Evidence map›Paper›PMID 41741616›Full record

ArticleScientific reports2026

Lack of group-to-individual generalizability in pseudocontingencies.

Jiri Kaan, Sonja Kunz, Spencer Moore, Yara Khaluf

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jiri KaanHealth and Society, Wageningen University, Hollandseweg 1, 6706 KN, Wageningen, The Netherlands. jiri.kaan@wur.nl.
Sonja KunzDepartment of Economics and Social Sciences, Institute of Marketing and Innovation, BOKU University, Feistmantelstrasse 4, 1180, Vienna, Austria.
Spencer MooreHealth and Society, Wageningen University, Hollandseweg 1, 6706 KN, Wageningen, The Netherlands.
Yara KhalufComputer Science Department, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands.

Funding

ZonMw 05550032110022
6 · The paper itself

Abstract

Decades of research have shown that people use a basic learning process called pseudocontingency inference to form beliefs about relationships between variables. Rather than relying on co-occurrences, people infer relationships based on separate occurrences of each variable. However, a fundamental question remains unanswered: how do individuals differ in their reliance on pseudocontingencies when forming beliefs? Existing computational models on pseudocontingencies have focused on group-level patterns, obscuring how individual differences affect belief formation. To this end, we formalize the degree to which people rely on actual contingencies or on pseudocontingencies. We focus on the belief that unhealthy food tastes better, a pseudocontingency effect observed even when actual contingencies suggest no or a negative relationship. Using data from previous experiments, we estimate the reliance on pseudocontingencies by calibrating a bias strength parameter at both individual and group levels. Our results reveal that people generally rely on pseudocontingencies instead of actual contingencies, but they do so to varying degrees. Bootstrapped estimates suggest that the median reliance on pseudocontingencies was 22-28% lower in individual-level compared to group-level models. The findings have implications for normative models that assume that people form beliefs about relationships based on actual contingencies. The significant lack of group-to-individual generalizability warrants concerns about the validity of group-level models as these may overestimate the reliance on pseudocontingencies.

Indexed as

LearningHumansIndividualitySocial GroupComputational modelingContingency learningPseudocontingencies

Identifiers

PMID41741616
PMCPMC13031770

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.