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146 REFERENCE SUMMARIES Reviewers: Dianne Davis, Alison Smiley Title: Arnedt, J.T., Wilde, G.J.S., Munt, P.W., and Maclean A.W. "How do prolonged wakeful- ness and alcohol compare in the decrements they produce on a simulated driving task?" (2001). Accident Analysis and Prevention, Vol. 33, 337344. Abstract: This report looks at a comparison of the effects of alcohol with those of prolonged wake- fulness on a simulated driving task. Eighteen males (18 to 35 years old) with BACs of 0.00, 0.05 and 0.08% drove a simulator for 30 minutes. Dependent measures included subjective sleepiness before and after the driving task as well as simulator measures (e.g., tracking, speed deviation, etc.). Tracking variability, speed variability and off-road events increased with BAC. In contrast, speed deviation (calculated as the deviation from the speed limit) decreased as a result of subjects driving faster. With increased BAC, ratings of sleepiness increased and were higher following the driving task. The authors compared the results of this study with a previous study by Arnedt and Maclean (1996), examining simulated driv- ing performance during one night of prolonged of wakefulness. They found that "mean tracking, tracking variability, and speed variability 18.5 and 21 h of wakefulness produced changes of the same magnitude as 0.05 and 0.08% blood alcohol concentrations, respec- tively." In addition, they found that alcohol consumption produced changes in speed devi- ation and off-road occurrences of greater magnitude than the corresponding levels of pro- longed wakefulness. Methodology: Eighteen males between 19 and 35 years old, who met the inclusion criteria (e.g., neither extreme morning nor evening type) were recruited for this study at Queen's University in Kingston, Ontario. On the nights before the first experimental day and for the duration of the study, subjects were instructed to go to bed between 2300 and 0100 and to get up between 0700 and 0900. The Stanford Sleepiness Scale (SSS) and a Modified Stanford Scale (MSS) were used as the subjective dependent measures for the study. Performance was assessed using a York Driving Simulator. A variety of dependent measures were col- lected using the simulator such as speed deviation, off-road incidents, etc. Subjects were given a training session prior to the start of the experiment to orient them to the driving sim- ulator as well as other aspects of the study. They were then informed of their condition allo- cation (0.00, 0.05, and 0.08% BAC) and underwent all the three test conditions at the same time of day either 1400, 1700 or 2000. Experimental days consisted of brief training ses- sions to re-familiarized subjects with the driving simulator, followed by consumption of drinks mixed so that they would attain peak BACs of 0.0, 0.05 or 0.08%. Subjects were given one-half hour to ingest the drinks, and at 30 minutes post-ingestion, completed the SSS and the MSS and then drove the simulator for 30 minutes. The scales were also com- pleted after the 30-minute simulator task. Subjects in Arnedt and Maclean's (1996) study underwent one night of prolonged wakefulness and drove on the driving simulator at 2400, 0230, 0500, and 0730. For 0.05 and 0.08% BAC, the most comparable test times in the Arnedt and Maclean (1996) study were 0230 (18.5 h of wakefulness) and 0500 (21 h of wakefulness), respectively. Scope of Work: Comparison of effects of alcohol with those of prolonged wakefulness on driving. Sample Size: 18 males (students) between 19 and 35 years of age (Note: Report does not indicate the number of subjects in Arnedt et al.'s (1996) comparison study). Industry Sector: n/a Major Limitations: The driving situations were limited to situations in which there was no other traffic present. The authors noted "had drivers been exposed to the perceptual and judgment demands of

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147 dealing with the greater hazards created by the presence of other traffic, it is possible that driv- ing performance would have differed under prolonged wakefulness and alcohol conditions." Findings: 1. ". . . wakefulness prolonged by as little as 3 h can produce decrements in the ability to maintain speed and road position as serious as those found at the legal limits of alcohol consumption." 2. The ratings of subjective sleepiness increased as alcohol dosage increased for the SSS and Factors 1 (`an energic or activating factor') and 2 (`related to consciousness, sleepi- ness and a loss of control over remaining awake') of the MSS. Subjects rated themselves as more sleepy after the driving task than before on each of these scales. No significant time-of-day effects were found for the subjective sleepiness measures. 3. With increased alcohol dose tracking variability, speed variability and number of off- road accidents increased. Speed deviation from the posted speed decreased as subjects drove faster. 4. Performance within the 30-minute driving period declined overall but only reached sta- tistical significance in the case of tracking variability. 5. Time-of-day effects were largely absent, expect for speed deviation, which was lowest at 1700 relative to the other two test times. 6. "Performance following 19 and 22 h of wakefulness was equivalent to 0.05 and 0.08% BAC, respectively." 7. "Alcohol produced a more marked increase in speed than prolonged wakefulness, with a statistically significant difference between 0.08% BAC and the 05:00 h test time (21 h of wakefulness) but not the 07:30 h test time" (23.5 h wakefulness). 8. "The frequency of off-road occurrences was significantly greater in the 0.08% BAC con- dition than in the 05:00 h test time" (21 h of wakefulness) but not significantly different from the 07:30 h test time (23.5 hr wakefulness). 9. The study raised important issues "regarding driving after consuming alcohol at times of increased physiological sleepiness, namely between the 23:0007:00 and 14:0017:00 h" time periods as fatigue-related accidents are more likely to occur during these peak times for sleepiness. Findings Directly Related Driver Fatigue/Alertness to HOS (include page references): p. 341, ". . . performance following 19 and 22 h of wakefulness was equivalent to 0.05 and 0.08% BAC, respectively." p. 341, ". . . driving performance was in a number of respects, affected similarly by pro- longed wakefulness and by alcohol. With increasing time awake and increasing blood alco- hol level, subjects tracked increasingly to the left of the center of the lane . . .), and their tracking variability . . . and speed variability . . . increased)." Driver Health No significant findings or assumptions concerning impact on health.

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148 Reviewers: Dianne Davis, Alison Smiley Title: Beilock, R. "Schedule-induced hours-of-service and speed limit violations among tractor- trailer drivers" (1995). Accident Analysis and Prevention, Vol. 27, No. 1, 3242. Abstract: This objective of this study was to determine the frequency of "schedule-induced hours-of- service rules (HSR) and/or speed limit violations by drivers of tractor-trailers by estimat- ing the tightness of driver schedules over a specific trip." The authors use self-report data to estimate the frequency of violation-inducing schedules for a sample of 498 long-distance drivers. Twenty-six percent of the drivers, assuming average legal speed limits of 55 mph, were found to have violation-inducing schedules. Drivers most likely to have these sched- ules included solo drivers, drivers hauling refrigerated loads, regular route drivers, and those with longer current trip distances. Methodology: Drivers were interviewed at Florida Agricultural Inspection Station about their current trip (e.g., origin, location of next pick-up/drop, time/date for pick-up/drop, number of miles over previous 7 days, participation of co-driver). The authors developed an index of sched- ule tightness (DRVSPD) which consisted of the "average speed a vehicle would need to maintain to reach the next destination without being late and with the driver obeying the driving times mandated by HSR." Previous driving time was "estimated by determining the time required to complete the driver-reported mileage driven over the previous seven days." In the analysis, three scenarios were examined assuming average road speed limits: 55 mph, 60 mph, and 65 mph. Weekly driving time was estimated by assuming an average speed, and then determining the driving time necessary to cover the driver's weekly mileage. While non-driving tasks (e.g., vehicle inspections) are an integral part of work for most drivers, the drivers in the sample were not questioned regarding non-driving work hours, to avoid raising their apprehension by asking too many questions related to HSR. Scope of Work: An analysis of schedule-induced HSR and/or speed limit violations by drivers of tractor trailers. Sample Size: Schedules of 498 long-distance drivers Industry Sector: Long-distance truck drivers Major Limitations: The authors note that the potential for response bias is always present when determining the incidence of any illegal activity. While the study relied heavily on information from questioning truck drivers, the authors employed measures to mitigate the response bias problem (e.g., limited their questions). Findings: 1. Depending on the average speed limit scenario (i.e., 55, 60, 65 mph), between 17% and 30% of the drivers were found to have violation-suspect schedules and between 14% and 26% had schedules sufficiently demanding to be also judged as violation-inducing." (Author's Note: For a schedule to be considered violation-suspect or violation-inducing, a minimum average trip speed must be attained or exceeded. Therefore, a violation- inducing schedule would also be considered to be violation-suspect.") 2. Using the 55 mph average speed limits, an estimated 26% of all drivers had violation- inducing schedules. Ignoring the 60- and 70-hour rules, 15% of the drivers would have had such schedules due to the demands of the current trip. For 13% of the drivers, nei- ther the 60- nor the 70-hour rules could be adhered to without violating speed limits. For 1% of the drivers (15 + 13 - 26)/2, both the current trip and the 60- or 70-hour rules result in violation-inducing schedules." These findings suggest a lower incidence of vio- lation than was found in the Hertz study. 3. "Solo drivers were more likely than team drivers to have tight schedules due to the cur- rent trip."

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149 4. "Depending upon the average speed limit assumed, drivers with refrigerated loads were between 50% and 80% more likely than other drivers to have violation-suspect or violation-inducing schedules (differences statistically significant at the .01 or .05 levels). 5. "For all three average speed limits, drivers for regular route carriers were significantly more likely than drivers on irregular routings to have violation-suspect schedules (at the .01 or .05 levels). 6. Longer current trip distance was positively correlated with tight schedules. Drivers with current trips over 1,000 miles were between five and seven times more likely to have violation-inducing schedules than were drivers with trips not over 500 miles. 7. "Assuming the average roadway traveled has 55 mph speed limits, over a quarter of all drivers must violate HSR or speed limits." 8. There is a trade-off between speed and driving time. "For example, at 45 mph average speed the average driver must drive 51 hours per week, compared with 38 hours if 60 mph is averaged. " 9. The authors present the estimated mean total weekly work hours for various assumed average speeds, as well as the work hours at each quartile. A very large majority of long- distance drivers have more than 40-hour work weeks (82%, assuming average main- tained speeds of 50 mph). Assuming 50 mph average maintained speed, half the drivers work more than 65 hours weekly and one-quarter work over 81 hours. Findings Directly Related Driver Duration to HOS (include page references): p. 37, "Depending upon the average speed limit scenario, between 17% and 30% of the drivers were found to have violation-suspect schedules and between 14% and 26% had schedules sufficiently demanding to be also judged as violation-inducing." p. 37, "Using the 55 mph average speed limits, an estimated 26% of all drivers had violation- inducing schedules. Ignoring the 60- and 70-hour rules, 15% of the drivers would have had such schedules due to the demands of the current trip. For 13% of the drivers, neither the 60- nor the 70-hour rules could be adhered to without violating speed limits. For one per- cent of the drivers (15 + 13 - 26)/2, both the current trip and the 60- or 70-hour rules result in violation-inducing schedules." p. 39, "There is a very strong and positive relationship between current trip distance and schedule tightness. For all three average speed limit scenarios, the simple correlation between DRVSPD and trip distance is positive (ranging between .31 and .35) and signifi- cantly different from zero at the .01 level... "For all average speed limit scenarios and for current rip, the 60/70 hour rule, and total: the longer the journey, the greater the fre- quency of violation-suspect and violation-inducing schedules. In all cases, the differences are easily significant at the .01 level." p. 40, "Depending upon the average speed limits assumed, drivers with current trips over 1,000 miles are between five and seven times more likely to have violation-inducing sched- ules than are drivers with trips not over 500 miles." p. 41, "Assuming 50 mph average speed, the average driver works 58 hours in total and drives 46 hours weekly. Seventy-five percent of these drivers work over 49 hours and drive more than 39 hours per week. Half the drivers exceed 65 hours total work and, of that, drive over 52 hours. Finally, a quarter of the drivers work more than 81 hours and drive over 64 hours per week (which is not legal under HSR)." p. 41, "The findings indicate that the very large majority of long-distance drivers have more than 40-hour work weeks (82%, assuming average maintained speeds of 50 mph), and extremely lengthy work weeks are common. For example, assuming 50 mph average

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150 maintaining speed, half the drivers work more than 65 hours weekly and a quarter work over 81 hours." p. 41, "Solo drivers were found to have much higher frequencies of violation-suspect and violation-inducing schedules, than team drivers. Again assuming 55 mph average speed limits, 28% of the solo drivers, but only 11% of the team drivers, would have to violate HSR and/or speed limits to stay on schedule. Due to these differences, the analysis focused on solo drivers. Among solo drivers, groups with higher incidences of violation-inducing schedules were those driving longer trip distances, driving refrigerated loads, and driving regular route carriers." Driver Health No significant findings or assumptions concerning impact on health.

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151 Reviewers: Dianne Davis, Alison Smiley Title: Belenky, G., Wesensten, N.J., Thorne, D.R., Thomas, M.L., Sing, H.C., Redmond, D.P., Russo, M.B., and Balkin, T.J. "Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study" (2003). Journal of Sleep Research, Vol. 12, 112. Abstract: The data reported in this study are a subset of data collected in a larger study analyzed and published as a U.S. Department of Transportation Report (Balkin et al. 2000; see Part I). This paper focuses on the findings for psychomotor vigilance task performance (PVT), sleep latency, and subjective sleepiness. According to the authors, of the measures taken in the larger study, the PVT was chosen for this paper because it was the most sensitive to the effects of sleep restriction and was the least subject to learning effects." The purpose of the study was to empirically determine the effects of 3, 5, 7 and 9 hours of sleep over 7 con- secutive days on objective and subjective alertness and objective performance. In addition, the study looked at the extent to which 3 days of subsequent recovery sleep restored per- formance and alertness to baseline levels. Methodology: Drivers had 3 days of orientation and baseline sleep in the laboratory before data collection commenced over 7 days of performance testing with 3, 5, 7, or 9 hours of sleep each night. The recovery period, that followed, lasted 4 days with 8 hours in bed each night. A wide variety of measures were utilized. Measures consisted of the PVT, the cognitive perfor- mance assessment battery, driving simulator tasks (e.g., lane tracking) as well as sleep latency, EMG, and sleepiness ratings. In addition to these measures, a number of health measures were taken (e.g., tympanic temperature, heart rate, and blood pressure). Scope of Work: Study of effect of sleep restriction on performance. Sample Size: Sixty-six CMV drivers (16 females, media age = 43 years; 50 males, mean age = 37 years) Industry Sector: CMV drivers Major Limitations: Study only looked at daytime driving. Recovery sleep was restricted to 8 hours. The trade-off for using a wide variety of measures was that the number of daily admin- istrations for each particular measure was restricted--precluding evaluation of circadian rhythms in this study. Subjects were heterogeneous with respect to age, which may have contributed to error variance in performance measures. Findings: (See Balkin et al. (2000) in Part I.) 1. "Seven days of sleep restriction degraded psychomotor vigilance performance in a sleep- dose dependent manner. With mild to moderate sleep restriction (7- and 5-hr time in bed [TIB]), performance initially declined and, after a few days, appeared to stabilize at a lower-than-baseline level for the remainder of the sleep restriction period. In contrast, with severe sleep restriction (3-hr TIB) performance declined continuously across the sleep restriction period, with no apparent stabilization of performance. Sleep augmen- tation (9-hr TIB) had no effect on performance over the 7-day experimental period." 2. Three days of recovery sleep did not restore performance to baseline levels for subjects with mild to moderate sleep restriction (5- or 7-hr TIB). Findings Directly Related Driver Fatigue/Alertness to HOS (include page references): p. 9, ". . . it appears that the inflection point (i.e., the minimum amount of nightly sleep required to achieve a state of equilibrium in which daytime alertness and performance can

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152 be maintained at a stable, albeit reduced, level) is approximately 4 hr per night. If less than 4 hr of sleep per night is obtained, daily decrements in performance capacity may be unavoidable at least across a 7-day period of sleep restriction." p. 10, "The present findings suggest that core sleep might best be considered as the mini- mum amount of sleep needed by the brain to achieve a state of equilibrium in which alert- ness and performance are maintained at a stable but lower-than-normal level. In this view, sleep durations that do not satisfy the core sleep requirement would, across days, result in continued degradation of alertness and performance relative to baseline, but degradation would not continue across days indefinitely--an asymptotic, stable level of reduced alert- ness and performance would eventually be achieved; and additional sleep (i.e., incremen- tal increases in the duration of sleep beyond the core requirement) would produce corre- spondingly higher, and stable, levels of alertness and performance." p. 10, "Following chronic, mild to moderate sleep restriction (5- or 7-hr TIB), 3 days of recovery sleep (8-hr TIB) did not restore performance to baseline levels." Driver Health No significant findings or assumptions concerning impact on health.

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153 Reviewers: Dianne Davis, Alison Smiley Title: Braver, E.R., Preusser, C.W., and Ulmer, R.G., "How long-haul motor carriers determine truck driver work schedules: The role of shipper demands." (1999). Journal of Safety Research, Vol. 30, No. 3, pp. 193204. Abstract: The objective of this research was to identify determinants of drivers' schedules. In partic- ular, the study looks at the "role of shipper demands within the load scheduling decision chain for individual drivers, as reported by dispatchers working for long-haul motor carri- ers." Two hundred and seventy dispatchers participated in telephone interviews. Dispatch- ers' reasons for accepting or rejecting loads from shippers were based on revenue (75%), delivery deadlines (24%) and the HOS status of the nearest driver (9%). However, dis- patchers reported that shippers ask for "sufficient time for drivers to adhere to both speed limits and hours-of-service rules." Dispatchers were asked how the "time required to make a particular trip was determined." Trip mileage was reported "as the key determinant of trip schedule assignments (58%)"; however, other factors were also considered, "including speed limits (27%) and past experience with particular routes (13%). The authors concluded that the results of the survey suggested that, "tight schedules cannot be attributed solely to shipper demands." Methodology: Long-haul drivers were surveyed at weigh stations in Wyoming and Tennessee about job characteristics (e.g., size of carrier, penalties for late delivery), and asked to identify who arranged their current loads. Interviewers eliminated a number of drivers (e.g., those who worked for private or terminal-to-terminal carriers), to focus on "U.S long-haul motor car- riers that make decisions concerning the acceptance or refusal of potential loads and that figure out driver delivery schedules based on a single truck, meeting the needs of an indi- vidual shipper for transport of a specific load." Interviews were conducted with 270 of the 309 dispatchers identified by drivers. Dispatchers were asked a number of questions: "how they figured the time necessary for trips; how often shippers imposed penalties for late deliverables; what percentages of shippers asked for just enough time, not enough time, or more than enough time to pick up and deliver loads; and what factors affected their deci- sions to accept or reject loads from customers. Dispatchers were also asked if they used any computer program to estimate the time necessary for trips," as these programs "can include criteria needed to comply with hours-of-service rules." Scope of Work: Focus on long-haul motor carrier dispatchers as to determinants of drivers' schedules. Sample Size: 309 long-haul drivers; 270 long-haul motor carrier dispatchers Industry Sector: Long-haul motor carriers Major Limitations: Dispatchers reported that shippers rarely requested tight delivery schedules. However, there is a possibility that dispatchers may have responded to questions about tight delivery sched- ules according to typical driver work schedules rather than HOS regulations. In particular, the authors note, that the study "did not attempt to quantify how a dispatcher defined `more than enough time,' `just enough time,' or `not enough time' to pickup and deliver. The drivers interviewed for this study were interviewed during summer morning hours at two specific sites. As a result, the authors note that "whether afternoon or nighttime truck traffic differs from morning traffic in terms of shippers' requested delivery schedules, whether these sites differ from others in the United States, and whether there are seasonal variations in motor carrier characteristics at these sites cannot be assessed from existing data." Findings: 1. Approximately 20% of drivers reported penalties (e.g., fines, suspension, demotion, reprimands) from their motor carriers for late deliveries.

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154 2. Motor carrier dispatchers pointed to multiple sources of information to determine the time required to make a particular trip: computer programs (75%), miles to be traversed (58%), speed limits (27%), and experience (13%). 3. Two-thirds of the dispatchers said they used rules of thumb for the average speed driv- ers could travel. Thirty percent said specific routes were examined. 4. "Among all dispatchers (i.e., both using and not using rules of thumb) 18% reported using 50 mph or slower; 14% used 5155 mph; 21% used 5560 mph; and 14% used a speed in excess of 60 mph." 5. "There was no association between the following variables and reports of expecting average speeds faster than 60 mph: penalties assigned for late delivery (reported by driver or dispatcher), hauling perishable products, and owner-operator status." 6. 61% of respondents said that time allotted per shipment for non-driving duties were up to the driver. Of those giving a quantitative estimate, most expected 2 to 4 hours. 7. Few dispatchers reported penalties imposed by shippers for late deliveries although 20% of drivers reported penalties from their motor carriers for late deliveries. Approximately 60% percent of dispatchers said this never happened and 40% said it rarely happened. 8. In response to questions regarding shipper time frames, more than one-third of dis- patchers said 95% or more of their shippers gave more than enough time for deliver- ables to be made. Only 12% of dispatchers said that 10% or more of shippers give insuf- ficient time for pick up and delivery. More than 80% of dispatchers said that zero shippers request insufficient time. 9. Of the 233 of 270 dispatchers who had the authority to accept or reject loads, only 9% mentioned the HOS status of the nearest driver as a factor in their decision. 10. The authors conclude, "according to dispatchers, revenue generation is a primary deter- minant in decisions to accept or reject loads. Delivery deadlines and the HOS status of the nearest driver were cited much less frequently. Revenue, probably, is a strong influ- ence on delivery schedules in the very competitive trucking industry." Findings Directly Related Driver Duration to HOS (include page references): p. 199, "Dispatchers were asked about factors affecting their decisions to accept or reject loads (Table 5), and 233 of 270 said they had the authority to make such decisions. Among these 233 dispatchers, revenue was cited by 75%, followed by the credit rating of the ship- per (41%), the need to find a back haul (load for return trip; 26%), the delivery deadline (24%), and whether the shipper was a regular customer (19%). The hours-of-service sta- tus of the nearest driver was mentioned by 9% of respondents." p. 201, "Federal and state efforts to decrease violation-inducing delivery schedules appear more likely to succeed if they continue to be directed primarily toward motor carriers. If government agencies start to monitor driver adherence to work hour limits effectively, then motor carriers will have no choice but to refuse shippers' requests for unreasonable deliv- ery schedules." Driver Health No significant findings or assumptions concerning impact on health.

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155 Reviewers: Dianne Davis, Alison Smiley Title: Campbell, K. "Estimates of the prevalence and risk of fatigue in fatal accidents involving medium and heavy trucks." 2002. University of Michigan Transportation Research Institute. Abstract: This paper summarizes the results of a report on baseline estimates of the prevalence and risk of truck driver fatigue in fatal accidents that was prepared for the FMCSA in support of the HOS rulemaking. Data is presented on fatigue in fatal accidents by power unit type, trip distance, for-hire versus private carriers, time of day, and by hours driving. Fatigue was coded as a contributing factor for 511 truck drivers (1.9%) out of a total of 27,463 medium and heavy trucks involved in fatal accidents from 1991 to 1996. More than half of all fatigue-related fatal accidents involve for-hire tractors on trips of a one-way distance of more than 200 miles. "The risk of a fatigue-related fatal accident increases with trip dis- tance." The fatigue risk "increases with hours driving in any operating environment and shows the characteristic circadian pattern." Methodology: The report is based on data from the UMTRI Trucks Involved in Fatal Accidents (TIFA) files and the 1992 Truck Inventory and Use Survey (TIUS) conducted by the Bureau of the Census. The data is used to provide estimates of the vehicle miles of travel and fatal acci- dents involving fatigue for various segments of the trucking industry. In addition, the inci- dence of fatigue accidents is combined with travel data to estimate the overall risk of fatigue in fatal accidents. The authors use the same definition of fatigue as coded in the Fatality Analysis Reporting System (FARS). Scope of Work: Report looks at TIFA and TIUS data from 1991 to 1996. Truck driver fatigue is the depen- dent variable and power unit type, trip distance, for-hire versus private carriers, time of day, and hours driving are the independent variables for the analysis. Sample Size: Over 27,463 medium and heavy trucks involved in fatal accidents over the 6-year period Medium and heavy trucks Industry Sector: The coding of fatigue is taken from the "driver-related factors" variables in FARS which Major Limitations: relies on the original police accident report. The authors note that the coding of fatigue by state shows some large variations. In addition, the authors note that fatigue is "particularly difficult to assess, even with in-depth investigations, since there is no physical evidence of fatigue." The authors suggest that the "prevalence of fatigue reported here is in all likeli- hood too low." 1. Fatigue is coded as a contributing factor for 511 truck drivers (1.9%) out of a total of Findings: 27,463 medium and heavy trucks involved in fatal accidents from 1991 to 1996. 2. The prevalence of truck driver fatigue in fatal accidents by time of day for all medium and heavy trucks involved in fatal accidents from 1981 to 1996 follows the circadian pattern. 3. (p. 23) ". . . more than half of all fatigue-related fatal accidents involve for-hire trac- tor on trips with a one-way distance of more than 200 miles. The risk of a fatigue- related fatal accident increases with trip distance. Straight trucks have a substantially higher risk of a fatigue-related fatal accident when operated on trips outside the local area, as compared with tractor combinations. For-hire carriers have a greater risk of fatigue-related fatal accident involvement based on miles traveled in nearly all oper- ating environments as compared with private carriers. Finally, the fatigue risk increases with hours driving in any operating environment and shows the characteris- tic circadian pattern." 4. The prevalence of truck driver fatigue was shown for six industry groups: Straight: Local, 50 to 200 miles, >200 miles; Tractor: Local, 50 to 200 miles, >200 miles. The

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156 greatest portion (62.3%) of the fatigue cases was in the category for tractors on trips greater than 200 miles. 5. The majority of reported fatigue occurs in the first few hours of driving as "half of all reported truck driver fatigue occurs in the first four hours of driving" for trucks involved in fatal accidents from 1981 to 1996. More than 25% of the accidents occurred in the first hour, and two-thirds in the first 4 hours. "Only about 4 percent of all medium and heavy truck drivers involved in a fatal accident reported driving more than 8 hours at the time of the accident." The authors note that this pattern is driven "by exposure, not risk" as the "nature of the exposure distribution will always keep the number of accidents after many hours driving a small proportion of the total, even with dramatic increases in risk with hour driving." (In other words, there are more 4-hour trips than 8-hour or 12-hour trips). Consequently there will be more accidents associated with 4-hour trips than with 12-hour trips. This is a different issue from the risk per 4-hour trip or per 12-hour trip-- the per trip risk is higher for longer trips.) The authors also note that fatigue is cumula- tive and that while the amount of work and rest during the previous day and week also affect the level of fatigue during any hours of the current trip, no information on the pre- vious work schedule was available for this study. 6. The relative risk of fatigue given involvement in a fatal accident follows the circadian rhythm. 7. The relative risk of fatigue given involvement in a fatal accident gradually increases dur- ing the first 8 hours, doubles during the ninth hour and is higher by a factor of 6 by the 12th hour. Findings Directly Related Driver Fatigue/Alertness to HOS (include page references): p. 3, "The reporting of fatigue was also examined for collisions where the only fatalities were truck occupants. Overall, 14% of all trucks involved in fatal accidents had one or more fatalities in the truck. Of the truck occupant fatalities, 9.5 percent (361 cases) were coded for truck driver fatigue. These fatigue cases are 70 percent of all fatigue coded for truck drivers in the TIFA data for 19911996. The proportion of fatigue in the non-truck fatalities is 0.6 percent." p. 23, "Risk increases steeply after eight hours of driving. However, most of the fatigue- related fatal accidents occur during the first four hours of driving. This result may suggest that cumulative fatigue is a greater problem than hours driving on any given day, although exposure data are needed to confirm the result. The circadian pattern has a pervasive effect on both the risk and the prevalence of fatigue-related fatal accidents. The risk of a fatigue- related fatal accident is elevated by a factor of four in the early morning hours. Only driv- ing more than 10 hours produces comparable risk levels. Time of day and hours driving are the dominant risk factors. Distributions of these factors suggest that the lower risk of fatigue-related fatal accidents of private carriers operating long-haul tractors may be due to less nighttime driving and shorter driving hours." Driver Duration p. 17, "The relative risk of fatigue gradually increases during the first 8 hours. During the ninth hour the fatigue risk is nearly double and by the 12th hour the risk is higher by a fac- tor of over 6. A pronounced increase is also shown in the fifth hour. Fatigue risk drops back below 1.0 during the sixth hour and increases with each additional hour. Aggregate risk for the second four hours is greater than the first four hours by a factor of 1.6. This pattern holds in every subset examined... While these results confirm the generally accepted fact that fatigue increases with time on duty, they also illustrate that time on duty is not the only factor. The time of day when each hour of driving takes place also influences the risk of

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185 Reviewers: Dianne Davis, Alison Smiley Title: Roehrs, T., Burduvali, E., Bonahoom, A., Drake, C., and Roth, T. "Ethanol and Sleep Loss: A "Dose" Comparison of Impairing Effects." (2003). Sleep, Vol. 26, No. 8, 981985. Abstract: This study looks at the effects of sleep loss (0, 2, 4, and 8 hours of sleep loss) as compared with those of ethanol ingestion in 32 adults (ages 21 to 35). "The study was conducted in a mixed design with a between-subject factor, ethanol or sleep loss, and a within-subject fac- tor, dose of either ethanol or sleep loss." The authors found that "sleep loss was more potent than ethanol in its sedative effects but comparable in effects on psychomotor performance. Ethanol produced greater memory deficits, and subjects were less aware of their overall per- formance impairment." Methodology: Thirty-two adult volunteers (21 to 35 years old) were randomly assigned to a sleep loss (n = 12) or ethanol (n = 20) group. "The ethanol arm of the study was conducted in a double- blind fashion." Sleep loss participants had 8, 6, 4, and 0 hours time in bed which produced 0, 2, 4, and 8 hours of sleep loss. Participants in the ethanol group ingested 0.0 g/kg, 0.3 g/kg, 0.6 g/kg and 0.9 g/kg ethanol from 8:30 a.m. to 9:00 a.m. after 8 hours of time in bed the previous night. "Each participant received his or her 4 doses of ethanol or sleep loss in a Latin square design with 3 to 7 days between doses." Subjects completed the Multiple Sleep Latency Test (MSLT) (9:30 a.m., 11:30 a.m., 1:30 a.m., 3:30 p.m., and 5:30 p.m.) and a performance battery (10:00 a.m., 12:00 Noon, 2:00 p.m., and 4:00 p.m.), which con- sisted of memory, psychomotor vigilance, and divided attention tests. "The order in which subjects underwent the ethanol or sleep-loss does was determined by a Latin square design with 3 to 7 days for recovery between doses." Scope of Work: Study of the risks associated with sleep loss relative to risks of ethanol. Sample Size: 32 adult volunteers (21 to 35 years old) Industry Sector: n/a Major Limitations: n/a Findings: 1. Sleep loss was "more potent than ethanol in its sedative effects but comparable in effects on psychomotor performance." 2. Ethanol "produced greater memory deficits, and subjects were less aware of their over- all performance impairment." 3. Sleep loss was at least as potent as ethanol in its performance-impairing and amnesic effects: Central reaction time was slowed by sleep loss with 8 hours and 6 hours of time in bed (TIB) differing from 0 hours of TIB. In addition, tracking deviations were increased by sleep loss with 8 hours of TIB differing from 0 hours of TIB. Sleep loss produced an increase in lapses (PVT) with the 8 hours of TIB differing from 0 hours of TIB. Findings Directly Related Driver Fatigue/Alertness to HOS (include page references): p. 984, ". . . at the studied doses, sleep loss is at least as potent as ethanol in its performance- impairing and amnesic effects and is significantly more potent in its sedative effects." p. 984, "In terms of sedative effects as measured by the MSLT, sleep loss was 2.7 times more potent, meaning that 8 hours of sleep loss is equivalent to 2.16 g/kg of ethanol and 2 hours of sleep loss is equivalent to 0.54 g/kg."

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186 p. 984, "In vigilance and divided-attention performance, sleep loss and ethanol were equipotent. In memory, ethanol was slightly more potent." p. 984, "Increasing sleep loss was perceived as increasingly impairing, while only the high- est ethanol does was rated as impairing." p. 985, " While sleep loss and ethanol produced equal impairment on the performance tests, at the low and medium ethanol doses, participants did not perceive that impairment. Only at the high dose was performance impairment perceived." p. 983, PVT change scores for number of lapses: "Sleep loss produced an increase in lapses (F=3.19, P<.04) with the 8 hours of TIB differing from 0 hours of TIB." p. 984, DAT measures--tracking deviations and central reaction times: "Central reaction time was slowed by sleep loss (F = 6.20, P < .002), with 8 hours and 6 hours of TIB differ- ing from 0 hours of TIB. The ingestion of ethanol did not alter central reaction time . . . Tracking deviations were increased by sleep loss (F = 4.35, P < .01), with 8 hours of TIB differing from 0 hours of TIB. Ethanol ingestion also increased tracking deviation with the 0.3-g/kg dose differing from the 0.9-g/kg dose. Both ethanol (F = 9.25, P < .01) and sleep loss (F = 4.32, P < .05) produced linear dose effects. Ethanol ingestion and sleep loss did not differ in effects on tracking deviations, which the relative potency analyses also reflected (NS)." p. 984, "While both performance tests used in this study have previously been shown to be sensitive to sleep-deprivation effects, these tests are relatively short (10 and 15 minutes), and longer tests may have revealed a greater potency of sleep loss compared to ethanol. As to MSLT sensitivity, in previous studies from this laboratory, the MSLT has consistently been found to be more sensitive to the effects of ethanol compared to performance testing." p. 984, "Ethanol and sleep loss were equipotent in impairing psychomotor performance at the studies does. Tracking deviation on the DAT were increased to the same extent by both ethanol and both sleep loss, while the reaction-time parameters on this task did not show consistent effects. Subjects often concentrate on 1 component of the task at the expense of the other, which in this case was the tracking component. On the PVT, which does not require divided attention, reaction times were affected. But, interestingly, on this task, both ethanol and sleep loss slowed the fastest reaction times, parenthetically to the same degree and in a dose-related linear fashion, while lapses and the slowest reaction times were not consistently affected. This is not supportive of the "lapse" hypothesis of sleep-deprivation effects, which suggests lapses in performance occur as one becomes sleepier. What these data show is that best performance is degraded." Driver Health No significant findings or assumptions concerning impact on health.

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187 Reviewers: Alison Smiley, Dianne Davis Title: Saccomanno, F.F, Shortreed, J.H., and Yu, M. (1996). "Effect of Driver Fatigue on Com- mercial Vehicle Accidents." In Truck Safety: Perceptions and Reality (ed. Saccomanno, F. and Shortreed, J.) (1995). The Institute for Risk Research, University of Waterloo, Water- loo, Canada. Abstract: A Canadian study, by Saccomanno et al. (1996), used several different databases to deter- mine accident risk associated with different driving times. Databases included police acci- dent reports, a commercial vehicle survey of driver demographics, work hours, and routes. The focus of the study was fatigue-related accidents, defined as single-vehicle accidents that occurred between midnight and 8:00 a.m. or single-vehicle accidents where the driver was recorded as being at fault. Fatigue-related accident risk was significantly higher for routes characterized by long driving times, that is, where the 85th percentile driving time was 9.5 hours or longer. There were more single-vehicle accidents at night (assumed to be associated with fatigue) than during the day. There was a higher proportion of single- vehicle accidents on routes typified by long driving times. In remote regions, the nighttime single-vehicle accident rates were particularly high--13 times greater than for more popu- lated areas in the daytime. Methodology: This study used "surrogate measures of fatigue derived from the accident data and surveys of drivers who reported on their driving time, to compare accident rates between locations and times for different types of fatigue." Four databases from the Province of Ontario were used in this analysis: Ontario motor vehicle accident data, Ontario Highway Inventory Man- agement System, Ontario Traffic Volume Information System, and Ontario Commercial Vehicle Survey (CVS). The CVS data, which provided information on commercial vehi- cles surveyed at 75 representative locations in the provincial highway network, were key to the fatigue analysis as these data provided direct evidence on the hours of driving from the last rest stop for each sampled truck driver in the traffic stream. Scope of Work: Database analysis to compare accident rates between locations and times for different types of fatigue. Sample Size: 19881989 truck accident data Industry Sector: Trucks Major Limitations: n/a Findings: 1. Fatigue-related accident risk was significantly higher for routes characterized by long driving times, that is, where the 85th percentile driving time was 9.5 hours or longer. 2. There were more single-vehicle accidents at night (assumed to be associated with fatigue) than during the day. The results confirm the presence of circadian fatigue. 3. There was a higher proportion of single-vehicle accidents on routes typified by long driv- ing times. 4. In remote regions, the nighttime single-vehicle accident rates were particularly high-- 13 times greater than for more populated areas in the daytime. This points to the effect of circadian fatigue on truck accident rates appearing to be additive to the effect of indus- trial fatigue. Findings Directly Related Driver Fatigue/Alertness to HOS (include page references): p. 170, "Longer hours of driving without rest result in significantly higher fatigue accident rates. An appreciable increase in rates (i.e., a pronounced discontinuity in the relationship) was found to occur for more than 9.5 hours of driving without proper rest."

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188 p. 171, "The results of the study confirm the presence of circadian fatigue in the Ontario truck accident data by indicating higher fatigue-related accident rates at nighttime as com- pared to daytime over the entire highway network (northern and southern regions)." p. 171, "The effect of circadian fatigue on truck accident rates appears to be additive to the effect of industrial fatigue. In the northern region, where longer driving is expected to result in industrial fatigue, the nighttime single vehicle accident rate is 3.3 times higher than the daytime rate. A similar relationship was found in the southern region with a ratio of 2.3 night accident rates to day accident rates." Driver Health No significant findings or assumptions concerning impact on health.

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189 Reviewers: Dianne Davis, Alison Smiley Title: Van Dongen, Hans P.A., Maislin, G., Mullington, J.M., and Dinges, D. "The cumulative cost of additional wakefulness: Dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation." (2003). Sleep, Vol. 26, No. 2, 117126. Abstract: Forty-eight adults participated in a laboratory study of chronic sleep restriction or total sleep deprivation. Subjects in the chronic restriction experiment were randomly assigned one of three sleep doses (4 h, 6 h, or 8 h time in bed per night), which were maintained for 14 con- secutive days. Subjects in the total sleep deprivation experiment had 3 nights without sleep (0 time in bed). Both experiments had 3 baseline (pre-deprivation) days and 3 recovery days. The researchers found that "chronic restriction of sleep periods to 4 h or 6 h per night over 14 consecutive days resulted in significant cumulative, dose-dependent deficits in cog- nitive performance on all tasks." Lapses in behavioral alertness and reductions in working memory performance, in the 4 h condition, reached levels equivalent to those observed after 2 nights without sleep. After 14 days of sleep restriction, cognitive throughput performance was equivalent to that observed after 1 night without any sleep. Methodology: Forty-eight healthy adult subjects participated in a chronic sleep restriction experiment or a total sleep deprivation experiment. Both experiments began with 1 adaptation day and 2 baseline days with 8 h sleep opportunities. In the chronic sleep restriction experiment, this was followed by randomization to 8 h, 6 h or 4 h sleep periods (time in bed ending at 0730) for 14 days. In the total sleep deprivation experiment, subjects were kept awake for 88 h. Both experiments concluded with 3 recovery days. Subjects in all experimental conditions (e.g., psychomotor vigilance task, Stanford Sleepiness Scale, Karolinska Sleepiness Scale) underwent neurobehavioural assessments every 2 h during scheduled wakefulness. In addi- tion to neurobehavioural measures, polysomnographic (PSG) recordings were made during the third baseline sleep period and during 10 of the 14 restricted sleep periods. Scope of Work: Chronic sleep restriction and total sleep deprivation. Sample Size: 48 healthy adults (ages 21 to 38) Industry Sector: n/a Major Limitations: n/a Findings: 1. "Chronic restriction of the nocturnal sleep period to either 6 h or 4 h per day for 14 days resulted in significant cumulative performance deficits relative to the 8 h sleep period condition." 2. "Subjects allowed an 8 h sleep period per night displayed only minor, non-significant increases in lapses of behavioral alertness over the 14 days." . . . "In contrast, subjects in the 4 h sleep period condition displayed escalating numbers of lapses in behavioral alertness and decreasing cognitive accuracy and speed across the 14 days. The magni- tude of changes in performance over days of sleep restriction in the 6 h sleep period was between that observed in the 8 h and 4 h sleep period conditions." 3. "In the 4 h sleep period condition, lapses in behavioral alertness and reductions in work- ing memory performance reached levels equivalent to those observed after 2 nights with- out sleep. Cognitive throughput performance after 14 days of sleep restriction was equiv- alent to that observed after 1 night without any sleep. Subjects in the 6 h sleep period condition also reached levels of impairment equivalent to those observed after 1 night of total sleep loss for lapses in behavioral alertness and working memory performance." 4. "Chronic restriction of the nocturnal sleep period to either 6 h or 4 hr per day for 14 days resulted in a relatively small but significant build-up of subjective sleepiness, as measured with the Stanford Sleepiness Scale (SSS) relative to the 8 h sleep period condition."

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190 5. "Cumulative total sleep time increased near-linearly over days in the 8 h, 6 h and 4 h sleep period conditions. 6. "Cumulative sleep loss over 14 days in the 4 h sleep period condition was significantly greater than cumulative sleep loss over 3 days in the total sleep deprivation condition." 7. The findings of this study contradict the "core sleep" hypothesis. The "core sleep" hypothesis asserts that "core" or "obligatory" sleep occupies the first part of the night and serves to "repair the effects of waking wear and tear on the cerebrum." In this hypothesis, all sleep obtained beyond this core sleep (especially that dominated by SWS and SWA) duration is considered to be "optional" or "facultative" sleep. As SWS and SWA were conserved among sleep restriction conditions in this study, the finding that cumulative cognitive impairment developed "in cerebral functions at 4 h and 6 h time for sleep per night indicates that the current threshold of 6 h for core sleep duration can- not be correct. If 6 h sleep per day were the maximum duration of sleep required to main- tain normal cerebral functions, cumulative cognitive performance deficits should not have developed in that condition. Thus, the results from the present study do not support a functional distinction between "core" and "optional" sleep." Findings Directly Related Fatigue/Alertness to HOS (include page references): p. 122, ". . . the two modes of sleep loss yielded similar maximum deficits for PVT perfor- mance but chronic sleep restriction resulted in much greater cumulative sleep loss than did 3 days of total sleep deprivation. p. 124, "Contrary to earlier, uncontrolled studies of prolonged sleep restriction, this exper- iment yielded convergent findings of sleep dose-response effects on all three cognitive per- formance functions. Sleep periods chronically limited to 4 h and 6 h per night progressively eroded the effectiveness of psychomotor vigilance performance, working memory perfor- mance and cognitive throughput performance, providing convergent evidence for the adverse effects of chronic sleep restriction on cognitive functions . . . Claims that humans adapt to chronic sleep restriction within a few days on the other hand, are not supported by the present findings." p. 124, "Since chronic restriction of sleep between 4 h and 6 h per night for 14 days pro- duced cognitive performance deficits comparable to those found under conditions of 1 to 2 days of total sleep deprivation, it appears that even relatively moderate sleep restriction-- if sustained night after night--can seriously impair waking neurobehavioural functions in healthy young adults." p. 124, "We conclude that the effects of sleep chronically limited to 4 h and 6 h per night on cognitive performance appear to reflect progressive neurocognitive dysfunction in sys- tems underlying sustained attention and working memory." p. 124, ". . . unlike performance measures, sleepiness ratings appeared to show adaptation to chronic partial sleep deprivation . . . These findings for subjective sleepiness suggest that once sleep restriction is chronic, subjects either cannot reliably introspect with regard to their actual sleepiness levels, or as long as they are receiving at least approximately 4 h of sleep nightly they do not experience a sense of sleepiness anywhere near the levels found for total sleep deprivation." p. 124, "Measures of sleep physiology were less responsive to chronic sleep restriction than were waking neurobehavioural functions. The primary effects on sleep architecture were immediate, overall reductions in the amounts of stages 1, 2 and REM sleep." Driver Health No significant findings or assumptions concerning impact on health.

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191 Reviewers: Dianne Davis, Alison Smiley Title: Williamson, A., Friswell, R. and Feyer, A.M. "Fatigue and performance in heavy truck drivers working day shift, night shift or rotating shifts." (2004). National Transportation Commission. Abstract: This field study was designed to compare the impact of day and night shift rosters on sub- jective fatigue, performance, and the sleep and work of drivers. In addition to permanent day shift and night shift drivers, drivers working alternating weeks of day and night shifts participated in the study. Drivers participated for 2 weeks to "attempt to obtain a reliable sample of their work." Over the 2 weeks, each driver was measured repeatedly. In addition to completing tests of concentration and reaction speed, drivers completed performance tests, kept diaries of their work, break, and sleep times and completed ratings of their sub- jective fatigue. Actigraph data was also collected to provide objective measures of the tim- ing and quality of their sleep. The researchers found that while the night shifts made driv- ers feel more tired than day shifts, it did not "produce significantly poorer performance, suggesting that night drivers can manage their fatigue." Methodology: Fifty-four Australian drivers participated in the study: 22 permanent day shift drivers, 21 permanent night shift drivers, and 11 rotating shift drivers. Each driver was repeatedly mea- sured over a 2-week period. Drivers completed concentration and reaction speed tests at the start of the first shift of the study fortnight (baseline), and at the end of the last shift in week 1 and week 2. Drivers also self-administered the Simple Reaction Time test as well as the Macworth Clock Vigilance task (shortened version) at the start and end of each shift dur- ing the fortnight, as well as at the start of one midshift break in each shift. In addition to these performance tests, drivers kept diaries of their work, break, and sleep times and com- pleted ratings of their subjective fatigue and quality of sleep. Actigraphy data was also col- lected to complement the self-report measures. Scope of Work: Impact of day and night shift rosters on subjective fatigue, performance, and sleep and work on long-haul drivers. Sample Size: 54 male professional long-distance drivers (22 permanent day shift drivers, 21 permanent night shift drivers, and 11 rotating shift drivers) Industry Sector: Professional long-distance drivers Major Limitations: Two practical and methodological issues limited the current study: driver recruitment and missing data. The authors had to relax their initial recruitment specifications to select groups of drivers on the basis that they did a particular shift. Instead the final sample included "any driver working permanent day or night shifts that were rostered to be 11 or more hours long." "As a result, in order to obtain a sufficiently large sample of drivers who did day shifts, the study also included drivers who worked rotating day shifts." According to the authors, "missing data posed a serious problem for the current study, limiting the type of data analyses that could be conducted and the strength of conclusions that could be drawn." Findings: 1. Over a typical workweek of five consecutive 10- to 12-hour shifts, there was a signifi- cant increase in subjective ratings of fatigue by all drivers. 2. Between the start and end of each shift within the workweek, rated fatigue also increased. Permanent night shift drivers and drivers on rotating night shifts showed greater increases than day drivers. However, it is important to note that the permanent night shift drivers had lower fatigue ratings at the start of their shift than permanent day drivers. 3. The study failed to find significantly poorer performance for night drivers as compared with day drivers. Simple reaction time test performance tended to be slower at the end of the week for all drivers. Similarly, there were no differences between day and night dri- vers on subjective fatigue ratings. The results of the PVT suggest a slowing in reaction

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192 speed across the work week for night drivers while day drivers showed faster response time at the end of the week; however, this was non-significant. While the authors note that this lack of difference could be due to the testing time for night drivers, who tended to complete their end-of-week tests around dawn, this would not explain the absence of differences between rotating day drivers and night shift drivers who completed their end- of-week testing earlier in the morning during the circadian low. 4. The authors note that an alternative explanation for failing to find the predicted effect for night drivers could be that the "work-rest pressures were more important than the circa- dian influences experienced in night work." All of the drivers worked similar long hours (e.g., 50 to 55 hours arranged in five 10- to 12-hour shifts), which may eclipse any effects due to circadian or time of day influences. Drivers had between 4 and 6 hours sleep between work shifts. The authors note that all of the drivers in this study "were being affected by restricted sleep and that any differential effects of night work may be over- shadowed by this effect." In addition, they note that night shift drivers performed as well as day shift drivers as they are experienced professional drivers "who are well-suited to cope with the demands of the road transport industry by organizing their work-rest." 5. Night shift drivers worked longer shifts than day shift drivers and spent much more of their working time driving than day shift drivers "which might predict that night shifts would be more tiring than day shifts." However, the authors suggest that night shift driv- ers may have performed as well as day shift drivers as they may be "especially tolerant of fatigue or skilled at managing fatigue" and because they organize their sleep differ- ently (e.g., napping in the hours before their first shift of the week) which may partly explain how they could maintain performance. For example, the authors noted that night drivers "endeavored to capitalize on the sleep propensity influences of the circadian rhythm by getting as much sleep as they could as close as possible to the early morning circadian trough when sleep is most likely." Findings Directly Related Driver Fatigue/Alertness to HOS (include page references): p. 43, "For permanent shift drivers, 2 (group) by 2 (occasion) repeated measures MANOVA showed a significant occasion effect, with the overall subjective fatigue rating higher at the end of the working week compared to baseline. Although the mean scores suggest a greater increase in rated fatigue across the week for night shift drivers, no statistically significant difference in overall subjective fatigue was found between day shift drivers and night shift drivers." p. 45, "Repeated measures MANOVA showed that permanent day and night shift drivers did not differ on any of the Simple Reaction Time task measures. RT tended to be higher at the end-of-week compared to baseline but there was no significant interaction on any perfor- mance measures between type shift and test occasion. These results indicate that both day and night drivers showed slowing of reaction speed over the week but to an equal extent." p. 46, "On average, there was no significant difference between permanent day shift driv- ers and permanent night shift drivers on any of the Mackworth Clock Vigilance perfor- mance measures." p. 48, "There were no significant differences in any PVT performance measures between the beginning of the week and the end of the selected study week. Analysis of interaction effects showed two non-significant trends for interaction between driver group and test occasion." Driver Health No significant findings or assumptions concerning impact on health.

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193 Reviewers: Dianne Davis, Alison Smiley Title: Williamson, A., Feyer, A.M., Friswell, R., and Leslie, D. "Strategies to combat fatigue in the long-distance road transport industry: Stage 2 evaluation of alternative work practices." (2004). National Transportation Commission. (Note: This study was covered in Part I in Williamson et al. (1996) "The impact of work practices on fatigue in long distance truck drivers." Accident Analysis & Prevention, Vol. 28, No. 6, 70971. The following presents findings not covered in Part I.) Abstract: A repeated measures design was used in this study. Twenty-seven subjects participated in each of three work practices: staged trip driving (two drivers from different points of ori- gin meet mid-trip and exchange loads, within HOS regulations), flexible trip driving (sin- gle driver, trip scheduled without reference to HOS regulations) and single trip driving (single driver, within HOS regulations) A range of fatigue measures were used including performance tests, physiological, and subjective measures. The authors found that "a 1012 hour trip is tiring no matter how the work is organized, and that the effects of accumulated fatigue may overshadow the effects of fatigue on a single 1012 hour trip." Methodology: A sample of 27 drivers participated in a repeated measures design. Each driver participated in three work practices: staged driving (within HOS), flexible trip driving (outside HOS), and single trip driving (within HOS). The three methods were compared on a 10- to 12-hour route between Sydney and Melbourne. Each driver was assessed before the trip, on the road, and after the trip for all three work practices. A range of fatigue measures were used includ- ing performance tests (cognitive performance tests, on-road performance test), physiolog- ical (e.g., hear rate), and subjective measures (e.g., Stanford Sleepiness Scale). Monitoring of drivers' cognitive and physiological functioning, as well as monitoring of their driving performance, were on-road measures. "The equipment was designed to obtain data in real time without interfering with the driving task, and allowing the driver to use his regular vehicle." In addition to a questionnaire (e.g., demographics, driving experience) adminis- tered prior to the trip, drivers were asked to complete a trip diary including driving details (e.g., breaks) as well as their ratings of feelings of fatigue. Scope of Work: A repeated measures design comparison of trips within HOS regulations: staged trip driv- ing and single trip driving; and driving outside HOS: flexible trip driving. Sample Size: 27 long-distance truck drivers (mean age: 38.4; driving experience: 15.9 years) Industry Sector: Professional long-distance drivers Major Limitations: The authors note that the analysis of the results of this study was hampered to some extent by missing data, particularly in the data collected during the trip. When only a section of data is missing in a repeated measures design, cases can be rejected and the "power of the study to detect differences between groups when differences actually exist" is weakened. As a result, this may lead to more conservative conclusions. Findings: 1. Drivers experienced higher subjective fatigue at the end of the trip compared with the beginning for all trip types. 2. While staged drivers reported higher fatigue at the beginning of staged trips compared with the other trip types, this "most likely reflects the cumulative impact of the previous week's work which was typical of the schedules routinely worked by these drivers. Fatigue levels were also higher for staged drivers at the end of the trip compared to the ratings at the end of the trip for the other trip types, suggesting that if a driver starts the trip more tired, he is likely to be more fatigued at the end of the trip." 3. "The results of this study show that overall there was relatively little difference between the trip types in the effects on the drivers' performance."

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194 4. Some performance tests did show poorer performance for staged strips compared to con- trol trips. These results suggested that when doing staged trips drivers did not handle tasks requiring prolonged attention as well as when they were doing the other trip types. The conclusion cannot be drawn, however that the unique characteristics of staged driving created this inferior performance." 5. "For the vigilance and unstable tracking tasks, drivers showed poorer performance when on staged trips than on either of the other trips." 6. "Performance for the CFF test also revealed poorer performance by drivers on staged trips, but only for the beginning of the trip." 7. There were no differences related to type of trip or the time in the trip that the test occurred for the simple reaction time test or for the on-road reaction time test. 8. "On staged and control trips, heart rate decreased across the trip, indicating decreasing alertness. In contrast, when on flexible trips heart rates were much slower at the begin- ning of the trip, but increasing such that by the end of the trip they had much faster heart rate than the other trip types. This suggests that when on flexible trips, drivers had lower alertness, based on the heart rate measure, at the beginning of the trip but their alertness increased by the end of the trip." Findings Directly Related Driver Fatigue/Alertness to HOS (include page references): p. 3, "Drivers experienced higher subjective fatigue at the end of the trip compared to the beginning for all trip types indicating that the experience of driving for 10 to 12 hours was tiring, no matter how the work was organized." p. 3, ". . . drivers reported higher fatigue at the beginning of staged trips compared to the other trip types. This most likely reflects the cumulative impact of the previous week's work which was typical of the schedules routinely worked by these drivers." p. 3, "Fatigue levels were also higher for staged drivers at the end of the trip compared to the ratings at the end of the trip for the other trip types, suggesting that if a driver starts the trip more tired, he is likely to be more fatigued at the end of the trip." p. 6, "Factors other than experiences during a 12 hour trip must be considered as causes of fatigue in these drivers. The results of this study suggest that factors leading to chronic fatigue, such as heavy work load over the past few days may account for differences in fatigue levels of drivers. Of the three types of trips, the staged trips were most vulnerable to the effects of work in the past week due to their order in the study. The impact of aspects of work organization was clearly revealed in the finding that on staged trips drivers were much more tired at the very start of the trip and remained so at the end of the trip. Given that drivers are fatigued by 12 hour trips, irrespective of how they are driven, it is essen- tial that they start fresh and fit to drive. Further, it seems likely that if 12 hour trips and the work organization surrounding them render drivers vulnerable to fatigue, the impact of work organization on trips involving even longer hours will also be considerable." Driver Duration p. 5, "Differences between driving types were not sufficient to account for changes in fatigue or performance in this study. All drivers reported more fatigue over the trip, but not all drivers showed poorer performance. It seems that the 12 hour trip is relatively immune to any effects of differences in work practices. It is possible that studying such relatively short trips will not provide clear findings. It may be that longer trips are needed to assess the effect of the differences between these three work practices. It is certainly noteworthy that flexible trips produced no worse an outcome than either of the other two ways of doing the same trip. In fact, a more exhaustive evaluation of flexibility, where drivers have the

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195 opportunity to learn about manipulating the timing of work and rest during several trips, might reveal that flexibility is of benefit in managing fatigue." p. 105, "There is little evidence that allowing drivers the freedom to organize the work-rest schedules of their own trips affected their performance. Drivers on flexible trips showed few differences on any of the cognitive or on-board performance tests compared to control trips. It seems that the requirement to comply with the regulated work-rest arrangement does not enhance the drivers' cognitive functioning or work performance, nor does it reduce the amount of fatigue that drivers report. It should be noted, however that flexible drivers did tend to select work-rest schedules which were quite similar to the regulated working hours. It would be interesting to determine whether this similarity persists when the trip is longer." Driver Health p. 5, "Even though studies have linked general health and lifestyle to increased fatigue, the design of this study allowed us to rule out factors relating to individual drivers such as level of experience, general health and lifestyle as causes of fatigue in this group of drivers. Undoubtedly 12 hours of driving produces fatigue, but this study suggests that the fatigue does not occur because of factors like poor driver preparation, poor rest and break behav- ior, driving route, or their motivation to complete their trip."