- In line with findings from the laboratory study, interstitial warning labels do impact behavioral patterns; interstitial warnings could potentially cause users to change their behavior, especially if they keep encountering those warnings
- Interstitial warnings are effective and informative, but being more informed does not guarantee that users will response differently

Adapting Security Warnings to Counter Misinformation - Crowdworker Study Discussion

- Exclamation label with the words fake news warning had highest mean informativeness score and lowest mean harm score
- Skull label with the words “WARNING: This website is dangerous” was the least informative and most extreme warning 
- CTR of crowdworker study (16%) much lower than in laboratory study (40%)
- AVR in treatment (86%) much higher than in control (19%)

University of Michigan - Ann Arbor

- Crowdworker study was used study the behavior effects of interstitial warnings
- Recruited 238 participants through Amazon Mechanical Turk and used a similar setup as laboratory study where participants had to answer questions about topics that were not talked about in the US, researchers paid attention to CTR and AVR and administered surveys, but treatment consisted of one of eight potential interstitial warnings 
- Using a multi-armed bandit algorithm to increase the chance that participants would encounter warnings that were deemed most/least informative and most/least effective at inducing fear of harm 
- Designed 8 interstitial warnings – 4 targeting information and 4 targeting fear of harm; information warnings contained detailed explanations and harm warnings used threatening and more extreme language to evoke fear
- 4 rounds of surveys asking participants why they decided on a result after each time they enter their answers before moving on to the next task
- Treatment surveys had an extra step that asked if participants understood the purpose and presence of the warnings (choice of malware, information theft, disinformation) and whether they felt fearful or harmed by the warnings
- Changes in behavior effects measured as the difference between the mean scores for informativeness and harm

Adapting Security Warnings to Counter Misinformation - Crowdworker Study Methodology

Kaiser, B., Wei, J., Lucherini, E., Lee, K., Matias, J. N., & Mayer, J. (2020). Adapting Security Warnings to Counter Misinformation. arXiv preprint arXiv:2008.10772. https://arxiv.org/abs/2008.10772

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