Evidence map›Paper›PMID 38273882›Full record

ArticleFrontiers in human neuroscience2023

Attentional bias to threat is modulated by stimulus content: an fNIRS study.

Hejun Liu, Qihan Zhang, Jon D Elhai, Christian Montag, Haibo Yang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in human neuroscience, 2023. 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, top 99% of its field
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, 0 citations in OpenAlex.

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 at 3 institutions in 3 countries.

Hejun LiuAcademy of Psychology and Behavior, Faculty of Psychology, Tianjin Normal University, Tianjin, China.
Qihan ZhangAcademy of Psychology and Behavior, Faculty of Psychology, Tianjin Normal University, Tianjin, China.
Jon D ElhaiDepartment of Psychology, University of Toledo, Toledo, OH, United States.
Christian MontagDepartment of Molecular Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany.
Haibo YangAcademy of Psychology and Behavior, Faculty of Psychology, Tianjin Normal University, Tianjin, China.
Tianjin Normal University · CNUniversität Ulm · DEUniversity of Toledo · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People are evolutionarily predisposed to associate threat relevant stimuli with fear or aversiveness and show an attentional bias toward threat. Attentional bias modification (ABM) has been shown to reduce threat biases, while quantitative reviews assessing the effectiveness of bias modification yielded inconsistent results. The current study examined the relationship between the training effect of attentional bias to threat and the type of threatening stimuli. Twenty-two participants performed a modified dot-probe task while undergoing functional near-infrared spectroscopy (fNIRS) imaging. Results indicated that there was a strong pattern of attentional avoidance among individuals in an animal but not human threat condition. Furthermore, findings from fNIRS confirmed that the influence from type of threatening stimulus would be modulated by cortical activation patterns, especially in the ventrolateral prefrontal cortices (vlPFC) and angular gyrus. Overall, these results suggest that stimulus-specific may play a major role in personalization of specific psychological interventions.

Indexed as

attentional biasattentional bias modification (ABM)eye gazefunctional near-infrared spectroscopy (fNIRS)threat type

Identifiers

PMID38273882
PMCPMC10808614
OpenAlexW4390743914

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.