The skydiving scenario captures a phenomenon economists call moral hazard, the tendency of people to take on more risk when someone else bears part of the cost. A student without insurance faces the full financial consequences of a broken leg, while an insured student knows that a policy will absorb much of the bill. Neither faces any risk of death in the hypothetical, which strips the exercise down to its economic essentials. When the class compares choices, students can see directly how coverage alters behavior at the level of a single decision, and then trace how those decisions aggregate into claims, premiums, and the overall cost of care. Concepts that can feel remote when presented in a textbook chapter become immediate and personal, because the students have just made the kind of choice the theory describes.

Zane and his colleagues, including associate professor Debora Goetz Goldberg and doctoral students Shaan Muberra Khan and Sravya Vunnam, describe the approach in a new paper titled More Than a Game, published in a special issue of The Journal of Health Administration Education devoted to gamification. The paper documents how simulation-based gaming, anchored in the principles of game theory, helped students grasp complex health economics concepts and the dynamics of insurance markets. Course evaluations collected from 129 students between 2022 and 2025 suggest the method resonated strongly: roughly 89 percent of respondents found the class environment engaging, and 85 percent said the teaching methods enhanced their learning. In written feedback, students reported that the games clarified challenging concepts and exposed them to classmates’ different approaches to the same problem.

The origin of the experiment-based course was, fittingly, a problem of engagement itself. During a summer of online teaching in 2022, Zane found most of his students keeping their cameras off, their attention drifting somewhere beyond the screen. It is a topic that I love, but they didn’t seem to get it, he recalled. Many of the students in his Health Economics and Policy course arrived with little background in economics and, in some cases, little interest in it. Health administration programs attract students motivated by careers in hospitals, clinics, and health systems, not by abstract models of markets and incentives. Zane needed a way to make the economic machinery of health care visible and worth caring about.

Game theory offered the way in. The field examines how people make decisions when their outcomes depend on the choices of others, a situation that describes nearly everything in health care: insurers setting premiums while anticipating who will enroll, hospitals negotiating with payers, patients deciding whether to seek care, and governments designing rules that shape all of the above. Before entering academia, Zane had worked as an antitrust lawyer, where he used game-theoretic reasoning to help clients decide whether to settle lawsuits. That professional experience convinced him that strategic decision-making under interdependence could be taught through direct experience rather than lecture, and that students who played through the incentives themselves would understand them more deeply than students who merely read about them.

His first experiment was the ultimatum game, one of the most well-established exercises in behavioral economics. In the classic version, one party receives a financial windfall and proposes how to divide it with a second party, who can either accept the offer or reject it, leaving both with nothing. Rational self-interest predicts that the proposer should offer the smallest possible share and that the responder should accept anything above zero, since something beats nothing. In Zane’s classroom adaptation, Kit Kat candy bars stand in for cash. The results defy the cold logic of the model in a way students can watch unfold in real time: some students would rather walk away with nothing than accept a share they consider unfair. That outcome opens a discussion about why fairness considerations can outweigh personal gain, a lesson with direct relevance to health care, where perceptions of equity shape everything from patient trust to public support for insurance expansions.

From that starting point, Zane built a growing library of exercises, some adapted from existing game-theory models and others of his own design, refining them according to student feedback each term. One of his original creations is the orange juice game, which teaches market structure and price competition. Students are assigned to groups representing different levels of competition, ranging from a single seller holding a monopoly to a crowded market with many sellers. Zane tells each group that he is willing to pay up to $5 for a bottle of juice. The monopolist, facing no rivals, can hold its price near that ceiling. Sellers in competitive markets, by contrast, must undercut one another to win sales, and in the most crowded market the price can fall close to zero. The demonstration shows students how competition drives down prices, a foundational insight for understanding why economists worry about market concentration among hospitals, insurers, and pharmaceutical companies.

Crucially, the games are only half the lesson. After each round, students explain the reasoning behind their choices and compare their logic with that of their classmates. These structured reflections serve a double purpose. They force students to articulate the economic principles guiding their behavior, converting an intuitive play experience into explicit understanding, and they give Zane a diagnostic window into whether the intended lesson actually landed. Reading the reflections, he said, it became pretty clear that most of the students were getting it. The debriefing stage reflects a broader consensus in education research that active learning exercises work best when paired with guided reflection, since experience alone does not guarantee that the underlying concept is extracted from the activity.

The published evidence, drawn from three years of course evaluations, positions the George Mason experiment as a case study in how gamification can transform the teaching of quantitative and strategic subjects. The stakes are considerable: health economics underpins policy debates on insurance design, provider consolidation, and cost containment, and the professionals who manage health systems often make decisions with billions of dollars and public health on the line. If future administrators internalize concepts like moral hazard, market power, and strategic interaction not as vocabulary to memorize but as forces they have personally experienced in a classroom game, the argument runs, they will carry that intuition into practice. What began as a desperate attempt to keep online students from turning off their cameras has matured into a documented pedagogy, one in which a free, perfectly safe skydive teaches more about insurance than a semester of slides ever could.

Subject of Research: Simulation-based game theory exercises for teaching health economics and insurance market dynamics to university students

Article Title: Study finds simulation game helps students grasp complex health economics concepts

Article References: Study finds simulation game helps students grasp complex health economics concepts. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: health economics, game theory, gamification, simulation-based learning, health insurance, moral hazard, ultimatum game, market competition, health administration education, student engagement, George Mason University, active learning

The review, conducted by Hanmo Yin and Nasrudin Subhi of Universiti Kebangsaan Malaysia together with Rozainee Khairudin of Taylor’s University, set out to answer a deceptively simple question: do depression and socioeconomic position reliably change how people respond to unfair offers? The question matters because both factors have been repeatedly implicated in studies of economic behavior. Depression is known to alter emotional processing, reward sensitivity, and social cognition, while socioeconomic status shapes everything from risk tolerance to long-term planning. If either factor systematically distorts fairness-related decision-making, the implications could reach into mental health practice, economic policy, and our understanding of social inequality itself.

To investigate, the team searched PubMed, PsycINFO, Web of Science, and Google Scholar for peer-reviewed articles published up to June 2026. They applied strict eligibility criteria: studies had to use the Ultimatum Game or a closely related paradigm and had to examine either depression or socioeconomic status in relation to the rejection of unfair offers. Rejection rates served as the behavioral index throughout, because refusing a low offer is widely interpreted as costly punishment—the participant sacrifices real money to penalize a partner perceived as unfair. After screening and appraisal using PRISMA reporting standards and the Joanna Briggs Institute critical appraisal checklist, eighteen studies met the inclusion criteria: eleven examining depression alone, six examining socioeconomic status alone, and a single study addressing both factors simultaneously.

The narrative synthesis of these eighteen studies revealed a strikingly inconsistent picture. Among the depression-focused studies, some reported that depressed participants rejected unfair offers more often than healthy controls, consistent with theories that heightened negative emotion or impaired emotion regulation amplifies reactions to unfairness. Others found the opposite pattern, with depression linked to lower rejection rates, perhaps reflecting diminished sensitivity to social reward or a reduced willingness to engage in costly punishment. Still others detected no significant association at all. The socioeconomic status literature told an equally fragmented story, with income, education, occupation, and subjective social standing producing divergent results depending on how each was measured and which task variant was deployed.

To move beyond narrative impressions, the researchers conducted separate random-effects meta-analyses for the depression-related and socioeconomic-status-related effects. The pooled estimates for both factors were non-significant, meaning that across studies, neither depression nor socioeconomic status showed a reliable overall effect on unfair-offer rejection. In the depression meta-analysis, heterogeneity—the statistical variability among study effects—was significant, signaling that the true effect likely differs across populations, clinical profiles, and experimental conditions. In the socioeconomic status analysis, the heterogeneity index was high even though the Q-test for heterogeneity did not reach significance, a pattern the authors attribute to limited statistical power given the small number of included studies.

These findings strike a direct blow against a seductive simplification: the idea that depression uniformly makes people more vindictive toward unfairness, or that poverty or low social standing makes people either more compliant or more rebellious in economic negotiations. The evidence, the authors conclude, supports no such uniform conclusion. Instead, the effects of both depression and socioeconomic status on fairness-related decision-making appear heterogeneous and deeply context-dependent. What happens in the brain of a person with major depressive disorder rejecting a lowball offer may depend on symptom severity, current clinical status, medication, the size of the stakes, and the cultural framing of the task. Likewise, the behavioral signature of socioeconomic disadvantage may shift depending on whether status is measured by income, educational attainment, occupational prestige, or a person’s subjective sense of where they stand on the social ladder.

The technical details of the meta-analytic approach reinforce the credibility of the null result. The authors used restricted maximum likelihood estimation, a standard method for fitting random-effects models that accommodates between-study variability, and followed the PRISMA 2020 guidelines for transparent reporting, with supplementary materials including the full checklist, critical appraisal forms, extraction data, and the R code used for the analyses. This open methodological scaffolding allows other researchers to reproduce the pooled estimates, test alternative models, and identify precisely where the heterogeneity originates. In a field where small samples and task variations frequently produce contradictory findings, such transparency is itself a form of scientific progress.

Why might the expected effects fail to materialize at the pooled level? The review points to several plausible cognitive-affective mechanisms. Rejection of an unfair offer is thought to emerge from an interplay between fairness appraisal—cognitive judgments about whether a split violates social norms—and emotional responses to unfairness, such as anger or resentment. Depression could plausibly act on either side of this ledger: it may blunt the emotional sting of unfairness through anhedonia and reduced reward responsiveness, or it may intensify negative interpretation biases that make ambiguous offers feel hostile. Which direction dominates could depend on the severity of symptoms, the phase of the illness, or comorbid anxiety. Similarly, socioeconomic status could shape rejection behavior through long-term exposure to scarcity, which sometimes promotes acceptance of uneven deals out of necessity, and sometimes fosters heightened sensitivity to being exploited. The single study that examined depression and socioeconomic status together underscores how little direct empirical work exists on their joint influence—a gap the authors identify as a priority for future research.

The methodological critique embedded in the review is equally consequential. Studies in this literature vary widely in how they operationalize both the clinical and the socioeconomic constructs, and in how they configure the Ultimatum Game itself. Stake sizes, offer distributions, partner identity, and whether offers come from humans or computers all modulate rejection behavior. Without standardized paradigms and clearly defined clinical and socioeconomic measures, meta-analytic pools inevitably mix apples and oranges, inflating heterogeneity and obscuring genuine effects. The authors recommend that future studies adopt standard behavioral Ultimatum Game protocols and precise, validated measurements, and that they explicitly test interaction effects between depression and socioeconomic status rather than treating the two as separate, competing predictors.

The broader lesson resonates well beyond the economics laboratory. Public discourse often leans on simple narratives in which mental illness or poverty determines behavior in predictable ways. This meta-analysis is a reminder that human social decision-making resists such neat categorization. The inclination to punish unfairness emerges from a dynamic negotiation between emotion, cognition, context, and identity—and no single demographic or clinical variable appears to command it. For researchers, the null pooled effects are not an endpoint but an invitation: to design better-powered, better-specified studies that can map the conditions under which depression and social position do, in fact, bend our sense of fairness. For the rest of us, the findings counsel humility about how much we can infer about a person’s choices from a diagnosis or a paycheck alone.

Subject of Research: The impact of depression and socioeconomic status on fairness-related socioeconomic decision-making.

Article Title: What is the impact of depression and socioeconomic status on socioeconomic decision-making: a systematic review and meta-analysis

Article References: What is the impact of depression and socioeconomic status on socioeconomic decision-making: a systematic review and meta-analysis. (n.d.). https://doi.org/10.1186/s40359-026-05443-z

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05443-z

Keywords: depression, socioeconomic status, Ultimatum Game, decision-making, meta-analysis, systematic review, fairness, behavioral economics, mental health, social inequality, impact, socioeconomic