Evidence map›Paper›PMID 39695770›Full record

ArticleBMC psychology2024

Dynamic calibration of self-efficacy to cognitive load: the longitudinal mediation effect of state anxiety.

Xiaolong Li, Mu Xia

Abstract read
In one paragraph

Article in BMC psychology, 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

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

2 authors.

Xiaolong LiGuangxi Minzu University, Nanning, China.
Mu XiaGuangxi Minzu University, Nanning, China. muxiasci@163.com.

Funding

Department of Education of Gyangxi Zhuang Autonomous Region FIN301640601Guangxi Degree and Graduate Education Reform Project Grant No. JGY2021069
6 · The paper itself

Abstract

backgroundPrevious research has shown that higher self-efficacy predicts lower cognitive load. Nevertheless, there is limited research exploring the dynamic calibration phenomenon of cognitive resources by self-efficacy during task execution through experimental methods.

methodsThis study elucidates the relationships and longitudinal mediating effects among self-efficacy, state anxiety, and cognitive load through two studies that employed convenience sampling. Study 1, which aims to provide a comprehensive theoretical understanding of the research question, is an interview study that examines the prevalence of fluctuations in self-efficacy among 22 university students through an in-depth interview. On the other hand, study 2 reveals further causal relationships through experimental methods. It adopts a 3 (repeated measures: first time, second time, third time) × 2 (conditions: feedback group, non-feedback group) mixed design by 86 participants, utilizing a false feedback paradigm to manipulate participants' self-efficacy, with the task of the experiment being emotion recognition.

resultsThe results demonstrate that, compared to the non-feedback group, false feedback can successfully manipulate the self-efficacy of the participants, and the data from the feedback group further reveals the multilevel mediating role of state anxiety in the process of self-efficacy influencing cognitive load.

conclusionIn general, the findings from two studies suggest that the enhancement of college students' self-efficacy during task execution can reduce their state anxiety, which in turn can further alleviate cognitive load.

Indexed as

AnxietyCognitionSelf EfficacyStudentsAdolescentAdultFemaleHumansLongitudinal StudiesMaleUniversitiesYoung AdultCognitive loadMediating effectSelf-efficacyState anxiety

Identifiers

PMID39695770
PMCPMC11657581

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.