Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

197
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
197
Decision Making01:20

Decision Making

305
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
305
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.8K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.8K
Ethical Dilemmas II01:30

Ethical Dilemmas II

1.5K
Resolving an ethical dilemma in healthcare involves a systematic approach that considers every aspect of the issue, respecting both the patient's needs and values and the healthcare professional's ethical obligations. Here are potential steps to resolve an ethical dilemma:
1.5K
Errors In Hypothesis Tests01:14

Errors In Hypothesis Tests

4.8K
When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.
4.8K
Actuarial Approach01:20

Actuarial Approach

150
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
150

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Hypothetical Bias in the SG and TTO.

Medical decision making : an international journal of the Society for Medical Decision Making·2026
Same author

The prevention puzzle.

The Geneva risk and insurance review·2022
Same author

The QALY at 50: One story many voices.

Social science & medicine (1982)·2022
Same author

A comparison of individual and collective decision making for standard gamble and time trade-off.

The European journal of health economics : HEPAC : health economics in prevention and care·2020
Same author

Discounting health and money: New evidence using a more robust method.

Journal of risk and uncertainty·2019
Same author

Ambiguity preferences for health.

Health economics·2018
Same journal

Adapting temporal preference to scarcity: A role for emotion?

Journal of risk and uncertainty·2025
Same journal

Grit, discounting, & time inconsistency.

Journal of risk and uncertainty·2025
Same journal

Monetary values of increasing life expectancy: Sensitivity to shifts of the survival curve.

Journal of risk and uncertainty·2023
Same journal

On the role of monetary incentives in risk preference elicitation experiments.

Journal of risk and uncertainty·2023
Same journal

Risky choice: Probability weighting explains independence axiom violations in monkeys.

Journal of risk and uncertainty·2023
Same journal

Seen and not seen: How people judge ambiguous behavior during the COVID-19 pandemic.

Journal of risk and uncertainty·2022
See all related articles

Related Experiment Video

Updated: Oct 11, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K

Insurance decisions under nonperformance risk and ambiguity.

Timo R Lambregts1,2, Paul van Bruggen3, Han Bleichrodt4,5

  • 1Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, Netherlands.

Journal of Risk and Uncertainty
|December 6, 2021
PubMed
Summary
This summary is machine-generated.

People underinsure against future risks due to uncertainty about non-reimbursement. This study shows insurance demand decreases when nonperformance risk is ambiguous, especially for risk-prudent individuals.

Keywords:
AmbiguityInsuranceNonperformance riskPrudence

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.2K
Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

9.2K

Related Experiment Videos

Last Updated: Oct 11, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.2K
Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations
09:07

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

9.2K

Area of Science:

  • Behavioral economics
  • Decision theory
  • Risk management

Background:

  • Societal underinsurance against low-probability, long-term risks is a significant issue.
  • Uncertainty regarding risk non-reimbursement may deter individuals from purchasing adequate insurance.
  • Ambiguity aversion and risk prudence are potential factors influencing insurance decisions.

Purpose of the Study:

  • To experimentally investigate the impact of ambiguity in non-reimbursement risk on insurance demand.
  • To test the hypothesis that ambiguity aversion and risk prudence lead to reduced insurance uptake.
  • To explore the relationship between decision-maker characteristics and insurance purchasing behavior under uncertainty.

Main Methods:

  • An insurance experiment was designed to compare insurance demand under known versus ambiguous nonperformance risks.
  • Participants' decision-making behavior was observed in controlled experimental conditions.
  • Statistical analysis was employed to evaluate the effect of risk ambiguity and individual risk attitudes on insurance take-up.

Main Results:

  • Insurance demand was significantly lower when the nonperformance risk was ambiguous compared to when it was known.
  • This reduction in demand was particularly pronounced among decision-makers identified as risk prudent.
  • The study's measure of ambiguity aversion did not fully explain the observed decrease in insurance take-up.

Conclusions:

  • Ambiguity surrounding non-reimbursement risk demonstrably reduces insurance demand, especially for risk-prudent individuals.
  • The findings support the role of ambiguity in suboptimal insurance decisions for future or unlikely risks.
  • Further research is needed to capture the multifaceted nature of ambiguity attitudes beyond simple aversion.