Related Experiment Video
Updated: Aug 7, 2026

Measuring Delay Discounting in Humans Using an Adjusting Amount Task
Published on: January 9, 2016
Population-based time preferences for future health outcomes
T G Ganiats1, R T Carson, R M Hamm
1Department of Family and Preventive Medicine, University of California San Diego, School of Medicine, La Jolla 92093-0622, USA. tganiats@ucsd.edu
Context:
Time preference (how preference for an outcome changes depending on when the outcome occurs) affects clinical decisions, but little is known about determinants of time preferences in clinical settings.
Objectives:
To determine whether information about mean population time preferences for specific health states can be easily assessed, whether mean time preferences are constant across different diseases, and whether under certain circumstances substantial fractions of the patient population make choices that are consistent with a negative time preference.
Design:
Self-administered survey.
Setting:
Family physician waiting rooms in four states.
Patients:
A convenience sample of 169 adults.
Intervention:
Subjects were presented five clinical vignettes. For each vignette the subject chose between interventions maximizing a present and a future health outcome. The options for individual vignettes varied among the patients so that a distribution of responses was obtained across the population of patients.
Main Outcome Measure:
Logistic regression was used to estimate the mean preference for each vignette, which was translated into an implicit discount rate for this group of patients.
Results:
There were marked differences in time preferences for future health outcomes based on the five vignettes, ranging from a negative to a high positive (116%) discount rate.
Conclusions:
The study provides empirical evidence that time preferences for future health outcomes may vary substantially among disease conditions. This is likely because the vignettes evoked different rationales for time preferences. Time preference is a critical element in patient decision making and cost-effectiveness research, and more work is necessary to improve our understanding of patient preferences for future health outcomes.
More Related Videos
06:55Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
08:24The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
Published on: August 25, 2023
Related Concept Videos
The Availability Heuristic
Analysis of Population Pharmacokinetic Data
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Life Tables
Kaplan-Meier Approach
Hazard Rate