Evidence map›Paper›PMID 39088275›Full record

ArticleJournal of behavioral addictions2024

Attentional bias to social media stimuli is moderated by fear of missing out among problematic social media users.

Yang Wang, Jon D Elhai, Christian Montag, Lei Zhang, Haibo Yang

Abstract read
In one paragraph

Article in Journal of behavioral addictions, 2024. 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

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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.

Yang Wang1Academy of Psychology and Behavior, Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.ORCID 0000-0002-5177-7907
Jon D Elhai2Department of Psychology, University of Toledo, Toledo, OH, 43606, USA.ORCID 0000-0001-5205-9010
Christian Montag4Department of Molecular Psychology, Institute of Psychology and Education, Ulm University, 89081 Ulm, Germany.ORCID 0000-0001-8112-0837
Lei Zhang1Academy of Psychology and Behavior, Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.ORCID 0009-0005-5147-1720
Haibo Yang1Academy of Psychology and Behavior, Faculty of Psychology, Tianjin Normal University, Tianjin, 300387, China.ORCID 0000-0003-0386-5336

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: Previous evidence has indicated that problematic social media use (PSMU) is characterized by an attentional bias to social media icons (such as Facebook icons), but not to social webpages (such as Facebook webpages). They suggest that there may be other factors influencing attentional bias like fear of missing out (FoMO). But it remains unclear how FoMO moderates attentional bias in PSMU. This study aims to investigate whether PSMU show attentional bias for stimuli associated with social media, and how FoMO moderates on attentional bias among PSMU through experimental methods. Methods: Based on the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study explored mechanisms of attentional bias to social media icons (such as WeChat) related to PSMU and further examined the role of FoMO in this relationship. Specifically, attentional bias patterns to social media icons of 62 participants (31 PSMU and 31 control group) were explored during a dot-probe paradigm combined with eye-tracking in Experiment 1, and attentional bias patterns to social media icons of another 61 individuals with PSMU with different FoMO levels was explored during a dot-probe paradigm combined with eye-tracking in Experiment 2. Results: Results revealed that individuals with PSMU had an attentional bias toward social media icons, demonstrated by attentional maintenance, and such bias such bias was moderated by FoMO negatively, demonstrated by attentional vigilance and maintenance in PSMU/high FoMO. Conclusion: These results suggest that attentional bias is a common mechanism associated with PSMU, and FoMO is a key factor on the development of PSMU.

Indexed as

Attentional BiasFearSocial MediaAdolescentAdultEye-Tracking TechnologyFemaleHumansInternet Addiction DisorderMaleYoung Adultattentional biasdot-probeeye-trackingfear of missing out (FoMO)problematic social media use (PSMU)

Identifiers

PMID39088275
PMCPMC11457032

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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.