Development and evaluation of a matrix for assessing fatigue-related risk, derived from a national survey of nurses' work patterns.

BACKGROUND: Multiple aspects of nurses' rosters interact to affect the quality of patient care they can provide and their own health, safety and wellbeing. OBJECTIVES: (1) Develop and test a matrix incorporating multiple aspects of rosters and recovery sleep that are individually associated with three fatigue-related outcomes - fatigue-related clinical errors, excessive sleepiness and sleepy driving; and (2) evaluate whether the matrix also predicts nurses' ratings of the effects of rosters on aspects of life outside work. DESIGN: Develop and test the matrix using data from a national survey of nurses' fatigue and work patterns in six hospital-based practice areas with high fatigue risk. METHODS: Survey data included demographics, work patterns (previous 14 days), choice about shifts, and the extent to which work patterns cause problems with social life, home life, personal relationships, and other commitments (rated 1 = not at all to 5 = very much). Matrix variables were selected based on univariate associations with the fatigue-related outcomes, limits in the collective employment contract, and previous research. Each variable was categorised as lower (score 0), significant (score 1), or higher risk (score 2). Logistic multiple regression modelling tested the independent predictive power of matrix scores against models including all the (uncategorised) work pattern and recovery sleep variables with significant univariate associations with each outcome variable. Model fit was measured using Akaike and Bayesian Information Criterion statistics. RESULTS: Data were included from 2358 nurses who averaged at least 30 h/week in the previous fortnight in one of the target practice areas. Final matrix variables were: total hours worked; number of shift extensions >30 min, night shifts; breaks < 9 h; breaks ≥ 24 h; nights with sleep 11pm to 7am; days waking fully rested; and roster change. After controlling for gender, ethnicity, years of nursing experience, and the extent of shift choice, the matrix score was a significant independent predictor of each of the three fatigue-related outcomes, and for all four aspects of life outside work. For all outcome variables, the model including the matrix score was a better fit to the data than the equivalent model including all the (uncategorised) work pattern variables. CONCLUSIONS: A matrix that predicts the likelihood of nurses reporting fatigue-related safety outcomes can be used to compare the impact of rosters both at work and outside work. It can be used for roster design and management, and to guide nurses' choices about the shifts they work.

Drowsy Driving Considerations in Non-Commercial Drivers for the Sleep Physician.

ABSTRACT: The sleep physician faces many challenges in the assessment of drowsy driving. The following article reviews current clinical evaluation methods and legal considerations at the state level in the United States.

Fatigue and nurses' work patterns: An online questionnaire survey.

BACKGROUND: Fatigue resulting from shift work and extended hours can compromise patient care and the safety and health of nurses, as well as increasing nursing turnover and health care costs. OBJECTIVES: This research aimed to identify aspects of nurses' work patterns associated with increased risk of reporting fatigue-related outcomes. DESIGN: A national survey of work patterns and fatigue-related outcomes in 6 practice areas expected to have high fatigue risk (child health including neonatology, cardiac care/intensive care, emergency and trauma, in-patient mental health, medical, and surgical nursing). METHODS: The 5-page online questionnaire included questions addressing: demographics, usual work patterns, work in the previous two weeks, choice about shifts, and four fatigue-related outcomes - having a sleep problem for at least 6 months, sleepiness (Epworth Sleepiness Scale), recalling a fatigue-related error in clinical practice in the last 6 months, and feeling close to falling asleep at the wheel in the last 12 months. The target population was all registered and enrolled nurses employed to work in public hospitals at least 30 h/week in one of the 6 practice areas. Participation was voluntary and anonymous. RESULTS: Respondents (n = 3133) were 89.8% women and 8% Maori (indigenous New Zealanders), median age 40 years, range 21-71 years (response rate 42.6%). Nurses were more likely than New Zealand adults in general to report chronic sleep problems (37.73% vs 25.09%, p < 0.0001) and excessive sleepiness (33.75% vs 14.9%, p < 0.0001). Fatigue-related error(s) in the last 6 months were recalled by 30.80% and 64.50% reported having felt sleepy at the wheel in the last 12 months. Logistic regression analyses indicated that fatigue-related outcomes were most consistently associated with shift timing and sleep. Risk increased with more night shifts and decreased with more nights with sleep between 11 p.m. and 7 a.m. and on which nurses had enough sleep to feel fully rested. Risk also increased with roster changes and more shift extensions greater than 30 min and decreased with more choice about shifts. Comparisons between intensive care/cardiac care and in-patient mental health nursing highlight that fatigue has different causes and consequences in different practice areas. CONCLUSIONS: Findings confirm the need for a more comprehensive and adaptable approach to managing fatigue. We advocate an approach that integrates safety management and scientific principles with nursing and management expertise. It should be data-driven, risk-focused, adaptable, and resilient in the face of changes in the services required, the resources available, and the overall goals of the healthcare system.

Sleepy driving and risk of obstructive sleep apnea among truck drivers in Saudi Arabia.

Objective: Truck drivers represent a group at a particularly higher risk of motor vehicle accidents (MVAs). Sleepy driving and obstructive sleep apnea (OSA) among truck drivers are major risk factors for MVAs. No study has assessed the prevalence of sleepy driving and risk of OSA among truck drivers in Saudi Arabia. Therefore, this study aimed to assess sleepy driving and risk of OSA among these truck drivers. Methods: This study included 338 male truck drivers working in Saudi Arabia. A validated questionnaire regarding sleepy driving and OSA was used. The questionnaire included sociodemographic assessment, the Epworth Sleepiness Scale (ESS), the Berlin Questionnaire (BQ), and driving-related items. Results: The drivers had a mean age of 42.9 ± 9.7 years. The majority (94.7%) drove more than 5 h a day. A history of MVAs during the last 6 months was reported by 6.5%. Approximately 95% of the participants reported that they had accidentally fallen asleep at least once while driving over the past 6 months, and 49.7% stated that this had happened more than 5 times during the last 6 months. Based on the BQ score, a high risk of OSA was detected in 29% of the drivers. "Not getting good-quality sleep" (odds ratio [OR] = 2.89; 95% confidence interval [CI], 1.08-7.75; P = .014) and driving experience from 6 to 10 years (OR = 3.37; 95% CI, 1.28-8.91; P = .034) were the only independent predictors of MVAs in the past 6 months. Conclusions: Sleepy driving and a high risk of OSA was prevalent among the study population of male truck drivers in Saudi Arabia. Not getting good-quality sleep and driving experience from 6 to 10 years contributes to the accident risk among these truck drivers.

Crash risk perception of sleepy driving and its comparisons with drink driving and speeding: Which behavior is perceived as the riskiest?

OBJECTIVE: Driver sleepiness is a major crash risk factor but may be underrecognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding. METHODS: Three hundred Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants' perceptions of crash risk were assessed for 5 different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, nighttime) of driving. RESULTS: The analysis confirmed that sleepy driving was considered a risky driving behavior but not as risky as high levels of speeding (P < .05). Yet, the risk of crashing at 4 a.m. was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky because time of day/circadian influences were not reported as high risk. CONCLUSIONS: The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long-distance driving and driver sleepiness. Further efforts are required to improve the community's awareness of the impairing effects from sleepiness and, in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.

Prevalence of sleep-related accidents among drivers in Saudi Arabia.

INTRODUCTION: The prevalence of sleepy driving and sleep-related accidents (SRA) varies widely, and no data exist regarding the prevalence of sleepy driving in Saudi Arabia. Therefore, this study was designed to determine the prevalence and predictors of sleepy driving, near-misses, and SRA among drivers in Saudi Arabia. MATERIALS AND METHODS: A questionnaire was developed to assess sleep and driving in detail based on previously published data regarding sleepy driving. The questionnaire included 50 questions addressing socio-demographics, the Epworth Sleepiness Scale (ESS), driving items, and the Berlin Questionnaire. In total, 1,219 male drivers in public places were interviewed face-to-face. RESULTS: The included drivers had a mean age of 32.4 ± 11.7 years and displayed a mean ESS score of 7.2 ± 3.8. Among these drivers, 33.1% reported at least one near-miss accident caused by sleepiness. Among those who had actual accidents, 11.6% were attributed to sleepiness. In the past six months, drivers reported the following: 25.2% reported falling asleep at least once during, driving and 20.8% had to stop driving at least once because of severe sleepiness. Young age, feeling very sleepy during driving, and having at least one near-miss accident caused by sleepiness in the past six months were the only predictors of accidents. CONCLUSION: Sleepy driving is prevalent among male drivers in Saudi Arabia. Near-miss accidents caused by sleepiness are an important risk factor for car accidents and should be considered as a strong warning signal of future accidents.

Continuing to drive while sleepy: the influence of sleepiness countermeasures, motivation for driving sleepy, and risk perception.

Driver sleepiness is a major contributor to road crashes. The current study sought to examine the association between perceptions of effectiveness of six sleepiness countermeasures and their relationship with self-reports of continuing to drive while sleepy among 309 drivers after controlling for the influence of age, sex, motivation for driving sleepy, and risk perception of sleepy driving. The results demonstrate that the variables of age, sex, motivation, and risk perception were significantly associated with self-reports of continuing to drive while sleepy and only one countermeasure was associated with self-reports of continuing to drive while sleepy. Further, it was found that age differences in self-reports of continuing to drive while sleepy was mediated by participants' motivation and risk perception. These findings highlight modifiable factors that could be focused on with interventions that seek to modify drivers' attitudes and behaviours of driving while sleepy.

Driving habits and risk factors for traffic accidents among sleep apnea patients--a European multi-centre cohort study.

Obstructive sleep apnea is associated with increased motor vehicle accident risk, and improved detection of patients at risk is of importance. The present study addresses potential risk factors in the European Sleep Apnea Database and includes patients with suspected obstructive sleep apnea [n = 8476, age 51.5 (12.5) years, body mass index 31.0 (6.6) kg m(-2) , 82.4% driver's licence holders]. Driving distance (km year(-1) ), driver's licence type, sleep apnea severity, sleepiness and comorbidities were assessed. Previously validated risk factors for accident history: Epworth Sleepiness Scale ≥16; habitual sleep time ≤5 h; use of hypnotics; and driving ≥15 000 km year(-1) were analysed across European regions. At least one risk factor was identified in male and female drivers, 68.75 and 51.3%, respectively. The occurrence of the risk factors was similar across Europe, with only a lower rate in the eastern region (P = 0.001). The mean number of risk factors increased across classes of sleep apnea severity. Frequent driving was prevalent [14.0 (interquartile range 8.0-20.0) × 10(3)  km year(-1) ] and 32.7% of drivers had severe obstructive sleep apnea [apnea-hypopnea index 50.3 (38.8-66.0) n h(-1) ]. Obesity, shorter sleep time and younger age were associated with increased traffic exposure (P ≤ 0.03). In conclusion, the risk factors associated with accident history were common among European patients with suspected obstructive sleep apnea, but varied between geographical regions. There was a weak covariation between occurrence of risk factors and clinically determined apnea severity but frequent driving, a strong risk factor for accidents, was over-represented. Systematic evaluation of accident-related risk factors is important to detect sleep apnea patients at risk for motor vehicle accidents.

Feasibility of force platform based roadside drowsiness screening - a pilot study.

Previous research on driver drowsiness detection has focused on developing in-car systems that continuously monitor the driver while driving and warn him/her when drowsiness compromises safety. In occupational settings a simple test of postural control has showed sensitivity to work shift induced fatigue in drivers. Whether the test is feasible for surveillance purposes in roadside settings is unknown. The present research sought to evaluate the feasibility of using a force platform test of postural control as a breathalyzer-like drowsiness-test at the roadside. Seventy-one commercial drivers stopped by at our measurement sites and volunteered to participate in the study. We tested postural control with a computerized force platform, on which the drivers stood eyes open while it sampled body center-of-pressure excursions at 33Hz for 30s and scored postural control as the area of the 95% confidence ellipse enclosing the excursions. The drivers also completed the Karolinska Sleepiness Scale (KSS) and we recorded each driver's wake up time, time on task, and time of testing. Five of the seventy-one drivers exhibited significantly poorer postural control than their peers (P=0.03). The wake up times and times on task for these five drivers indicated that they were on a night shift schedule or had a long time on task. Furthermore, their postural control and KSS scores correlated (r=-0.88, P=0.04), whereas the scores did not correlate for their peers (r=0.10, P=0.48). These results indicate that the force platform test identified drivers, whose impairment in postural control was drowsiness-related. Specifically, the test identified the few drivers in this roadside sample whose wake- and work histories resembled a night shift schedule. In this kind of roadside setting, with a demographically heterogeneous group and interindividual differences in people's responses to drowsiness, it suggests that the method, further developed, may provide a drowsiness test for roadside surveillance.