Evidence map›Paper›PMID 38540552›Full record

ArticleBehavioral sciences (Basel, Switzerland)2024

From Stress to Screen: Understanding Cyberloafing through Cognitive and Affective Pathways.

Xinyuan Lu, Yizhou Wang, Xiaoxiao Chen, Quan Lu

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Xinyuan LuSchool of Information Management, Central China Normal University, Wuhan 430079, China.
Yizhou WangSchool of Information Management, Central China Normal University, Wuhan 430079, China.ORCID 0009-0004-5015-5542
Xiaoxiao ChenSchool of Information Management, Central China Normal University, Wuhan 430079, China.
Quan LuSchool of Economics and Management, Hubei University of Technology, Wuhan 430068, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This investigation delves into the pervasive yet insufficiently examined phenomenon of "cyberloafing", characterized by employees engaging in non-work-related internet activities during office hours. Despite its frequent occurrence in contemporary work environments, the fundamental mechanisms underpinning cyberloafing remain largely uncharted. This study uses the conservation of resources theory and the cognitive-affective personality system framework to demystify the relationship between role stress and cyberloafing. We developed a dual-path model to assess the mediating roles of perceived insider status and emotional exhaustion. Employing SPSS and Smart PLS for data analysis, our research sampled 210 corporate employees. The findings reveal that role stress predicts perceived insider status and emotional exhaustion significantly. Notably, while perceived insider status negatively correlates with cyberloafing, emotional exhaustion shows a positive correlation. These factors mediate the relationship between role stress and cyberloafing, underscoring a multifaceted dynamic. Our results provide new theoretical insights into the mechanisms of employee counterproductive behavior, specifically in the context of cyberloafing, and broaden our understanding of its determinants. This study illuminates theoretical nuances and offers practical implications for managerial strategies and future scholarly inquiries into organizational behavior.

Indexed as

cognitive–affective personality systems theoryconservation of resources theorycyberloafingPLS-SEMrole stress

Identifiers

PMID38540552
PMCPMC10967900

What OpenQuestion holds

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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.