Evidence map›Paper›PMID 42258556›Full record

ArticlePloS one2026

How work hours affect well-being: A target trial emulation.

Ballerina X S Chong, Chris G Sibley, Joseph A Bulbulia

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ballerina X S ChongSchool of Psychology, Victoria University of Wellington, Wellington, New Zealand.ORCID https://orcid.org/0000-0002-0206-0782
Chris G SibleySchool of Psychology, University of Auckland, Auckland, New Zealand.
Joseph A BulbuliaSchool of Psychology, Victoria University of Wellington, Wellington, New Zealand.ORCID https://orcid.org/0000-0002-5861-2056

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies link longer work hours to multiple dimensions of well-being, but correlations do not show what would happen if hours changed. Target-trial emulation addresses this problem by specifying the experiment we would like to run and then approximating it with observational data. Using three annual waves of the New Zealand Attitudes and Values Study (NZAVS, N = 24,579; 2020-2023), we estimate how 28 well-being outcomes would differ if the same cohort of pre-retirement adults worked 10 more or 10 fewer hours per week than observed. We compare what would happen if weekly hours shifted up by 10 or down by 10 with what actually occurred, after accounting for dropout, using machine-learning methods to adjust for baseline differences. Increasing work hours by 10 most clearly raises fatigue and reduces sleep; body mass index (BMI) and perceived physical health also shift adversely but are more sensitive to residual confounding, while perceived support increases slightly but remains confounding-sensitive. Decreasing work hours by 10 most clearly lowers fatigue; BMI and perceived physical health also shift favourably but are likewise more sensitive to residual confounding. Most outcomes show little movement under either policy, and the downward shift is better supported by the data. Naive baseline associations are broader, larger, and sometimes reversed in sign, whereas sensitivity analyses (E-values) indicate that the clearest fatigue effects are robust to moderately strong residual confounding. Under the stated assumptions, work-hour shifts affect recovery and perceived physical health more than broad well-being.

Indexed as

Work Schedule ToleranceAdultBody Mass IndexFatigueFemaleHumansMaleNew ZealandPsychological Well-BeingSleepWorking Conditions

Identifiers

PMID42258556
PMCPMC13245862

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.