Evidence map›Paper›PMID 31447743›Full record

ArticleFrontiers in psychology2019

Inhibitory Control in Excessive Social Networking Users: Evidence From an Event-Related Potential-Based Go-Nogo Task.

Qiufeng Gao, Ge Jia, Jun Zhao, Dandan Zhang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  19. Differences in Reward Sensitivity between High and Low Problematic Smartphone Use Adolescents: An ERP Study.International journal of environmental research and public health · 2021
    Article
  20. Response inhibition in problematic social network sites use: an ERP study.Cognitive, affective & behavioral neuroscience · 2021
    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

4 authors.

Qiufeng GaoDepartment of Sociology, Shenzhen University, Shenzhen, China.
Ge JiaDepartment of Sociology, Shenzhen University, Shenzhen, China.
Jun ZhaoCollege of Psychology, Shenzhen University, Shenzhen, China.
Dandan ZhangCollege of Psychology, Shenzhen University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inhibitory control is a core executive function module that monitors and suppresses inappropriate behavior. Inhibitory deficits have been observed in different addiction types (e.g., smoking, alcohol, drug and gambling). The excessive use of social networking sites (SNSs) has attracted increasing attention; however, it is unknown whether inhibitory control is impaired in excessive SNS users. This study used event-related potentials in an SNS-related Go-Nogo task to investigate inhibitory control in excessive SNS users. Although the behavioral data did not show any significant differences between groups, the N1 amplitude was larger following SNS images than control images in excessive SNS users. Furthermore, excessive users showed larger N2 amplitude and smaller Nogo-P3 amplitude than non-excessive users irrespective of stimuli. These findings suggested that excessive SNS users are inefficient in allocating monitoring resources in the Go-Nogo task (reflected by enhance N2) and show difficulty in late inhibitory control procedure (reflected by reduced Nogo-P3) compared to non-excessive users. Also, excessive SNS users pay more attention to SNS-related images compared to non-SNS-related images (reflected by the N1). Interventions for this specific population should focus on limiting exposure to SNS cues and enhancing inhibitory control.

Indexed as

event-related potentialexcessive use of social networking siteGo-Nogoinhibitory controlN2P3

Identifiers

PMID31447743
PMCPMC6692436

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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.