Managing fatigue: It really is about sleep

A network model of depressive and anxiety symptoms: a statistical evaluation

BACKGROUND

Although network analysis studies of psychiatric syndromes have increased in recent years, most have emphasized centrality symptoms and robust edges. Broadening the focus to include bridge symptoms within a systematic review could help to elucidate symptoms having the strongest links in network models of psychiatric syndromes. We conducted this systematic review and statistical evaluation of network analyses on depressive and anxiety symptoms to identify the most central symptoms and bridge symptoms, as well as the most robust edge indices of networks.

METHODS

A systematic literature search was performed in PubMed, PsycINFO, Web of Science, and EMBASE databases from their inception to May 25, 2022. To determine the most influential symptoms and connections, we analyzed centrality and bridge centrality rankings and aggregated the most robust symptom connections into a summary network. After determining the most central symptoms and bridge symptoms across network models, heterogeneity across studies was examined using linear logistic regression.

RESULTS

Thirty-three studies with 78,721 participants were included in this systematic review. Seventeen studies with 23 cross-sectional networks based on the Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder (GAD-7) assessments of clinical and community samples were examined using centrality scores. Twelve cross-sectional networks based on the PHQ and GAD-7 assessments were examined using bridge centrality scores. We found substantial variability between study samples and network features. 'Sad mood', 'Uncontrollable worry', and 'Worrying too much' were the most central symptoms, while 'Sad mood', 'Restlessness', and 'Motor disturbance' were the most frequent bridge centrality symptoms. In addition, the connection between 'Sleep' and 'Fatigue' was the most frequent edge for the depressive and anxiety symptoms network model.

CONCLUSION

Central symptoms, bridge symptoms and robust edges identified in this systematic review can be viewed as potential intervention targets. We also identified gaps in the literature and future directions for network analysis of comorbid depression and anxiety.

Neuropsychological considerations for long-duration deep spaceflight

The deep space environment far beyond low-Earth orbit (LEO) introduces multiple and simultaneous risks for the functioning and health of the central nervous system (CNS), which may impair astronauts' performance and wellbeing. As future deep space missions to Mars, moons, or asteroids will also exceed current LEO stay durations and are estimated to require up to 3 years, we review recent evidence with contemporary and historic spaceflight case studies addressing implications for long-duration missions. To highlight the need for specific further investigations, we provide neuropsychological considerations integrating cognitive and motor functions, neuroimaging, neurological biomarkers, behavior changes, and mood and affect to construct a multifactorial profile to explain performance variability, subjective experience, and potential risks. We discuss the importance of adopting a neuropsychological approach to long-duration deep spaceflight (LDDS) missions and draw specific recommendations for future research in space neuropsychology.

A feast-and-famine pattern of sleep: Do railway staff get the sleep they need?

The relationship between sleep and health and wellbeing is receiving increasing attention in our society, following decades of research that has demonstrated the impact of insufficient sleep on performance and health. Fatigue has been identified as a factor in 21% of high-risk incidents in the GB rail industry, and insufficient sleep and long periods of being awake are known to be two key contributors to fatigue. This paper presents evidence from a recent survey conducted in the GB rail industry, which enabled the sleep and wakefulness of railway workers to be quantified. There were 7807 responses to the survey, which represents a very large sample. Responses were primarily collected online, though paper copies were made available in some organisations. Respondents reported sleeping less when working nights, more when working days, and the most on days off, which suggests a feast-and-famine pattern of sleep. 41% were getting 6 h of sleep or less when working days, compared to 63% when working nights. Getting 6 h or less of sleep was associated with excessive daytime sleepiness. Although it is accepted that individuals' sleep requirements vary, the patterns that shift workers reported in this survey suggest that many are not achieving the amount of sleep they need. The findings of the survey presented in this paper highlight that there is work to be done to understand and address the causes of insufficient sleep in railway workers.

Musculoskeletal Disorders Associated with Occupational Driving: A Systematic Review Spanning 2006–2021

Several occupations require workers to spend long periods of time driving road vehicles. This occupational task is associated with musculoskeletal disorders. The purpose of this review was to collate, synthesize, and analyze research reporting on musculoskeletal disorders associated with occupational driving, in order to develop a volume of evidence to inform occupational disorder mitigation strategies. A systematic search of academic databases (PubMed, EBSCO host, CINAHL, SPORTDiscus, and Web of Science) was performed using key search terms. Eligible studies were critically appraised using the Joanna Briggs Institute critical appraisal checklists. A Cohen’s kappa analysis was used to determine interrater agreement between appraisers. Of the 18,254 identified studies, 25 studies were selected and appraised. The mean critical appraisal score is 69% (range 38–100%), with a fair level of agreement (k = 0.332). The studies report that musculoskeletal disorders, most commonly lower back pain, is of concern in this population, particularly in truck, bus, and taxi drivers. Risk factors for these occupations include long hours in a sitting position, years in the profession, vehicle ergonomics, and vibration.

How effective are Fatigue Risk Management Systems (FRMS)? A review

OBJECTIVE

Fatigue Risk Management Systems (FRMS) are a data-driven set of management practices for identifying and managing fatigue-related safety risks. This approach also considers sleep and work time, and is based on ongoing risk assessment and monitoring. This narrative review addresses the effectiveness of FRMS, as well as barriers and enablers in the implementation of FRMS. Furthermore, this review draws on the literature to provide evidence-based policy guidance regarding FRMS implementation.

METHODS

Seven databases were drawn on to identify relevant peer-reviewed literature. Relevant grey literature was also reviewed based on the authors' experience in the area. In total, 2129 records were screened based on the search strategy, with 231 included in the final review.

RESULTS

Few studies provide an evidence-base for the effectiveness of FRMS as a whole. However, FRMS components (e.g., bio-mathematical models, self-report measures, performance monitoring) have improved key safety and fatigue metrics. This suggests FRMS as a whole are likely to have positive safety outcomes. Key enablers of successful implementation of FRMS include organisational and worker commitment, workplace culture, and training.

CONCLUSIONS

While FRMS are likely to be effective, in organisations where safety cultures are insufficiently mature and resources are less available, these systems may be challenging to implement successfully. We propose regulatory bodies consider a hybrid model of FRMS, where organisations could choose to align with tight hours of work (compliance) controls. Alternatively, where organisational flexibility is desired, a risk-based approach to fatigue management could be implemented.

Sleep assessment by means of a wrist actigraphy-based algorithm: agreement with polysomnography in an ambulatory study on older adults

The purpose of the present work is to examine, on a clinically diverse population of older adults (N = 46) sleeping at home, the performance of two actigraphy-based sleep tracking algorithms (i.e., Actigraphy-based Sleep algorithm, ACT-S1 and Sadeh's algorithm) compared to manually scored electroencephalography-based PSG (PSG-EEG). ACT-S1 allows for a fully automatic identification of sleep period time (SPT) and within the identified sleep period, the sleep-wake classification. SPT detected by ACT-S1 did not differ statistically from using PSG-EEG (bias = -9.98 min; correlation 0.89). In sleep-wake classification on 30-s epochs within the identified sleep period, the new ACT-S1 presented similar or slightly higher accuracy (83-87%), precision (86-89%) and F1 score (90-92%), significantly higher specificity (39-40%), and significantly lower, but still high, sensitivity (96-97%) compared to Sadeh's algorithm, which achieved 99% sensitivity as the only measure better than ACT-S1's. Total sleep times (TST) estimated with ACT-S1 and Sadeh's algorithm were higher, but still highly correlated to PSG-EEG's TST. Sleep quality metrics of sleep period efficiency and wake-after-sleep-onset computed by ACT-S1 were not significantly different from PSG-EEG, while the same sleep quality metrics derived by Sadeh's algorithm differed significantly from PSG-EEG. Agreement between ACT-S1 and PSG-EEG reached was highest when analyzing the subset of subjects with least disrupted sleep (N = 28). These results provide evidence of promising performance of a full-automation of the sleep tracking procedure with ACT-S1 on older adults. Future longitudinal validations across specific medical conditions are needed. The algorithm's performance may further improve with integrating multi-sensor information.

Working time limits at sea, a hundred-year construction

In a view to protect workers from extended work periods as well as to comply with the Versailles Peace Treaty requirements, the International Labour Organization (ILO) regulated hours of work from 1919 using '8-hour workday and 48-h workweek' as yardsticks. However, a historical perspective demonstrates the ILO's difficulties in integrating such standards for sea workers. From 1920 to 1958, the ILO endeavoured to anchor the 8-hour workday principle in maritime conventions on working time and to ensure compliance by quantifying manning levels. Facing sectoral opposition and the obstacle of the minimum tonnage requirement, none of the conventions adopted during the first period entered into force. A second regulatory wave (1995-2007) initiated by the International Maritime Organization (IMO) orientated working time towards fatigue management and adopted the 14-hour workday. Absorbed by the ILO from 1996, this threshold facilitated the implementation of working time standards for sea workers. The existence of autonomous maritime governance at the ILO and the IMO complemented by the incorporation of the tonnage clause in maritime convention allowed the acceptance of the 14-hour workday system in spite of breaching the universal principles established a century ago. The departure between maritime and land standards show that sectoral interests prevail over labour rights. More decisively, current standards detached labour rights from workers' human nature and attached them directly to sectoral interests.

Fatigue and recovery among Malaysian doctors: the role of work-related activities during non-work time

OBJECTIVES

This paper aims to estimate the level of acute fatigue, chronic fatigue and intershift recovery among doctors working at public hospitals in Malaysia and determine their inter-relationship and their association with work-related activities during non-work time.

DESIGN

Cross-sectional.

SETTING

Seven core clinical disciplines from seven tertiary public hospitals in Malaysia.

PARTICIPANTS

Study was conducted among 330 randomly-sampled doctors. Response rate was 80.61% (n=266).

RESULTS

The mean score of acute fatigue, chronic fatigue and intershift recovery were 68.51 (SD=16.549), 54.60 (SD=21.259) and 37.29 (SD=19.540), respectively. All these scores were out of 100 points each. Acute and chronic fatigue were correlated (r=0.663), and both were negatively correlated with intershift recovery (r=-0.704 and r=-0.670, respectively). Among the work-related activities done during non-work time, work-related ruminations dominated both the more frequent activities and the association with poorer fatigue and recovery outcomes. Rumination on being scolded/violated was found to be positively associated with both acute fatigue (adjusted regression coefficient (Adj.b)=2.190, 95% CI=1.139 to 3.240) and chronic fatigue (Adj.b=5.089, 95% CI=3.876 to 6.303), and negatively associated with recovery (Adj.b=-3.316, 95% CI=-4.516 to -2.117). Doing work task at workplace or attending extra work-related activities such as locum and attending training were found to have negative associations with fatigue and positive associations with recovery. Nevertheless, doing work-related activities at home was positively associated with acute fatigue. In terms of communication, it was found that face-to-face conversation with partner did associate with higher recovery but virtual conversation with partner associated with higher acute fatigue and lower recovery.

CONCLUSIONS

Work-related ruminations during non-work time were common and associated with poor fatigue and recovery outcomes while overt work activities done at workplace during non-work time were associated with better fatigue and recovery levels. There is a need for future studies with design that allow causal inference to address these relationships.

Safety implications of fatigue and sleep inertia for emergency services personnel

Emergency services present a unique operational environment for the management of fatigue and sleep inertia. Communities request and often expect the provision of emergency services on a 24/7/365 basis. This can result in highly variable workloads and/or significant need for on-demand or on-call working time arrangements. In turn, the management of fatigue-related risk requires a different approach than in other more predictable shift working sectors (e.g., mining and manufacturing). The aim of this review is to provide a comprehensive overview of fatigue risk management that is accessible to regulators, policy makers and organisations in the emergency services sector. The review outlines the unique fatigue challenges in the emergency services sector, examines the current scientific and policy consensus around managing fatigue and sleep inertia, and finally discusses strategies that emergency services organisations can use to minimise the risks associated with fatigue and sleep inertia.

Precision Medicine for Sleep Loss and Fatigue Management

Sleep loss is a widespread phenomenon and a public health threat. Sleep disorders, medical conditions, lifestyles, and occupational factors all contribute to insufficient sleep. Regardless of the underlying cause, insufficient sleep has well-defined consequences and the severity of said consequences partially influenced by individual characteristics. It is here where precision medicine needs to understand and define sleep insufficiency in hopes for personalizing medical approach to improve patient outcomes. Following a discussion on causes and consequences of sleep loss, this article discusses tools for assessing sleep sufficiency, mitigating strategies to sleep loss, and sleep loss in the context of fatigue management.

Testing Alertness of Emergency Physicians: A Novel Quantitative Measure of Alertness and Implications for Worker and Patient Care

BACKGROUND

Establishing practical solutions to manage fatigue in health care settings could reduce errors. Predictive Safety SRP Inc.'s AlertMeter is a 2-min cognitive assessment tool currently used in high-hazard industries to identify fatigued staff.

OBJECTIVE

No prior study has attempted to address fatigue in emergency medicine (EM). We objectively assessed provider alertness to determine potential application of software-based fatigue recognition for risk reduction.

METHODS

In a double-blind, prospective evaluation from July 1 to September 30, 2016, we applied the AlertMeter to EM residents at an academic level I trauma center. The tool was applied before and after shifts to evaluate alertness in three types of shifts: day, evening, and night. All residents were invited to participate-27 of 30 enrolled. Analysis of covariance (ANCOVA) was implemented to examine shift and completion effects on alertness score using baseline score as a covariate. Additionally, three separate ANCOVAs were conducted to examine alertness score differences between portion (start vs. end) and type of shift (day, evening, or night).

RESULTS

Residents were significantly less alert at the completion of the evening shift. Scores at the end of the night shift were significantly lower than the start of the night shift.

CONCLUSIONS

Alertness software can be reliably integrated into the emergency department. Alertness was lower at the end of the evening shift and end of the night shift. This work could have positive implications on shift and task scheduling and potentially reduce errors in patient care by quantifying providers' fatigue and identifying areas for countermeasures.

Physiological and pathological covariates of persistent concussion-related fatigue: results from two regression methodologies

BACKGROUND

Fatigue severity in persons with mild traumatic brain injury (mTBI) has received little research attention, despite its typically positively skewed nature. Investigation of covariates across a range of fatigue severity may provide insight into important contributors.

OBJECTIVE

To assess the relative significance of a priori-hypothesized covariates of physiological and pathological (mental and physical) fatigue in persons with mTBI/concussion, applying ordinary least squares (OLS) and quantile regression (QR) approaches.

METHODS

We conducted a cross-sectional investigation in 80 participants with mTBI/concussion (mean age 45.4 ± 10.1 years, 59% male). The fatigue severity scale (FSS) was used as an outcome measure. Predictors of this outcome, grouped into physiological and pathological models of fatigue were assessed using OLS and QR.

RESULTS

The mean total FSS score was 46.13 ± 14.59, and the median was 49 (interquartile range 37-57), demonstrating positive skewness. Fatigue severity was associated with variables within the mental, psychological and psychiatric domains at different levels of the fatigue score distribution.

CONCLUSION

Results highlighted that some covariates had a significant impact on the FSS total score at non-central parts of its distribution, while others exhibited significant impact across the entire distribution. Addressing covariates of fatigue across the severity continuum can enhance research and clinical management.

Bio-mathematical fatigue models predict sickness absence in hospital nurses: An 18 months retrospective cohort study

This study examined the associations between bio-mathematical fatigue-risk scores and sickness absence (SA) in hospital nurses over 18 months. Work schedules and SA data were extracted from the hospital's attendance system. Fatigue-risk scores were generated for work days using the Fatigue Audit InterDyne (FAID) and Fatigue Risk Index (FRI). Over the study period, 5.4% of the shifts were absence shifts. FAID-fatigue ranged from 7 to 154; scores for a standard 9-5 work schedule can range from 7 to 40. Nurses with high FAID-scores were more likely to be absent from work when compared to standard FAID-scores (41-79, OR = 1.38, 95%CI = 1.21-1.58; 80-99, OR = 1.63, 95%CI = 1.37-1.94 and ≥ 100, OR = 1.73, 95%CI = 1.40-2.13). FRI-fatigue ranged from 0.9 to 76.8. When FRI-scores were >60, nurses were at 1.58 times (95%CI = 1.05-2.37) at increased odds for SA compared to scores in the 0.9-20 category. Nurse leaders can use these decision-support models to adjust high-risk schedules or the number of staff needed to cover anticipated absences from work.

A Preliminary Review of Fatigue Among Rail Staff

Background: Fatigue is a severe problem in the rail industry, which may jeopardize train crew's health and safety. Nonetheless, a preliminary review of all empirical evidence for train crew fatigue is still lacking. The aim of the present paper is, therefore, to provide a preliminary description of occupational fatigue in the rail industry. This paper reviews the literature with the research question examining the risk factors associated with train crew fatigue, covering both papers published in refereed journals and reports from trade organizations and regulators. It assesses the progress of research on railway fatigue, including research on the main risk factors for railway fatigue, the association between fatigue and railway incidents, and how to better manage fatigue in the railway industry.

Methods: Systematic searches were performed in both science and industry databases. The searches considered studies published before August 2017. The main exclusion criterion was fatigue not being directly measured through subjective or objective methods.

Results: A total of 31 studies were included in the main review. The causes of fatigue included long working hours, heavy workload, early morning or night shifts, and insufficient sleep. Poor working environment, particular job roles, and individual differences also contributed to fatigue.

Conclusion: Fatigue in the rail industry includes most of the features of occupational fatigue, and it is also subject to industry-specific factors. The effect of fatigue on well-being and the fatigued population in the railway industry are still not clear. Future studies can consider associations between occupational risk factors and perceived fatigue by examining the prevalence of fatigue and identifying the potential risk factors in staff within the railway industry.

Relationship between Physical Activity and Fatigue in Adults with Cystic Fibrosis

Purpose: We examined the relationship between the amount of physical activity and level of fatigue in adults with cystic fibrosis (CF). Method: Participants were recruited from the Toronto Adult Cystic Fibrosis Centre at St. Michael's Hospital. Participants completed the Habitual Activity Estimation Scale, the Multidimensional Fatigue Inventory, and the Depression subscale of the Hospital Anxiety and Depression Scale, in that order. Descriptive statistics and linear and multiple regressions were computed. Results: Over a 6-month period, 51 individuals were approached, and 22 (10 men, 12 women) participated in this study. The participants' median age was 33, and forced expiratory volume in 1 second (FEV₁) was 64% predicted. When holding both FEV₁ and depression constant, a significant negative correlation was found between total active hours per weekday and general fatigue (β=-0.735, p=0.03); there was a negative trend between total active hours per weekday and physical fatigue (β=-0.579, p=0.09). Conclusions: This study is the first to demonstrate that among adults with CF, a higher level of physical activity is associated with a lower level of general and physical fatigue when controlling for lung function and level of depression. Physical activity may be used as a means of mitigating the levels of general and physical fatigue in people with CF.

Causes, consequences and countermeasures to driver fatigue in the rail industry: The train driver perspective

Fatigue is an important workplace risk management issue. Within the rail industry, the passing of a stop signal (signal passed at danger; SPAD) is considered to be one of the most major safety breaches which can occur. Train drivers are very aware of the negative consequences associated with a SPAD. Therefore, SPADs provide a practical and applied safety relevant context within which to structure a discussion on fatigue. Focus groups discussing contributing factors to SPADs were undertaken at eight passenger rail organisations across Australia and New Zealand (n = 28 drivers). Data relating to fatigue was extracted and inductively analysed identifying three themes: causes, consequences, and countermeasures (to fatigue). Drivers experienced negative consequences of fatigue, despite existing countermeasures to mitigate it. Organisational culture was a barrier to effective fatigue management. A fatigue assessment tool consistently informed rostering, however, shift swapping was commonplace and often unregulated, reducing any potential positive impact. In discussing fatigue countermeasure strategies, drivers talked interchangeably about mitigating task related fatigue (e.g. increasing cognitive load) and sleepiness (e.g. caffeine). Ensuring the concepts of fatigue and sleepiness are properly understood has the potential to maximise safety.

How should a bio-mathematical model be used within a fatigue risk management system to determine whether or not a working time arrangement is safe?

Bio-mathematical models that predict fatigue and/or sleepiness have proved a useful adjunct in the management of what has been typically referred to as fatigue-related risk. Codifying what constitutes appropriate use of these models will be increasingly important over the next decade. Current guidelines for determining a safe working time arrangement based on model outputs generally use a single upper threshold and are, arguably, over-simplistic. These guidelines fail to incorporate explicitly essential aspects of the risk assessment process - namely, the inherent uncertainty and variability in human sleep-wake behavior; the non-linear relationship between fatigue, task performance and safety outcomes; the consequence of a fatigue-related error and its influence on overall risk; and the impact of risk mitigation or controls in reducing the likelihood or consequence of a fatigue-related error. As industry and regulatory bodies increasingly move toward performance-based approaches to safety management, any fatigue risk management system that includes a bio-mathematical model should specify what exactly is measured by the model, and how the model can be used in the context of a safety management system approach. This will require significant dialog between the various parties with an interest in bio-mathematical models, i.e. developers, vendors, end-users, and regulators.

Adrenal fatigue does not exist: a systematic review

BACKGROUND

The term "adrenal fatigue" ("AF") has been used by some doctors, healthcare providers, and the general media to describe an alleged condition caused by chronic exposure to stressful situations. Despite this, "AF" has not been recognized by any Endocrinology society, who claim there is no hard evidence for the existence. The aim of this systematic review is to verify whether there is substantiation for "AF".

METHODS

A systematic search was performed at PUBMED, MEDLINE (Ebsco) and Cochrane databases, from the beginning of the data until April 22nd, 2016. Searched key words were: "adrenal" + "fatigue", "adrenal" + "burnout", "adrenal" + "exhaustion", "hypoadrenia", "burnout" + "cortisol", "fatigue" + "cortisol", "clinical" + "burnout", "cortisol" + "vitalility", "adrenal" + "vitality", and "cortisol" + "exhaustion". Eligibility criteria were: (1) articles written in English, (2) cortisol profile and fatigue or energy status as the primary outcome, (3) performed tests for evaluating the adrenal axis, (4) absence of influence of corticosteroid therapy, and (5) absence of confounding diseases. Type of questionnaire to distinct fatigued subjects, population studied, tests performed of selected studies were analyzed.

RESULTS

From 3,470 articles found, 58 studies fulfilled the criteria: 33 were carried in healthy individuals, and 25 in symptomatic patients. The most assessed exams were "Direct Awakening Cortisol" (n = 29), "Cortisol Awakening Response" (n = 27) and "Salivary Cortisol Rhythm" (n = 26).

DISCUSSION

We found an almost systematic finding of conflicting results derived from most of the studies methods utilized, regardless of the validation and the quality of performed tests. Some limitations of the review include: (1) heterogeneity of the study design; (2) the descriptive nature of most studies; (3) the poor quality assessment of fatigue; (4) the use of an unsubstantiated methodology in terms of cortisol assessment (not endorsed by endocrinologists); (5) false premises leading to an incorrect sequence of research direction; and, (6) inappropriate/invalid conclusions regarding causality and association between different information.

CONCLUSION

This systematic review proves that there is no substantiation that "adrenal fatigue" is an actual medical condition. Therefore, adrenal fatigue is still a myth.