Interdisciplinary

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

AI Insight

This study used three years of survey data from 24,579 New Zealand adults to estimate what would happen to well-being if people worked 10 hours more or less per week. Using statistical methods that mimic experimental trials, researchers found that increasing work hours most clearly raised fatigue and reduced sleep, with possible negative effects on BMI and physical health, while decreasing hours most clearly lowered fatigue. Most other well-being measures showed little change under either scenario, and the effects were smaller and more specific than simple correlations suggested.


The findings suggest that debates about work-hour policies should focus on fatigue and physical recovery rather than assuming broad well-being improvements. The study demonstrates that observational data can be analyzed more rigorously to approximate what would happen under different work-hour policies, helping inform workplace regulations and organizational decisions.


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

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.

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