Thirdhand smoke educational narratives on the risks of exposure to children
Examining Facebook’s algorithmic priorities and user engagement
Keywords:
Facebook, Algorithms, Campaign, thirdhand smoke, tobacco preventionAbstract
Digital advertising platforms, such as Facebook, push paid advertisements on their platform via algorithms. Algorithmic coding, patterns, and decision making are at the discretion of each business with little public transparency. The lack of transparency creates uncertainty surrounding best practice strategies for evaluating public health campaigns, which typically would seek to identify a large sample of target audience members exposed to the campaign. Through using a thirdhand smoke education campaign distributed via Facebook’s advertising platform, the purpose of this study was to critically consider the ability of public health campaigns to rely on social media algorithms to determine campaign reach and effectiveness. Following a recruitment advertisement to establish a panel sample (n = 684), four campaign messages designed to inform parents and caregivers about the harms of thirdhand smoke exposure for children were disseminated on Facebook. Messages included images of children with a 4-part narrative that varied in scenario specificity. Following eight months of data collection, analyses found that the algorithm detected a strong user preference for more specific narrative scenarios with higher personalization. However, engagement data suggests that users might be more curious or have more opinions across messages than the algorithm could detect. Finally, data suggest the algorithm is not sufficiently pushing advertisements to users who clicked on a past advertising link, making panel sampling especially difficult. Findings suggest that public health campaigns cannot rely on recruitment advertisements to develop panel samples and that traditional survey-based methods of assessing participant recall should be reconsidered to capture participant exposure more accurately.
References
An, R., Ji, M., & Zhang, S. (2017). Effectiveness of social media-based interventions on weight-related behaviors and body weight status: review and meta-analysis. American Journal of Health Behavior, 41(6), 670-682. https://doi.org/10.5993/AJHB.41.6.1
Andridge, R. R., & Little, R. J. (2010). A review of hot deck imputation for survey non‐response. International Statistical Review, 78(1), 40-64. https://doi.org/10.1111/j.1751-5823.2010.00103.x
Atkin, C. K., & Freimuth, V. (2013). Guidelines for formative evaluation research in campaign design. In R. E. Rice & C. K. Atkins (Eds.), Public communication campaigns (4th ed., pp. 53-68). Sage.
Chen, M., & Bell, R. A. (2022). A meta-analysis of the impact of point of view on narrative processing and persuasion in health messaging. Psychology & Health, 37(5), 545-562. https://doi.org/10.1080/08870446.2021.1894331
Crain, M. (2019). A critical political economy of web advertising history. In N. Brügger & I. Milligan (Eds.), The SAGE Handbook of Web History. Sage.
Dempster, C., & Lee, J. (2015). The rise of the platform marketer: Performance marketing with Google, Facebook, and Twitter, plus the latest high-growth digital advertising platforms. John Wiley & Sons.
Hang, B., Wang, P., Zhao, Y., Sarker, A., Chenna, A., Xia, Y., Snijders, A. M., & Mao, J.-H. (2017). Adverse health effects of thirdhand smoke: From cell to animal models. International Journal of Molecular Sciences, 18(5), 932. https://doi.org/10.3390/ijms18050932
Hornik, R., Binns, S., Emery, S., Epstein, V. M., Jeong, M., Kim, K., Kim, Y., Kranzler, E. C., Jesch, E., & Lee, S. J. (2022). The effects of tobacco coverage in the public communication environment on young people’s decisions to smoke combustible cigarettes. Journal of Communication, 72(2), 187-213. https://doi.org/10.1093/joc/jqab052
IBM (2019). SPSS (Version 29). [Software.] https://www.ibm.com/spss
Jacob III, P., Benowitz, N. L., Destaillats, H., Gundel, L., Hang, B., Martins-Green, M., Matt, G. E., Quintana, P. J., Samet, J. M., & Schick, S. F. (2017). Thirdhand smoke: New evidence, challenges, and future directions. Chemical research in toxicology, 30(1), 270-294. https://doi.org/10.1021/acs.chemrestox.6b00343
Kim, H. S., Yang, S., Kim, M., Hemenway, B., Ungar, L., & Cappella, J. N. (2019). An experimental study of recommendation algorithms for tailored health communication. Computational Communication Research, 1(1), 103-129. https://doi.org/10.5117/CCR2019.1.005.SUKK
Kousoulis, A. A., Kympouropoulos, S. P., Pouli, D. K., Economopoulos, K. P., & Vardavas, C. I. (2014). From the classroom to Facebook: A modern approach for smoking education in adolescents. Tobacco Induced Diseases, 12(supplement 1), A19. https://doi.org/10.1186/1617-9625-12-S1-A19
Laranjo, L., Arguel, A., Neves, A. L., Gallagher, A. M., Kaplan, R., Mortimer, N., Mendes, G. A., & Lau, A. Y. (2015). The influence of social networking sites on health behavior change: A systematic review and meta-analysis. Journal of the American Medical Informatics Association, 22(1), 243-256. https://doi.org/10.1136/amiajnl-2014-002841
Lee, D., Hosanagar, K., & Nair, H. S. (2018). Advertising content and consumer engagement on social media: Evidence from Facebook. Management Science, 64(11), 5105-5131. https://doi.org/10.1287/mnsc.2017.2902
Liu, J., Siegel, L., Gibson, L. A., Kim, Y., Binns, S., Emery, S., & Hornik, R. C. (2019). Toward an aggregate, implicit, and dynamic model of norm formation: Capturing large-scale media representations of dynamic descriptive norms through automated and crowdsourced content analysis. Journal of Communication, 69(6), 563-588. https://doi.org/10.1093/joc/jqz033
Martins-Green, M., Adhami, N., Frankos, M., Valdez, M., Goodwin, B., Lyubovitsky, J., Dhall, S., Garcia, M., Egiebor, I., & Martinez, B. (2014). Cigarette smoke toxins deposited on surfaces: Implications for human health. PloS One, 9(1), e86391. https://doi.org/10.1371/journal.pone.0086391
Matt, G., Quintana, P., Hovell, M., Bernert, J., Song, S., Novianti, N., Juarez, T., Floro, J., Gehrman, C., & Garcia, M. (2004). Households contaminated by environmental tobacco smoke: Sources of infant exposures. Tobacco Control, 13(1), 29-37. https://doi.org/10.1136/tc.2003.003889
Matt, G. E., Quintana, P. J., Destaillats, H., Gundel, L. A., Sleiman, M., Singer, B. C., Jacob III, P., Benowitz, N., Winickoff, J. P., & Rehan, V. (2011). Thirdhand tobacco smoke: Emerging evidence and arguments for a multidisciplinary research agenda. Environmental Health Perspectives, 119(9), 1218-1226. https://doi.org/10.1289/ehp.1103500
Matt, G. E., Quintana, P. J., Hoh, E., Zakarian, J. M., Dodder, N. G., Record, R. A., Hovell, M. F., Mahabee-Gittens, E. M., Padilla, S., & Markman, L. (2020). Persistent tobacco smoke residue in multiunit housing: Legacy of permissive indoor smoking policies and challenges in the implementation of smoking bans. Preventive medicine reports, 18, 101088. https://doi.org/10.1016/j.pmedr.2020.101088
Matt, G. E., Quintana, P. J., Hoh, E., Zakarian, J. M., Dodder, N. G., Record, R. A., Hovell, M. F., Mahabee-Gittens, E. M., Padilla, S., & Markman, L. (2021). Remediating thirdhand smoke pollution in multiunit housing: Temporary reductions and the challenges of persistent reservoirs. Nicotine and Tobacco Research, 23(2), 364-372. https://doi.org/10.1093/ntr/ntaa151
Matt, G. E., Quintana, P. J., Hovell, M. F., Chatfield, D., Ma, D. S., Romero, R., & Uribe, A. (2008). Residual tobacco smoke pollution in used cars for sale: Air, dust, and surfaces. Nicotine & Tobacco Research, 10(9), 1467-1475. https://doi.org/10.1080/14622200802279898
Northrup, T. F., Jacob III, P., Benowitz, N. L., Hoh, E., Quintana, P. J., Hovell, M. F., Matt, G. E., & Stotts, A. L. (2016). Thirdhand smoke: State of the science and a call for policy expansion. Public Health Reports, 131(2), 233-238. https://doi.org/10.1177/00333549161310020
Oschatz, C., & Marker, C. (2020). Long-term persuasive effects in narrative communication research: A meta-analysis. Journal of Communication, 70(4), 473-496. https://doi.org/10.1093/joc/jqaa017
Pócs, D., Adamovits, O., Watti, J., Kovács, R., & Kelemen, O. (2021). Facebook users’ interactions, organic reach, and engagement in a smoking cessation intervention: Content analysis. Journal of medical Internet research, 23(6), e27853. https://doi.org/10.2196/27853
Ramo, D. E., Rodriguez, T. M., Chavez, K., Sommer, M. J., & Prochaska, J. J. (2014). Facebook recruitment of young adult smokers for a cessation trial: Methods, metrics, and lessons learned. Internet interventions, 1(2), 58-64. https://doi.org/10.1016/j.invent.2014.05.001
Record, R. A., Greiner, L. H., Wipfli, H., Strickland, J., Owens, J., Pugel, J., & Matt, G. E. (2023). Evaluation of a social media campaign designed to increase awareness of thirdhand smoke among California adults. Health communication, 38(3), 437-446. https://doi.org/10.1080/10410236.2021.1954760
Record, R. A., Helme, D., Savage, M. W., & Harrington, N. G. (2017). Let’s clear the air: a campaign that effectively increased compliance with a university’s tobacco-free policy. Journal of Applied Communication Research, 45(1), 79-95. https://doi.org/10.1080/00909882.2016.1248471
Record, R. A., Matt, G. E., Greiner, L. H., & Wipfli, H. (2024). Parental Knowledge, Attitudes, Efficacy, and Protective Behaviors About Thirdhand Smoke and Children Ages 0-17. Journal of Environmental Health, 86(7). 18.
Romberg, A. R., Bennett, M., Tulsiani, S., Simard, B., Kreslake, J. M., Favatas, D., Vallone, D. M., & Hair, E. C. (2020). Validating self-reported AD recall as a measure of exposure to digital advertising: An exploratory analysis using AD tracking methodology. International Journal of Environmental Research and Public Health, 17(7), 2185. https://doi.org/10.3390/ijerph17072185
Snyder, L. B., & Hamilton, M. A. (2002). A meta-analysis of US health campaign effects on behavior: Emphasize enforcement, exposure, and new information, and beware the secular trend. In R. C. Hornik, Public health communication (pp. 373-400). Lawrence Erlbaum Associates.
StataCorp. (2023). Stata statistical software: Release 18. [Software]. https://www.stata.com/
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