A systems science approach to fatigue management in research and health care

Lee, Kathryn A.; Dziadkowiec, Oliwier; Meek, Paula

doi:10.1016/j.outlook.2014.07.002

Cited by 18 publications

(10 citation statements)

References 33 publications

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“…The model of Occupational Fatigue in Nursing (Steege & Pinekenstein, ) and the SEIPS model (Systems Engineering Initiative for Patient Safety) (Carayon et al, ) highlight the impact of occupational factors on fatigue. Based on these theoretical perspectives, negative factors such as workplace violence and occupational stress may damage nurses' health (Barker & Nussbaum, ; Spector, Zhou, & Che, ; Steege, Pasupathy, & Drake, ) and potentially lead to fatigue (Carayon et al, ; Lee, Dziadkowiec, & Meek, ). In addition, positive factor existing in workplace, such as organizational support, may be beneficial to avoiding fatigue (Prins et al, ).…”

Section: Introductionmentioning

confidence: 99%

Associations of occupational stress, workplace violence, and organizational support on chronic fatigue syndrome among nurses

Shu

Huang

et al. 2020

Journal of Advanced Nursing

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Aims Chronic fatigue syndrome is an agnogenic disease worldwide. Nurses are at a high risk of chronic fatigue syndrome. However, no research has been done to examine the associations of workplace violence, organizational support, and occupational stress with chronic fatigue syndrome among Chinese nurses. This study aimed to examine effects of these factors on chronic fatigue syndrome in this occupational group. Design Cross‐sectional. All participants voluntarily completed a questionnaire survey. Methods The study was conducted in Liaoning province from December 2017–January 2018. Self‐administered questionnaires were distributed to 1,200 nurses, including Effort‐Reward‐Imbalance, Workplace Violence Scale, Survey of Perceived Organizational Support, together with age, gender, marital status, education levels, physical activities, job rank, monthly income, and weekly working hours. Complete responses were obtained from 1,080 (90%) participants. Chronic fatigue syndrome was diagnosed by doctors according to the Centers for Disease Control and Prevention criteria. Multivariable logistic regression was performed to examine these independent risk factors. Results The prevalence of chronic fatigue syndrome was 6.76%. The results of logistic regression analysis showed that nurses who experienced serious higher levels of overcommitment, workplace violence and less organizational support were more likely to be classified as chronic fatigue syndrome. Conclusion There was a high prevalence of chronic fatigue syndrome. Lower workplace violence, more organizational support and lower overcommitment could be effective resources for reducing chronic fatigue syndrome. Impact Workplace violence, organizational support, and occupational stress were related to chronic fatigue syndrome, which helped to explain why Chinese nurses suffered higher prevalence of chronic fatigue syndrome. Overcommitment explained chronic fatigue syndrome better than Effort/Reward Ratio, so intrinsic stress played a more critical role than extrinsic stress in chronic fatigue syndrome. Chinese nurses suffered serious sleep disorders and impairment of concentration and memory. These symptoms might also attribute to serious occupational stress, unsafe and unsupportive working environment. Creating a safe and supportive working environment, relieving intrinsic occupational stress should be considered as an institutional strategy to early prevent chronic fatigue syndrome.

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Section: Introductionmentioning

confidence: 99%

Associations of occupational stress, workplace violence, and organizational support on chronic fatigue syndrome among nurses

Shu

Huang

et al. 2020

Journal of Advanced Nursing

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“…Work-related fatigue in nurses has been defined as "a multidimensional state that arises in workers who are exposed to excessive demands through their work tasks, environment and schedules, and that can interfere with workers' physical and cognitive abilities and their ability to function at their normal capacity" (Steege, Drake, Olivas, & Mazza, 2015). Fatigue can be experienced as an acute phenomenon that occurs in temporary intervals or as a chronic condition that lasts for an extended period (Barker & Nussbaum, 2011;Lee, Dziadkowiec, & Meek, 2014). Without sufficient recovery from the physical, cognitive and emotional demands associated with nurse work, nurse fatigue can progress from an acute to a chronic state (Steege, Pasupathy, & Drake, 2018;Winwood, Winefield, Dawson, & Lushington, 2005).…”

Section: Fati G Ue and The Impac T Of N Ur S E Fati G U Ementioning

confidence: 99%

Understanding the impact of the physical health care environment on nurse fatigue

Wingler

Keys

2019

J Nurs Manag

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Aim(s) The purpose of this study was to investigate factors in the physical health care environment (PHE) contributing to nurse fatigue. Background Nurses experience high levels of physical, mental and overall fatigue related to the physically demanding and mentally complex nature of bedside care. Method(s) This study used secondary data analysis of a 2017 focus group session, which explored: (a) challenges nursing professionals face while delivering care, (b) the effect of nurse fatigue on care delivery and (c) system factors that can either reduce or contribute to nurse fatigue. Eleven volunteers from a health care design focused nursing organisation participated in the focus group. Results Twenty‐seven design elements across four environmental categories were identified in this study as impacting fatigue. The effects of fatigue were found to have implications at the individual level (nurse and patient), the organisational level and the profession at large. Fatigue effects were found to be cumulative. Conclusion(s) Findings suggest that the PHE can have a substantial impact on nurse fatigue and contribute to profound effects with patient and staff safety implications. Implications for Nursing Management This study provides nursing managers, hospital administrators, nurses and designers with evidence for utilizing the PHE to mitigate and prevent nurse fatigue.

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“…One reason for this could be the lack of a unified definition of “Big Data”. In the 38 publications in PubMed Nursing Journals (identified using the PubMed Nursing Journals full text keyword search function and the keyword “Big Data”; a full list of the 38 publications can be found in Appendix Table A1), scholars in nursing have adopted very different definitions of Big Data [14,15,16], while some made no attempts to define the term before using it [17,18]. Among the 38 publications related to Big Data in PubMed Nursing Journals, 22 explicitly defined Big Data.…”

Section: The Challenge Of Big Data To Scholars In Nursingmentioning

confidence: 99%

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness

Wong

Chiang

Choi

et al. 2016

IJERPH

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The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term “Big Data”, which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.

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A systems science approach to fatigue management in research and health care

Cited by 18 publications

References 33 publications

Associations of occupational stress, workplace violence, and organizational support on chronic fatigue syndrome among nurses

Associations of occupational stress, workplace violence, and organizational support on chronic fatigue syndrome among nurses

Understanding the impact of the physical health care environment on nurse fatigue

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness

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