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On Research: Do people’s work schedules put them at risk?

Journal of Safety Research contributors talk about their work


What’s your study about?

We were really wanting to know whether an employee’s schedule would predict the likelihood of an incident or near miss. Things like, “Are you working a day or night shift? How many of those shifts in a row are you working?” And then also working around holidays. There might be other variables, other things going on. We were really interested in, depending on your schedule, did that predict the likelihood there might be an incident or near miss? And if that were to be the case, then we know when employees might need more rest or when we need to allocate our resources to mitigate harm if there’s an increased chance of an incident.

What drove your interest in studying the topic?

For me personally, I used to work in automobile manufacturing – second-shift assembly line. One thing I learned from that: I was tired all the time. But sometimes, I would cover first shift and kind of alternate back and forth and, in addition to the fatigue, the work kind of changed between the shifts. So, when we were trying to get into more predictive safety analytics, that topic came up of how someone’s schedule might affect that.

Which findings stood out?

What we found is the more consecutive day shifts you work actually increases the likelihood of an incident, but the fourth consecutive day tended to be the biggest risk. But that pattern didn’t really carry over to night shifts. So working consecutive night shifts didn’t increase risk. Where we did see night shift coming up is that first and second night shift. When you go from a day shift to a night shift, that first and second day seem to be more likely for near misses to happen. More incidents and near misses occurred on the transition to night shift.

In what ways might your research affect workers?

Everyone has a schedule they’re working, right? And knowing when risk is more likely would allow you to change work schedules to minimize the risk, which, in turn, would potentially put less strain on our bodies if we were figuring out the optimal times of when we should be working. The only thing I would probably caution is, for each organization, it might be different, right? But I think looking at schedules would be important across all industries and all organization sizes.

What, if anything, surprised you about the results?

I was surprised that working consecutive night shifts didn’t increase the likelihood of an incident. Going into it, I thought for sure night shifts would be more likely. That goes to my earlier comment of, for every organization, it might be different depending on what their data are actually like.

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