A Computational Model of Non-optimal Suspiciousness in the Minnesota Trust Game

Rebecca A Kazinka, Iris Vilares, Angus MacDonald

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This study modelled spite sensitivity, the worry that others are willing to incur a loss to hurt you, which is thought to undergird suspiciousness and persecutory ideation. Two samples performed a parametric, non-iterative trust game known as the Minnesota Trust Game (MTG). The MTG distinguishes suspicious decision-making from otherwise rational mistrust by incentivizing the player to trust in certain situations but not others. In Sample 1, 243 undergraduates who completed the MTG showed less trust as the amount of money they could lose increased. However, only for choices where partners had a financial disincentive to betray the player was variation in the willingness to trust associated with suspicious beliefs. We modified the Fehr-Schmidt (1999) inequity aversion model, which compares unequal outcomes in social decision-making tasks, to include the possibility for spite sensitivity. An anticipated partner’s dislike of advantageous inequity (i.e., guilt) parameter included negative values, with negative guilt indicating spite. We hypothesized that the anticipated guilt parameter would be strongly related to suspicious beliefs. Our modification of the Fehr-Schmidt model improved estimation of MTG behavior. Furthermore, the estimation of partner’s spite-guilt was highly correlated with choices associated with beliefs in persecution. We replicated our findings in a second sample. This parameter was weakly correlated with a self-reported measure of persecutory ideation in Sample 2. The “Suspiciousness” condition, unique to the MTG, can be modeled to isolate spite sensitivity, suggesting differentiation from inequity aversion or risk aversion. The MTG offers promise for future studies to quantify persecutory beliefs in clinical populations.

Original languageEnglish (US)
Pages (from-to)60-78
Number of pages19
JournalComputational Psychiatry
Volume6
Issue number1
DOIs
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s).

Keywords

  • computational modeling
  • decision-making
  • inequity aversion
  • risk aversion
  • Spite sensitivity
  • trust, suspiciousness

Fingerprint

Dive into the research topics of 'A Computational Model of Non-optimal Suspiciousness in the Minnesota Trust Game'. Together they form a unique fingerprint.

Cite this