Paperdoi:10.1177/01939459241236631

Examining the Relationship Between Nurse Fatigue, Alertness, and Medication Errors

Venue listed2024Added Nov 9, 2026

  • AA

Authors: Amany Farag et al. (3 authors)

Western Journal of Nursing Research 46(4):288–295

TL;DR

90 hospital nurses wore Readiband and answered EMA fatigue prompts. Device-derived alertness did not predict self-reported medication errors; EMA-reported fatigue did (OR 1.26). Alertness fell ~31 points on night shifts.

Abstract

Background:

Working for extended hours in a physically and mentally demanding profession has subjected nurses to occupational fatigue. Limited evidence exists about nurse fatigue and alertness changes throughout shift work and their relationship with medication errors and near misses.

Purpose:

The purposes of this study were to: (1) assess the relationship between nurses’ fatigue and alertness, (2) evaluate nurses’ fatigue and alertness changes throughout their shift, and (3) examine the relationship between nurses’ fatigue, alertness, and medication errors and near misses.

Methods:

This prospective study is part of a larger mixed-method study. Fatigue and alertness data from 14 work and non-workdays were collected from a convenience sample of 90 nurses. A wearable actigraph (Readiband TM ) was used to measure alertness, while ecological momentary assessment (EMA) using text messaging was used to measure nurses’ fatigue.

Results:

A 1-unit increase in fatigue was associated with a 1.06-unit reduction in nurses’ alertness score (β = –1.06, 95% CI: [–1.33, –0.78], p Conclusion:

Initiating fatigue mitigation measures during mid-shift, especially for night-shift nurses, may be a viable option to mitigate fatigue and alertness deterioration among nurses and to maintain patient safety. The multifaceted nature of fatigue, as captured by EMA, is a stronger predictor of medication errors and near misses than device-measured alertness.

Verbatim from the publisher's DOI record (opens in a new tab) · Publisher licence: https://journals.sagepub.com/page/policies/text-and-data-mining-license

Results on ChatPPG leaderboards

All leaderboards

No results from this paper on ChatPPG leaderboards yet. Browse the leaderboards.

Tasks & signals

Tasks

Stress

Signals

Keywords

FatigueReadibandSAFTENursesHealthcareMedication Errors

How it works

How Method works: Setup → Method → TargetSetup: Signals (ACC (Readiband), EMA). Method: Method. Target: Stress.SetupSignals: ACC (Readiband), EMAxyzSignalsACC (Readiband), EMAMethodMethodTargetStressStress

Cite this paper

Cite this paper with the fields recorded here. Check it against the publisher before submitting.

Farag, A., et al. (2024). Examining the Relationship Between Nurse Fatigue, Alertness, and Medication Errors. Western Journal of Nursing Research, 46(4), 288–295. https://doi.org/10.1177/01939459241236631
Farag, Amany, et al. 2024. "Examining the Relationship Between Nurse Fatigue, Alertness, and Medication Errors." Western Journal of Nursing Research 46 (4): 288–295. https://doi.org/10.1177/01939459241236631.
Farag, A. et al. (2024) 'Examining the Relationship Between Nurse Fatigue, Alertness, and Medication Errors', Western Journal of Nursing Research, 46(4), pp. 288–295. doi: 10.1177/01939459241236631.
Farag, Amany, et al. "Examining the Relationship Between Nurse Fatigue, Alertness, and Medication Errors." Western Journal of Nursing Research, vol. 46, no. 4, 2024, pp. 288–295. https://doi.org/10.1177/01939459241236631.
A. Farag et al., "Examining the Relationship Between Nurse Fatigue, Alertness, and Medication Errors," Western Journal of Nursing Research, vol. 46, no. 4, pp. 288–295, 2024, doi: 10.1177/01939459241236631.
@article{farag2024examining,
  title         = {{Examining the Relationship Between Nurse Fatigue, Alertness, and Medication Errors}},
  author        = {Farag, Amany and others},
  year          = {2024},
  journal       = {Western Journal of Nursing Research},
  volume        = {46},
  number        = {4},
  pages         = {288--295},
  doi           = {10.1177/01939459241236631}
}

Added to the ChatPPG research hub