Evidence map›Paper›PMID 37736057›Full record

ArticleFrontiers in psychiatry2023

The effect of smartphone dependence on learning burnout among undergraduates: the mediating effect of academic adaptability and the moderating effect of self-efficacy.

Chunmei Chen, Yuanyi Shen, Fanghao Xiao, Jianchao Ni, Yujie Zhu

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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.

Chunmei ChenTeachers College, Jimei University, Xiamen, Fujian, China.
Yuanyi ShenSchool of Aerospace Engineering, Xiamen University, Xiamen, Fujian, China.
Fanghao XiaoCollege of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen, Fujian, China.
Jianchao NiSchool of Aerospace Engineering, Xiamen University, Xiamen, Fujian, China.
Yujie ZhuSchool of Marine Culture and Law, Jimei University, Xiamen, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Smartphone dependence is closely related to the physical and mental health development of undergraduates and their learning. The purpose of this study was to explore the relationship between smartphone dependence, academic adaptability, self-efficacy and learning burnout among undergraduates and its underlying mechanisms. Methods: The study was conducted on 2,110 undergraduates using the Smartphone Dependence Scale, the Undergraduates Learning Adjustment Scale, the Learning Burnout Undergraduates Scale and the Self-Efficacy Scale to develop a mediation model and a moderation model. Results: The findings of this study revealed that (1) smartphone dependence significantly negatively predicted academic adaptability; (2) academic adaptability significantly negatively predicted learning burnout; (3) smartphone dependence significantly positively predicted learning burnout; (4) academic adaptability partially mediated the effect of smartphone dependence on learning burnout; (5) self-efficacy played a moderating role in the effect of academic adaptability on learning burnout. Conclusion: These findings can help researchers and educators better understand the underlying mechanisms between smartphone dependence and learning burnout in undergraduates.

Indexed as

academic adaptabilitylearning burnoutmediating effectmobile phone dependencemoderating effectself-efficacy

Identifiers

PMID37736057
PMCPMC10509764

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.