Evidence map›Paper›PMID 41283576›Full record

ArticleVision (Basel, Switzerland)2025

Biases in Perceiving Positive Versus Negative Emotions: The Influence of Social Anxiety and State Affect.

Vivian M Ciaramitaro, Erinda Morina, Jenny L Wu, Daniel A Harris, Sarah A Hayes-Skelton

Abstract read
In one paragraph

Article in Vision (Basel, Switzerland), 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

5 authors.

Vivian M CiaramitaroDepartment of Psychology, University of Massachusetts Boston, Boston, MA 02125, USA.ORCID 0000-0001-6767-6441
Erinda MorinaDepartment of Psychology, University of Massachusetts Boston, Boston, MA 02125, USA.ORCID 0000-0002-7635-4345
Jenny L WuDepartment of Psychology, University of Massachusetts Boston, Boston, MA 02125, USA.ORCID 0000-0001-6721-0377
Daniel A HarrisDepartment of Psychology, University of Massachusetts Boston, Boston, MA 02125, USA.
Sarah A Hayes-SkeltonDepartment of Psychology, University of Massachusetts Boston, Boston, MA 02125, USA.ORCID 0000-0002-1933-6896

Funding

University of Massachusetts Boston Dean's Reserach Funds
6 · The paper itself

Abstract

Models suggest social anxiety is characterized by negative processing biases. Negative biases also arise from negative mood, i.e., state affect. We examined how social anxiety influences emotional processing and whether state affect, or mood, modified the relationship between social anxiety and perceptual bias. We quantified bias by determining the point of subjective equality, PSE, the face judged equally often as happy and as angry. We found perceptual bias depended on social anxiety and state affect. PSE was greater in individuals high (mean PSE: 8.69) versus low (mean PSE: 3.04) in social anxiety. The higher PSE indicated a stronger negative bias in high social anxiety. State affect modified this relationship, with high social anxiety associated with stronger negative biases, but only for individuals with greater negative affect. State affect and trait anxiety interacted such that social anxiety status alone was insufficient to fully characterize perceptual biases. This raises several issues such as the need to consider what constitutes an appropriate control group and the need to consider state affect in social anxiety. Importantly, our results suggest compensatory effects may counteract the influences of negative mood in individuals low in social anxiety.

Indexed as

emotionfacesperceptual biassocial anxietystate affect

Identifiers

PMID41283576
PMCPMC12642024

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.