Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout
- PMID: 27227151
- PMCID: PMC4869240
- DOI: 10.2196/publichealth.5304
Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout
Abstract
Background: Awareness campaigns are ubiquitous, but little is known about their potential effectiveness because traditional evaluations are often unfeasible. For 40 years, the "Great American Smokeout" (GASO) has encouraged media coverage and popular engagement with smoking cessation on the third Thursday of November as the nation's longest running awareness campaign.
Objective: We proposed a novel evaluation framework for assessing awareness campaigns using the GASO as a case study by observing cessation-related news reports and Twitter postings, and cessation-related help seeking via Google, Wikipedia, and government-sponsored quitlines.
Methods: Time trends (2009-2014) were analyzed using a quasi-experimental design to isolate spikes during the GASO by comparing observed outcomes on the GASO day with the simulated counterfactual had the GASO not occurred.
Results: Cessation-related news typically increased by 61% (95% CI 35-87) and tweets by 13% (95% CI -21 to 48) during the GASO compared with what was expected had the GASO not occurred. Cessation-related Google searches increased by 25% (95% CI 10-40), Wikipedia page visits by 22% (95% CI -26 to 67), and quitline calls by 42% (95% CI 19-64). Cessation-related news media positively coincided with cessation tweets, Internet searches, and Wikipedia visits; for example, a 50% increase in news for any year predicted a 28% (95% CI -2 to 59) increase in tweets for the same year. Increases on the day of the GASO rivaled about two-thirds of a typical New Year's Day-the day that is assumed to see the greatest increases in cessation-related activity. In practical terms, there were about 61,000 more instances of help seeking on Google, Wikipedia, or quitlines on GASO each year than would normally be expected.
Conclusions: These findings provide actionable intelligence to improve the GASO and model how to rapidly, cost-effectively, and efficiently evaluate hundreds of awareness campaigns, nearly all for the first time.
Keywords: big data; evaluation; health communication; infodemiology; infoveillence; mass media; smoking cessation; social media; tobacco control; twitter.
Conflict of interest statement
Conflicts of Interest: Drs Ayers and Althouse share an equity stake in a consultancy, Directing Medicine LLC, that advises clinician-scientists on how to implement some of the methods embodied in this work. Dr Dredze has been paid by Directing Medicine LLC in the past 5 years. Dr Ayers owns an equity position in HealthWatcher Inc. a data analytics firm specializing in media monitoring. Neither the data nor the methods described in this article are proprietary. There are no other potentially relevant conflicts. The other authors have no conflicts of interest to declare.
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References
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