Elsevier

Applied Ergonomics

Volume 42, Issue 2, January 2011, Pages 210-213
Applied Ergonomics

Performance on a simple response time task: Is sleep or work more important for miners?

https://doi.org/10.1016/j.apergo.2010.06.010Get rights and content

Abstract

The purpose of the current study was to investigate the impact of work- and sleep-related factors on an objective measure of response time in a field setting. Thirty-five mining operators working 12-h shift patterns completed daily sleep and work diaries, wore activity monitors continuously and completed palm-based psychomotor vigilance tests (palmPVT) at the start and end of each shift. Linear mixed models were used to test the main effects on response time of roster, timing of test, sleep history and prior wake. The time at which the test occurred was a significant predictor of response time (F3,403.4 = 6.72, p < .01) with the end of night shifts being associated with significantly slower response times than the start of night shifts, and the start or end of day shifts. Further, the amount of sleep obtained in the 24 h prior to the test was also a significant predictor of response time (F3,407.0 = 3.05, p < .01). The results suggest that, as expected, the end of night shift is associated with changes in response time indicative of performance impairments. Of more interest however is that immediate sleep history was also predictive of changes in response time with lower amounts of prior sleep related to slower response times. The current data provides further evidence that sleep is a primary mediator of performance, independent of roster pattern.

Introduction

Shiftwork, particularly night work, is associated with an increased risk for incident and accident (Akerstedt, 1995, Dinges, 1995). Specific features of shiftwork patterns that are thought to contribute to increased risk include extended shifts, night work and consecutive shifts. For example, the risk of a fatal accident increases significantly beyond 9 h at work (Nachreiner et al., 2000), and accident risk after 12 h on shift is twice that seen after 8 h (Folkard and Tucker, 2003). Night shift, particularly the end of night shift, is also reported to be a high-risk time (Axelsson et al., 1998, Folkard and Tucker, 2003, Rosa and Bonnet, 1993) and is associated with a range of performance impairments (Folkard, 1997, Jay et al., 2006, Monk et al., 1997, Muller et al., 2008, Rollinson et al., 2003). Finally, the number of consecutive shifts worked is also a risk factor for accidents and incidents (Folkard and Tucker, 2003). Twelve-hour shift rosters, particularly those involving night shifts contain each of these elements – long hours, night work and strings of shifts.

A major advantage of 12-h shifts is that they compress the working week into fewer days, thus providing more rest days away from work. In addition, the rest days are often grouped together to provide blocks of time off. While extended blocks of days off are attractive for employees (Smith et al., 1998), there may be negative repercussions for performance and safety when the number of consecutive shifts is increased. The number and timing of rest days is an important component of the shift pattern, particularly in 12-h rosters (Tucker et al., 1999) and insufficient and/or infrequent recovery days may cause impairment due to cumulative sleep loss.

A 12-h break provides for approximately 6 h of sleep depending on the start time of the break (Roach et al., 2003). Current knowledge suggests that 6 h of sleep per night is a threshold below which performance becomes significantly impaired due to cumulative sleep restriction (Belenky et al., 2003, Van Dongen et al., 2003). Analysis of accident and error data confirm this hypothesis such that sleep loss associated with work hours is indeed predictive of impaired performance (Dorrian et al., 2004a, Dorrian et al., 2004b, Dorrian et al., 2008, Lockley et al., 2004). Thus, in any investigation of work hours and waking function, sleep history is an essential component.

Each of the work factors discussed, long shifts, nights, and consecutive shifts, is associated with circadian misalignment, extended wakefulness, inadequate sleep, or a combination thereof. The current study therefore looked at the impact of both work- and sleep-related factors on an objective measure of performance in operators working different 12-h shift patterns. It was expected that both work- and sleep-related factors would be associated with performance changes in this population and that roster type would mediate performance due to different distribution of rest days.

Section snippets

Participants

The study was conducted in two phases in 2005 and 2007. Initially, a total of 111 participants across four different roster patterns were recruited to the study – 54 in phase 1 and 57 in phase 2. Individual datasets were not included in the analysis if individuals did not complete all aspects of the data collection, if they worked a pattern significantly different to one of the main rosters (sick/annual leave, overtime etc) or if they withdrew from the study. The dataset used in the current

Work-related factors

As illustrated in Fig. 1, the 7 × 4 roster was associated with lowest RRT scores (indicating highest performance impairment), followed by the 14 × 7, then the 4 × 4. Analyses indicated that these differences were not significant (F2,34.1 = 2.69, p = 0.08). There was a main effect of test time (F3,402.6 = 8.25, p < .001) on RRT. Pairwise comparisons indicated that RRT was significantly lower during tests conducted at the end of night shifts compared to any other shift/timing combination indicating poorer

Discussion

The study examined performance on a psychomotor vigilance task in three different rosters in the same mine site. As expected, response times were slower at the end of night shifts compared to any other testing time. However, there were no significant differences in response times across roster. Sleep history was a significant predictor of response time in this group: Tests conducted with less than 6 h of prior sleep produced slower response times than those conducted following more than 7 h of

Acknowledgements

The authors would like to acknowledge the participating organisation and individuals for their contribution to the study.

References (35)

  • J. Axelsson et al.

    Effects of alternating 8- and 12-hour shifts on sleep, sleepiness, physical effort and performance

    Scandinavian Journal of Work and Environmental Health

    (1998)
  • G. Belenky et al.

    Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose–response study

    Journal of Sleep Research

    (2003)
  • D. Dawson et al.

    Work hours and reducing fatigue-related risk: good research vs good policy

    JAMA

    (2005)
  • D.F. Dinges

    An overview of sleepiness and accidents

    Journal of Sleep Research

    (1995)
  • D.F. Dinges et al.

    Microcomputer analyses of performance on a portable, simple visual RT task during sustained operations

    Behavior Research Methods, Instruments and Computers

    (1985)
  • J. Dorrian et al.

    Train driving efficiency and safety: examining the cost of fatigue

    Journal of Sleep Research

    (2007)
  • J. Dorrian et al.

    A prior sleep/wake model of fatigue-related accident risk in truck drivers

    Journal of Sleep Research

    (2004)
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