complaints related to pruritus in Germany: A 4-year retrospective analysis using Google AdWords Keyword Planner. J. Eur. Acad. Dermatol. Venereol. 2019, 33, 151–156. [Google Scholar] [CrossRef]
- Seidl, S.; Schuster, B.; Rüth, M.; Biedermann, T.; Zink, A. What Do Germans Want to Know about Skin Cancer? A Nationwide Google Search Analysis from 2013 to 2017. J. Med. Internet Res. 2018, 20, e10327. [Google Scholar] [CrossRef]
- Tizek, L.; Schielein, M.; Rüth, M.; Ständer, S.; Pereira, M.P.; Eberlein, B.; Biedermann, T.; Zink, A. Influence of Climate on Google Internet Searches for Pruritus Across 16 German Cities: Retrospective Analysis. J. Med. Internet Res. 2019, 21, e13739. [Google Scholar] [CrossRef]
- Tizek, L.; Schielein, M.; Rüth, M.; Szeimies, R.; Philipp-Dormston, W.; Braun, S.; Hecker, C.; Eberlein, B.; Biedermann, T.; Zink, A. Interest in Skin Cancer in Urban Populations: A Retrospective Analysis of Google Search Terms in Nine Large German Cities. Acta Derm. Venereol. 2019, 99, 797–804. [Google Scholar] [CrossRef] [PubMed]
- Wongvibulsin, S.; Khanna, R.; Kwatra, S.G. Anatomic localization and quantitative analysis of the burden of itch in the United States. J. Am. Acad. Dermatol. 2019. [Google Scholar] [CrossRef] [PubMed]
- Wickham, H. Ggplot2: Elegant Graphics for Data Analysis (Use R!), 2nd ed.; Springer: Cham, Switzerland, 2016; ISBN 978-3-319-24277-4. [Google Scholar]
- Eysenbach, G. Infodemiology and Infoveillance. Am. J. Prev. Med. 2011, 40, S154–S158. [Google Scholar] [CrossRef] [PubMed]
- Seo, D.-W.; Jo, M.-W.; Sohn, C.H.; Shin, S.-Y.; Lee, J.; Yu, M.; Kim, W.Y.; Lim, K.S.; Lee, S.-I. Cumulative Query Method for Influenza Surveillance Using Search Engine Data. J. Med. Internet Res. 2014, 16, e289. [Google Scholar] [CrossRef] [PubMed]
- Wongkoblap, A.; Vadillo, M.A.; Curcin, V. Researching Mental Health Disorders in the Era of Social Media: Systematic Review. J. Med. Internet Res. 2017, 19, e228. [Google Scholar] [CrossRef]
- Xu, X.; Litchman, M.L.; Gee, P.M.; Whatcott, W.; Chacon, L.; Holmes, J.; Srinivasan, S.S. Predicting Prediabetes Through Facebook Postings: Protocol for a Mixed-Methods Study. JMIR Res. Protoc. 2018, 7, e10720. [Google Scholar] [CrossRef]
- Risson, V.; Saini, D.; Bonzani, I.; Huisman, A.; Olson, M. Patterns of Treatment Switching in Multiple Sclerosis Therapies in US Patients Active on Social Media: Application of Social Media Content Analysis to Health Outcomes Research. J. Med. Internet Res. 2016, 18, e62. [Google Scholar] [CrossRef]
- Ayers, J.W.; Westmaas, J.L.; Leas, E.C.; Benton, A.; Chen, Y.; Dredze, M.; Althouse, B.M. Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout. JMIR Public Health Surveill. 2016, 2, e16. [Google Scholar] [CrossRef]
- Ayers, J.W.; Althouse, B.M.; Dredze, M. Could Behavioral Medicine Lead the Web Data Revolution? JAMA 2014, 311, 1399–1400. [Google Scholar] [CrossRef]
- Bolin, T.D.; Korman, M.G.; Hansky, J.; Stanton, R. Heartburn: Community perceptions. J. Gastroenterol. Hepatol. 2000, 15, 35–39. [Google Scholar] [CrossRef]
- Dean, B.B.; Aguilar, D.; Johnson, L.F.; Fass, R.; Orr, W.C.; McGuigan, J.E.; Calimlim, B.; Yan, N.; Morgenstern, D.; Dubois, R.W. The relationship between the prevalence of nighttime gastroesophageal reflux disease and disease severity. Dig. Dis. Sci. 2010, 55, 952–959. [Google Scholar] [CrossRef] [PubMed]
- Bollschweiler, E.; Knoppe, K.; Wolfgarten, E.; Hölscher, A.H. Prevalence of dysphagia in patients with gastroesophageal reflux in Germany. Dysphagia 2008, 23, 172–176. [Google Scholar] [CrossRef] [PubMed]
- Nocon, M.; Keil, T.; Willich, S.N. Prevalence and sociodemographics of reflux symptoms in Germany—Results from a national survey. Aliment. Pharmacol. Ther. 2006, 23, 1601–1605. [Google Scholar] [CrossRef] [PubMed]
- Ziółkowski, B.A.; Pacholec, A.; Kudlicka, M.; Ehrmann, A.; Muszyński, J. Prevalence of abdominal symptoms in the Polish population. Gastroenterol. Rev. 2012, 1, 20–25. [Google Scholar] [CrossRef]
- Hassid, B.G.; Day, L.W.; Awad, M.A.; Sewell, J.L.; Osterberg, E.C.; Breyer, B.N. Using Search Engine Query Data to Explore the Epidemiology of Common Gastrointestinal Symptoms. Dig. Dis. Sci. 2017, 62, 588–592. [Google Scholar] [CrossRef]
- Chen, K.-Y.; Lou, H.-Y.; Lin, H.-C.; Lee, S.-H. Seasonal variation in the incidence of gastroesophageal reflux disease. Am. J. Med. Sci. USA 2009, 338, 453–458. [Google Scholar] [CrossRef]
- Shahar, D.R.; Froom, P.; Harari, G.; Yerushalmi, N.; Lubin, F.; Kristal-Boneh, E. Changes in dietary intake account for seasonal changes in cardiovascular disease risk factors. Eur. J. Clin. Nutr. 1999, 53, 395–400. [Google Scholar] [CrossRef]
- Ledeboer, M.; Masclee, A.A.; Batstra, M.R.; Jansen, J.B.; Lamers, C.B. Effect of cholecystokinin on lower oesophageal sphincter pressure and transient lower oesophageal sphincter relaxations in humans. Gut 1995, 36, 39–44. [Google Scholar] [CrossRef]
- Ma, Y.; Olendzki, B.C.; Li, W.; Hafner, A.R.; Chiriboga, D.; Hebert, J.R.; Campbell, M.; Sarnie, M.; Ockene, I.S. Seasonal variation in food intake, physical activity, and body weight in a predominantly overweight population. Eur. J. Clin. Nutr. 2006, 60, 519–528. [Google Scholar] [CrossRef]
- Fraser-Moodie, C.A.; Norton, B.; Gornall, C.; Magnago, S.; Weale, A.R.; Holmes, G.K. Weight loss has an independent beneficial effect on symptoms of gastro-oesophageal reflux in patients who are overweight. Scand. J. Gastroenterol. 1999, 34, 337–340. [Google Scholar] [CrossRef]
- Ness-Jensen, E.; Lagergren, J. Tobacco smoking, alcohol consumption and gastro-oesophageal reflux disease. Best Pract. Res. Clin. Gastroenterol. 2017, 31, 501–508. [Google Scholar] [CrossRef] [PubMed]
- Arku, R.E.; Adamkiewicz, G.; Vallarino, J.; Spengler, J.D.; Levy, D.E. Seasonal variability in environmental tobacco smoke exposure in public housing developments. Indoor Air 2015, 25, 13–20. [Google Scholar] [CrossRef] [PubMed]
- Phillips, K.; Bentley, M.C. Seasonal assessment of environmental tobacco smoke and respirable suspended particle exposures for nonsmokers in Bremen using personal monitoring. Environ. Int. 2001, 27, 69–85. [Google Scholar] [CrossRef]
- Chandra, S.; Gitchell, J.G.; Shiffman, S. Seasonality in sales of nicotine replacement therapies: Patterns and implications for tobacco control. Nicotine Tob. Res. 2011, 13, 395–398. [Google Scholar] [CrossRef]
- Momperousse, D.; Delnevo, C.D.; Lewis, M.J. Exploring the seasonality of cigarette-smoking behaviour. Tob. Control 2007, 16, 69–70. [Google Scholar] [CrossRef]
- Oliveria, S.A.; Christos, P.J.; Talley, N.J.; Dannenberg, A.J. Heartburn Risk Factors, Knowledge, and Prevention Strategies: A Population-Based Survey of Individuals with Heartburn. Arch. Intern. Med. 1999, 159, 1592. [Google Scholar] [CrossRef][Green Version]
- Bell, J.; Dziekan, G.; Pollack, C.; Mahachai, V. Self-Care in the Twenty First Century: A Vital Role for the Pharmacist. Adv. Ther. 2016, 33, 1691–1703. [Google Scholar] [CrossRef]
- Sheikh, I.; Waghray, A.; Waghray, N.; Dong, C.; Wolfe, M.M. Consumer use of over-the-counter proton pump inhibitors in patients with gastroesophageal reflux disease. Am. J. Gastroenterol. 2014, 109, 789–794. [Google Scholar] [CrossRef]
- Yoon, S.L.; Grundmann, O.; Smith, K.F.; Mason, S.R. Dietary Supplement and Complementary and Alternative Medicine Use Are Highly Prevalent in Patients with Gastrointestinal Disorders: Results from an Online Survey. J. Diet. Suppl. 2019, 16, 635–648. [Google Scholar] [CrossRef]
- Abdallah, J.; George, N.; Yamasaki, T.; Ganocy, S.; Fass, R. Most Patients with Gastroesophageal Reflux Disease Who Failed Proton Pump Inhibitor Therapy Also Have Functional Esophageal Disorders. Clin. Gastroenterol. Hepatol. 2019, 17, 1073–1080.e1. [Google Scholar] [CrossRef]
- Schmulson, M. How to use Rome IV criteria in the evaluation of esophageal disorders. Curr. Opin. Gastroenterol. 2018, 34, 258–265. [Google Scholar] [CrossRef] [PubMed]
- Lanas, A. We Are Using Too Many PPIs, and We Need to Stop: A European Perspective. Am. J. Gastroenterol. 2016, 111, 1085–1086. [Google Scholar] [CrossRef] [PubMed]
- Merrell, J.G.; Levy, B.H.; Johnson, D.A. Patient assessments and online ratings of quality care: A “wake-up call” for providers. Am. J. Gastroenterol. 2013, 108, 1676–1685. [Google Scholar] [CrossRef] [PubMed]
- Nölke, L.; Mensing, M.; Krämer, A.; Hornberg, C. Sociodemographic and health-(care-) related characteristics of online health information seekers: A cross-sectional German study. BMC Public Health 2015, 15, 31. [Google Scholar] [CrossRef]
- Percheski, C.; Hargittai, E. Health information-seeking in the digital age. J. Am. Coll. Health 2011, 59, 379–386. [Google Scholar] [CrossRef]
- Zulfiqar, S.; Wahab, M.F.; Sarwar, M.I.; Lieberwirth, I. Is Machine Translation a Reliable Tool for Reading German Scientific Databases and Research Articles? J. Chem. Inf. Model. 2018, 58, 2214–2223. [Google Scholar] [CrossRef]
Variables | Australia | Canada | Germany | Poland | The United Kingdom | The United States |
---|---|---|---|---|---|---|
Google users (mln) | 16.6 | 27.9 | 60.3 | 24.0 | 54.4 | 252.0 |
Google search engine market share (%) | 94.1 | 92.1 | 94.7 | 98.4 | 92.1 | 88.4 |
Total number of heartburn-related queries | 11,777,020 | 19,878,045 | 29,869,865 | 19,170,430 | 33,194,490 | 196,037,375 |
(177.4) | (178.1) | (123.8) | (199.7) | (152.5) | (194.5) | |
(100.0%) | (100.0%) | (100.0%) | (100.0%) | (100.0%) | (100.0%) | |
Treatment | 2,621,875 | 4,292,545 | 12,321,890 | 4,894,605 | 6,300,165 | 43,828,760 |
(39.5) | (38.5) | (51.1) | (51.0) | (29.0) | (43.5) | |
(22.3%) | (21.6%) | (41.3%) | (25.5%) | (19.0%) | (22.4%) | |
Home-based treatment | 281,505 | 603,405 | 3,859,615 | 1,027,125 | 529,155 | 6,291,450 |
(4.2) | (5.4) | (16.0) | (10.7) | (2.4) | (6.2) | |
(2.4%) | (3.0%) | (12.9%) | (5.4%) | (1.6%) | (3.2%) | |
Herbal Remedies | 222,230 | 456,140 | 309,125 | 227,425 | 670,915 | 5,121,765 |
(3.3) | (4.1) | (1.3) | (2.4) | (3.1) | (5.1) | |
(1.9%) | (2.3%) | (1.0%) | (1.2%) | (2.0%) | (2.6%) | |
Diet | 565,995 | 1,326,825 | 3,020,700 | 2,043,985 | 1,724,810 | 13,340,085 |
(8.5) | (11.9) | (12.5) | (21.3) | (7.9) | (13.2) | |
(4.8%) | (6.7%) | (10.1%) | (10.7%) | (5.2%) | (6.8%) | |
What is heartburn? | 681,335 | 878,275 | 420,160 | 308,780 | 1,387,865 | 9,278,745 |
(10.3) | (7.9) | (1.7) | (3.2) | (6.4) | (9.2) | |
(5.8%) | (4.4%) | (1.4%) | (1.6%) | (4.2%) | (4.7%) | |
Causes | 946,825 | 1,011,130 | 1,170,705 | 727,500 | 3,310,060 | 8,323,060 |
(14.3) | (9.1) | (4.9) | (7.6) | (15.2) | (8.3) | |
(8.0%) | (5.1%) | (3.9%) | (3.8%) | (10.0%) | (4.2%) | |
Symptoms | 1,543,550 | 1,555,925 | 768,170 | 1,624,020 | 3,079,495 | 14,090,405 |
(23.2) | (13.9) | (3.2) | (16.9) | (14.2) | (14.0) | |
(13.1%) | (7.8%) | (2.6%) | (8.5%) | (9.3%) | (7.2%) | |
Pregnancy | 502,240 | 556,545 | 2,652,295 | 998,545 | 1,212,865 | 6,315,490 |
(7.6) | (5.0) | (11.0) | (10.4) | (5.6) | (6.3) | |
(4.3%) | (2.8%) | (8.9%) | (5.2%) | (3.7%) | (3.2%) |
Keyword Categories | Sp | Su | F | W | Differences between Seasons | Post-Hoc Test |
---|---|---|---|---|---|---|
All, AU | 252,245 (245,823–278,236) | 251,010 (237,648–264,998) | 234,718 (211,893–251,624) | 237,113 (177,743–261,780) | H(3) = 7.26; p = 0.06 | - |
All, CA | 432,500 (411,221–443 861) | 386,383 (367,905–414,604) | 415,440 (386,088–438,069) | 425,103 (412,505–444,550) | H(3) = 11.78; p < 0.01 | Sp vs. Su: p = 0.009; Su vs. W: p = 0.009 |
All, DE | 631,078 (573,800–752,476) | 479,933 (456,481–510,810) | 643,680 (584,064–689,920) | 702,133 (647,904–733,763) | H(3) = 22.83; p < 0.001 | Sp vs. Su: p < 0.001; Su vs. F: p < 0.001; Su vs. W: p < 0.001 |
All, PL | 413,855 (378,118–445,215) | 323,498 (290,604–392,360) | 415,118 (356,075–437,983) | 456,628 (410,374–477,133) | H(3) = 16.98; p < 0.001 | Sp vs. Su: p = 0.02; Su vs. F: p = 0.02; Sp vs. W: p < 0.001 |
All, UK | 685,568 (674,179–783,191) | 612,100 (591,113–639,895) | 718,958 (668,631–751,340) | 719,670 (677,175–755,749) | H(3) = 16.10; p < 0.01 | Sp vs. Su: p = 0.004; Sp vs. F: p < 0.001; Su vs. W: p = 0.002 |
All, US | 4,207,538 (4,104,083–4,292,430) | 4,062,750 (3,638,311–4,171,973) | 4,013,993 (3,933,988–4,253,546) | 4,189,768 (4,096,570–4,382,620) | H(3) = 6.37; p = 0.10 | - |
Keywords Categories | 1st Year | 2nd Year | 3rd Year | 4th Year | Differences between Seasons | Post-Hoc Test |
---|---|---|---|---|---|---|
All, AU | 177,658 (166,660–239,650) | 238,030 (230,169–243,031) | 252,768 (244,768–259,025) | 301,708 (266,355–317,310) | H(3) = 32.03; p < 0.001 | 1st vs. 3rd: p < 0.001; 1st. 4th: p < 0.001 2nd vs. 3rd: p = 0.01; 2nd vs. 4th: p < 0.001 3rd vs. 4th: p < 0.001 |
All, CA | 381,685 (366,026–396,723) | 412,075 (388,623–422,866) | 424,530 (415,586–436,820) | 449,035 (437,770–458,530) | H(3) = 28.51; p < 0.001 | 1st vs. 2nd: p = 0.01; 1st vs. 3rd: p < 0.001; 1st vs. 4th: p < 0.001; 2nd vs. 4th: p < 0.001; 3rd vs. 4th: p = 0.01 |
All, DE | 579,680 (503,728–625,795) | 581,775 (515,340–684,631) | 639,365 (584,765–692,158) | 722,873 (611,633–784,663) | H(3) = 7.45; p = 0.06 | - |
All, PL | 349,473 (306,336–374,835) | 402,253 (336,690–421,814) | 448,113 (392,473–474,101) | 442,365 (413,446–471,501) | H(3) = 19.21; p < 0.001 | 1st vs. 3rd: p = 0.005; 1st vs. 4th: p < 0.001; 2nd vs. 4th: p = 0.03 |
All, UK | 643,960 (616,890–667,300) | 681,508 (617,634–718,104) | 682,220 (673,995–746,873) | 769,765 (732,391–798,230) | H(3) = 13.90; p < 0.01 | 1st vs. 4th: p < 0.009; 2nd vs. 4th: p < 0.009 |
All, US | 3,910,660 (3,247,271–4,058,481) | 4,051,168 (3,997,063–4,163,929) | 4,207,538 (4,101,224–4,234,081) | 4,349,405 (4,302,763–4,435,236) | H(3) = 30.76; p < 0.001 | 1st vs. 2nd: p = 0.02; 1st vs. 3rd: p < 0.001; 1st vs. 4th: p < 0.001; 2nd vs. 4th: p < 0.001; 3rd vs. 4th: p < 0.001; |
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Kamiński, M.; Łoniewski, I.; Misera, A.; Marlicz, W. Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner. Int. J. Environ. Res. Public Health 2019, 16, 4591. https://doi.org/10.3390/ijerph16234591
Kamiński M, Łoniewski I, Misera A, Marlicz W. Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner. International Journal of Environmental Research and Public Health. 2019; 16(23):4591. https://doi.org/10.3390/ijerph16234591
Chicago/Turabian StyleKamiński, Mikołaj, Igor Łoniewski, Agata Misera, and Wojciech Marlicz. 2019. "Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner" International Journal of Environmental Research and Public Health 16, no. 23: 4591. https://doi.org/10.3390/ijerph16234591
APA StyleKamiński, M., Łoniewski, I., Misera, A., & Marlicz, W. (2019). Heartburn-Related Internet Searches and Trends of Interest across Six Western Countries: A Four-Year Retrospective Analysis Using Google Ads Keyword Planner. International Journal of Environmental Research and Public Health, 16(23), 4591. https://doi.org/10.3390/ijerph16234591