Project Summary
This is the only experimental study to examine the health and well-being effects of a shift to more stable schedules for hourly workers. The project team conducted a natural experiment to evaluate the health effects of targeted efforts to change employer scheduling practices that provide hourly workers with greater schedule stability, predictability, adequacy, and control.
Research Questions/Aims
- How are schedule stability, predictability, control, and adequacy related to employee health and work-life conflict, controlling for relevant store and individual characteristics?
- Did the Stable Schedules Study (SSS) intervention improve the health and well-being of hourly Gap employees?
Actionability
- Inform policymakers and businesses on whether and how stable scheduling and similar initiatives impact health, wellbeing, and other outcomes of low-income hourly retail workers, with the potential to reduce health disparities.
Results
Worker experiences before intervention implementation:
- 47% of workers reported that their work schedule interfered with their sleep.
- 51% of workers reported at least moderate food insecurity in the past month.
- 26% were late on utility payments in the past three months.
- 19% delayed going to the doctor or getting prescriptions filled because of financial concerns in the past three months.
Effects of the intervention:
- Self-rated sleep quality improved by 6-8% on average as a result of the intervention.
- The effects of the intervention on other health outcomes vary by subgroup. For example, the intervention reduced stress among parents and workers holding a second job.
Outcomes
Health: general health, perceived stress, psychosomatic health, psychological states of mind, schedule interferences in health, food insecurity
Other: general work-life conflict, financial hardship, supervisor support
Methodology
The investigators used a cross-sectional regression model to estimate whether there were significant differences in the health status of different classes of employees such as full-time/part-time and seniority. A generalized linear mixed model approach was used where the two time waves (baseline and post-intervention) were nested within store employees who were nested within the treatment and control stores.
