Sleep quality, but not quantity, is associated with self-perceived minor error rates among emergency department nurses

Weaver, Amy L.; Stutzman, Sonja E.; Supnet, Charlene; Olson, DaiWai M.

doi:10.1016/j.ienj.2015.08.003

Cited by 34 publications

(46 citation statements)

References 36 publications

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“…In our study, nurses were mostly affected by less than optimal sleep duration, whereas time to fall asleep and night‐time waking duration were not greatly affected. The mean sleep latency and night‐time waking duration values in our study were lower than those reported previously; for example, it was 26.8 min in Chien et al's () study and 18.6 min in Weaver et al's () study. The mean sleep duration was slightly shorter than that reported by Hazzard et al () who also used sleep diaries (6.21 vs 6.40).…”

Section: Discussioncontrasting

confidence: 89%

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Sleep disturbances and related factors among nurses

Chaiard

Deeluea

Suksatit

et al. 2019

Nursing & Health Sciences

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The aim of this study was to describe patterns and potential risk factors for sleep disturbances, including that of sleep apnea, among Thai registered nurses. A descriptive, cross-sectional design was implemented. A sample of 233 registered nurses was recruited from 10 nursing departments from a tertiary hospital. Participants completed a one-time, self-report questionnaire and a 1 week-long sleep diary. Descriptive and logistic regression statistics were used for the analysis. Approximately 76% of nurses slept less than 7 h, 12.3% had difficulty initiating sleep, and 5% had difficulty maintaining sleep. Short sleep duration was prevalent, and night shift work schedules that exceeded 10 episodes/month were perceived as contributing to difficulties with initiating sleep. After excluding males from the analysis, the risk for depression related to short sleep duration becomes statistically significant. Organizational policies for registered nurses' shift work should include effective management of night shift assignments, as well as interventional strategies and policy directions, to promote sleep quality and mental health to ensure nurse well-being and patient safety. K E Y W O R D S nurse, shift schedule, short sleep, sleep apnea, sleep disturbances

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Section: Discussioncontrasting

confidence: 89%

“…Bjorvatn et al () reported the frequency of difficulty falling asleep as “mostly” or “always” among intensive care nurses. In other studies, nurses reported averaging 4.30–6.67 h of sleep per night, which is below the optimum value (Hazzard et al, ; Ramadan & Al‐Saleh, ; Weaver, Stutzman, Supnet, & Olson, ).…”

Section: Introductionmentioning

confidence: 79%

Sleep disturbances and related factors among nurses

Chaiard

Deeluea

Suksatit

et al. 2019

Nursing & Health Sciences

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“…'s () survey study among Australian nurses completing 30‐day diaries indicated that struggling to stay awake was the main predictor of patient‐related errors. A recent study on sleep quality using actigraphy in 30 emergency room nurses indicated that 73% of the participants had poor sleep quality (Weaver, Stutzman, Supnet, & Olson, ). In this study, sleep quality was associated with higher self‐perceived minor errors, although the total number of hours slept was not associated with any kind of error.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

The impact of long work hours and shift work on cognitive errors in nurses

Rhéaume

Mullen

2017

J Nurs Manag

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“…In the past decade, many studies have documented the negative impacts from shift work on biological homeostasis and circadian rhythm, which can in turn lead to sleep disturbances (Boivin & Boudreau, ; Nea et al, ). Sleep disturbances can trigger the stress response, with subsequent activation of inflammatory pathways, and can result in adverse health outcomes and behavioural problems (Irwin, Olmstead, & Carroll, ), and increased risk of sleepiness‐related accidents and injuries in the workplace (Fafrowicz et al, ; Weaver, Stutzman, Supnet, & Olson, ).…”

Section: Introductionmentioning

confidence: 99%

A prediction model of sleep disturbances among female nurses by using the BP‐ANN

et al. 2019

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Aim To describe sleep disturbances and fatigue among female registered nurses in Beijing and to develop a prediction model for sleep disturbances. Background Chinese nurses are required to work rotating shifts on a weekly basis, which could negatively impact their sleep and well‐being. Method A total of 647 registered nurses participated in this study. Self‐reported sleep‐related data and selected physiological data were collected. Back propagation artificial neural networks was used to develop the prediction model by using the risk management and population health framework. Results Majority of them reported clinically significant poor sleep (69.4%) and fatigue (75.4%). A total of eight predictors were identified for sleep disturbances, and the top four normalized importance predictors are morning fatigue (100%), body mass index (30.5%), gastrointestinal symptoms (17.6%) and drinking caffeinated beverages at work (17.3%). The cross‐entropy error was 206.58, and the model accounted for 77.6% of the variance in sleep disturbances. Conclusions and implications for nursing management Female registered nurses in China experience clinically significant sleep disturbances. Morning fatigue severity along with seven significant influencing factors may be used to identify shift nurses who face a higher risk of sleep disturbances. The back propagation artificial neural networks model could be used as the foundation for health promotion interventions for registered nurses.

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Sleep quality, but not quantity, is associated with self-perceived minor error rates among emergency department nurses

Cited by 34 publications

References 36 publications

Sleep disturbances and related factors among nurses

Sleep disturbances and related factors among nurses

The impact of long work hours and shift work on cognitive errors in nurses

A prediction model of sleep disturbances among female nurses by using the BP‐ANN

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