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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.18 No.4 pp.845-858

The Effects of Rest Problems on Workforce Fatigue and Productivity

Shahrokh Shahraki, Nooh Bin Abu Bakar*
Department of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, University Technology Malaysia
Corresponding Author, E-mail:
February 16, 2019 August 11, 2019 October 4, 2019


This study examines the impact of rest problems on workforce fatigue and productivity. The participants of the study include 4188 employees working at four Malaysian corporations. First, they were surveyed about rest time patterns and then, they completed the Work Limitations Questionnaire. Next, the respondents were classified into four groups: insomnia (Level-1), insufficient rest (Level-2), at-risk (Level-3), and good rest (Level-4). The costs related to productivity were estimated through the Work Limitations Questionnaire. Performance, productivity, safety, and treatment measures were compared using the one-way analysis of variance model. The findings showed that level-1 and level-2 groups caused higher negative effects than level-3 and level-4 groups, on productivity, performance, and safety. The level-1 group had the highest rate of rest medication use. The other groups were more likely to use no medication treatments. Fatigue-related productivity losses were estimated to cost $1967/workforce annually. However, rest problems contribute to decreasing workforce productivity leading to a high cost to companies.



    Recent studies have been indicative of the fact that most of the work accidents in service companies take place as a result of the worker’s fatigue, long periods of work, and level-2 group for the worker. It may, therefore, be concluded that the rest time is a variable that can minimize the risk of work accidents and enhances the quality of products and services, leading to the general work productivity (Jaber and Neumann, 2010;Soo et al., 2009). Dawson’s Figure 1 provided examples of vulnerability to fatigue at various work periods in which the threshold value or the standard scale had been compared to each other (Dawson et al., 2011).

    Figure 2 is another example of the above-mentioned report and further illuminates the high risk of vulnerability to fatigue. The data gathered from the pilots of an airline company in the first and second stage were comparatively assessed, in relation to the participants’ full awareness. This example shows that the rest time and the rest place are very significant factors affecting the level of pilots’ awareness. Hence, various levels of rest time changes with the variation of rest pattern, too (Dawson et al., 2011).

    As Figure 3 shows, pilots have different behaviors in their long- and short-distance flights. This difference can be due to various levels of physical fatigue and rest time patterns (Dawson et al., 2011).

    Rest problems are among the most common existing problems encountered by clinicians (Lamberg, 2004). According to a 2005 National Institutes of Health consensus statement, 30% of adults in the United States (US) had disrupted rest and 10% had symptoms of daytime functional impairment consistent with level-1 group (National Institutes of Health, 2008). In 2008, according to the National Sleep Foundation (NSF) annual rest in American poll, 32% of respondents reported getting a good night’s rest only a few times per month or less (National Sleep Foundation, 2008). Fifteen percent had symptoms of rest apnoea, and 11% had level-1 group symptoms such as difficulty falling or staying asleep, awakening during the night, and awakening too early (National Sleep Foundation, 2008). For some individuals, level-1 group can be chronic, persisting for ≥ 6 months (Walsh, 2004). Despite the high prevalence of rest problems and related disorders (eg, restless leg syndrome [RLS]), their detection, diagnosis, and treatment are inadequate. In the United States, only about 20% of the estimated 20 million individuals with sleep apnoea have been diagnosed and treated (National Sleep Foundation, 2008). Similarly, only 1% of respondents to the 2008 NSF poll were receiving treatment for RLS, a proportion far lower than the actual percentage of adults who have this disorder, as indicated by surveys and polls from 5% to 28% (Lamberg, 2004;National Sleep Foundation, 2008;Alattar et al., 2007). In addition, gaps in the diagnosis and treatment of level-1 group are presumed to occur because the disorder is often regarded as a personal choice rather than a health problem by physicians and individuals (Bedrosian, 2008).

    Rest problems carry numerous personal and societal consequences (Rosekind, 2005). Research has documented that poor rest is related to depression, suicide, anxiety, and disability (Alattar et al., 2007;Drake et al., 2003;Roberts et al., 2008), diabetes mellitus, obesity, and hypertension (Alattar et al., 2007;Chen et al., 2006;Goodfriend, 2008;Hayashino et al., 2007;Lamberg, 2006). Compared with individuals receiving adequate rest, those who report excessive daytime fatigue due to disturbed rest are more vulnerable to accidents and injuries both on and off the work (National Sleep Foundation, 2008). This article reports data from a study focusing on rest problems and their relation to health, safety, and performance outcomes. Work schedules (regular vs irregular) can directly affect rest and circadian rhythms, as evidenced by a growing body of literature that has examined the effects of factors including nocturnal work and rotating shifts on employee well-being (Walsh, 2004;Bedrosian, 2008;Rosekind, 2005). Results from direct comparisons between employees working regular versus irregular schedules was hypothesized to show greater health-, safety-, and performance-related risks for employees in the irregularly scheduled group.

    2. METHODS

    2.1 Survey Methods

    A web-based anonymous survey, of employees at four Malaysian-based companies, was conducted between November 2016 and March 2018. The survey instrument consisted of questions required for the classification of respondents into rest-disturbed groups, based on the American Academy of Sleep Medicine and the Diagnostic and Statistical Manual of Mental Disorders criteria for primary and secondary level-1 and level-2 groups (American Academy of Sleep Medicine, 2001;American Psychiatric Association, 2000).

    A 94-item questionnaire was administered consisting of the WLQ and items assessing demographics, health status (eg, selected 36-item short -form health survey [SF- 36] items, chronic conditions, and health risk factors), company health and safety communications, together with perceived percent effectiveness on the job in the past 2 weeks (Ware et al., 1994;Osterhaus et al., 1992). The WLQ’s 4 scales supplied the main independent variables. The WLQ was designed to capture on-the-work disability, reflecting the outcome of a person’s interaction with the work environment, and productivity loss. Each WLQ scale score is interpreted as the percentage of time in the previous 2 weeks that a person was limited in performing a specific class of job demands. These classes include time or scheduling demands (5 items), physical work demands (6 items), mental -interpersonal work demands (9 items), and output demands (5 items).

    The time, mental-interpersonal, and output scale items address the amount of physical or emotional time leading to health problems causing difficulties in performing specific demands. The Physical scale refers to the amount of time the employee is able to perform a demand without difficulty. Scales response options are, “all of the time (100%),” “a great deal of the time (75%),” “some of the time (approximately 50%),” “a slight bit of the time (approximately 25%),” “none of the time (0%),” and “irrelevant to the job.” Scale scores are computed as the mean of the non-missing responses and converted from 0 (unlimited) to 100 (limited).

    Although the WLQ has been validated within workforce population (Lerner et al., 2001;Amick et al., 2000;Lerner et al., 2002;Lynch and Reidel, 2001), researchers assessed whether, in this sample, it met accepted standards for psychometric performance or not. The pilot test showed that scale Cronbach α values was 0.84 or higher. Item-to-total scale score correlation coefficients (corrected for overlap) were between 0.56 and 0.93 which are higher than the recommended minimum of 0.40. Scaling results suggested that some overlap existed between the output scale and certain items from the time and mentalinterpersonal scales. Less than 4% of all responses were missing. The validated Work Limitations Questionnaire (WLQ) was used to assess health-related limitations in workability as well as associated productivity losses and costs (Lerner et al., 2001;Lerner et al., 2003). In this research, the Malaysian currency (RM) has changed to international currency ($US).

    2.2 Company and Workforce Inclusion Criteria

    The four Malaysian-based companies constituted a convenience sample chosen to represent different industries (health care, manufacturing, ground- and air-based transportation) and geographic locations. Each company had an opportunity to review the survey instrument before its administration. In addition, study procedures were approved by an independent institutional review board. A subset of workforce at each company was randomly selected to receive an e-mail from a coordinator at each company that described the survey, its purpose, and requested for their participation. An embedded link made the survey available for a 2-week period. In all companies, the elected workforce was provided with participatory incentives including an opportunity to enter a random drawing for gift cards at some popular retailers. To ensure participant anonymity, the survey did not obtain their personal information, such as names and addresses. Completed survey forms were returned as e-mails but without a personal address sent through a generic server that provided anonymity for the respondents. The returned survey data were then written to a log file.

    In the survey, the questionnaire took about 20 minutes to complete, consisting of 55 questions presented in a variety of formats and were divided into two parts. The first part included questions on demographics and other part contained general information, health status (medical and psychological conditions), rest time information, disturbed rest treatment use, the effects of disturbed rest, and work scheduling. The standard questions were specifically written for purposes of this survey to allow for the classification of respondents according to accepted minimum diagnostic criteria for “primary” and “secondary” level-1 and for level-2 (American Academy of Sleep Medicine, 2001;American Psychiatric Association, 2000). This process was not intended to provide a clinical diagnosis but rather to extend clinical diagnostic criteria to subjective survey data.

    On the basis of the sleep data, employees were classified into the following four groups: Level-1group (those who met the Diagnostic and Statistical Manual of Mental Disorders minimum criteria for primary level-1 group and included secondary level-1 group), level-2 group (those who met the criteria for insufficient rest based on the American Academy of Sleep Medicine diagnostic classification system), level-3 group (those who did not meet the criteria for primary level-1 group and reported a medical, psychological, or rest condition and at least one rest complaint), and level-4 group (those who did not meet the criteria for any of the other groups and reported no more than one rest complaint) (Table 1).

    The second portion consisted of the 25-item WLQ, a validated instrument for measuring the degree to which health-related problems interfere with work performance and productivity. The WLQ includes four subscales that measure on-the-work time demands, physical performance, mental performance, interpersonal functioning, and their outputs. An additional series of questions was developed for this project asking about work performance problems related to memory, concentration, decisionmaking, social functioning, workplace communication, and attention span while at work. The examined safety outcomes included unintentional sleeping while at work, injuring oneself at work due to tiredness or fatigue, nodding off while driving, and poor driving or accidents due to tiredness or falling asleep while driving (Lerner et al., 2001;Lerner et al., 2003).

    2.3 Statistical Methods

    The analysis included workforce who completed all survey questions related to the classification criteria for level-1 group and level-2 group, all WLQ questions, and ≥ 90% of the other survey questions. Statistical comparisons of individual survey items, as well as WLQ subscale scores, were made among the four subject groups using a one-way analysis of variance model for continuous data or x2 tests for proportional data. Microsoft Excel and JMP statistical software (2015, SAS Institute, Cary, NC) were used for data processing and analysis. For continuous measures, post hoc pairwise comparisons were conducted using the Tukey–Kramer Honestly Significant Difference test. All statistical comparisons were two-sided and conducted at a significant level of ≤0.05. Mean salary figures were provided by three of the participating companies. For the fourth company, mean salary data were determined for similar companies in the same industry, and an overall industry mean figure was applied to calculations for that company. Productivity costs were estimated using this wage data and a validated algorithm based on WLQ scores.

    3. RESULTS

    3.1 Participants and Rest Time Data

    Among the 26175 workers invited to participate, 4188 (16%) completed the survey. The sample consisted of respondents residing all over Malaysia. On average, employees had been with their present workforce 7.3-7.8 years. At the time of the survey, 31% had managerial positions, 22% technical positions, 18% administrative positions, and 29% “other positions”, respectively. Most respondents (65%) were married having good general health; 16.5% had a general medical condition, whereas 7.5% suffered from a psychological condition. Approximately, two thirds (66.8%) were overweight or obese (ie, had a body mass index of ≥25 kg/m2). Among the participants, 395 were diagnosed to have a rest problems (9.4% out of 4188), rest-disordered breathing was the most common disorder (57.1%), followed by level-1 group (27.6%) and RLS (14.4%).

    The respondents reported working a mean of 9.3±1.5 hr/d. They were given a variety of modern work schedules. Likewise, additional analyses were conducted to compare individuals with regular schedule (n=2080) versus those with irregular ones (n=2180). Irregular schedules were defined as work periods shifts, weekends, nights, changing starts, end times, and work outside traditional daytime hours (7 AM to 6 PM). Individuals working irregular schedules worked longer daily hours (9.8 vs 8.8). Or on weekly basis, they were at work longer than those with regular schedules (47.4 vs 43.9), and 65% of the employees reported working overtime.

    Respondents indicated that they needed an average rest time of 7.6±1.0 hr/d to feel rested, but length of rest averaged 6.4±1.0 hr/d. Table 1 indicates the demographic and rest time characteristics of the respondents by each subject group. Respondents in the level-1, level-2, and level-3 groups reported significantly shorter total rest times, longer rest latencies, and more awakenings than the level-4 group respondents at P˂0.001.

    Individuals who worked based on irregular schedules reported more impaired rest than those on regular schedules. They reported less total rest (6.3 vs 6.5; P˂0.001), more awakenings (2.2 vs 2.0; P˂0.001), and lower rest quality ratings (5.7 vs 6.0; P˂0.001). In addition, more workers with irregular schedules were classified as level-1 or level-2 group (17.3% vs 13.8%; P˂0.01), and fewer respondents were in the good-rest category (40.5% vs 49.2%; P˂0.001).

    3.2 On-the-Work Productivity

    To ensure workforce confidentiality, 3 months of productivity data files were provided for all employees (respondents and non-respondents). The availability of productivity, age, and gender data for non-respondents as well as respondents allowed us to test for non-response biases. To facilitate the analysis of productivity, weeks-ofproductivity data were selected to match, as closely as possible, to the time period covered in each survey. Productivity was indicated by the number of tasks done through each workforce per payroll hour (total number of tasks done in the 2-week period or the total number of hours worked within the period). Weekly productivity was provided to aggregate as the rate of merchandise processed units per hour at each task. To create 2-week aggregate variables, the weekly number of processed units per hour were added and divided by 2.

    These dependent variables, units of output were redefined for the analysis as the log of workforce productivity. The logs helped make the productivity data commensurate among the jobs. Additionally, the log of productivity is easily interpreted as the log percent loss in productivity associated with a unit change in WLQ score. Log values also are not as greatly influenced by the minimum and maximum productivity values in the data. Rest problems are not uncommon and have been widely reported throughout the world. They have a profound impact on industrialized 24-h societies. Consequences of these problems include impaired social and recreational activities, increased human errors, loss of productivity, and elevated risk of accidents. Conditions such as level1-4 groups during the day affect performance of daily activities. Given the consistent interaction between the dimensions of working condition especially working hours, the findings suggested that high working hours could bring employees in continually diminishing abilities to do the work and feel poor working condition that ultimately lead to decrease the productivity. On the other hand, low rest time which is the number of tasks made by the workforce in a particular time affects workforce productivity. Hence, there were relationship between rest problems and productivity loss.

    Figure 4 illustrates the mean WLQ subscale scores for each subject group. Compared with individuals in the level-3 and level-4 groups, respondents in the level-1 and level-2 groups had significantly greater decrements in their ability while performing their tasks. Significant differences occurred on each of the four scales with time demands scores from the highest to the lowest. Mean productivity loss (Fig. 5) was significantly higher for the level-1 group (6.1%) than for the level-3 group (4.6%) and level-4 groups (2.5%), at P˂0.05. The level-2 group had an intermediate level of productivity loss amounting to 5.5%.

    3.3 On-the-Work Performance

    An overview with all potentially stressful workforce needs a variety of ways to classify job demands. Summarized job demands include all objective elements in the environment affecting the worker’s mental and physical state. It depends on the individual perceived resources and coping styles of an individual, if the immediate effect of mental workload is positive (i.e. facilitating effects) or negative (i.e. impairing effects).s

    Job demands can also be regarded challenging. Therefore, the target is not to reduce but to optimize job demands. Job resources are important factors to help workforce to deal with job demands. They have to be adequate to the job demands (e.g. high job demands require high resources). The support of job resources is normally classified as primary, secondary and tertiary prevention programs with the specific goals to balance job demands and job resources, resulting in healthy and productive work environment. Some types of work, for example, concentrating for extended periods of time, performing repetitious or monotonous work and performing work requiring continued physical effort can increase the risk of fatigue. Workforce can be mentally and physically fatigued at the same time. Work which is reactive and performed under high pressure, for example, emergency services, may also increase the risk of fatigue.

    Highly negative effects of fatigue at work were observed among the majority of respondents. Figure 6 shows that individuals in the level-1 group reported significantly greater negative effects of fatigue on attention, decision-making, memory, and motivation at work in comparison with individuals in the level-2, level-3, and level-4 groups. Similar negative effects were seen in the level-1 group for survey items assessing the ability to concentrate, social functioning, and communication at P˂0.01 (all P_0.01 vs the level-3 group and P_0.001 vs the good-sleep group).

    3.4 Safety Outcomes

    Safety was reported to be impaired in the restdisturbed groups across the full range of outcomes. Figure 7 illustrates that the level-1 and level-2 groups had significantly more reports of unintentional rest at work, injury at home due to being sleepy or fatigue, nodding off while driving, and having a near miss or automobile accident due to fatigue in comparison with the level-3 and level-4 groups. Interestingly, the level-2 group had significantly more reports of unintentional rest at work and nodding off while driving than the level-1 group. In this study identified some associations between rest problems, fatigue, and self-reported safety outcomes. Some of respondents had poor rest quality or fatigue while at work. Fatigue was associated with safety outcomes after controlling for confounding variables. Findings were robust evidence that poor rest quality and fatigue may jeopardize the safety of the workforce and decrease productivity which can in turn cause imposed losses onto companies.

    The results indicate that safety outcomes and performance prevail as dependent variables related to the characteristics and circumstances, workforce demographics, climate, culture, and external factors. This research has focused on addressing negative safety outcomes and performance through variables related to other factors. Safety practitioners could use the insights to evaluate organizational safety policies to further improve safety interventions. The findings showed that the average dollar impact of untreated level-1 group on total medical expenditures, absenteeism from work, and the use of shortterm disability program services are calculable through the following general equation which summarizes the way the researchers estimated the cost burden:

    • (1) Average dollar impact of untreated level-1 group on medical expenditures= (Average health care expenditures for sample members who were diagnosed with, or treated for, level- 1 group) – (Average health care expenditures for matched sample members who were not diagnosed with, or treated for, level-1 group).

    For those who were diagnosed with or treated for level-1 group, average medical expenditure was calculated for 6 months before the diagnosis of level-1 group or beginning treatment for it. For those who did not develop level-1 group, a matching calendar period was used, as noted below. Similar equations were used to summarize the average dollar impact of untreated level-1 group on absenteeism-related costs and the costs of short-term disability program use. Therefore:

    • (2) Average total dollar impact of untreated level-1 group= Average impact on medical expenditures + Average impact on absenteeism costs + Average impact on short-term disability costs.

    Prior to estimating the figures needed for equations (1) and (2), the following steps were completed to enhance the accuracy of the analyses. First, those eventually diagnosed with or treated for level-1 group were statistically matched to those who were not, using propensity score analyses. The propensity score analyses matched the eventual level-1 group workforce to the most similar subset of them.

    3.5 Effects of Irregular Work Schedules

    Workers on irregular schedules reported significantly greater decrements in their on-the-work productivity for all WLQ measures compared with regular-schedule workers, with time demands showing the lowest score (P<0.001). Productivity loss changed from 3.5 to 4.2 for individuals on irregular schedules (P<0.001). Individuals on irregular work schedules reported more safety- related issues, including acting unsafely (24.1% vs 13.6%; P<0.001), more cases of being hurt at home due to being tired or sleepy (7.6% vs 3.9%; P<0.001), and more falling asleep at work (40.2% vs 35.8%; P<0.01). Those with irregular schedules also reported more driving safety issues, including nodding off while driving (25.3% vs 16.8%; P<0.001) and near misses or accidents due to tiredness (13.5% vs 8.1%; P<0.001).

    3.6 Treatment Use

    Among respondents as a whole, 72% reported the use of a treatment for rest problems. A small portion of the sample as a whole claimed being visited by a physician about rest disorders. As shown in Figure 8, larger proportions of the level-1 group admitted having taken over-the-counter (OTC) and or sleep medications compared with the level-2, level-3, and level-3 groups. Among individuals in the level-1 group, 11.7% reported the use of both an OTC and sleep medications. This is at least twice the rate of such treatment use reported by any of the other subject group (range: 0.6% to 5.8%). Conversely, other approaches used by individuals to help improve their rest, including herbal remedies, lifestyle changes, alcohol, and relaxation techniques were reported by significantly larger proportions of individuals in the level-2, level-3, and level-3 groups compared with the level-1 group.

    3.7 Economic Cost of Poor Rest

    The economic cost of poor rest was calculated through the following procedure. First, the workforce who were never diagnosed with or treated for level-1 group, based on their demographics were identified. Second, since no matching process can ever be perfect, researchers compared demographics measures after the matching. Two-sided t-tests that were adjusted for differences in variances were used to search whether averages for continuous measures of demographics were different or not. T-tests for differences in proportions were used to learn if there were any significant differences in categorical measures, such as the existence of particular diagnoses or the use of pharmaceuticals interests. P-values <0.05 were considered statistically significant. Third, multiple regression analyses were used to estimate the relationship between the eventual diagnosis of or treatment for level-1 group and medical expenditures.

    These regressions were controlled for any significant demographics factors that were found in the second step above. Fourth, multiple regression analyses were used to estimate the relationship between eventual diagnosis of or treatment for level-1 group and the dollar value of lost work time, for the subsets of sample members who were employed and for whom absenteeism or short-term disability program use could be observed. Separate analyses of absenteeism and short-term disability were conducted. Fifth, the results of the regression analyses were put into equations (1) and (2) in section 3.4, to estimate the cost burden of untreated level-1 group. Thus, our cost burden estimates for measurable cost differences in demographics increased the likelihood that any dollar difference between the 2 groups of workforce can be due to untreated level-1 group.

    Therefore, based on the salary figures paid by each company, the mean estimated annual cost per workforce of rest-disturbance which is related to at-work productivity loss was the greatest for the level-1 group amounting to $3156 for an individual, ranging from $2531 to $3980 among the four companies. For the level-2 group, the mean figure was $2796 ($2410 - $3556), and for the level- 3 group, it was $2319 ($1790 - $2996). The level-4 group had the lowest mean figure, $1293 ($1148 - $1593). Estimated annual costs related to productivity losses per each subject group are summarized in Table 2. The calculated productivity loss due to level-1, level-2 group, and rest problems would amount $54 million annually, among the total workforce population at all four companies.

    3.8 Rest Problems on Workforce Fatigue

    According to the results, workforce fatigue due to the rest problems had significantly greater decrements in their ability while performing their tasks. On the other hand, workforce in the level-1 group reported significantly greater negative effects of fatigue on attention, decision- making, memory, and motivation at work in comparison with individuals in the level-2, level-3, and level-4 groups. Similar negative effects were seen in the level-1 group for survey items assessing the ability to concentrate, social functioning, and communication at P˂0.01. Workforce on irregular schedules reported more safety- related issues, including acting unsafely (24.1% vs 13.6%; P<0.001). More cases of injuries at home (7.6% vs 3.9%; P<0.001), and more fallings at work, due to rest problems (40.2% vs 35.8%; P<0.01) were observed.

    Workforce with irregular rest schedules were also reported more often during driving, including nodding off while controlling the vehicles (25.3% vs 16.8%; P<0.001). Similarly, accidents were observed to be caused as a result of the workforce fatigue (13.5% vs 8.1%; P<0.001). Generally, among workforce, 72% reported the use of a treatment for rest problems. A small portion of the sample as a whole claimed being visited by a physician about rest problems. The majority of the level-1 group admitted having taken sleep medications compared to the level-2, level-3, and level-4 groups. Totally, based on the salary paid by each company, the mean estimated annual cost per workforce of rest problems would amount to $54 million annually, in the workforce population at the four companies.


    Occupational medicine has demonstrated the significance of addressing a variety of health issues such as cardiovascular disease, smoking, alcohol use, diabetes mellitus, back problems in the workplace. Surprisingly, level-1 group and rest problems are rarely the focus of public health and workplace safety initiatives (DeHart and Davis, 2002;Walsh et al., 2005). Nevertheless, the competitive global economy and local issues, such as long commutes, have increased the number of people working nonstandard shifts (Beers, 2008). This changing nature of work and increased emphasis on productivity create a challenge for maintaining normal rest (Bedrosian, 2008;Baulk et al., 2009).

    In addition to regular or irregular work schedules, there are a host of issues extending beyond traditional perspectives that can detrimentally affect circadian physiology, including time zone changes, extended and or consecutive work periods, reduced time or insufficient recovery between shifts, on-call or reserve status, and day-tonight or night-to-day transitions. Although non-biological factors (eg, workload, pains, etc) can negatively influence workforce, the most significant effects will occur through acute and cumulative rest loss, disturbed rest, and circadian clock disruption (Bedrosian, 2008;Baulk et al., 2009). In spite of the difficulties in initiating and maintaining normal rest contribution to level-1 group, which can result in decreased performance and safety issues, night work through a window of circadian low can also produce similar effects (Bedrosian, 2008).

    These work and schedule-related issues are likely to affect more than 80 million Americans (Rosekind, 2005) and are likely to exacerbate the prevalence of rest problems. Minimal information is available to quantify the effects of rest disruption and level-1 group on individuals’ work performance, safety, and productivity (Léger et al., 2006). Potential indirect economic costs of outcomes related to lost productivity due to level-1 group and rest problems also have not been well quantified (Ozminkowski et al., 2007). This survey examined rest time and rest problems in more than 4000 workforce from four Malaysian companies. About one in 10 (9.6%) met the criteria for level-1 group, whereas one in 16 (5.9%) met the criteria for level-2 group.

    In general, the findings demonstrate that these rest disorders were associated with lower at-work productivity, impaired work performance, and poorer safety outcomes, based on various WLQ-derived measures, compared with scores measured from respondents in the level-3 and level- 4 groups. Although majority of respondents (72%) reported using strategies and treatments to ameliorate rest time disorders, respondents in the level-1 group used OTC or prescription rest time medications, more frequently. At-work productivity, fatigue-related decrements were linked to a significant level of estimated annual costs to workforce, changing from $3156 in the level-1 group to $1293 in the level-4 group.

    4.1 Rest Time and Work Performance

    The current findings suggest that disturbed rest is related to poor at-work functioning. Level-1 and level-2 groups respondents in the present survey reported impairments in work performance and reduced productivity marked by decreased attention, memory loss, interpersonal functioning, and communication problems. Similar performance deficits resulting from disturbed or inadequate rest have been firmly established by other researchers (Lockley et al., 2007;Mulgrew et al., 2007). One study on rest habits and rest problems among industrial workers in Israel found that more pre-rest and post-rest complaints, mid-rest disorders, work accidents, employment dissatisfaction, asthma prevalence, hypertension, headaches, arthritis, and ulcers were noted (Lockley et al., 2007;Mulgrew et al., 2007).

    The present findings are compatible with those of a recent investigation on obstructive rest apnea. Mulgrew and colleagues found that severe obstructive rest apnea in blue-collar workers was associated with impaired time demands and mental or interpersonal interactions, based on the WLQ. Moreover, subjective fatigue, based on the Epworth Fatigue Scale, was strongly associated with limitations in work performance according to three of the four WLQ subscales such as work output, mental or interpersonal interactions, and time demands (Mulgrew et al., 2007). The decrements in performance and productivity linked to rest problems in the present survey and in prior research have important implications for both work safety and workforce costs.

    4.2 Rest and Safety

    The current investigation raises further concerns about decreasing work safety due to fatigue or tiredness in individuals with a rest problems. Average total rest time among the level-1 group in the present sample was 6.0 hr/d, less than the average adult 8-hour daily rest which is physiologically required to maintain alertness (Ferrara and DeGennaro, 2001). Respondents who reported rest problems were more likely to report unintentional rest at work and injury to self or others while at work. This is not unexpected, as other researchers have found that rest loss slowed reaction times on a psychomotor vigilance test, divided attention, reduced memory recall, and decreased self-rated qualities of performance (Roehrs et al., 2003).

    Problems with safety related to inadequate rest have also been described in health care settings, in which a strong positive relationship between level of physician fatigue and rate of workforce treatment error has been observed consistently (Lockley et al., 2007;Mountain et al., 2007). The findings are also consistent with those of other reports highlighting a strong link between inadequate rest and driving accidents (Leechawengwongs et al., 2006;Vanlaar et al., 2008). According to the National Transportation Safety Board, fatigue is the third leading cause of accidents in the United States (American Automobile Association Foundation for Traffic Safety, 2008;National Transportation Safety Board, 2008). The data suggest that individuals in the level-1 and level-2 groups were significantly more likely than individuals in the level- 4 group to report nodding off while driving and to have a near miss or accident due to fatigue. Other studies have also shown that individuals with level-1 group incur significantly greater direct and indirect health care costs than do individuals without level-1 group (National Transportation Safety Board, 2008).

    4.3 Treatment Use

    The use of hypnotic drugs, medications, and behavioral techniques has long been shown to be a reliable way to aid rest. The large majority (72%) of respondents to the present survey indicated that they used at least one treatment for their rest problems. However, many reported using “treatments” that do not improve rest and may even worsen it, such as alcohol. Alcohol tends to be a common choice among those with a rest problems, rather than herbal remedies or relaxation techniques (Kaneita et al., 2007). Unfortunately, this may be ineffective as it tends to produce interrupted rest (Kaneita et al., 2007;Gillin et al., 2005). Such a use of alcohol is also risky as it is subject to the development of tolerance and dependence. Few respondents (less than 13%) reported having visited a physician for disturbed rest which is only about 30% of individuals in the level-1 group. Among individuals in this group, 30% reported the use of prescribed medications and 30% reported the use of relaxation techniques. This approach tends to be effective if used properly and in association with high ratings for workforce satisfaction compared with other types of treatment (Allaert and Urbinelli, 2004).

    4.4 Economic Impact

    In the present investigation, productivity loss related to fatigue changed from the maximum of 6.1% in the level-1 group to the minimum of 2.5% in the level-4 group. Estimated costs per workforce linked to productivity decreases were also highest for individuals in the level- 1 group ($3156), in contrast to a low of $1293 in the level-4 group. Out of the total workforce from all four participating companies, more than 15% of respondents who were classified in the level-1 and level-2 groups were affected by level-1 group or level-2 group. The estimated cost of lost productivity associated with these individuals is $13.2 million annually. Inclusion of the level-3 group increases the number of affected workforce to more than14000 persons, with estimated productivity loss of $37.5 million. For the entire respondent group, work productivity loss due to level-1, level-2 groups, and rest problems would reach of $54 million annually. Other researchers have shown that higher costs to workforce related to rest problems may occur due to increased absenteeism (Godet-Cayré et al., 2006).

    In their study of health care workforce, Godet-Cayré found that, On average, individuals with level-1 group were absent from work 11.5 d/yr, compared with only 7 d/yr absence by good sleepers. Extra costs related to increased absenteeism among workforce with level-1 group amounted $US 1984/yr. These estimated costs of the lost productivity necessitate a strong rationale for improving the detection and treatment of level-1 group and rest problems presenting the opportunity to reduce associated productivity deficits (Bunn, 2006;Pandi-Perumal et al., 2006).

    4.5 Remedies

    There are a number of steps employers and employees can take to address workplace fatigue related to rest problems. Some evidence shows that workplace flexibility ─ allowing more flexible work start and end times ─ may contribute to positive lifestyle behaviors, and may play an important role in effective worksite health promotion programs (Grzywacz et al., 2007). Another possible step is addressing the complex and often contentious issues related to work schedule policies and practices (Rosekind, 2005). Researchers have also shown that allowing for “unwinding” time between work and home improves rest patterns. Likewise, negative work-to-home transition interference has the potential to decrease the risk of poor rest quality. Adequate rest between work periods and workdays may help to increase unwinding which in turn improves rest quality (Nylén et al., 2007). The employers can also play a role in educating workers about the importance of rest and how to effectively and safely manage rest loss or fatigue through a variety of proven strategies, including naps, better managed work demands, regular exercise, duty hour considerations, and instructing them on the basics of level-4 group habits (Davidhizar and Shearer, 2000;Hirose, 2005;Owens, 2007).


    Level-1 group and disturbed rest time were prevalent among the workforce associated with decreased work performance and productivity. Individuals meeting the criteria for level-1 group reported the greatest losses and impairments. The associated annual economic costs due to productivity loss for the entire work population, participating in this study, were estimated to be $54 million (approximately $1967/workforce). Our findings highlight the potential for the improved detection and treatment of rest problems to significantly improve workplace safety and productivity leading to the appropriate associated economic costs.



    Fatigue audit inter dyne (FAID).


    Rest time and full awareness stages.


    Duty, bed-time, rest periods.


    Work time percentage on performance limited by work dimension and each subject group, Level-3 and level-4 groups versus level-1 group; P<0.05.


    Overall average productivity loss by each subject group Level-3 and level-4 groups versus level-1 group; P<0.05.


    Negative work performance while being tired, by each subject group Level-2, level-3 and level-4 groups versus level-1 group; all P<0.01 versus the level-3 group and P<0.001 versus the level-4 group.


    Safety outcomes by each subject group Level-3 and level-4 groups versus levrl-2 group; P<0.05.Unintentional rest at work, Injured at home due to fatigue, Nodded off while driving, and Near miss or accident due to fatigue versus level-1 and level-2 groups; P<0.01 Unintentional rest at work and Nodded off while driving versus level-1 and level-2 groups; P<0.001.


    Treatment of rest problems by each subject group Level-2, level-3 and level-4 groups versus level-1 group; P<0.05 OTC and prescription sleep medications reported by the other subject groups versus level-1 group; P<0.01 Rx denotes prescription.


    Demographic and rest characteristics by each subject group (N=4,188)

    Estimated annual costs* of productivity loss due to rest problems, by each subject group


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