Abstract
Objectives
The objectives of this research were to test the impacts of three shift lengths (8-, 10-, and 12-hour) on performance, health, safety, quality of life, sleep, fatigue, alertness, off-duty employment, and overtime among police.
Methods
This study consisted of a randomized block experimental design. There were 275 participating officers from two large police departments. Data were collected as part of a multi-site clinical trial for which we employed the same protocols in both sites. The blocks included site and time of day of the shift. Unique measures of work performance, safety, and fatigue were collected using laboratory-based simulations collected during the end of the shifts, and self-report instruments were used to capture other outcomes such as health and quality of life. The analysis model we employed was a block randomized ANCOVA in which the pre-test dependent measures served as the covariate.
Results
The results indicated that those working 10-hour shifts had a significantly higher quality of work life (f = .16) and averaged significantly more sleep (f = .19) than those on 8-hour shifts. Furthermore, those working 8-hour shifts averaged significantly more overtime (f = .42) than did those assigned to 10- and 12-hour shifts. In addition, officers working 12-hour shifts experienced greater levels of sleepiness (f = .20) and reported lower levels of alertness (f = .21) at work than officers on 8-hour shifts.
Conclusions
There do not appear to be any significant health, safety, or performance problems associated with compressed work week schedules in policing. Indeed, the implementation of 10-hour shifts may be a viable alternative to traditional 8-hour schedules considering the findings of this study. It is important to note that the benefits associated with 10-hour shifts did not inure to the 12-hour shifts. Although our study did not reveal any significant effects associated with objective measures of fatigue across shifts, the implementation of 12-hour shifts should be done only after careful consideration of some of the potential concerns. Limitations of this study include lack of information regarding the methods and costs associated with implementation of compressed schedules, and the low level of reliability for driving and shooting simulation exercises. Future research should examine the impact of overtime hours on fatigue, safety, and performance, and ways to more effectively regulate hours of work in policing.
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Notes
These data are from the 2007 Law Enforcement Management and Administrative Statistics, Bureau of Justice Statistics (Reaves, personal communication, September 29, 2010).
179 were randomly assigned, and 51 did not follow through with treatment.
In this case, the rater was an experienced law enforcement officer with a PhD, who had received formalized training by personnel from the B-PAD® Group, Inc.
IES has released various versions of this simulator. In the Arlington, Texas, police department, they were using the version called the RANGE 3000®, which is functionally equivalent to the newer simulator called the MILO® that we used in Detroit (provided by IES for the purposes of the study).
In Detroit, two officers are assigned to one car, generally speaking. As a result, some operational issues arose, which required two individuals to be switched to a different condition by their supervisors. While this was highly discouraged, it was necessary from an operational standpoint. In two districts, on a particular shift, there were an uneven number of officers assigned to 12-hour shifts. In order to keep the extra officer in the 12-hour condition, we allowed a person on the 8-hour to be reassigned to the 12-hour condition. In another district, an officer applied to work alone and because the officer’s request was accommodated, he had to be moved out of the 12-hour shift and on to the 8-hour shift. In Detroit, after dark, departmental policy requires two officers per vehicle. Because of the time of year and start time of this officer’s shift, it was not possible for this officer to work the 12-hour tour because he would be working alone after dark.
Fleiss (1982) actually suggests a more conservative alpha level of p < .01
Cohen’s effect size f index formula is the square root of the eta squared (η2 ) divided by 1 minus η2 (Cohen 1988, p. 280-288). η2 is calculated as the ratio of the effect variance (SSeffect) to the total variance (SStotal) − η2 = SSeffect / SStotal. The value for the SStotal in the formula includes the SS for each of the effects and the error term, but does not include the SS for the intercept in the GLM models. Note the η2column in one version of SPSS provided only partial η2output. As such, η2 was manually calculated.
While we recognize that the Cronbach’s alpha levels for the shooting performance and driving simulator were low (.43 and .58, respectively), we felt that the items used in each measure were an accurate reflection of the dependent variable of interest in the study. The low alphas on the two scales may be attributed to the sample’s homogeneity and the results may be justified for use in the analyses (see Bernardi 1994). It is important to note that since many of the outcome measures were derived from self-reported items that assessed officers’ personality, temperament, and demeanor, we examined whether officers were responding to the items honestly or whether they were attempting to present themselves in a more favorable way. Our survey included a 33-item scale developed by Crowne and Marlowe (1960) to identify the extent to which officers exhibited this social desirability bias, allowing us to pinpoint any outlying participants and remove them from our analysis. All of the participating officers fell within acceptable ranges and, as a result, none of the participants’ data were excluded on the basis of a social desirability bias in responding to the survey items. For more details regarding items used in the study see Amendola et al. (2011, in press).
For QWL, there was also a significant interaction between shift length and site, F(2,197) = 4.76, p = .010. In an effort to better understand which comparisons were accounting for the interaction effect between treatment and quality of work life, we examined within-site main effects. In Detroit, while there were no statistically significant differences, the effect size was small to medium (f = .19); those on the 8-hour shifts had the lowest mean level of QWL. In Arlington, the main effect of shift length was F(2,125) = 8.49, p = .000, which translates to an effect size of f = .31 (medium). The 10-hour group reported a significantly higher quality of work life (mean = 3.08) as compared to those in the 8-hour (mean = −0.63, p = .001) and 12-hour (mean = −0.13, p = .004) groups. It is important to note that those participants working 8-hour shifts in both sites reported the lowest quality of work life.
There was also a very significant treatment by site interaction for level of alertness, F(2,132) = 6.01, p = .003. In an effort to better understand which comparisons were accounting for the interaction effect between treatment and level of alertness, we examined within-site main effects. In Detroit, there was a medium to large effect size (f = .34), but the comparison did not reach statistical significance. The limited sample size in Detroit makes this finding hard to interpret. However, it appears that those working 8-hour shifts in Detroit are more alert than either those on 10s or 12 s, suggesting decrements in alertness for compressed schedules. On the other hand, in Arlington, the main effect of shift length was F(2,91) = 8.47, p = .000, with an effect size of f = .29 (medium). Those on 12-hour shifts were significantly less alert (mean = 6.10 hours) than those on the 10-hour (mean = 6.74, p = .000) and 8-hour shifts (mean = 6.53, p = .037), showing a clear disadvantage for those working 12-hour shifts, but not for 10-hour shifts.
There was also a significant interaction effect for shift length by study site when considering amount of overtime, F(2,145) = 5.86, p = .004. The analysis revealed that while officers on 8-hour shifts in both sites worked the most amount of overtime, those in Detroit worked considerably more (mean = 8.76) than those in Arlington (mean = 2.74 hours). In an effort to better understand which comparisons were accounting for the interaction effects, we examined within site main effects of the treatment. Indeed, in both sites, there was a significant difference across groups. In Detroit, the main effect of shift length was F(2,44) = 7.39, p = .002, which translates to an effect size of f = .53 (large). The 8-hour group had significantly more overtime (mean = 9.01 hours) than both the 10-hour group (mean = 1.49, p = .002) and 12-hour group (mean = 3.02, p = .013), indicating that either type of compressed schedule in Detroit results in less overtime than for 8-hour shifts. And it is quite clear that those in the 10-hour group worked substantially less overtime than those on 8-hour shifts in Detroit. In Arlington, the main effect of shift length was F(2,104) = 3.03, p = .053, which translates to a medium effect size (f = .25). Whereas the 8-hour group had more overtime (mean = 2.54 hours) than those on the 10-hour shift (mean = 0.75, p = .064), and 12-hour group (mean = 1.04 hours, p = ns), the first comparison approached statistical significance and the latter was not statistically significant.
Although the mean level of sleep for those on 12-hour shifts was higher than for those on 8-hour shifts, these differences did not reach statistical significance.
The extreme outlier was removed from our analysis so as not to bias the results.
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Acknowledgments
We wish to thank collaborators Anneke Heitmann, PhD; Jon Shane, PhD; Christopher Ortiz, PhD; and Eliab Tarkghen for their significant contributions to this work who are co-authors of our complete technical report of the National Institute of Justice and available at www.ncjrs.org (Amendola et al., 2011, in press).
No project of this magnitude would be possible without the participation of dedicated and forward-thinking leaders in law enforcement agencies. As such we wish to thank Chief (ret.) Ella Bully-Cummings of the Detroit (MI) Police Department and Chief Theron Bowman, PhD of the Arlington (TX) Police Department for their participation in the study, and very much appreciate all of the officers who participated on the part of those agencies.
We also acknowledge the U.S. Department of Justice, National Institute of Justice for providing funding for this experiment under grant #: 2005-FS-BX-0057. Specifically, our thanks go to Brett Chapman, PhD, Thomas Feucht, PhD, Winifred Reed, and Director John Laub, PhD. Former NIJ personnel Maggie Heisler, Akiva Liberman, PhD, and Bryan Vila, PhD were instrumental to the research.
Finally, we are appreciative of former staff, fellows, and interns of the Police Foundation.
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Amendola, K.L., Weisburd, D., Hamilton, E.E. et al. An experimental study of compressed work schedules in policing: advantages and disadvantages of various shift lengths. J Exp Criminol 7, 407–442 (2011). https://doi.org/10.1007/s11292-011-9135-7
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DOI: https://doi.org/10.1007/s11292-011-9135-7