Evidence map›Paper›PMID 40564552›Full record

ArticleBehavioral sciences (Basel, Switzerland)2025

Exploring the Influence of Napping Habits on Job Satisfaction: A Quasi-Natural Experimental Study Based on Longitudinal Data from China.

Xin Liu, Xiaochong Wei, Longxin Zhang

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Xin LiuSchool of Public Administration and Policy, Renmin University of China, Beijing 100872, China.ORCID 0000-0002-8179-0635
Xiaochong WeiSchool of Public Administration and Policy, Renmin University of China, Beijing 100872, China.ORCID 0000-0002-0357-7732
Longxin ZhangSchool of Public Administration and Policy, Renmin University of China, Beijing 100872, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sleep behaviors, particularly midday rest periods, represent an often overlooked yet potentially significant factor in workplace attitudes and experiences. Despite their common practice in many cultures, the relationship between these restorative breaks and employees' evaluations of their work environment remains underexplored in organizational research. This study investigates this relationship using longitudinal data from the China Family Panel Studies (CFPS), applying the work, non-work, and sleep framework (WNSF) as our theoretical foundation. Through a quasi-natural experimental approach, we discovered that midday rest periods positively influence workplace evaluations, but in a nuanced manner. Our findings reveal a pronounced inverted U-shaped relationship, suggesting that both insufficient and excessive duration of these breaks might diminish their benefits, while optimal duration maximizes positive outcomes. We strengthened these conclusions through rigorous methodological approaches including instrumental variable techniques, sensitivity analysis, treatment effect models, and matching models. The consistency of results across multiple analytical approaches corroborates our findings. This research both validates and extends the WNSF, highlighting the importance of strategic rest periods in organizational settings and offering practical insights for workplace policy development that can benefit both individuals and organizations in contemporary work environments.

Indexed as

job satisfactionnapnap durationNon-work and Sleep Framework (WNSF)quasi-natural experiment

Identifiers

PMID40564552
PMCPMC12190085

What OpenQuestion holds

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LicenceCC BY
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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.