Evidence map›Paper›PMID 39322583›Full record

ArticleIndustrial health2024

How changes in laughter predict work engagement and workaholism: reciprocal relationships among Japanese employees.

Akihito Shimazu, Keiko Sakakibara, Fuad Hamsyah, Michiko Kawada, Daisuke Miyanaka, Masahito Tokita

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Industrial health, 2024. 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

6 authors.

Akihito ShimazuFaculty of Policy Management, Keio University, Japan.
Keiko SakakibaraFaculty of Sociology, Toyo University, Japan.
Fuad HamsyahGraduate School of Media and Governance, Keio University, Japan.
Michiko KawadaCommerce and Economics, Chiba University of Commerce, Japan.
Daisuke MiyanakaFaculty of Policy Management, Keio University, Japan.
Masahito TokitaKeio Research Institute at SFC, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Laughter is related to better well-being in daily life. Previous cross-sectional research among employees showed a positive relationship between laughter and work-related well-being (i.e., work engagement). However, longitudinal and even bidirectional relationships have not been yet explored. This study thus investigated the longitudinal and reciprocal relationships of laughter, with work engagement and workaholism as positive and negative aspects of work-related well-being. Specifically, we conducted two-wave web-based surveys among Japanese employees via an Internet survey company with a one-year interval, and 855 valid data were analyzed. The hypotheses were then tested using structural equation modeling. The results showed that increases in laughter during the previous year were positively and negatively related to future work engagement and workaholism, respectively. In addition, through changes in laughter, the initial work engagement led to future work engagement (gain cycle), whereas initial workaholism led to future workaholism (loss cycle). These findings suggest that laughter and work-related well-being influence each other reciprocally rather than unidirectionally. This underlines the importance of studying reversed as well as regular causal effects in the relationship between laughter and employee well-being.

Indexed as

LaughterWork EngagementAdultBehavior, AddictiveCross-Sectional StudiesEast Asian PeopleFemaleHumansJapanMaleMiddle AgedSurveys and QuestionnairesGain cycleJapanese employeesLaughterLoss cycleReciprocal relationsWorkaholismWork engagement

Identifiers

PMID39322583
PMCPMC11611533

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.