Subjective Expected Utility Decision Making Under Diagnostic Uncertainty
When objective probabilities of health outcomes or infection states are unknown, decision makers must rely on subjective probability assessments to make choices under risk and uncertainty.
Picture this
Imagine deciding whether to carry an umbrella when you cannot read an official weather report. You estimate the likelihood of rain based on cloud patterns and decide if the inconvenience of carrying the umbrella is worth preventing getting wet. When new information arrives—like seeing neighbors walk by without umbrellas—you adjust your subjective likelihood of rain and decide whether to drop the umbrella to maximize personal comfort.
What the evidence says
Providing objective information via testing enables individuals to revise subjective probability distributions and re-optimize future behaviors to maximize expected utility.
- Who
- N = 1,995 HIV-negative rural Malawians across 117 villages (baseline N = 2,654 tested in 2004).
- How
- Theoretical framework extending Savage (1954) subjective expected utility and von Neumann-Morgenstern (1944) decision theory to health diagnostics and risk responses.
What to do
Incorporate subjective expectation assessments into health diagnostic evaluations to predict how population belief adjustments influence behavior under uncertainty.
From the source
"Savage (1954) advanced a theory that allows decision makers to maximize expected utility based on subjective probabilities of different states when objective probabilities are unknown."
Learning from Others' HIV Testing: Updating Beliefs and Responding to Risk
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