Evidence map›Paper›PMID 39923410›Full record

ReviewCurrent opinion in psychology2025

Biased information-seeking and information-integration in social anxiety.

Yukta Thyagaraj, Selin Topel, Caroline J Charpentier

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Current opinion in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Yukta ThyagarajUndergraduate Program, Indian Institute of Science, Bangalore, Karnataka, India; Department of Psychology, University of Maryland, College Park, MD, USA; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA.
Selin TopelInstitute of Psychology, Leiden University, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands.
Caroline J CharpentierDepartment of Psychology, University of Maryland, College Park, MD, USA; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA; Brain and Behavior Institute, University of Maryland, College Park, MD, USA. Electronic address: ccharpen@umd.edu.

Funding

Neuro-computational mechanisms of social learning and variation along psychiatric symptom dimensions and in autismR00MH123669 · NIMH · UNIV OF MARYLAND, COLLEGE PARK · PI Caroline Juliette Charpentier · 2024 to 2026
$747k
NIMH NIH HHS R00 MH123669
6 · The paper itself

Abstract

Social anxiety is associated with an intense fear of social evaluation and rejection, often leading to avoidance behaviors and distress. In this review, we summarize the current understanding of how various cognitive biases may lead to the development and maintenance of social anxiety. While early models of social anxiety have focused on negative biases in perception, attention, memory and emotion regulation, more recent literature has started to characterize biases in information-seeking and information-integration, especially in the context of self-referential information and social feedback. We also highlight directions for future work, including characterizing how different biases in social anxiety relate to each other, and how they may help dissociate social anxiety symptoms from co-occurring conditions such as generalized anxiety and depression.

Indexed as

AnxietyInformation Seeking BehaviorPhobia, SocialSocial PerceptionHumansCognitive biasesFear of evaluationFeedback-seekingInformationLearningSocial anxiety

Identifiers

PMID39923410
PMCPMC12794393

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.