Evidence map›Paper›PMID 40065465›Full record

ArticleBMC psychology2025

Overconfident, but angry at least. AI-Based investigation of facial emotional expressions and self-assessment bias in human adults.

Roland Kasek, Enikő Sepsi, Imre Lázár

Abstract read
In one paragraph

Article in BMC psychology, 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.

Roland KasekInstitute of Behavioural Sciences, Semmelweis University, Budapest, Hungary. roland@kasek.com.
Enikő SepsiInstitute of Arts Studies and General Humanities, Károli Gáspár University of the Reformed Church, Budapest, Hungary.
Imre LázárInstitute of Behavioural Sciences, Semmelweis University, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metacognition and facial emotional expressions both play a major role in human social interactions [1, 2] as inner narrative and primary communicational display, and both are limited by self-monitoring, control and their interaction with personal and social reference frames. The study aims to investigate how metacognitive abilities relate to facial emotional expressions, as the inner narrative of a subject might project subconsciously and primes facial emotional expressions in a non-social setting. Subjects were presented online to a set of digitalised short-term memory tasks and attended a screening of artistic and artificial stimuli, where their facial emotional expressions were recorded and analyzed by artificial intelligence. Results show self-assessment bias in association with emotional expressivity - neutrality, saturation, transparency - and the display of anger and hostility as an individually specific trait expressed at modality-dependent degrees. Our results indicate that self-assessment bias interplays in subconscious communication - the expression, control and recognition of facial emotions, especially - with empathetic skills and manipulation.

Indexed as

AngerArtificial IntelligenceEmotionsFacial ExpressionFacial RecognitionMetacognitionSelf-AssessmentAdultFemaleHumansMaleYoung AdultArtificial intelligenceFacial emotional expressionMetacognitionNonverbal communicationSelf-assessment bias

Identifiers

PMID40065465
PMCPMC11895137

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.