Universal Suffering Units: A Proposed Framework with a Simulation Study of Duration Matching

Background: Efforts to relieve suffering can prevent adverse experiences, reduce their severity, or shorten their duration. Comparing these benefits matters for health care, humanitarian work, and charitable funding. We propose Universal Suffering Units (USU), a framework for comparing cumulative negative experience with a specified renal-colic reference. Methods: One USU is the modeled burden of a stipulated six-hour, pain-focused window. The principal proposed method seeks a matching temporary-state duration through comparisons with that reference. Dividing a candidate duration by its match gives an episode coefficient under a proportional-duration assumption; unresolved comparisons are retained. Mapped symptom reports and structured expert elicitation are complementary proposals. We specify aggregation, shared mapping uncertainty, and optional overlap handling, and examine mathematical properties. Eight constructed records illustrate response handling. A prespecified simulation study (444 scenarios, 2,000 repetitions each) evaluated panel summaries of matching responses against known population coefficients, including under misspecified response models. No participant-derived calibration was conducted. Results: Four of eight synthetic records yielded finite matching intervals, with a mean eight-hour coefficient of 0.611 USU. Others retained directional bounds or no mapping. In core simulation scenarios, the finite-match mean was biased by −67% to +47% when matching durations extended beyond the search range, mainly through which respondents obtained finite matches rather than matching error. An interval-censored model retaining one-sided bounds met the ±5% relative-bias criterion, including its Monte Carlo margin, in 267 of 324 core scenarios drawn from its assumed log-normal distribution, but some fits in 20-person panels were extreme, and its bias reached −41% to +50% under anchoring, non-proportional duration, or a skewed population. Changing only the positive reference denominator preserves the ordering of fixed profile estimates; changing intensity weighting can reverse it. Conclusions: USU makes proposed comparisons explicit and testable. With suitable calibration and evidence about intervention effects, it could support research on suffering reduction. Matching panels should report responses outside the search range; models retaining them are promising but need assumption checks. Reference comprehension, response stability, duration proportionality, and population transfer require evaluation; a common unit does not establish interpersonal or cross-domain comparability.