HYBRID EVENT: You can participate in person at Boston, Massachusetts, USA or Virtually from your home or work.

7th Edition of Nursing World Conference

October 16-18, 2023 | Boston, Massachusetts, USA

October 16 -18, 2023 | Boston, Massachusetts, USA
NWC 2023

Huiling Hu

Speaker at  Nursing World Conference 2023 - Huiling Hu
Peking University, China
Title : Effects of different types of interference on nurses' working memory: An ERP study

Abstract:

Objectives
To explore the effects of different types of interference on nurses’ working memory, and evaluate how attention control moderates the effects of interference on nurses’ working memory.
Methods
A delayed recognition paradigm with a single factor in different four levels was adopted. Participants completed four blocks: Interrupting Stimulus (stimuli requiring attention), Distracting Stimulus (stimuli to-be-ignored), No Interference and Passively View. Each block consisted of three stages: Cue, Interference and Probe. Participants were instructed to make a match/nonmatch button press response of the nursing information system before and after the interference stage as quickly and accurately as possible. Behavioral responses of the participants were recorded. At the same time, Neuroscan was used to collect EEG data, specifically the indexes of P100 and N170 components. MATLAB 21b and EEGLAB 21b were used for EEG data preprocessing and data extraction. 
Results
Firstly, when nursing information system was used as task material, interruption and distraction had different effects on nurses’ working memory. The accuracy rate and false alarm rate of tasks under interruption interference was significantly different with that of distraction interference and no interference condition (P < 0.001). The average amplitude of N170 component under interruption interference is significantly more negative than that under distraction interference and passively view (all Ps < 0.05). There is a significant difference in ERP measurement between correct response and wrong response under interruption interference. Secondly, regulatory mechanisms for interruption and distraction were different. For P100 component, there was a significant positive correlation between the average amplitude distraction attention control index and task accuracy (r = 0.405, P = 0.029), and there was a significant negative correlation between the latency interruption attention control index of P100 component and the accuracy of working memory task (r = -0.339, P = 0.036). Finally, those who can best deal with distraction were also those who can better deal with interruption.
Conclusions
When using the nursing information system, there were different effects of interruptions and distractions on nurses’ working memory and the moderate mechanisms of attention control were also different. Attention control regulated the effect of distraction on working memory mainly through goal enhancement, and regulated the effect of interruption on working memory through adjusting the time of the target task resumption. Therefore, a series of measures and intervention can be designed according to these results to reduce the negative impact of interference on nurses, so as to improve work efficiency and reduce patient risk.

Audience Take away Notes:

  • The use of EEG/ERP in nursing research.
  •  Interruption has a negative impact on nurses, while distraction has a weak positive impact.
  • Interruption will lead to the redistribution of attention resources; Attention control regulates the impact on performance by adjusting the goal task recovery speed after interruption.
  • In the distracted environment, individuals will actively suppress the distraction and enhance the target information; The degree of target information enhancement is related to working performance.
  • Interventions should be designed to reduce the time needed for nurses to extract task information after an interruption, such as providing key clues in the information system interface.

Biography:

Huiling Hu is a PhD student studying Nursing at the Peking University, China and graduated as MS in 2022. She is passionate about the design and optimization of nursing information systems interfaces, particularly in improving nursing staff's work efficiency, enhancing patient care experience, and reducing errors by EEG and eye-tracking tools. She has published 5 articles in SCI journals as the first/co-first author.

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