Sailors’ Work/Rest Schedule and Fatigue on a Canadian Patrol Frigate During Exercise Trident Fury 2015
Wenbi Wang, PhD Renee Chow, PhD Henry Peng, PhD Fethi Bouak, PhD Matthew Lamb Ken Ueno DRDC – Toronto Research Centre
Defence Research and Development Canada Scientific Report DRDC-RDDC-2017-R048 June 2017
Template in use:
© Her Majesty the Queen in Right of Canada, as represented by the Minister of National Defence, 2017 © Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017
Abstract
Sailors’ work, rest schedules and fatigue were collected onboard of the Her Majesty’s Canadian Ship (HMCS) Calgary during the 10-day Exercise Trident Fury 2015 for supporting the validation of sleep and fatigue prediction algorithms to be implemented in naval crewing analysis software, the Simulation for Crew Optimization and Risk Evaluation (SCORE). This report summarises the data analysis that was focused on the distribution of sailors’ daily times on various on-duty and off-duty activities, as well as the fluctuation of their fatigue throughout the exercise. The results identified distinctively different patterns of sleep for 1-in-2, 1-in-3 watch-standers and non-watch standers. Averaged across participants from all five ship departments, a moderate level of fatigue was observed during the exercise. Results from this analysis provide a benchmark for validating the sleep and fatigue prediction algorithms.
Significance to Defence and Security
SCORE is a bespoke crew modeling software developed by Defence Research and Development Canada (DRDC) for the Royal Canadian Navy (RCN). This report summarises the analysis of sailors’ work, rest schedules and fatigue during an at-sea trial. The results will be used to validate two key algorithms in SCORE, which is critical for generating robust crewing solutions for future RCN platforms.
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Résumé
On a recueilli des données sur les horaires de travail et les périodes de repos, ainsi que sur l’état de fatigue des marins à bord du Navire canadien de Sa Majesté (NCSM) Calgary au cours de l’exercice de 10 jours Trident Fury 2015. Cet exercice venait appuyer la validation des algorithmes de prédiction du sommeil et de la fatigue à intégrer au logiciel d’analyse de l’armement en équipage des navires, l’outil de simulation pour l’optimisation de l’équipage et l’évaluation des risques (SCORE). Le présent rapport résume l’analyse des données qui était axée sur la répartition du temps consacré chaque jour par les marins à diverses activités en service et hors-service, ainsi que sur les variations de leur état de fatigue pendant l’exercice. Selon les résultats obtenus, les habitudes de sommeil des marins de quart par bordée ou par tiers et de ceux qui ne suivent pas un régime de quart sont nettement différentes. On a observé un niveau de fatigue modéré durant l’exercice parmi les participants des cinq services du navire. Les résultats de l’analyse fournissent un point de référence pour la validation des algorithmes de prédiction du sommeil et de la fatigue.
Importance pour la défense et la sécurité
L’outil SCORE est un logiciel sur mesure de modélisation d’équipage élaboré par Recherche et développement pour la défense Canada (RDDC) à l’intention de la Marine royale canadienne (MRC). Le présent rapport résume l’analyse des données recueillies sur les horaires de travail et les périodes de repos, ainsi que sur l’état de fatigue des marins lors d’un essai en mer. Les résultats serviront à valider deux algorithmes clés du logiciel SCORE, lesquels sont essentiels à l’élaboration de solutions fermes d’armement en équipage pour les futures plateformes de la MRC.
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Table of Contents
Abstract ...... i Significance to Defence and Security ...... i Résumé ...... ii Importance pour la défense et la sécurité ...... ii Table of Contents ...... iii List of Figures ...... vi List of Tables ...... vii Acknowledgements ...... ix 1 Introduction ...... 1 1.1 SCORE and DRDC Fatigue Model ...... 1 1.2 Ex Trident Fury 2015 and Two Research Studies ...... 1 1.3 Study Purpose ...... 2 2 Methodology ...... 3 2.1 Participants ...... 3 2.2 Activity Logs ...... 4 2.3 Data Collection ...... 6 3 Results and Discussions ...... 7 3.1 Global Overview Across All Departments ...... 7 3.2 Combat Department (CBT) ...... 9 3.2.1 On-Duty Activities ...... 11 3.2.1.1 Watch ...... 11 3.2.1.2 Administration ...... 11 3.2.1.3 Maintenance ...... 11 3.2.1.4 Evolution ...... 12 3.2.1.5 Other ...... 12 3.2.2 Off-Duty Activities ...... 12 3.2.2.1 Sleep ...... 12 3.2.2.2 Personal ...... 13 3.2.2.3 Messing ...... 13 3.2.3 Fatigue Ratings ...... 13 3.2.4 Actigraphic Sleep and Work Assignment Data for Watch Standers .... 16 3.3 Combat Systems Engineering Department (CSE) ...... 17 3.3.1 On-Duty Activities ...... 18 3.3.1.1 Watch ...... 18 3.3.1.2 Administration ...... 18 3.3.1.3 Maintenance ...... 18 3.3.1.4 Evolution ...... 19
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3.3.1.5 Other ...... 19 3.3.2 Off-Duty Activities ...... 19 3.3.2.1 Sleep ...... 19 3.3.2.2 Personal ...... 19 3.3.2.3 Messing ...... 20 3.3.3 Fatigue Ratings ...... 20 3.3.4 Actigraphic Sleep and Work Assignment Data for Watch Standers .... 22 3.4 Deck Department (Deck) ...... 23 3.4.1 On-Duty Activities ...... 24 3.4.1.1 Watch ...... 24 3.4.1.2 Administration ...... 24 3.4.1.3 Maintenance ...... 24 3.4.1.4 Evolution ...... 24 3.4.1.5 Other ...... 25 3.4.2 Off-Duty Activities ...... 25 3.4.2.1 Sleep ...... 25 3.4.2.2 Personal ...... 25 3.4.2.3 Messing ...... 25 3.4.3 Fatigue Ratings ...... 26 3.4.4 Actigraphic Sleep and Work Assignment Data for Watch Standers .... 28 3.5 Logistics Department (LOG) ...... 29 3.5.1 On-Duty Activities ...... 30 3.5.1.1 Watch ...... 30 3.5.1.2 Administration ...... 30 3.5.1.3 Maintenance ...... 30 3.5.1.4 Evolution ...... 30 3.5.1.5 Other ...... 30 3.5.2 Off-Duty Activities ...... 30 3.5.2.1 Sleep ...... 30 3.5.2.2 Personal ...... 31 3.5.2.3 Messing ...... 31 3.5.3 Fatigue Ratings ...... 31 3.6 Marine Systems Engineering Department (MSE) ...... 33 3.6.1 On-Duty Activities ...... 34 3.6.1.1 Watch ...... 34 3.6.1.2 Administration ...... 34 3.6.1.3 Maintenance ...... 34 3.6.1.4 Evolution ...... 34 3.6.1.5 Other ...... 34 3.6.2 Off-Duty Activities ...... 34 3.6.2.1 Sleep ...... 34
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3.6.2.2 Personal ...... 35 3.6.2.3 Messing ...... 35 3.6.3 Fatigue Ratings ...... 35 3.6.4 Actigraphic Sleep and Work Assignment Data for Watch Standers .... 36 3.7 Limitations of this Study ...... 37 4 Conclusions ...... 39 4.1 Summary of Findings ...... 39 4.2 Future Work ...... 41 References ...... 43 Annex A Work, Rest and Fatigue Log ...... 45 Annex B Work Activity Assignment Log ...... 47 List of Symbols/Abbreviations/Acronyms/Initialisms ...... 49
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List of Figures
Figure 1: Daily activity durations across all departments, obtained from self-reported logs...... 8 Figure 2: Average daily fatigue ratings across the 9-day trial...... 9 Figure 3: The distribution of average daily activity times in the CBT department. ... 10 Figure 4: Fatigue profiles for non-watch standers (top), port watch (middle), and stbd watch (bottom) in the CBT department...... 15 Figure 5: Average fatigue rating for three watch groups in the CBT department. ... 16 Figure 6: The distribution of average daily activity times in the CSE department. ... 17 Figure 7: Fatigue profiles for non-watch standers (top), port watch (middle), and stbd watch (bottom) in the CSE department...... 21 Figure 8: Average fatigue rating for three groups in the CSE department...... 22 Figure 9: The distribution of average daily activity times in the Deck department. ... 23 Figure 10: Fatigue profiles for non-watch standers (top), port watch (middle), and stbd watch (bottom) in the Deck department...... 27 Figure 11: Average fatigue rating for three watch groups in the Deck department. ... 28 Figure 12: The distribution of average daily activity times in the LOG department. ... 29 Figure 13: Fatigue profiles for non-watch standers in the LOG department...... 32 Figure 14: Average fatigue rating for non-watch standers in the LOG department. ... 32 Figure 15: The average daily activity times in the MSE department for non-watch standers...... 33 Figure 16: Fatigue profiles for non-watch standers in the MSE department...... 35 Figure 17: Average fatigue rating for non-watch standers in the MSE department. ... 36 Figure 18: Summary of major sleep episodes for watch-standers and non-watch standers in five ship departments...... 40
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List of Tables
Table 1: Self-report participants across ship departments and watch syndicates. .... 3 Table 2: Supervisor participants and the number of operators and engineers they rated across watch syndicates...... 4 Table 3: On-duty and off-duty activities and their codings...... 5 Table 4: The Stanford sleepiness scale [10]...... 5 Table 5: A daily activity and fatigue log based on a 15-min resolution...... 5 Table 6: Tabular breakdown of daily activity times across all departments...... 8 Table 7: The breakdown of activity times and their variabilities in the CBT department. (Unit: hour/day)...... 10 Table 8: 1-in-2 watch rotation schedule adopted in Ex Trident Fury 2015...... 11 Table 9: Sleep on-set, wake-up times, and duration for the CBT department, obtained from self-reported logs...... 13 Table 10: Sleep on-set, wake-up times, and duration for the CBT department, based on actigraph data from the Watch Evaluation study...... 16 Table 11: Off-watch work assignment for watch standers in the CBT department. (Unit: hour/day)...... 17 Table 12: The breakdown of daily activity times and their variabilities in the CSE department. (Unit: hour/day)...... 18 Table 13: Sleep on-set, wake-up times, and duration for the CSE department...... 19 Table 14: Sleep on-set, wake-up times, and duration for the CSE department, based on actigraph data from the Watch Evaluation study...... 22 Table 15: Off-watch work assignment for watch standers in the CSE department. (Unit: hour/day)...... 23 Table 16: The breakdown of daily activity times and their variabilities in the Deck department. (Unit: hour/day)...... 24 Table 17: Sleep on-set, wake-up times, and duration for the Deck department. .... 25 Table 18: Sleep on-set, wake-up times, and duration for the DECK department, based on actigraph data from the Watch Evaluation study...... 28 Table 19: The breakdown of daily activity times and their variabilities in the LOG department. (Unit: hour/day)...... 29 Table 20: Sleep on-set, wake-up times, and duration for non-watch standers in the LOG department: (top) day workers, (bottom) night workers...... 31 Table 21: The breakdown of daily activity times and their variabilities in the MSE department. (Unit: hour/day)...... 33
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Table 22: Sleep on-set, wake-up times, and duration for non-watch standers in the MSE department...... 34 Table 23: 1-in-3 watch schedule for the MSE department...... 36 Table 24: Sleep on-set, wake-up times, and duration for watch-standers in the MSE department, obtained from actigraphic sleep data...... 37 Table 25: Daily off-watch work assignment for watch standers in the MSE department. (Unit: hour/day)...... 37 Table 26: Comparison of logged sleep (L) and actigraphically-measured sleep (A) for 1-in-2 watch standers...... 38
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Acknowledgements
We are grateful to the crew of the HMCS Calgary for their participation in this study, to our DRDC colleagues Michel Paul and Ryan Love for sharing the actigraph sleep data from their watch evaluation study, and Elaine Maceda and Cerys McGuinness for their assistance in data verification and analysis.
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1 Introduction
This report summarises the analysis of sailors’ work and rest schedule, as well as self-reported fatigue levels onboard Her Majesty’s Canadian Ships (HMCS) Calgary during the Trident Fury 2015 exercise. The data were collected for an exploratory study which had a main objective to inform and improve the development of sleep and fatigue prediction algorithms that will be implemented in Defence Research and Development Canada (DRDC) naval crewing analysis software, the Simulation for Crew Optimization and Risk Evaluation (SCORE). The work was funded by the DRDC project 01ab entitled Royal Canadian Navy (RCN) Crewing and Human Factors, specifically the Work Breakdown Element for SCORE validation.
1.1 SCORE and DRDC Fatigue Model
SCORE has been developed for the RCN to conduct what-if assessment on crewing options for its future platforms [1, 2]. The tool enables analysts to articulate work requirements on an RCN vessel, its crewing options, and alternative work assignment schemes in a software environment. A sailor’s daily work schedule and productivity (measured as a utilization rate) can then be estimated, based on which the effectiveness of a crewing option is assessed.
Currently, development effort is taking place to expand SCORE by introducing two algorithms for predicting (1) sailors’ daily sleep patterns based on their work schedules, and (2) their fatigue levels and subsequently the impact on cognitive task performance based on one’s sleep schedules. These algorithms are collectively referred to as the DRDC Fatigue Model (DFM) [3] in this report. Their integration into SCORE will enhance the capability of crewing assessment by connecting crewing options to task performance measures.
The main underlying principles for DFM are similar to those adopted by commercial software like Fatigue Avoidance Scheduling Tool (FAST) [4] and Optimized Work-schedule & Logistics (OWL) [5]. In addition, DFM is comprised of three candidate models for sleep and fatigue prediction [6]. Further validation is needed to ensure the sleep prediction model is well calibrated and the most appropriate fatigue prediction model is selected for the DFM’s future integration with SCORE. An important aspect of the validation effort is to compare model predictions against benchmark data obtained empirically from maritime operations. The Trident Fury 2015 exercise provided an opportunity to collect such operational data. Within the project timeline, this study reflected a preliminary effort to identify major deficiencies in the current modeling approach and prepare for a full-scale validation study that is scheduled for Fall 2016 in the RCN’s Experimental Ship (i.e., X-ship) initiative.
1.2 Ex Trident Fury 2015 and Two Research Studies
Trident Fury is a biennial joint and multinational naval exercise organized by the RCN Maritime Forces Pacific. Running from 4 to 15 May 2015, more than 1200 military personnel, onboard of seven Canadian and American naval and coast guard vessels, participated in the exercise in which a range of air and surface joint operations was conducted, including maritime surveillance, live air and surface weapons firing, and anti-submarine warfare training.
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During this high op-tempo exercise, two teams of DRDC researchers went onboard the HMCS Calgary and collected operational data required for two separate studies: one for evaluating alternative work schedules of the tactical and the engineering watch standers, and the other for analysing the work, rest and fatigue patterns of a more general sailor population to inform SCORE development. In this report, these two studies are referred to as the watch evaluation study and the SCORE development study respectively. These two studies followed different experimental protocols. Between them, watch evaluation was considered the primary study in this exercise and its results have been published elsewhere [5]. The current report is a summary of the SCORE development study.
While their main objectives differed, these two studies shared some similarity in their technical approaches as both required the collection of sleep and fatigue data. However, participants’ sleep was tracked by an actigraph device for watch evaluation whereas self-reported logs were used in the SCORE development study. More importantly, the recruited participants were mutually exclusive from one study to the other, that is, an individual could only participate in one study, but not both.
To utilise the actigraphic sleep data collected in the watch evaluation study, we purposely modified our methodology so that work and rest patterns for participants of the watch evaluation study could also be established to support SCORE development. Specifically, in addition to a daily self-report log that we asked participants to maintain for themselves (which directly tracked their own work/rest schedules), we also created a daily work activity assignment log that was given to supervisors of participants of the watch evaluation study, so that these participants’ work schedule could be recorded. More details about these logs will be provided in the next section.
1.3 Study Purpose
The primary purpose of this study was to analyze the general patterns of sailors’ work, rest schedules and perceived fatigue during this exercise. This report is written to assist SCORE development, particularly the calibration of DFM for maritime application. The existing models in DFM are based on human physiology, thus in principle are applicable to naval personnel. Prior to this study however, the DFM parameters were configured and tested using empirical data obtained from literature which included such operator populations as airline pilots [7]. Recognizing the very different operational conditions faced by sailors, we initiated this study on a Canadian patrol frigate so that DFM will be calibrated using data obtained from its target user population, consequently improving the precision of SCORE predictions. The main objective of this analysis was to supply the following information regarding an RCN sailor’s work, rest and fatigue patterns during Ex Trident Fury 2015. An overview across all ship departments, the durations for various on-duty and off-duty activities that a sailor performs each day, the fluctuation of average daily fatigue ratings during this exercise; For each of the five departments, the specific patterns of work schedule for both watch-standers and non-watch standers; Sailors’ rest schedules in each department, primarily their sleep patterns including the number of sleep episodes each day, the average duration and on-set and wake-up times for each episode, for different watch syndicates and non-watch standers; Average fatigue ratings in each department for sailors that shared similar work and rest schedules.
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2 Methodology
The section primarily describes the trial methodology adopted in the SCORE development study. However, given that actigraphic sleep data were also examined in this analysis, a brief explanation is also provided for the watch evaluation study when such information is deemed important for interpreting the results. For a comprehensive documentation of the watch evaluation study however, readers are referred to its own scientific report [8].
2.1 Participants
A total of 63 volunteers participated in the SCORE development study, and they were classified into two categories. Fifty of them were self-report participants who maintained their own work/rest schedules and fatigue ratings by using a work, rest and fatigue log. These participants were sampled from five ship departments and across different watch rotations, as shown in Table 1.
Table 1: Self-report participants across ship departments and watch syndicates.1
Department 1-in-2 1-in-2 Non-watch Total port stbd standers
Combat department (CBT) 3 1 4 8
Combat Systems Engineering department 4 4 1 9 (CSE)
Deck department (Deck) 3 4 1 8
Logistics department (LOG) 22 22
Marine Systems Engineering department 3 3 (MSE)
Total number of self-report participants 10 9 31 50
Among the 50 self-report participants, 42 of them were male and 8 were female. Their ages ranged from 21 to 51, with a mean age and standard deviation of 33.7 9.1. They were sampled from 34 military occupations and covered 8 rank levels ranging from Ordinary Seaman to Chief Petty Officer 2nd Class.
The remaining 13 participants (out of 63) were supervisors whose task was to complete a daily work activity assignment log, not for themselves, but for members of their team who took part in
1 Watch standing is a naval terminology that refers to the division of personnel on a ship so that it can be operated continuously. 1-in-2 or 1-in-3 are common watch systems where the qualified personnel is divided into 2 or 3 teams respectively. Port and starboard (stbd) are common labels for the 1-in-2 watch teams. White, blue and red are one way to label the 1-in-3 teams.
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the watch evaluation study. Overall, the supervisors provided information for 71 operators or engineers in 5 watch syndicates that were evaluated in this exercise, that is, 1-in-2 port or starboard (stbd) watch, 1-in-3 red or white or blue watch, as shown in Table 2.
For the sake of brevity, we will omit the 1-in-2 and 1-in-3 notation in the rest of this report and refer to these watch syndicates simply as stbd, port, red, white, and blue watch.
Remuneration for participation complied with the guidelines established by DRDC and DND.
Table 2: Supervisor participants and the number of operators and engineers2 they rated across watch syndicates.
Supervisor CBT CBT CSE CSE DECK DECK MSE MSE MSE Total ID port stbd port stbd port stbd red white blue 301 4 4 302 4 2 6 303 3 1 4 304 3 4 7 305 3 3 306 4 4 307 3 3 308 3 3 309 3 5 8 310 8 8 311 9 9 312 7 7 313 2 3 5 Total 22 25 3 3 2 3 7 9 8 71
2.2 Activity Logs
Two logs were used in this study as the primary means for data collection. Firstly, a daily work, rest and fatigue log that is similar to those adopted in past research for the United States Navy [9–12]. It records basic demographic information about a participant, including age, rank level, and military occupation. Sailors’ on-duty and off-duty activities are classified into 8 categories and each is assigned with a unique code (see Table 3). Most activities in this table are self-explanatory except evolution which is a naval term for a scheduled work activity and messing which refers to daily
2 Note, these were participants of the watch evaluation study. Overall, 73 volunteers were recruited in the watch evaluation study and 71 of them were tracked by their supervisors, as shown in this table.
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meals. A 7-point fatigue rating scale is used (see Table 4), which is based on a slight modification of the Stanford Sleepiness Scale [13]. Each log covers a 24-hour period where activity and fatigue are tracked for each 15-min block (see Table 5). The commpplete log is available in Annex A.
Table 3: On-duty and off-duty activitiies and their codings.
Table 4: The Stanford sleepiness scale [10].
Table 5: A daily activity and fatigue log based on a 15-min resolution.
Secondly, a work activity assignment log was created to record work schedules for participants of the watch evaluation study. Because we could not directtly ask thosee participants (of the Watch Evaluation study) to self-report their work schedule, this log was deveeloped for thheir supervisors to describe the assignment of work activities to these members. Thee same set of activity codes (i.e., Table 3) is used in this log and activities are tracked for each 30-minute block throughout a day. The information obtained from this log was associated to the same individual’s sleep data collected in the watch evaluation study, so that a complete picture of work assignment and rest schedule can be established for these watch standers. The complete log is available in Annex B.
2.3 Data Collection
The experimental protocol (#2015-016) for this study was approved by the DRDC Human Research Ethics Committee.
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The data were collected by a team of two researchers who boarded the HMCS Calgary during the entire duration of Ex Trident Fury 2015 from May 4th to 15th. Prior to day one of the exercise, the Commanding Officer of HMCS Calgary identified potential participants for the SCORE development study from a pool of volunteers. These crew members were then briefed about the procedural details of the study. Each was given a copy of the experimental protocol and a consent form. Only those who provided written, informed consent became formal participants. The relevant logs were distributed to them on day one. Participants were instructed to complete a log and return it to the experimenter on a daily basis.
During this exercise, a total of ten days of log data (i.e., from May 4th to 13th) were collected. Since many participants’ logs for day one of the trial (May 4th) were incomplete, we decided to remove all logs for the first day from analysis. Consequently, the results reported in this section are based on log data from the remaining nine days of the trial. Among 50 self-report participants, four of them departed the ship before the end of the exercise which resulted in a loss of 15 logs. Overall, a total of 435 daily self-reported logs (50 participants x 9 days – 15 logs) were analyzed in this study.
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3 Results and Discussions
This section explains key results obtained from this analysis. A summary of all self-reported logs is first presented to provide an overview across ship departments (see 3.1). For SCORE development, an in-depth examination of each department is then provided (see 3.2–3.6), with a further grouping of participants according to their work schedules. Results presented in this section emphasize descriptive statistics of the log data. Cross-department or cross-team comparison could not be reliably conducted due to small sample sizes.
Where applicable, the work and rest schedules for participants of the watch evaluation study are also presented in this section. They are grouped under separate subsection headings (3.2.4, 3.3.4, 3.4.4) to highlight the data collected based on a method that was different from self-reported logs.
3.1 Global Overview Across All Departments
The daily activity times, averaged across all participants during the trial, are shown in Figure 1. It is apparent that a majority portion of a sailor’s daily time was spent on the following four activities: sleep, administration, watch and personal. Together they added up to 21.3h/day or 88.7% of each day. These four activities will be the focus in the following subsections where in-depth analyses for each department are presented. The other four activities (i.e., messing, evolution, maintenance, and other) were accountable for the remaining 11.2% or 3.6h of each day in this exercise. The error bars in this and subsequent graphs represent 95% confidence intervals.
On average, a participant’s daily on-duty time was 11.3h which was distributed across five activities, with watch and administration being the two major contributors (4.7h and 5.0h respectively). A participant’s daily off-duty time was 12.7h, including a mean daily sleep time of 8.3h.
Notably, a small amount of missing data (i.e., 0.1h/day) still existed in the dataset. Its magnitude was too small to affect major conclusions reached in this analysis; therefore it will not be further discussed in this report.
To assist DFM validation, activity times were also reported in Table 6 to show their ranges and variabilities.
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Time (Hour) 9 8.3 8 7 6 5.0 4.7 5 3.3 4 3 1.2 2 0.8 0.5 1 0.3 0.1 0
Figure 1: Daily activity durations across all departments, obtained from self-reported logs.
Table 6: Tabular breakdown of daily activity times across all departments.
Activity Mean StdDev Minimum Maximum Admin 5.0 4.4 0.0 16.3 Watch 4.7 4.6 0.0 16.5 Evolution 0.8 1.6 0.0 9.0 Maintenance 0.5 1.6 0.0 15.5 Other 0.3 1.3 0.0 15.0 On-Duty Total 11.3 2.6 2.8 18.5
Sleep 8.3 1.8 1.3 17.3 Personal 3.3 2.3 0.0 12.3 Messing 1.2 1.3 0.0 7.0 Off-Duty Total 12.7 2.6 5.3 21.3
Missing Data 0.1 0.3 0.0 2.0
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Averaged across all self-report participants, the mean daily fatigue rating was 2.7 and there were no significant differences in fatigue ratings across trial dates, as shown in Figure 2.
7.0 Fatigue rating
6.0
5.0
4.0 2.8 2.8 2.6 2.5 2.7 2.7 2.7 2.7 2.7 3.0
2.0
1.0
0.0 May 5May 6May 7May 8May 9May 10 May 11 May 12 May 13
Figure 2: Average daily fatigue ratings across the 9-day trial.
3.2 Combat Department (CBT)
Eight (8) self-report participants were recruited for the SCORE development study from the Combat department. They were classified into three groups based on their work schedule: three of them stood port watch, one stbd watch and the remaining four were non-watch standers (i.e., day workers).
Figure 3 shows the breakdown of average daily activity times for the three groups, with the data repeated in a tabular form for assisting DFM validation in Table 7.
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14 Time (hour) CBT department 12 Non‐Watch stander
10 Port
Stbd 8
6
4
2
0
Figure 3: The distribution of average daily activity times in the CBT department.
Table 7: The breakdown of activity times and their variabilities in the CBT department. (Unit: hour/day). Non-watch stander Port Stbd All Mean StdDev Mean StdDev Mean StdDev Mean StdDev Sleep 8.4 1.3 9.2 1.8 9.7 0.8 8.9 1.5 Admin 0.5 0.8 2.4 4.3 0.0 0.0 1.2 2.9 Watch 8.8 2.6 9.3 5.5 12.3 0.3 9.5 4.0 Personal 4.0 1.5 1.8 1.7 1.3 0.7 2.7 1.9 Messing 1.6 1.7 0.9 1.5 0.1 0.4 1.1 1.6 Evolution 0.3 1.0 0.4 1.0 0.2 0.7 0.3 0.9 Maintenance 0.0 0.0 0.0 0.0 0.5 0.8 0.1 0.4 Other 0.6 2.6 0.0 0.1 0.0 0.0 0.3 1.7 MissingData 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 OnDutyTotal 10.2 2.2 12.1 2.2 13.0 0.9 11.4 2.3 OffDutyTotal 13.9 2.2 11.9 2.2 11.1 0.9 12.7 2.4
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3.2.1 On-Duty Activities
3.2.1.1 Watch
Watch keepers in this exercise followed a 1-in-2 rotation and an 8-4-4-8 schedule. The 1-in-2 stbd team started work each day at 0400h for an 8-hour watch, then they were off watch for 4 hours before starting a second, 4-hour, watch at 1600h. They had an 8-hour off-watch between 2000h and 0400h. The schedules for the 1-in-2 port team were complementary to those of the 1-in-2 stbd team. In total, each watch keeper was on watch for 12 hours every day, their detailed duty periods are shown in Table 8.
Table 8: 1-in-2 watch rotation schedule adopted in Ex Trident Fury 2015.
Watch Duty periods 1-in-2 Stbd 04:00-12:00 and 16:00-20:00 1-in-2 Port 20:00-04:00 and 12:00-16:00
According to the self-reported logs, many participants started before their scheduled watch for shift turnover, in some cases up to 30 min earlier. This was reflected by the stbd participant’s data for time-on-watch (12.3h/day), as shown in Table 7. The port watch participants logged fewer hours (9.3h/day) because a portion of their watch-keeping involved administrative activities, and was logged as such.
The non-watch standers reported an average of 8.8h/day for watch keeping, which created some confusion since technically they were categorized as non-watch standers and their work time should not be coded as watch-standing. It reveals an issue in activity coding used in the logs which should be revised in future studies. In the current analysis, the time-on-watch reported by non-watch standers was simply treated as on-duty work time. Another possibility is that some participants assumed more than one role on the ship. While they self-identified as a day-worker, they sometimes stood watch when needed.
3.2.1.2 Administration
Participants on port watch logged a significant amount of time (2.4h/day) for administrative activities such as meeting, training or departmental work. None was reported by the stbd watch operator, notably in this case, by a single participant.
Only 0.5h/day was recorded by non-watch standers as administrative tasks. As indicated previously, most of non-watch standers’ on-duty activities were reported as watch-keeping.
3.2.1.3 Maintenance
Minimal maintenance activities were reported, with 0.1h/day averaged across all CBT department participants.
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3.2.1.4 Evolution
A small amount of evolution activities was reported in this exercise, with an average of 0.3h/day for each CBT department participant.
3.2.1.5 Other
Day workers logged 0.6h/day as other work-related activities, whereas the coding was essentially not used by watch keepers.
3.2.2 Off-Duty Activities
3.2.2.1 Sleep
Based on self-reported logs, participants reported a mean of 8.9h for daily sleep in the CBT department. Watch standers logged longer sleep time (9.2h/day for port and 9.7h/day for stbd) than day workers (8.4h/day).
The sleep patterns between watch standers and day workers are different, as shown in Table 9. A watch stander’s sleep was typically fragmented into two episodes each day, with a long sleep that covered a portion of the night time (average duration: 6.9h for port and 6.2h for stbd) and a shorter nap during the day (average duration: 2.8h for port and 3.0h for stbd). Most non-watch standers reported a single long sleep at night (average duration 8.0h) and only occasionally afternoon naps were taken when needed. In this exercise, only a single nap was logged by a CBT non-watch stander with a duration of 1.8h.
Further characterizations of each sleep episode are also presented in Table 9, including the mean on-set and wake-up times for each sleep episode. As an example, for port watch keepers, 23 observations of night sleep were obtained from the logs, with an average start and end times at 4.4 (04:24) and 11.3 (11:18) respectively, thus a mean duration of 6.9 hours. Notably in this table and similar ones in the following subsections, the reported duration of a sleep episode was calculated by counting the actual time when participants were asleep. In cases where sleep interruptions took place, the calculated duration will be less than the length between its start and end times, such as the 1st sleep period for non-watch standers in Table 9. Also, the number of observations (i.e., N) of each sleep episode indicates how often such a sleep was taken. For example, only 19 observations of the 2nd sleep period were recorded for port watch, reflecting not all port watch participants took the second sleep period in this exercise.
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Table 9: Sleep on-set, wake-up times, and duration for the CBT department, obtained from self-reported logs. Watch Sleep period 1 Sleep period 2 start3 end duration start end duration Port N 23 23 23 19 19 19 Mean 4.4 11.3 6.9 17.0 19.8 2.8 StdDev 0.4 0.8 1.0 0.5 0.4 0.8 Stbd N 8 8 8 8 8 8 Mean 21.1 3.3 6.2 12.4 15.4 3.0 StdDev 0.9 1.3 1.3 0.6 0.5 0.7 Day workers N 24 24 24 1 1 1 Mean 22.2 6.3 8.0 14.0 15.8 1.8 StdDev 0.8 1.9 1.9 0 0 0
3.2.2.2 Personal
A 4.0h/day was logged by non-watch standers for personal activities, in contrast to 1.8h/day and 1.3h/day by port and stbd watch respectively.
3.2.2.3 Messing
On average, 1.1h/day was reported for messing (i.e., meals) in the CBT department.
3.2.3 Fatigue Ratings
Figure 4 shows the temporal profiles of fatigue rating for three watch groups. Each data point in these graphs represents an average value of all fatigue ratings available for the respective time block. Therefore, a fatigue rating of zero indicates all participants were asleep at that time block throughout the exercise. On the other hand, a non-zero rating for a time block that is commonly the sleep hour of a group reflects that at least one participant from this group consistently did not sleep at this time block during the exercise. A threshold of four occurrences was adopted to filter out one-off instances where a participant did not sleep at the regular rest time.
These diagrams reveal that participants’ sleep patterns were synchronised to some extent. There were periods of time that all participants of the same group were asleep, i.e., 23:15–05:00 for non-watch standers, 04:30–11:00 for port, 21:00–03:30 and 12:45–15:30 for stbd. These periods reflect a portion of the time window designed for the major daily sleep of each group. It is useful to point out that the duration of these synchronised sleep periods are shorter than the mean
3 In this and subsequent similar tables,the mean start and end times of each sleep period represent a time of the day, wheras the StdDev reflects a duration. For example, in this table, the mean start time for the first sleep period is 4.4 which reflects a clock time of 04:24, and the variability of this start time is measured by its StdDev of 0.4 which corresponds to 24 minutes.
DRDC-RDDC-2017-R048 13
duration of each sleep episode presented in the previous subsection, reflecting the variabilities in sleep on-set and wake-up times among participants.
An elevated level of fatigue was observed for time blocks immediately before and after these synchronised sleep periods, indicating some participants needed either to stay up later or wake up earlier, both of which intuitively would lead to an increase of fatigue.
For the port watch, an elevated level of fatigue (i.e., greater than 4) was observed during the period between 00:00 and 04:00. Also their afternoon naps were not reflected in the diagram, indicating such naps were not consistently taken by all group members throughout the exercise. A further investigation revealed one port watch participant consistently skipped the afternoon nap.
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Fatigue rating CBT department 7 (Non‐watch standers) 6 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Fatigue rating 7 CBT department 6 (Port watch) 5 4 3 2 1 0 Time
0000 0045 0130 0215 0300 0345 0430 0515 0600 0645 0730 0815 0900 0945 1030 1115 1200 1245 1330 1415 1500 1545 1630 1715 1800 1845 1930 2015 2100 2145 2230 2315 Fatigue rating CBT department 7 6 (Stbd watch) 5 4 3 2 1 0 Time
0000 0045 0130 0215 0300 0345 0430 0515 0600 0645 0730 0815 0900 0945 1030 1115 1200 1245 1330 1415 1500 1545 1630 1715 1800 1845 1930 2015 2100 2145 2230 2315 Figure 4: Fatigue profiles for non-watch standers (top), port watch (middle), and stbd watch (bottom) in the CBT department.
DRDC-RDDC-2017-R048 15
The average fatigue rating for three watch groups is shown in Figure 5, with a higher level of fatigue reported by port watch (M = 3.6, StdDev = 1.0), and a lower level by non-watch standers (M = 2.2, StdDev = 0.8).
Fatigue rating 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 Non‐watch stander Port Stbd
Figure 5: Average fatigue rating for three watch groups in the CBT department.
3.2.4 Actigraphic Sleep and Work Assignment Data for Watch Standers
In addition to self-reported logs analyzed above, actigraphic sleep data were collected for 34 watch-standers in the CBT department (18 stbd and 16 port) as a part of the watch evaluation study. These participants’ daily work assignments were recorded by their supervisors using the daily work assignment log. A thorough analysis of this dataset, for the purpose of watch schedule evaluation, was completed and documented elsewhere [8]. In this report, we review the actigraphic sleep data for watch-standers and their work assignment beyond the regular watch hours.
Table 10 shows the same set of sleep statistics that were previously compiled for two watch teams based on self-reported logs. Compared to Table 9, it is apparent that the general sleep patterns obtained from these two datasets were comparable, however actigraphically tracked sleep durations were shorter than logged sleep times for both sleep periods. Such discrepancy will be discussed in Section 4.
Table 10: Sleep on-set, wake-up times, and duration for the CBT department, based on actigraph data from the Watch Evaluation study. Watch Sleep period 1 Sleep period 2 start end duration start end duration Port N 166 166 166 123 123 123 Mean 4.3 10.9 6.7 17.4 19.2 1.9 StdDev 0.5 0.8 0.8 0.7 0.9 0.6 Stbd N 167 167 167 137 137 137
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Watch Sleep period 1 Sleep period 2 start end duration start end duration Mean 21.2 3.4 6.1 12.8 15.2 2.4 StdDev 0.7 1.7 0.9 0.5 0.7 0.8
Table 11 summarises work assignment for watch standers beyond their regular watch hours. These are work activities conducted during their off-watch hours, in other words, in addition to their daily 12h watch-keeping.
Table 11: Off-watch work assignment for watch standers in the CBT department. (Unit: hour/day). Watch Administration Evolution Maintenance Other Watch Total Port 0.3 0.1 0.0 0.0 0.2 0.6 Stbd 0.3 0.0 0.0 0.0 0.1 0.4
3.3 Combat Systems Engineering Department (CSE)
Nine (9) self-report participants were recruited from the CSE department, four stood port watch, four stbd watch and one was a non-watch stander (i.e., day worker). For watch standers, they also followed a 1-in-2 rotation and an 8-4-4-8 schedule in this exercise, identical to the CBT watch standers (see Table 8). Figure 6 shows the breakdown of average daily activity times for three watch groups, with the data repeated in a tabular form in Table 12.
Time (Hour) 14 CSE department
12 Non‐Watch stander
10 Port
8 Stbd
6
4
2
0
Figure 6: The distribution of average daily activity times in the CSE department.
DRDC-RDDC-2017-R048 17
Table 12: The breakdown of daily activity times and their variabilities in the CSE department. (Unit: hour/day). Non-watch stander Port Stbd All Mean StdDev Mean StdDev Mean StdDev Mean StdDev Sleep 8.3 0.7 7.8 1.7 7.7 1.7 7.8 1.6 Admin 11.3 1.3 4.0 3.7 6.4 5.0 5.8 4.7 Watch 0.0 0.0 5.8 3.7 3.5 3.3 4.1 3.7 Personal 2.0 0.7 3.4 1.7 2.4 1.6 2.8 1.7 Messing 0.8 0.8 0.2 0.3 1.2 0.8 0.7 0.8 Evolution 0.0 0.0 1.7 1.8 0.5 0.8 1.0 1.4 Maintenance 1.8 1.0 1.0 1.4 1.9 3.9 1.5 2.8 Other 0.0 0.0 0.2 0.5 0.5 2.5 0.3 1.7 MissingData 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.1 OnDutyTotal 13.0 0.9 12.7 1.3 12.7 1.9 12.7 1.6 OffDutyTotal 11.1 0.9 11.3 1.4 11.3 1.9 11.3 1.6
3.3.1 On-Duty Activities
Overall, participants from the CSE department reported an average of 12.7h/day for various work activities.
3.3.1.1 Watch
For watch-standers, a longer time-on-watch was recorded for port (5.8h/day) than stbd watch (3.5h/day), but both were shorter than the theoretical 12h/day. A review of logs revealed a significant portion of on-watch hours were regularly spent for other types of work activities, such as administration, evolution, and maintenance.
3.3.1.2 Administration
An average of 5.8h/day was logged as administration activities in the CSE department. It was the primary activity for the non-watch stander who recorded 11.3h/day. For watch keepers, 4.0h/day and 6.4h/day were logged for port and stbd respectively.
3.3.1.3 Maintenance
All three groups reported time for maintenance activities, with a mean duration of 1.5h/day in this exercise.
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3.3.1.4 Evolution
On average, 1.0h/day for evolution was reported by watch standers, with 1.7h/day for port and 0.5h/day for stbd.
3.3.1.5 Other
Minimal time was recorded for other activities, with an average of 0.3h/day for all participants.
3.3.2 Off-Duty Activities
3.3.2.1 Sleep
Overall participants of the CSE department reported a mean of 7.8h for daily sleep, which can be further broken down into 7.8h/day for port, 7.7h/day for stbd, and 8.3h/day for the day worker respectively.
A watch keeper’s sleep was commonly fragmented into two episodes each day, occurring at two off- watch periods, with a long sleep that covered a portion of the night time (average duration: 6.6h for port and 6.3h for stbd) and a nap during the day (average duration: 3.0h for port and 2.2h for stbd), as shown in Table 13.
It is useful to note these two sleep periods were not strictly followed by all watch-standers. In this exercise, two participants’ sleep times deviated from others, resulting in a 3rd sleep period for each watch team. Based on a closer examination, we decided to treat the 3rd sleep period as an anomaly, rather than the general pattern for either watch team. The non-watch stander reported a single sleep period for each day during this exercise.
Table 13: Sleep on-set, wake-up times, and duration for the CSE department. Watch Sleep period 1 Sleep period 2 Sleep period 3 start end durationstart end duration start end duration Port N 33 33 33 13 13 13 3 3 3 Mean 4.3 10.96.6 16.919.9 3.0 0.3 8.2 7.8 StdDev 0.3 0.9 0.9 0.9 0.4 1.0 0.6 0.6 1.2 Stbd N 28 28 28 24 24 24 8 8 8 Mean 21.2 3.6 6.3 13.315.5 2.2 0.9 3.5 2.6 StdDev 0.8 0.6 1.3 0.6 0.3 0.7 1.3 0.6 1.4 Non-watch stander N 8 8 8 Mean 22.3 6.7 8.4 StdDev 0.2 0.7 0.7
3.3.2.2 Personal
The mean time spent on personal activities was 2.8h/day across all nine participants.
DRDC-RDDC-2017-R048 19
3.3.2.3 Messing
On average, 0.7h/day was recorded for messing by CSE participants.
3.3.3 Fatigue Ratings
Figure 7 shows the temporal profiles of fatigue rating for three watch groups. Constructed in the same way as Figure 4, each data point in these graphs represents an average value of all fatigue ratings available for the respective time block.
A period of sleep time was consistently followed by all participants of each group throughout the exercise. They were 22:00–06:30 for the non-watch stander, 04:30–08:15 for port watch, and 22:30–03:30 for stbd watch. Elevated fatigue ratings were observed immediately before and after these synchronised sleep times. A high level of fatigue was reported by port watch-standers during 00:00–04:00. However, the overall average fatigue ratings were comparable to one another, as shown in Figure 8.
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Fatigue rating 7 CSE department 6 (non‐watch stander) 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300
Fatigue rating 7 CSE department 6 (Port watch) 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Fatigue rating CSE department 7 6 (Stbd watch) 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Figure 7: Fatigue profiles for non-watch standers (top), port watch (middle), and stbd watch (bottom) in the CSE department.
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Fatigue rating 7
6
5
4
3
2
1
0 Non‐watch stander Port Stbd
Figure 8: Average fatigue rating for three groups in the CSE department.
3.3.4 Actigraphic Sleep and Work Assignment Data for Watch Standers
Actigraphic sleep data were collected for six watch-standers in the CSE department (3 stbd and 3 port) as a part of the watch evaluation study. These participants’ daily work assignments were recorded by their supervisors using the daily work assignment log.
Table 14 shows the same types of sleep statistics that were previously compiled for two watch teams based on self-reported logs in Table 13. By comparing these two tables, it is apparent that the general patterns of two sleep periods are similar, with actigraphic data reflecting shorter sleep durations. A 3rd sleep period was not obtained from actigraphic data, confirming our earlier conclusion that such sleeps were an anomaly for the respective watch team.
Table 14: Sleep on-set, wake-up times, and duration for the CSE department, based on actigraph data from the Watch Evaluation study. Watch Sleep period 1 Sleep period 2 start end duration start end duration Port N 29 29 29 25 25 25 Mean 4.5 11.0 6.5 17.0 19.5 2.5 StdDev 0.3 1.0 1.1 0.6 0.5 0.6 Stbd N 38 38 38 28 28 28 Mean 21.8 3.3 5.6 13.1 15.3 2.1 StdDev 0.7 0.5 0.9 0.8 0.7 1.0
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Minimal work assignments were recorded in supervisor logs beyond watch-standers’ regular watch hours, as shown in Table 15. On average, 0.1h/day were assigned to the port watch for evolution activities when these participants were off-watch.
Table 15: Off-watch work assignment for watch standers in the CSE department. (Unit: hour/day). Watch Administration Evolution Maintenance Other Watch Total Port 0.0 0.1 0.0 0.0 0.0 0.1 Stbd 0.0 0.0 0.0 0.0 0.0 0.0
3.4 Deck Department (Deck)
Eight (8) self-report participants were recruited from the Deck department; three of them stood port watch, four stbd watch and one non-watch stander (i.e., day worker). For watch keepers, they also followed a 1-in-2 rotation and an 8-4-4-8 schedule in this exercise, identical to the CBT watch-standers (see Table 8).
Figure 9 shows the breakdown of average daily activity times for three watch groups, with the data repeated in a tabular form in Table 16.
Time (Hour) 16 Deck department
14 Non‐Watch stander
12 Port
10 Stbd
8
6
4
2
0
Figure 9: The distribution of average daily activity times in the Deck department.
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Table 16: The breakdown of daily activity times and their variabilities in the Deck department. (Unit: hour/day). Non-watch stander Port Stbd All Mean StdDev Mean StdDev Mean StdDev Mean StdDev Sleep 6.9 0.6 6.9 2.1 8.3 2.2 7.6 2.2 Admin 6.2 1.4 1.8 2.3 3.7 3.2 3.3 3.1 Watch 0.0 0.0 10.4 3.3 5.5 3.0 6.6 4.5 Personal 4.2 1.3 2.5 2.4 2.1 2.5 2.5 2.4 Messing 2.7 0.8 0.2 0.4 0.8 1.0 0.8 1.1 Evolution 3.0 1.8 1.8 2.2 2.1 2.3 2.1 2.2 Maintenance 0.0 0.0 0.5 1.0 0.5 1.1 0.4 1.0 Other 0.0 0.0 0.1 0.4 1.2 2.4 0.6 1.8 MissingData 1.0 0.7 0.0 0.0 0.0 0.3 0.1 0.4 OnDutyTotal 9.2 1.3 14.6 2.4 12.9 2.2 13.1 2.7 OffDutyTotal 13.9 1.2 9.5 2.4 11.1 2.2 10.8 2.6
3.4.1 On-Duty Activities
Overall the total on-duty time for participants of the Deck department was 13.1h/day, with watch keepers reporting 14.6h/day and 12.9h/day (for port and stbd respectively.)
3.4.1.1 Watch
A longer time-on-watch was reported by port (10.4h/day) than stbd watch keepers (5.5h/day). A review of logs revealed a significant portion of on-watch hours were logged as administration and evolution activities by the stbd participants.
3.4.1.2 Administration
An average of 3.3h/day was logged as administrative activities in the Deck department. It is the primary activity for the non-watch stander who reported 6.2h/day. For watch standers, 1.8h/day and 3.7h/day were logged for port and stbd respectively.
3.4.1.3 Maintenance
On average, 0.5h/day was recorded for maintenance activities by watch standers.
3.4.1.4 Evolution
Evolutions are a major activity for the Deck department, and participants logged a mean duration of 2.1h/day in this exercise. The non-watch stander recorded a longer time (3.0h/day) than either watch team (1.8h/day for port, 2.3h/day for stbd).
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3.4.1.5 Other
The stbd watch standers logged an average of 1.2h/day for other activities, whereas the coding was minimally used by port watch (0.1h/day) and the non-watch stander (0.0h/day).
3.4.2 Off-Duty Activities
3.4.2.1 Sleep
Overall participants of the Deck department reported a mean of 7.6h for daily sleep. The day-worker and port watch logged shorter sleep time (both 6.9h/day) than stbd watch standers (8.3h/day).
Many watch standers’ sleep was fragmented into two episodes each day, occurring at two off-watch periods, with a long sleep that covered a portion of the night time (average duration: 5.5h for port and 8.0h for stbd) and a nap during the day (average duration: 2.4h for port and 3.6h for stbd). However, such a 2-episode daily sleep schedule was not strictly followed by all watch-standers. Two (out of 4) stbd watch-standers did not have an afternoon nap at all and their sleep schedules resembled more closely to non-watch standers. As a result, the mean wake-up time of the first sleep period (i.e., 4:48) exceeded the regularly scheduled watch start time (i.e., 4:00).
Table 17: Sleep on-set, wake-up times, and duration for the Deck department. Watch Sleep period 1 Sleep period 2 start end duration start end duration Port N 25 25 25 17 17 17 Mean 4.4 9.9 5.5 17.2 19.6 2.4 StdDev 0.3 1.5 1.6 0.8 0.4 0.9 Stbd N 28 28 28 6 6 6 Mean 20.9 4.8 8.0 12.1 15.7 3.6 StdDev 1.3 1.5 1.1 0.1 0.7 0.7 Day N 9 9 9 Mean 22.7 5.1 6.4 StdDev 0.5 2.0 2.1
3.4.2.2 Personal
The mean time spent on personal activities was 2.5h/day across all nine participants, with 4.2h/day for the non-watch stander, 2.5h/day for port and 2.1h/day for stbd watch standers.
3.4.2.3 Messing
On average, 0.7h/day was recorded for messing in the Deck department.
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3.4.3 Fatigue Ratings
Figure 10 shows the temporal profiles of fatigue rating for the three watch groups. Constructed in the same way as Figure 4, each data point in these graphs represents an average value of all fatigue ratings available for the respective time block.
The log data revealed a period of sleep time was strictly followed by all participants of each group throughout the exercise. They were 00:00–04:30 for the non-watch stander, 04:30–07:00 for port watch, and 00:00–03:45 for stbd watch. Watch keepers reported a moderate level of fatigue throughout the day, with a higher level observed for port watch (see Figure 11) and a peak level logged by port watch at around 04:00.
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Fatigue rating 7 Deck department 6 (Non‐Watch Stander) 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300
Fatigue rating 7 Deck department 6 (Port Watch) 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Fatigue rating Deck department 7 6 (Stbd Watch) 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Figure 10: Fatigue profiles for non-watch standers (top), port watch (middle), and stbd watch (bottom) in the Deck department.
DRDC-RDDC-2017-R048 27
7 Fatigue 6 5 4 3 2 1 0 Non‐watch stander Port Stbd Figure 11: Average fatigue rating for three watch groups in the Deck department.
3.4.4 Actigraphic Sleep and Work Assignment Data for Watch Standers
Actigraphic sleep data were collected for five watch-standers in the Deck department (two stbd and three port) as a part of the watch evaluation study. One stbd watch-stander’s data were removed from analysis since the actigraphic sleep times could not reconcile with the participant’s assigned watch times.
Table 18 shows the same types of sleep statistics that were previously compiled for two watch teams based on self-reported logs in Table 17. By comparing these two tables, it is apparent that the general patterns of two major sleep periods are similar, with actigraphic data indicating shorter sleep durations, with an exception for the port watch-standers where actigraphically-tracked major sleep was longer (6.0h/day) than the logged one (5.5h/day).
The daily work assignment logs did not record any additional work activities for watch-standers beyond their watch hours.
Table 18: Sleep on-set, wake-up times, and duration for the DECK department, based on actigraph data from the Watch Evaluation study. Watch Sleep period 1 Sleep period 2 start end duration start end duration Port N 19 19 19 19 19 19 Mean 4.3 10.3 6.0 17.0 18.9 2.0 StdDev 0.5 1.4 1.3 0.7 0.7 0.7 Stbd N 29 29 29 18 18 18 Mean 21.4 3.4 6.0 13.3 15.1 1.9 StdDev 0.5 0.3 0.6 0.6 0.6 0.6
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3.5 Logistics Department (LOG)
Twenty-two (22) self-report participants were recruited from the LOG department; all of them were coded as non-watch standers. Among them, four (two cooks and two stewards) worked at night (hereafter referred to as night workers) and the rest were day workers. The subsequent analysis in this subsection examined work and rest schedules for these two groups separately.
Figure 12 shows the breakdown of average daily activity times the LOG department, with the data repeated in a tabular form in Table 19.
12.0 Hour LOG department
10.0 (Non‐watch standers)
8.0 dayworker nightworker
6.0
4.0
2.0
0.0
Figure 12: The distribution of average daily activity times in the LOG department.
Table 19: The breakdown of daily activity times and their variabilities in the LOG department. (Unit: hour/day). Day worker Night worker All Mean StdDev Mean StdDev Mean StdDev Sleep 8.1 1.3 9.4 2.5 8.3 1.7 Admin 6.7 4.1 4.7 4.9 6.4 4.4 Watch 2.7 3.5 4.9 5.1 3.1 3.9 Personal 3.9 2.4 3.0 2.1 3.8 2.3 Messing 1.7 1.2 1.7 1.4 1.7 1.3 Evolution 0.6 1.4 0.0 0.2 0.5 1.2 Maintenance 0.1 0.4 0.3 1.2 0.1 0.7 Other 0.2 0.6 0.1 0.2 0.2 0.6 MissingData 0.1 0.4 0.0 0.2 0.1 0.3
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Day worker Night worker All Mean StdDev Mean StdDev Mean StdDev OnDutyTotal 10.3 2.3 10.0 2.1 10.2 2.3 OffDutyTotal 13.7 2.5 14.1 2.3 13.7 2.4
3.5.1 On-Duty Activities
Overall the total on-duty time for LOG department participants was 10.2h/day.
3.5.1.1 Watch
An average 3.1h/day was recorded as watch-standing, with 2.7h/day for day workers and 4.9h/day for night workers.
3.5.1.2 Administration
Day workers logged a longer 6.7h/day for administrative activities than night workers’ 4.7h/day.
3.5.1.3 Maintenance
Minimal maintenance activities were recorded, with an average of 0.1h/day for each LOG participant.
3.5.1.4 Evolution
Day workers reported 0.6h/day for evolution in this exercise, compared to 0h/day for night workers.
3.5.1.5 Other
On average, 0.2h/day was logged for other on-duty activities.
3.5.2 Off-Duty Activities
3.5.2.1 Sleep
Overall participants of the LOG department reported a mean of 8.3h for daily sleep, which was comprised of a major long sleep and very occasional naps when needed.
In this exercise, the general sleep pattern for night workers was a single long sleep during the day, on average starting from 8:12 and ending at 17:36 with a duration of 9.3h. A brief break was sometimes observed during their sleep (in day time) to accommodate a meal. In this analysis, we counted such sleeps as a single episode but the brief wake-up times was not counted when computing the sleep duration.
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As shown in Table 20, for day workers, most reported a single night sleep with an average duration of 8.0h/day (start: 20:36; end: 6:24); however patterns of alternative sleep periods also emerged, such as periods 2 and 3 in the table indicating occasional changes of rest schedule likely due to operational requirements. The sleep periods 4, 5 and 6 were all observed from one participant whose rest schedule was more fragmented than other non-watch standers. No data was available in the current analysis to confirm whether such a pattern is regular or not.
Table 20: Sleep on-set, wake-up times, and duration for non-watch standers in the LOG department: (top) day workers, (bottom) night workers. Watch Sleep period 1 Sleep period 2 Sleep period 3 start end duration startend duration start end duration Dayworker N 133 133 133 13 13 13 3 3 3 Mean 20.6 6.4 8.0 14.115.8 1.7 5.4 8.3 2.9 StdDev 5.5 1.3 1.3 0.9 0.9 1.0 4.3 3.2 1.0 Watch Sleep period 4 Sleep period 5 Sleep period 6 start end duration startend duration start end duration Dayworker N 7 7 7 4 4 4 2 2 2 Mean 3.9 8.8 4.9 20.823.0 2.2 23.0 6.6 7.6 StdDev 0.2 1.0 0.9 0.7 0.0 0.7 1.4 0.5 0.9
Watch Sleep period 1 start end duration Nightworker N 35 35 35 Mean 8.2 17.6 9.3 StdDev 1.1 2.0 1.9
3.5.2.2 Personal
The mean time spent on personal activities was 3.8h/day for a LOG participant.
3.5.2.3 Messing
On average, 1.7h/day was recorded for messing.
3.5.3 Fatigue Ratings
Figure 13 shows the temporal profiles of fatigue rating for non-watch standers in the LOG department and a distinction was made between those who slept during night versus day. Constructed in the same way as Figure 4, each data point in these graphs represents an average value of all fatigue ratings available for the respective time block.
DRDC-RDDC-2017-R048 31
Different from other departments, a distinctive period of time could not be identified for the LOG department when every participant was asleep, which generally indicates a lack of synchronization in their rest schedules, thus their work schedules as well. Overall a moderate rating was obtained for average fatigue (see Figure 14), with a higher rating reported by night workers (M = 2.8, StdDev = 0.7) than day workers (M = 2.4, StdDev = 0.7). And elevated fatigue levels were typically associated with a disruption of regular sleep which was applicable to both night and day workers.
Fatigue rating 7 Average fatigue rating for LOG department (Non‐Watch standers) 6
5 Day workers
4
3
2
1 Night workers
0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Figure 13: Fatigue profiles for non-watch standers in the LOG department.
Fatigue rating 7
6
5
4
3
2
1
0 Day workers Night workers
Figure 14: Average fatigue rating for non-watch standers in the LOG department.
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3.6 Marine Systems Engineering Department (MSE)
Three (3) self-report participants were recruited from the MSE department, all of them were non-watch standers and notably two were trainees. Figure 15 shows the breakdown of average daily activity times, with the data repeated in a tabular form in Table 21.
Time (Hour) MSE department 12.0 (Non‐watch standers) 10.0
8.0
6.0
4.0
2.0
0.0
Figure 15: The average daily activity times in the MSE department for non-watch standers.
Table 21: The breakdown of daily activity times and their variabilities in the MSE department. (Unit: hour/day). Non-watch stander Mean StdDev Sleep 9.4 1.9 Admin 5.2 3.4 Watch 1.5 2.5 Personal 4.6 2.4 Messing 0.5 0.8 Evolution 0.5 1.1 Maintenance 1.9 2.7 Other 0.4 1.0 MissingData 0.0 0.0 OnDutyTotal 9.5 2.2 OffDutyTotal 14.5 2.2
DRDC-RDDC-2017-R048 33
3.6.1 On-Duty Activities
Overall, three non-watch standers recorded an average of 9.5h/day for various work activities in this exercise.
3.6.1.1 Watch
One non-watch stander (a trainee) recorded 1.5h/day for watch-standing.
3.6.1.2 Administration
An average of 5.2h/day was logged for administrative activities by each participant.
3.6.1.3 Maintenance
An average of 1.9h/day was logged for maintenance activities by each participant.
3.6.1.4 Evolution
0.5h/day was the average time spent on evolution. However, a closer examination of the logs revealed that two trainees were not involved in evolution activities in this exercise. As a result, all evolution activities were performed by the remaining participant and the daily task time should be revised to 1.5h/day.
3.6.1.5 Other
On average, 0.4h/day was reported for other work-related activities in this exercise.
3.6.2 Off-Duty Activities
3.6.2.1 Sleep
Overall three non-watch standers reported a mean daily total sleep of 9.4h, which was typically comprised of a single sleep at night with occasional afternoon naps when the night sleep was shortened due to a variety of reasons (e.g., maintenance tasks or personal activities). On average, the night sleep started at 21:24 and ended at 7:00, with a duration of 9.2h. A total of 5 afternoon naps were taken with a mean duration of 1.1h.
Table 22: Sleep on-set, wake-up times, and duration for non-watch standers in the MSE department. Watch Sleep period 1 Sleep period 2 start end duration start end duration Non-watch standers N 24 24 24 5 5 5 Mean 21.4 7.0 9.2 13.3 14.4 1.1 StdDev 1.2 1.8 1.9 2.8 2.8 0.5
34 DRDC-RDDC-2017-R048
3.6.2.2 Personal
An average of 4.6h/day was recorded for personal activities.
3.6.2.3 Messing
An average of 0.5h/day was recorded for messing.
3.6.3 Fatigue Ratings
Figure 16 shows the temporal profile of fatigue rating for non-watch standers in the MSE department. Constructed in the same way as Figure 4, each data point in these graphs represents an average value of all fatigue ratings available for the respective time block.
Three participants’ sleep schedules were well synched for the period between 22:30 and 06:00. A moderate level of fatigue (with a mean rating of 3.1, as shown in Figure 17) was reported for the wake-up hours.
Fatigue rating 7 MSE department 6 (Non‐watch standers) 5 4 3 2 1 0 Time 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 Figure 16: Fatigue profiles for non-watch standers in the MSE department.
DRDC-RDDC-2017-R048 35
Fatigue rating 7 6 5 3.1 4 3 2 1 0 Non‐watch stander
Figure 17: Average fatigue rating for non-watch standers in the MSE department.
3.6.4 Actigraphic Sleep and Work Assignment Data for Watch Standers
Twenty-four (24) watch standers from the MSE department participated in the watch evaluation study, 7 stood 1-in-3 red watch, 9 stood 1-in-3 white watch, 8 stood 1-in-3 blue watch. They followed a 1-in-3 rotation and each worked two 4-hour periods each day, as shown in Table 23. Their sleep patterns were actigraphically tracked in this exercise and three supervisors, one for each watch syndicate, provided daily work assignment data for each watch team.
Table 23: 1-in-3 watch schedule for the MSE department.
Watch Duty periods 1-in-3 Red 08:00–12:00 and 20:00–00:00 1-in-3 White 12:00–16:00 and 00:00–04:00 1-in-3 Blue 16:00–20:00 and 04:00–08:00
According to actigraphically-measured data (see Table 24), the average daily total sleep times for MSE watch-standers were 6.5h/day, 7.9h/day, and 6.7h/day for Red, White, and Blue watch respectively. Like watch-standers who followed 1-in-2 rotations, their daily sleep was typically comprised of two episodes, with a longer sleep that covers a portion of the night time and a shorter nap during the day. The timing for the shorter nap, however, was not always consistent for operators of the same watch. For the Blue watch team, 57% of the naps were taken between 9:12 and 12:36, and the other 43% between 12:06 and 14:36. For the Red watch team, 75% of the naps were between 14:00 and 15:30 whereas the other 25% were between 17:24 and 18:48. In contrast, all naps for the White watch team were taken between 19:30 and 22:48.
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The cause of such sub-team patterns could not be further investigated in this analysis due to the lack of supporting data.
Table 24: Sleep on-set, wake-up times, and duration for watch-standers in the MSE department, obtained from actigraphic sleep data. Watch Daily total sleep Sleep period 1 Sleep period 2 Sleep period 3 start end duration start end duration start end duration Blue N 8 78 78 78 28 28 28 21 21 21 Mean 6.7 21.5 3.1 5.6 12.114.6 2.5 9.2 12.6 3.2 StdDev 0.1 0.7 0.7 0.9 1.1 1.0 1.1 0.5 1.3 1.1 Red N 5 49 49 49 25 25 25 8 8 8 Mean 6.5 0.9 7.2 6.3 14.015.5 1.5 17.4 18.8 1.5 StdDev 0.5 0.5 0.3 0.5 1.2 1.4 0.7 0.3 0.5 0.5 White N 8 79 79 79 72 72 72 Mean 7.9 5.2 10.9 5.7 19.522.8 3.3 StdDev 0.9 0.6 0.9 1.2 1.3 1.3 1.3
A review of supervisor logs for MSE watch-standers revealed that a significant amount of work activities were performed off-watch, ranging from 4.7h/day for the White watch and 7.5h/day for the Blue watch, as shown in Table 25. Among these off-watch work activities, administration was the primarily contributor, with each team recorded 4.6h/day during this exercise.
Table 25: Daily off-watch work assignment for watch standers in the MSE department. (Unit: hour/day). Watch Administration Evolution Maintenance Other Watch Total syndicate Red 4.6 0.2 0.2 0.9 0.7 6.9 White 4.6 0.0 0.0 0.0 0.0 4.7 Blue 4.6 0.7 0.4 1.5 0.0 7.5
3.7 Limitations of this Study
The following three limitations should be noted for this study.
Firstly, the sample sizes for watch-standers or day worker teams were very small. In three cases, the logs from a single participant were available for analysis. Such small sample sizes made cross team statistical comparison impractical. As a result, we did not perform inferential statistical analysis and generally do not recommend comparing results (e.g., sleep times, activity times) between groups. However, it is useful to note that this limitation does not prevent us from obtaining useful insights from the dataset by mapping out sailors’ work and rest patterns, which was the main objective of this exploratory study.
Secondly, sleep patterns presented in this report were analyzed based on data obtained from two different recording methods, i.e., daily logs versus actigraph watch. Past research has revealed
DRDC-RDDC-2017-R048 37
discrepancies between these two methods, with most indicating that a longer sleep duration was reported by logs than actigraph [14, 15]. A common explanation is that actigraph measures actual time-in-sleep whereas the log tracks time-in-bed. Such discrepancies could create mis-leading conclusions if sleep patterns obtained from different measures were compared. To help readers better appreciate the magnitude of differences between two methods in this study, we have constructed Table 26 which contrasts sleep parameters of 1-in-2 watch standers obtained from two data sources. For all six watch teams where comparison could be made, five of them (i.e., except the port watch of the Deck department) generally showed a consistent pattern that logged sleep duration was longer than actigraphically tracked sleep duration, with an earlier on-set time and a later wake-up time obtained for each sleep episode by the log data. To confirm this finding more conclusively, further investigation is recommended that involves a larger sample size and comparison of sleep data (i.e., logged versus actigraphically-measured) collected from the same participants.
Table 26: Comparison of logged sleep (L) and actigraphically-measured sleep (A) for 1-in-2 watch standers. Sleep 1 (Major sleep) Sleep 2 (Nap) Department Watch On-set Wake-up Duration On-set Wake-up Duration A L A L A L A L A L A L CBT Port 4.3 4.4 10.911.3 6.7 6.9 17.417.0 19.2 19.8 1.9 2.8 CSE Port 4.5 4.3 11.010.9 6.5 6.6 17.016.9 19.5 19.9 2.5 3.0 Deck Port 4.3 4.4 10.39.9 6.0 5.5 17.017.2 18.9 19.6 2.0 2.4 CBT Stbd 21.2 21.13.4 3.3 6.1 6.2 12.812.4 15.2 15.4 2.4 3.0 CSE Stbd 21.8 21.23.3 3.6 5.6 6.3 13.113.3 15.3 15.5 2.1 2.2 Deck Stbd 21.4 20.93.4 4.8 6.0 8.0 13.312.1 15.1 15.7 1.9 3.6
Thirdly, the activity codings used in the daily logs did not appear to be interpreted consistently by all participants. For example, some non-watch standers recorded a portion of their daily work as watch-standing; there were questions about the specific definition of the messing activity. Although such codings have been repeatedly used in the past, primarily for the United States Navy studies (e.g., [8]), further clarification is needed for their future application in the RCN research.
Lastly, for participants of the watch evaluation study, their work schedules were collected by using a work assignment log, completed by their supervisors. Each supervisor was responsible for multiple participants and the data reflects the assignment of daily work activities to each participant. The quality of this data, particularly the timing information for each activity, was expected to be less precise than self-reported logs. This limitation reflects a constraint faced in this trial and will be addressed in future studies.
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4 Conclusions
The current DFM takes sailors’ work assignment schedules as input and generate predictions about their sleep patterns, and subsequently cognitive performance. To successfully integrate DFM into the naval crewing analysis tool SCORE, it is critical to compare DFM predictions against RCN sailors’ work and rest schedules obtained in operational settings, particularly to examine how well the predicted sleep patterns match those of empirical data. Such sleep patterns should consider the number of daily sleep episodes, the duration of each episode, as well as the on-set and wake-up times for each episode. While the general objective for a model like DFM is to produce a forecast for an average sailor, it is also important to consider the variability that exists in the target dataset. To support DFM validation, the analysis presented in this report is focused on four research objectives described previously. In this section, we will first summarise key findings from this study and then provide a list of recommendations for future DFM validation and SCORE development.
4.1 Summary of Findings
Key observations regarding sailors’ work and rest schedules during Ex Trident Fury 2015 are summarised in this subsection. Figure 18 illustrates sleep patterns of watch standers and non-watch standers for all five departments; it was created to facilitate discussion.
1. Based on all 50 participants that were sampled from five ship departments, on average, a sailor worked 11.3h/day during this exercise and the majority of which was accountable by administration and watch-standing activities. Together they represented 86% of work time or 9.7h/day. The rest of the on-duty activities, including evolution and maintenance, were accountable for the remaining 14% of daily work time.
2. On the flip side, the average daily off-duty time was 12.7h which was distributed between 8.3h for sleep, 3.3h for personal activities, and 1.2h for messing.
3. Large variances existed in the data, likely contributed by both individual differences and a change of operational intensity throughout the at-sea trial. Using the daily on-duty time as an example, its standard deviation was 2.6h/day and the largest recorded value was 18.5h/day. Similarly for the duration of daily sleep, the standard deviation was 1.8h/day and the shortest logged time was 1.3h/day.
4. Across all departments, average fatigue ratings resided in a reasonably acceptable range and remained at the same level (i.e., between 2 and 3) throughout the exercise, indicating on average participants had sufficient rest and were able to sustain the intensity of this exercise. This conclusion however should be taken with a grain of salt, as 62% of self-report participants were non-watch standers. As the log results revealed, 1-in-2 watch-standers did report a higher level of fatigue than non-watch standers. Therefore it is recommended that readers refer to the watch evaluation study for a focused analysis on watch-standers, including 1-in-3 watch standers from the Engineering department that were not sampled in this study [5].
DRDC-RDDC-2017-R048 39
Figure 18: Summary of major sleep episodes for watch-standers and non-watch standers in five ship departments.
(Note, actigraphcially-measured sleeps are indicated by dotted lines and logged sleep by solid lines; the two numbers underneath each line indicate average start and end times for the sleep episode.)
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5. Watch standers’ daily work and rest routine was primarily determined by their watch schedules. In this exercise, the 1-in-2 and 1-in-3 watch schedules adopted on the HMCS Calgary reflect a proposed improvement. Specifically, for the 1-in-2 watch, an 8-hour off-watch window was created to accommodate a longer major sleep period and the nocturnal watch time was equitably shared by both watch teams. For the 1-in-3 watch, the straight 4 watch schedules allowed operators to work for the same two 4-hour watch periods everyday which in principle enabled operators to better adapt to such fixed daily work hours [16]. The moderate level of fatigue as reported by 1-in-2 watch standers in this study could be an indication of the effectiveness of the improved watch schedule. For a complete treatment on the topic, readers are referred to [8].
6. For 1-in-2 watch standers, their daily schedule was more strictly shaped by their 12h watch hours than 1-in-3 watch standers. Many reported to work before the start of watch and stayed later after its end, to accommodate a brief turnover period. They typically slept twice a day, with all reported a longer sleep that covered a portion of the night time, and most also had a shorter nap during the afternoon. After the 8h watch-keeping period was completed, participants typically started to sleep in about 30min. In contrast, after the 4h watch-keeping period, participants commonly did not start the follow-up sleep until 60min later. Most other activities, including meals and personal time, were squeezed between watch and sleep schedules.
7. For 1-in-3 watch standers, the straight 4 schedule created 2 periods of 8h off-watch window for sleep or other work activities. Most watch standers slept twice a day. Unsurprisingly, the longer sleep took place during the 8h window that overlapped with night time. However, the timing of the daytime nap was not well synchronized for members of the same watch team. Subteam patterns were identified, but the data for further analyzing the cause of such subteam grouping was not collected in this study.
8. For non-watch standers, most participants were day workers, except a small team of cooks and stewards from the LOG department who worked the night shift. On average, the day workers’ rest patterns were similar across departments, but the daily total sleep durations varied. Due to the small sample sizes, a conclusive judgment on statistical differences could not be reliably made. The night workers in the LOG department recorded a longer daily sleep than their peers who worked during the day. One observation from the logs revealed that the night workers’ sleep (during day time) was more often disrupted to accommodate a brief meal or personal activities, which could be an indicator of a reduced sleep quality. Lastly, one day worker in the LOG department recorded a more fragmented rest schedule, implying a larger variability in work/rest patterns may exist in this department.
4.2 Future Work
Results from this analysis will be used for the validation of the sleep prediction algorithm in DFM which will be published in a separate report, as well as future SCORE modeling effort. The identified sleep patterns provide useful benchmarks for assessing the quality of the sleep prediction model. Generally, an acceptable model should be judged based on the accuracy of their prediction of sleep patterns, including the number of daily sleep episode, the sleep on-set and wake-up time (thus, duration) of each episode. Such a judgment however is not straightforward
DRDC-RDDC-2017-R048 41
due the variabilities that exist in the benchmark data. A criterion needs to be established based on a consideration of the underlying distribution of the benchmark data and a statistical significance threshold that is meaningful to RCN operations.
The fatigue ratings obtained in this study will be useful for calibrating the DFM’s sleep prediction algorithms. It should be noted that extreme levels of fatigue were not recorded in this exercise, therefore, the dataset may not be sufficient for identify the bounding conditions in the fatigue models. Psychomotor performance data will be collected in another at-sea trial to validate the DFM’s performance prediction algorithm.
Significant individual differences in daily sleep duration were observed in this analysis, however, such a factor is not currently modelled in either DFM or SCORE. For the purpose of crewing analysis, technically it is feasible to introduce a sensitivity analysis in the model, particularly for fine-tuning model parameters to represent individual differences that lead to a negative impact on operational effectiveness. Such a function will produce crewing solutions with enhanced robustness and the current analysis may provide some insights on how such a sensitivity analysis could be configured.
Categorically the sleep prediction algorithm in DFM is based on an underlying physiological model [17]. Thus theoretically, the algorithm is better suited for forecasting an individual’s actual sleep time, rather than time-in-bed as measured by the sleep log. As indicated in the previous subsection, subjectively logged sleep duration should be interpreted as time-in-bed and there exists discrepancy between logged sleep time and actigraphically-measured sleep duration. Such a difference should obviously be considered in DFM validation. For further research, it is recommended that objective sleep measures like actigraph are used for sleep tracking.
The time-in-bed data that were analyzed in this study may assist the development of an alternative, entirely if-then rule-based method, for sleep prediction like the one adopted by FAST AutoSleep [18]. This method is likely acceptable for analyzing naval operations where watch schedule is a key determinant of a sailor’s (e.g., a watch stander’s) overall work and rest patterns, and there are a limited set of common watch systems that the RCN considers for its platforms. The current study shed sufficient light on two watch systems that were tested, conceivably similar analyses could be performed for other common RCN watch schedules. Based on such data, a rule-based sleep prediction solution could be developed.
As a final remark, this study analyzed work, rest patterns and fatigue ratings for sailors’ onboard of the HMCS Calgary during the high op-tempo exercise Trident Fury 2015. The results support the on-going validation effort for DFM and SCORE. Future research will address the limitations identified in this analysis and a follow-up study has been planned for the experimental ship (x-ship) project that will take place in October 2016.
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References
[1] Chow, R., Wang, W., Lamb, M., Coates, C., Perlin, M., and McKay, P. (2013). Simulation for crew optimization and risk evaluation. In TTCP HUM TP-18 Workshop on Crewing Systems for Maritime Warfare: Portsdown West, UK.
[2] Chow, R., Perlin, M., McKay, P., Coates, C., Lamb, M., and Wang, W. (2015). Score 2.0 User's Guide: Crew Generation and Validation. DRDC-RDDC-2015-R052. Defence Research and Development Canada.
[3] Peng, H. and Bouak, F. (2015). Development of bio-mathematical models for human performance under fatigue. DRDC Scientific Report, DRDC-RDDC-2015-R280. Defence Research and Development Canada.
[4] Hursh, S. R., Redmond, D. P., Johnson, M. L., Thorne, D. R., Belenky, G., Balkin, T. J., Storm, W. F., Miller, J. C., and Eddy, D. R. (2004). Fatigue models for applied research in warfighting. Aviation, Space, and Environmental Medicine, 75 (3), A44–A53.
[5] McCauley, P., Kalachev, L., Mollicone, D., Banks, S., Dinges, D., and Van Dongen, H. (2013). Dynamic circadian modulation in a biomathematical model for the effects of sleep and sleep loss on waking neurobehavioral performance. Sleep, 36 (12), 1987–1997.
[6] Doubova, N. (2015). Comparison of sleep models for score-fatigue model integration. DRDC-RDDC-2015-C092. Azur Human Resources Ltd.
[7] Peng, H., Bouak, F., Wang, W., and Chow, R. (2015). Comparison and validation of sleep models to predict cognitive performance. In Military and Veteran Health Research Forum. 2015. Québec, QC, Canada.
[8] Paul, M. A., Love, R. J., Waggoner, L. B., Hursh, S. R., and Miller, J. C. (2016). An assessment of alternative 1-in-2 and 1-in-3 watch schedules on an RCN patrol frigate: Exercise Trident Fury, 2015. DRDC-RDDC-2016-R059. Defence Research and Development Canada.
[9] Haynes, L. E. (2007). A comparison between the navy standard workweek and the actual work and rest patterns of U.S. Navy sailors. Naval Postgraduate School: Monterey, California.
[10] Mason, D. R. (2009). A comparative analysis between the navy standard workweek and the work/rest patterns of sailors aboard U.S. Navy cruisers. Naval Postgraduate School: Monterey, California.
[11] Kerno, K. M. (2014). An analysis of warfighter sleep, fatigue, and performance on the USS Nimitz. Naval Postgraduate School: Monterey, California.
[12] Young, R. L. (2013). A comparison of sleep and performance of sailors on an operationally deployed u.S. Navy warship. Naval Postgraduate School: Monterey, California.
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[13] Hoddes, E., Zarcone, V., Smythe, H., Phillips, R., and Dement, W. C. (1973). Quantification of sleepiness: A new approach. Psychophsiology, 10, 431–6.
[14] Franklin, K. A. and Svanborg, E. (2000). The accuracy of subjective sleep time in sleep apnoea recordings. Respiratory Medicine, 94 (6), 569–73.
[15] Short, M. A., Gradisar, M., Lack, L. C., Wright, H., and Carskadon, M. A. (2012). The discrepancy between actigraphic and sleep diary measures of sleep in adolescents. Sleep Medicine, 13, 378–384.
[16] Paul, M. A., Hursh, S. R., and Miller, J. C. (2010). Alternative submarine watch systems: Recommendation for a new cf submarine watch schedule. DRDC Toronto TR 2010-001. Defence Research and Development Canada.
[17] Achermann, P. and Borbély, A. A. (2003). Mathematical models of sleep regulation. Front. Biosci., 8 (Suppl.), s683–s693.
[18] Federal Railroad Administration. (2011). Measurement and estimation of sleep in railroad worker employees. Report no.: RR11-02 (Online) Washington (DC): Federal Railroad Administration http://www.fra.dot.gov/eLib/details/L01337 Access date: October 2, 2015.
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Annex A Work, Rest and Fatigue Log
Work, Rest and Fatigue Log (Instruction and example) Instructions: Please follow the example below and (1) start from your morning wake-up, fill/update the log once every 4 hours, and complete the last daily entry right before you go to sleep. For example, if you wake up at 6:30, then the log should be filled out at 06:30 (wake-up), 10:30, 14:30, 18:30, 22:30, and 0:30 (last daily entry right before sleep). (2) circle the time slot when the log entry is made; (3) enter an activity code and a fatigue rating for each 15-minute time slot, use a hyphen (-) to simplify the entry when the code/rating remains the same as the preceding time slot.
Activity code Fatigue rating On Duty Off Duty 1 - Feeling active and vital; alert; wide awake Activity Code Activity Code 2 - Functioning at a high level, but not at peak, able to concentrate Watch W Sleeping S 3 - Relaxed; awake; not at full alert ness, responsive Evolution E Messing I 4 - A little foggy; not at peak; let down Maintenance M Personal Time P 5 - Fogginess; beginning to lose interest in remaining awake; slowed down Administration (e.g., meeting, A 6 - Sleepiness; prefer to be lying down; fighting sleep; woozy departmental work, training) 7 - Almost in reverie; sleeep onset soon; loost struggle to remain awake
Other (e.g., Cleaning station) O
Example of a completed log
Time 30 11:30 11:30 11:45 10:15 10:15 10:30 10:45 11:00 11:15 7:45 7:45 8:00 8:15 8:30 9:00 9:15 9:30 9:45 1:15 1:15 1:30 1:45 2:00 2:30 2:45 3:00 3:15 3:30 730 7: 8:45 8:45 10:00 10:00 0:00 0:00 0:15 0:30 0:45 1:00 1:00 2:15 2:15 3:45 4:00 4:15 4:30 4:45 5:00 5:15 5:30 5:45 6:00 6:15 6:30 6:45 7:00 7:15
Activity W W S ------I - P P W ------Fatigue 4 - 2 ------1 - 1 - - - - -
30 Time : 23:30 23:30 23:45 19:45 19:45 20:00 20:15 20:30 21:00 21:15 21:30 21:45 22:15 22:30 22:45 23:00 23:15 13:15 13:15 13:30 13:45 14:00 14:30 14:45 15:00 15:15 15:30 1919 30 20:45 20:45 22:00 22:00 12:00 12:00 12:15 12:30 12:45 13:00 13:00 14:15 14:15 15:45 16:00 16:15 16:30 16:45 17:00 17:15 17:30 17:45 18:00 18:15 18:30 18:45 19:00 19:15
Activity - - I - P - A - M - - E - - A - - - P - E - W ------Fatigue - - - - - 2 - - - - 3 ------2 - - - - - 2 ------3 - - - - 4 - - - - - Fatigue is not rated for sleep hours; the corresponding cells are left blank. DRDC-RDDC-2017-R048 45
Work, Rest and Fatigue Log
Date: ______Participant ID: ______
Department: ______Military Occupation: ______
Age: [ ] 18 to 24 Rank: [ ] Junior NCM (AB to MS) Watch: [ ] Port [ ] Stbd [ ] 25 to 34 [ ] Senior NCM (PO2 to CPO1) [ ] Red [ ] White [ ] Blue [ ] 35 to 44 [ ] Junior Officer (A-SLt to Lt (N)) [ ] 1st of Port [ ] 1st of Stbd [ ] 2nd of Port [ ] 2nd of Stbd [ ] 45 to 54 [ ] Senior Officer (LCdr to Flag) [ ] Not applicable (Day worker or On-Call)
[ ] 55 to 64 [ ] 65 +
Activity code Fatigue rating On Duty Off Duty Activity Code Activity Code 1 - Feeling active and vital; alert; wide awake Watch W Sleeping S 2 - Functioning at a high level, but not at peak, able to concentrate Evolution E Messing I 3 - Relaxed; awake; not at full alert ness, responsive Maintenance M Personal Time P 4 - A little foggy; not at peak; let down Administration (e.g., meeting A 5 - Fogginess; beginning to lose interest in remaining awake; slowed down departmental work, training) 6 - Sleepiness; prefer to be lying down; fighting sleep; woozy Other (e.g., Cleaning station) O 7 - Almost in reverie; sleep onset soon; lost struggle to remain awake
Time 0:00 0:00 0:15 0:30 0:45 1:00 1:15 1:30 1:45 2:00 2:15 2:30 2:45 3:00 3:15 3:30 3:45 4:00 4:15 4:30 4:45 5:00 5:15 5:30 5:45 6:00 6:15 6:30 6:45 7:00 7:15 7:30 7:45 8:00 8:15 8:30 8:45 9:00 9:15 9:30 9:45 10:00 10:15 10:30 10:45 11:00 11:15 11:30 11:45 Activity Fatigue
Time 12:00 12:00 12:15 12:30 12:45 13:00 13:15 13:30 13:45 14:00 14:15 14:30 14:45 15:00 15:15 15:30 15:45 16:00 16:15 16:30 16:45 17:00 17:15 17:30 17:45 18:00 18:15 18:30 18:45 19:00 19:15 19:30 19:45 20:00 20:15 20:30 20:45 21:00 21:15 21:30 21:45 22:00 22:15 22:30 22:45 23:00 23:15 23:30 23:45 Activity Fatigue
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Annex B Work Activity Assignment Log
Work Activity Assignment Log (Supervisor use, for 1‐in‐2 watch system)
Work Activity Code Date: ______Watch W Evolution E Maintenance M Department: ______Administratioon (e.g., meeting, A departmental wwork, training) Supervisor ID: ______Other (e.g., Clleaning station) O
Instructions: This log will be filled out by the supervisor of each team, to track work activities of those team members who are participating in the DRDC’s watch schedule evaluation study. Please enter the appropriate activity code into the log, for the whole team, and /or the Port and Stbd team. Name of 0100 0200 0400 0500 0700 0800 1500 1600 1700 1800 1900 2000 2100 2200 2300 Participant 0000 0000 0300 0300 0600 0600 0900 1000 1100 1200 1300 1400 ALL All Port Watch All Stbd Watch
Please circle each person’s watch. Note any activities that are in addition to or exceptions from what is nnoted above for his/her team. Name (Port / Stbd) Name (Port / Stbd) Etc…
DRDC-RDDC-2017-R048 47
Work Activity Assignment Log (Supervisor use, for 1‐in‐3 watch system)
Work Activity Code Date: ______Watch W Evolution E Maintenance M Department: ______Administration (e.g., meeting, A departmental work, training) Supervisor ID: ______Other (e.g., Cleaning station) O
Instructions: This log will be filled out by the supervisor of each team, to track work activities of those team members who are participating in the DRDC’s watch schedule evaluation study. Please enter the appropriate activity code into the log, for the whole team, and /or the Red, White and Blue team. Name of
Participant 0000 0100 0200 0300 0400 0500 0600 0700 0800 0900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 ALL All Red Watch All Blue Watch All White Watch
Please circle each person’s watch. Note any activities that are in addition to or exceptions from what is noted above for his/her team. Name (Red/Blue/White) Name (Red/Blue/White) Etc…
48 DRDC-RDDC-2017-R048
List of Symbols/Abbreviations/Acronyms/Initialisms
CBT Combat CSE Combat Systems Engineering DFM DRDC Fatigue Model DND Department of National Defence DRDC Defence Research and Development Canada FAST Fatigue Avoidance Scheduling Tool HMCS Her Majesty’s Canadian Ship LOG Logistics MSE Marine Systems Engineering OWL Optimized Work-schedule & Logistics RCN Royal Canadian Navy SCORE Simulation for Crew Optimization and Risk Evaluation STBD Starboard StdDev Standard Deviation X-ship Experimental Ship
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50 DRDC-RDDC-2017-R048
DOCUMENT CONTROL DATA (Security markings for the title, abstract and indexing annotation must be entered when the document is Classified or Designated) 1. ORIGINATOR (The name and address of the organization preparing the document. 2a. SECURITY MARKING Organizations for whom the document was prepared, e.g., Centre sponsoring a (Overall security marking of the document including contractor's report, or tasking agency, are entered in Section 8.) special supplemental markings if applicable.)
DRDC – Toronto Research Centre UNCLASSIFIED Defence Research and Development Canada 1133 Sheppard Avenue West P.O. Box 2000 2b. CONTROLLED GOODS Toronto, Ontario M3M 3B9 (NON-CONTROLLED GOODS) Canada DMC A REVIEW: GCEC DECEMBER 2013
3. TITLE (The complete document title as indicated on the title page. Its classification should be indicated by the appropriate abbreviation (S, C or U) in parentheses after the title.)
Sailors’ Work/Rest Schedule and Fatigue on a Canadian Patrol Frigate During Exercise: Trident Fury 2015
4. AUTHORS (last name, followed by initials – ranks, titles, etc., not to be used)
Wang, W.; Chow, R.; Peng, H.; Bouak, F.; Lamb, M.; Ueno, K.
5. DATE OF PUBLICATION 6a. NO. OF PAGES 6b. NO. OF REFS (Month and year of publication of document.) (Total containing information, (Total cited in document.) including Annexes, Appendices, etc.) June 2017 64 18
7. DESCRIPTIVE NOTES (The category of the document, e.g., technical report, technical note or memorandum. If appropriate, enter the type of report, e.g., interim, progress, summary, annual or final. Give the inclusive dates when a specific reporting period is covered.)
Scientific Report
8. SPONSORING ACTIVITY (The name of the department project office or laboratory sponsoring the research and development – include address.)
DRDC – Toronto Research Centre Defence Research and Development Canada 1133 Sheppard Avenue West P.O. Box 2000 Toronto, Ontario M3M 3B9 Canada
9a. PROJECT OR GRANT NO. (If appropriate, the applicable research 9b. CONTRACT NO. (If appropriate, the applicable number under and development project or grant number under which the document which the document was written.) was written. Please specify whether project or grant.)
10a. ORIGINATOR’S DOCUMENT NUMBER (The official document 10b. OTHER DOCUMENT NO(s). (Any other numbers which may be number by which the document is identified by the originating assigned this document either by the originator or by the sponsor.) activity. This number must be unique to this document.)
DRDC-RDDC-2017-R048
11. DOCUMENT AVAILABILITY (Any limitations on further dissemination of the document, other than those imposed by security classification.)
Unlimited
12. DOCUMENT ANNOUNCEMENT (Any limitation to the bibliographic announcement of this document. This will normally correspond to the Document Availability (11). However, where further distribution (beyond the audience specified in (11) is possible, a wider announcement audience may be selected.))
Unlimited
13. ABSTRACT (A brief and factual summary of the document. It may also appear elsewhere in the body of the document itself. It is highly desirable that the abstract of classified documents be unclassified. Each paragraph of the abstract shall begin with an indication of the security classification of the information in the paragraph (unless the document itself is unclassified) represented as (S), (C), (R), or (U). It is not necessary to include here abstracts in both official languages unless the text is bilingual.)
Sailors’ work, rest schedules and fatigue were collected onboard of the Her Majesty’s Canadian Ship (HMCS) Calgary during the 10-day Exercise Trident Fury 2015 for supporting the validation of sleep and fatigue prediction algorithms to be implemented in naval crewing analysis software, the Simulation for Crew Optimization and Risk Evaluation (SCORE). This report summarises the data analysis that was focused on the distribution of sailors’ daily times on various on-duty and off-duty activities, as well as the fluctuation of their fatigue throughout the exercise. The results identified distinctively different patterns of sleep for 1-in-2, 1-in-3 watch-standers and non-watch standers. Averaged across participants from all five ship departments, a moderate level of fatigue was observed during the exercise. Results from this analysis provide a benchmark for validating the sleep and fatigue prediction algorithms. ------
On a recueilli des données sur les horaires de travail et les périodes de repos, ainsi que sur l’état de fatigue des marins à bord du Navire canadien de Sa Majesté (NCSM) Calgary au cours de l’exercice de 10 jours Trident Fury 2015. Cet exercice venait appuyer la validation des algorithmes de prédiction du sommeil et de la fatigue à intégrer au logiciel d’analyse de l’armement en équipage des navires, l’outil de simulation pour l’optimisation de l’équipage et l’évaluation des risques (SCORE). Le présent rapport résume l’analyse des données qui était axée sur la répartition du temps consacré chaque jour par les marins à diverses activités en service et hors-service, ainsi que sur les variations de leur état de fatigue pendant l’exercice. Selon les résultats obtenus, les habitudes de sommeil des marins de quart par bordée ou par tiers et de ceux qui ne suivent pas un régime de quart sont nettement différentes. On a observé un niveau de fatigue modéré durant l’exercice parmi les participants des cinq services du navire. Les résultats de l’analyse fournissent un point de référence pour la validation des algorithmes de prédiction du sommeil et de la fatigue.
14. KEYWORDS, DESCRIPTORS or IDENTIFIERS (Technically meaningful terms or short phrases that characterize a document and could be helpful in cataloguing the document. They should be selected so that no security classification is required. Identifiers, such as equipment model designation, trade name, military project code name, geographic location may also be included. If possible keywords should be selected from a published thesaurus, e.g., Thesaurus of Engineering and Scientific Terms (TEST) and that thesaurus identified. If it is not possible to select indexing terms which are Unclassified, the classification of each should be indicated as with the title.)
Work and rest schedule; fatigue; Ex Trident Fury