Evidence map›Paper›PMID 41023088›Full record

ArticleScientific reports2025

The effect of probability and framing on the default effect in decision making under risk.

Joshua Lanier, Di Wang, Yusha Xie

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

3 authors.

Joshua LanierSchool of Social Sciences, Nanyang Technological University, 48 Nanyang Ave, Singapore, 639818, Singapore. jlanier84@gmail.com.
Di WangChina Center for Behavioral Economics and Finance, Southwestern University of Finance and Economics, Liutai Road 555, Wenjiang, 611130, Sichuan, China. wangd@swufe.edu.cn.
Yusha XieChina Center for Behavioral Economics and Finance, Southwestern University of Finance and Economics, Liutai Road 555, Wenjiang, 611130, Sichuan, China.

Funding

National Natural Science Foundation of China 72033006National Natural Science Foundation of China W2433187
6 · The paper itself

Abstract

This study examines how probability and outcome framing modulate the default effect in risky decision-making using two controlled experiments with probabilistically equivalent lotteries. Participants repeatedly chose among four equivalent betting options, with one highlighted as a default. Across both studies (N = 317), we document a robust default effect, with 38-39% choosing defaults versus a 25% random benchmark. Crucially, low winning probability (25% vs. 75%) consistently amplified default reliance. However, loss framing increased default choices significantly only in Study 1 (where task descriptions differed across probabilities) but not in Study 2 (where task framing was standardized). This suggests winning probability is a more reliable moderator than framing. Post-experiment surveys indicate cognitive ease and responsibility avoidance are key psychological mechanisms: low probability heightens the difficulty of winning, increasing default acceptance, while loss framing exacerbates responsibility aversion. The study advances understanding of the economic and contextual determinants of the default effect and highlights its implications for designing choice architectures in real-world applications where uncertainty is prominent.

Indexed as

Decision MakingRisk-TakingAdolescentAdultChoice BehaviorFemaleHumansMaleProbabilityUncertaintyYoung AdultCognitive easeDecision under riskDefault effectResponsibility avoidanceUtility of control

Identifiers

PMID41023088
PMCPMC12480121

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.