Evidence map›Paper›PMID 38744838›Full record

ArticleScientific reports2024

An integrative framework for mapping the psychological landscape of risk perception.

Sarah C Jenkins, Robert F Lachlan, Magda Osman

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Sarah C JenkinsCentre for Decision Research, Leeds Business School, University of Leeds, Leeds, Yorkshire, LS2 9JT, UK. s.c.jenkins@leeds.ac.uk.
Robert F LachlanDepartment of Psychology, Royal Holloway University of London, Egham, Surrey, TW20 0EX, UK.
Magda OsmanJudge Business School, University of Cambridge, Trumpington Street, Cambridge, CB2 1AG, UK.

Funding

Office for Product Safety and Standards Understanding the Psychological and Cultural Factors Underpinning Risk Perceptions of Products
6 · The paper itself

Abstract

We vary greatly in our perception of risk, not just because of differences between risks themselves, but also because of individual, contextual and cultural differences too. To better understand and predict responses to risk, we need to (a) integrate these components, combining approaches from different psychological disciplines and (b) also consider risk tolerance - how individuals trade-off between risks and benefits. We therefore developed an ICONS (individual, contextual, cognitive, social) framework; using it across two empirical studies (n = 4228) to examine how individuals perceive and respond to the quotidian risks associated with consumer products. Three dimensions underlined risk perceptions: benefits, dread and individual responsibility. Risk tolerance was typically predicted by interactions between individual (demographic, cultural worldview, personality) and contextual (product type/category, harm information) factors. In turn, perceived dread, benefits and individual differences shaped how likely participants were to communicate risk information. Our results demonstrate for the first time how the interaction between individual, cognitive (risk tolerance, intensity), contextual, and social (risk communication) factors is key to understanding and predicting risk perceptions. Together, our findings help explain why societal responses to risks are often difficult to predict and have implications for the spread, and amplification, of risk information.

Indexed as

PerceptionAdolescentAdultAgedFemaleHumansMaleMiddle AgedRiskRisk AssessmentYoung Adult

Identifiers

PMID38744838
PMCPMC11093976

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.