Hyperbolic modeling and assessment of hypothetical health behaviors during a viral outbreak using crowdsourced samples
Hyperbolic discounting predicts who will — and won’t — follow health rules when a virus gets scarier.
01Research in Context
What this study did
Rzeszutek et al. (2023) asked crowdsourced adults to imagine a new viral outbreak. They had to pick how likely they were to wear masks, stay home, or get a shot.
The team built a hyperbolic discounting curve for each choice. Fatality rate acted like delay — higher death risk made healthy acts feel more valuable now.
What they found
The hyperbola shape fit the data best. As the fake virus grew deadlier, people said they would comply faster and more often.
Political views, trust in science, and income bent the curve. Richer or science-trusting folks showed flatter discounting — they valued future safety more.
How this fits with other research
Hassin-Herman et al. (1992) first showed Herrnstein’s hyperbola works for human eye contact maintained by social praise. Rzeszutek moves the same math from social reinforcers to hypothetical health threats.
Raineri et al. (2024) also used a hyperboloid model, but with money across Chilean and Chinese students. Both studies confirm the curve shape holds when you swap the commodity — cash or safety.
Green et al. (2004) found pigeons and rats discount delayed food hyperbolically too. The 2023 study extends this cross-species pattern to adult humans making pandemic choices.
Why it matters
You can now sketch a client’s health-compliance curve before a real outbreak. Ask how likely they are to mask at 1 % vs 5 % fatality. Plug the numbers into a hyperbola to spot steep discounters who will need extra cues or incentives. The same quick assessment works for flu shots, diet change, or exercise referrals.
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02At a glance
03Original abstract
The COVID-19 pandemic provided an opportunity to investigate factors related to public response to public health measures, which could help better prepare implementation of similar measures for inevitable future pandemics. To understand individual and environmental factors that influence likelihood in engaging in personal and public health measures, three crowdsourced convenience samples from Amazon Mechanical Turk (MTurk) completed likelihood-discounting tasks of engaging in health behaviors given a variety of hypothetical viral outbreak scenarios. Experiment 1 assessed likelihood of mask wearing for a novel virus. Experiment 2 assessed vaccination likelihood based on efficacy and cost. Experiment 3 assessed likelihood of seeking health care based on number of symptoms and cost of treatment. Volume-based measures and three-dimensional modeling were used to analyze hypothetical decision making. Hypothetical public and personal health participation increased as viral fatality increased and generally followed a hyperbolic function. Public health participation was moderated by political orientation and trust in science, whereas treatment-seeking was only moderated by income. Analytic methods used in this cross-sectional study predicted population-level outcomes that occurred later in the pandemic and can be extended to various health behaviors.
Journal of the Experimental Analysis of Behavior, 2023 · doi:10.1002/jeab.824