An analysis of the work schedules of Great Barrier Reef pilots

Results and Discussion

A tour of duty consists of one or more work assignments and represents a continuous period during which the pilot alternates between working at sea and living ashore. Time spent ashore during a tour is frequently spent away from home, living in alternate accommodation such as hotels, motels or pilot houses. Following a tour of duty, the pilot returns home and usually takes a somewhat extended break from work (i.e. 5 or more days off work). For a complete definition of a tour of duty see Table 3.0.

4.1 Number of Tours of Duty

Figure 4.0 displays the mean number of tours of duty per pilot in the three time periods, for each company separately. Table 4.0 summarises the analysis of this data in terms of differences between companies and between the three 6-month periods. There were significant differences between the companies in the mean number of tours performed. Post hoc analysis indicated Company B personnel undertook more tours (5.68) than either Companies A (4.76) or C (4.11), which were statistically similar. The small number of tours recorded for Company C in the first 6-month period of the work schedule files relates to the establishment of this pilot company during this time (Figure 4.0).

Assessment of the number of tours of duty performed per pilot over the three 6-month periods revealed no significant differences over the 18 months. This pattern was exhibited by each of the pilot companies (Table 4.0).

Given that the central focus of the present study is to examine the fatigue aspects of the work practices of Great Barrier Reef pilots, it was considered important to identify situations where personnel undertook considerably more tours than depicted by average company figures. Hence, Figures 4.1a and Figure 4.1b present the number of tours of duty per pilot per period for Companies A and B respectively as frequency distributions. Clearly identifiable from these figures is that most pilots performed between 4 and 7 tours of duty per 6-month period. However, there was a minority group of pilots in both companies who undertook considerably more tours of duty per period. As it is those pilots performing greater than average amounts of work who are most likely to be susceptible to fatigue and decreased performance (Iskra-Golec et al. 1996; Rosa et al. 1989; Spurgeon et al. 1997), monitoring of extreme levels of work should be undertaken

Other differences noted in the frequency distributions are that considerably more pilots from Company B performed tours in the upper end of the distribution (e.g. between 8 and 10) than their colleagues in Company A. The small number of pilots in Company C made it inappropriate to show the distribution for this group.

Figure 4.0 Mean number of tours of duty per pilot, by company and period (1 Jan 1996 - 30 June 1997)

Note: Data analysis based on n values shown in Methods (Section 3.2).

Table 4.0 Analysis of the mean number of tours of duty per pilot (1 Jan 1996 - 30 June 1997) (1)

Notes

1. Results of full two-way analysis of variance (ANOVA) model including company and period effects. p < 0.01 considered statistically significant.
2. Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01) n/a Post hoc testing not performed when main effects not significant.

Company (Main Effect). This term measures whether or not there is a difference between companies averaged across the three time periods.

Period (Main Effect). This term measures whether or not there is a difference between the periods averaged across the companies.

Company * Period Interaction. This term measures whether or not the difference between the companies is the same in each period. Equally, it measures if the difference between periods is the same for each company. When the interaction is statistically significant there is little interest in the main effects. In this case averages over one of the factors ignore important variations.

Figure 4.1a Frequency distribution - Number of tours of duty per pilot - Company A

Figure 4.1b Frequency distribution - Number of tours of duty per pilot - Company B

4.2 Duration of Tours of Duty

The mean duration of tours across the three 6-month periods for each of the companies separately is illustrated in Figure 4.2. Analysis of between company and time period differences in this data is displayed in Table 4.1. Significant between company differences in mean tour duration existed and relate to the shorter tours performed by Company C (2.8 days) compared with Companies A (18.0 days) and B (17.2 days), which were similar. The considerably shorter duration of tours performed by pilots in Company C reflects the single operational region of this group (i.e. Hydrographers passage only). In contrast, pilots in Company A and B operate in three pilotage regions (Hydrographers passage, the Inner Route and the Great North East Channel) and hence receive a greater volume of work and tend to spend longer periods away from home.

When presenting the data for each company as frequency distributions (Figures 4.3a, Figure 4.3b and Figure 4.3c), it is evident that for both Companies A and B, tour duration varied greatly. Some tours were as short as 1 day in duration while other tours extended up to 35 days in duration. In contrast, much less variability existed in the data for Company C, with all tours performed by this company during the analysis period ranging between 1 and 15 days in duration. These inter-company differences are consistent with the mean data and most likely reflect the distinct operational differences between the pilotage groups.

Several possible factors may have contributed to the wide range of variability which existed in tour duration of Companies A and B. Firstly, it is likely that to a certain extent, tour duration reflects work availability. When shipping demands decrease and consequently, work availability is low, it could be anticipated that shorter tours would be engaged in whereas during extremely busy periods, tour duration would be expected to correspondingly increase.

Secondly, it is possible that the pilot’s location of residence may influence tour duration. For those pilots living in or close to operational regions, shorter tours of duty may be performed given the greater accessibility and convenience of returning home between work assignments. On the other hand, pilots who reside distant from their work locality may undertake longer tours of duty due to the additional expense and time associated with returning home.

Thirdly, tour duration may be related to the amount of notification pilots receive prior to beginning work. In situations when pilots are called upon at short notice to perform unexpected work during busy periods, tours of duty may be decisively shorter than when pilots have been informed with ample time to prepare themselves for upcoming work assignments.

Across the three 6-month periods there were significant differences in the duration of tours (Table 4.1). Post hoc analysis revealed that tours during the second 6-month period were significantly longer (13.98 days) than tours during the third six month period (12.01 days). No clear conclusion with regards to the first period was obtained from post hoc testing. As post hoc analysis incorporates sample size and variance, the lack of conclusions for this period may be related to these factors. The finding that mean tour duration increased in the second period applied to all of the companies, and may suggest that the total volume of shipping in all operational regions increased during this time.

To further explore the potential fatigue aspects of the work practices of Great Barrier Reef pilots, total time spent on tours of duty per pilot was determined (Table 4.0 and Table 4.1). During each 6 month period, it was evident that Company A pilots spent ~ 81 days on tour, Company B pilots ~ 102 days and Company C pilots ~ 11 days. Caution should be taken when interpreting these findings as at this stage of the analysis no breakdown of the amount of time spent working and resting during a tour has been incorporated. However, it is possible the extra 21 days of tour time per 6 month period for Company B personnel compared with Company A pilots, may contribute to increased fatigue and warrants further consideration. The work practices of Company C seem to be least problematic in terms of fatigue potential related to tour number and duration.

Figure 4.2 Mean duration of tours (days), by Company and period (1 Jan 1996 - 30 June 1997)

Note: Data analysis based on n values shown in Methods (Section 3.2).

Table 4.1 Analysis of the mean duration of tours of duty (days) (1 Jan 1996 - 30 June 1997) (1)

1. Results of full two-way analysis of variance (ANOVA) model including company and period effects. p < 0.01 considered statistically significant.
2. Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01).

Company (Main Effect). This term measures whether or not there is a difference between companies averaged across the three time periods.

Period (Main Effect). This term measures whether or not there is a difference between the periods averaged across the companies.

Company * Period Interaction. This term measures whether or not the difference between the companies is the same in each period. Equally, it measures if the difference between periods is the same for each company. When the interaction is statistically significant there is little interest in the main effects. In this case averages over one of the factors ignore important variations.

Figure 4.3a Frequency distribution - Duration of tours (days) per period - Company A

Figure 4.3b Frequency distribution - Duration of tours (days) per period - Company B

Figure 4.3c Frequency distribution - Duration of tours (days) per period - Company C

4.3 Duration of Breaks between Tours of Duty

Breaks between tours potentially represent time for pilots to spend at home relaxing and recuperating between one tour of duty and another. Previous research based on populations involved in home and away occupations indicates that such breaks provide the opportunity to spend highly valued time with family and friends (Parker et al. 1997; Sutherland & Flin 1989).

For each of the pilotage companies the mean duration of breaks between tours in the three 6-month periods are displayed in Figure 4.4. An analysis of the company and period differences in this data is shown in Table 4.2. Significant differences existed, with pilots from Company C experiencing the longest tour breaks (28.0 days), followed by pilots from Company A (19.5 days) and then pilots from Company B (12.8 days). This pattern of results is also clearly evident when the data is presented as frequency distributions (Figure 4.5a, Figure 4.5b and Figure 4.5c). The distribution curve for Company C is markedly skewed (Figure 4.5c) indicating that the majority of tour breaks were 20 days or longer in duration, whereas relatively few tour breaks experienced by Company B personnel exceeded 15 days duration (Figure 4.5b). These results are consistent with the findings reported in section 4.2 showing that during each 6 month period, Company C pilots spent less time on tour whereas Company B pilots spent more time on tour.

That a considerable number of pilots working for Company B live in or adjacent to the operational region (North and Central Queensland) may be one explanation for the significantly shorter duration of tour breaks experienced by this group. It is possible that pilots living in closer proximity to the working regions may be more frequently called upon to do work at short notice. Consequently, breaks between tours may be reduced, and tours of duty were not as clearly delineated for those living close to work locations.

There were no significant differences across the three time periods in the length of breaks (Table 4.2). This result was observed for each company.

Figure 4.4 Mean duration of breaks between tours (days), by Company and period (1 Jan 1996 - 30 June 1997)

Note: Data analysis based on n values shown in Methods (Section 3.2).

Table 4.2 Analysis of the mean duration of breaks between tours of duty (days) (1 Jan 1996 - 30 June 1997) (1)

• (1) Results of full two-way analysis of variance (ANOVA) model including company and period effects. p < 0.01 considered statistically significant.
• (2) Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01) n/a Post hoc testing not performed when main effects not significant.

Company (Main Effect). This term measures whether or not there is a difference between companies averaged across the three time periods.

Period (Main Effect). This term measures whether or not there is a difference between the periods averaged across the companies.

Company * Period Interaction. This term measures whether or not the difference between the companies is the same in each period. Equally, it measures if the difference between periods is the same for each company. When the interaction is statistically significant there is little interest in the main effects. In this case averages over one of the factors ignore important variations.

Figure 4.5a Frequency distribution - Duration of tour breaks (days) per period - Company A

Figure 4.5b Frequency distribution - Duration of tour breaks (days) per period - Company B

Figure 4.5c Frequency distribution - Duration of tour breaks (days) per period - Company C

4.4 Percent of Tour Time spent on Work Assignments

To assess the relative amount of time spent undertaking work assignments (ship time) while on a tour, the percent of tour spent on assignment was determined. Figure 4.6 illustrates this information for each company and time period separately, while Table 4.3 summarises the analysis of company and period differences in this data. On average, Company C pilots spent 72% of tours on work assignments whereas pilots from Companies A and B spent 56% and 53% respectively. However these differences between the companies failed to reach statistical significance. This may have been related to the large standard error associated with Company C’s data.

By presenting percent of tour spent on work assignments as frequency distributions (Figure 4.7a, Figure 4.7b and Figure 4.7c), further insight into the company mean figures is obtained. Data for both Companies A and B presents classical bell shaped curves, thereby suggesting that in the majority of situations approximately half of tour time is spent working on assignments and the other half is spent ashore resting and travelling to the next port location. In contrast, data for Company C presents as two distinct groups. Firstly, there were a substantial number of tours in which 90 - 100% of tour time was spent on assignments, whereas secondly, a number of tours during the second and third time periods involved only 10 - 40% of tour time being spent on assignments. Hence, tours of Company C tended to be much more variable, with some tours involving most, if not all time being spent on work assignments while other tours involved relatively little time being spent on the ship.

That Company C is only a small, newly established company operating in a single pilotage region undoubtedly contributes to these findings. Thus, in situations when only a single work assignment is to be performed during a tour, it is most likely that pilots would spend very little time ashore before returning home thereby accounting for those tours where 90 - 100% of tour time was spent on assignment. On the other hand, if pilots undertook 2 or more work assignments during a tour, the combination of a relatively short transit time through Hydrographers Passage, the need to meet minimum rest requirements between work assignments and the need to wait ashore for the next ship would account for those tours in which only 10 - 40% of tour time was spent working.

The bell shaped distributions presented for Companies A and B most likely relates to the greater number of pilots working for these companies, the more extensive operating regions and the larger volume of work performed. Additionally, the similarity between these two companies in terms of relative amount of tour time spent on work assignments reflects their similar operational regions.

There were no significant differences in the percent of tour time spent on work assignment across the three 6 month periods (Table 4.3). This temporal pattern was observed for all three companies.

Figure 4.6 Mean percent of tour time spent on work assignments, by company and period

Note: Data analysis based on n values shown in Methods (Section 3.2).

Table 4.3 Analysis of the mean percent of tour spent on work assignments (1 Jan 1996 - 30 June 1997) (1)

1. Results of full two-way analysis of variance (ANOVA) model including company and period effects. p < 0.01 considered statistically significant.
2. Results of Tukey’s Studentised Range Test for post-hoc differences (Type I Experimental Error Rate = .01) n/a Post hoc testing not performed when main effects not significant.

Figure 4.7a Frequency distribution - Percent of tour time spent on work assignments per period - Company A

Figure 4.7b Frequency distribution - Percent of tour time spent on work assignments per period - Company B

Figure 4.7c Frequency distribution - Percent of tour time spent on work assignments per period - Company C

4.5 Summary

One of the principle issues to be investigated by the present study is how the work practices of Great Barrier Reef pilots impact on fatigue. In line with this focus, an assessment of the number and duration of tours of duty, length of breaks between tours and percent of tour time spent on work assignments was undertaken. Clearly evident from these assessments was that Company C pilots performed significantly shorter tours, had longer rest breaks between tours and spent a greater percentage of tour time on work assignments, than pilots from Companies A and B. These findings most likely relate to the distinct differences in operations of Company C. This company is only a small, newly established company, operating in only a single pilotage region. As a consequence, work tends to be somewhat more sporadic, as is reflected by the present findings.

More meaningful inter-company comparisons can be made between Companies A and B, as these two companies have similar operations. With regards to mean data it was apparent that pilots working for Company B spend more time on tours and receive less time off between tours during each 6-month period, as compared to their colleagues working for Company A. Given that longer work hours and shorter rest breaks may place personnel at a greater risk of experiencing fatigue (Iskra-Golec et al. 1996; Rosa et al. 1989; Spurgeon et al. 1997), these findings warrant further examination. Caution should be observed when making judgments regarding the impact of fatigue based solely on the characteristics of tours of duty, as many other features of work patterns influence the fatigue state of an individual. Some of these features will be addressed in the following sections. Companies A and B recorded similar figures when percent of tour spent on work assignments was analysed, thereby confirming the similar operations of these two groups.

While mean data is useful in providing a general description of the data set, it fails to highlight the variability which exists within the data. For this reason, some of the measures examined in the present study have been presented as frequency distributions. This enables the identification of situations in which pilots are undertaking greater than the average amount of work, and hence, have an increased risk of fatigue development.

When the number and duration of tours per pilot per 6 month period and length of breaks between tours were presented as frequency distributions, it was evident that there were several pilots from Companies A and B who performed a considerably greater than average number of tours and experienced shorter breaks between tours during the analysis period. Such workloads are associated with a heightened fatigue potential. Thus, in order to ensure sufficient recuperation between tours of duty and prevent the development of fatigue, monitoring of extreme levels of work should be undertaken. The small company size and irregularity of work performed by Company C resulted in the frequency distributions for this group showing large amounts of variability.

Changes across time were evident in tour duration, with longer tours being undertaken during the second time period. This finding was observed for all of the companies suggesting that the total volume of shipping increased during this period.

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