Generated outcomes in risky choice reveal biased sampling and sequential dependencies.

Recent decision-making models have explained behaviour using mental sampling mechanisms, but there is still little agreement on the specific sampling process, such as whether sampling rates match true probabilities. Here, we seek to trace the sampling process using generation tasks: in two experimen...

Descripción completa

Detalles Bibliográficos
Publicado en:Communications Psychology Vol. 4; no. 1; pp. 1 - 13
Autores principales: Spicer, Jake, Li, Yun-Xiao, Castillo, Lucas, Falbén, Johanna K., Qian, C. Stella, Sanborn, Adam N.
Formato: equations & formulas research tables/charts Journal Article
Publicado: Springer Nature 5/7/2026
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195315892&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 195315892
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        27319121
        N51Q
      jtl: Communications Psychology
      issn: 27319121
      maglogo: N
    pubinfo:
      dt: 5/7/2026
      vid: 4
      iid: 1
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        195315892
        195315892
        195315892
        10.1038/s44271-026-00467-y
        195315892
      ppf: 1
      ppct: 12
      formats:
      tig:
        atl: Generated outcomes in risky choice reveal biased sampling and sequential dependencies.
      aug:
        au:
          Spicer, Jake
          Li, Yun-Xiao
          Castillo, Lucas
          Falbén, Johanna K.
          Qian, C. Stella
          Sanborn, Adam N.
        affil: https://ror.org/01a77tt86 Department of Psychology, University of Warwick, Coventry, UK
      sug:
        subj:
          Decision Making
          Risk Taking Behavior
          Cognition
          Models, Psychological
          Task Performance and Analysis
          Human
          Male
          Female
          Adult
          Middle Age
          Aged
          Probability
          Judgment
          Problem Solving
          Mental Processes
          Psychological Theory
          Attention
          Memory
          Learning
          Reproducibility of Results
          Linear Regression
          Logistic Regression
          Paired T-Tests
          Data Analysis Software
          Descriptive Statistics
          Funding Source
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
          Female
      ab: Recent decision-making models have explained behaviour using mental sampling mechanisms, but there is still little agreement on the specific sampling process, such as whether sampling rates match true probabilities. Here, we seek to trace the sampling process using generation tasks: in two experiments using general online samples (Ns = 52, 51), participants repeatedly produced potential outcomes from pairs of monetary gambles before choosing between them. Results found over-generation of rarer outcomes and under-generation of common outcomes overall, but not in initial responses, as well as avoidance of direct repetitions. Participants also tended to select options with higher average utility across their responses, implying generations guided choice. These findings suggest systematic biases in the information people may consider before a choice, and the influence that this can have on subsequent decisions, carrying implications for mental sampling models of this behaviour. We thus suggest explicit generation is a valuable method to access underlying choice processes, offering new assessments of existing theories of decision making. This study examined what information people may consider before a choice by asking them to repeatedly generate its possible outcomes. Participants overgenerated rare events and avoided direct repetitions, suggesting biases in what comes to mind.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N