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Nurses’ Perception and Cognition of Electrocardiogram Monitoring Alarms

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Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) (IEA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 818))

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Abstract

In this study, nurses’ perception and cognition of electrocardiogram (ECG) monitoring alarms were investigated in relation to their competence and experience of incidents or accidents related to ECGs. Questionnaires were given to 300 nurses who used ECG monitors at a hospital. Relationships between personal attributes and scores on questions about the perception and cognition of alarms were analyzed.

Analysis of variance was performed to determine the tendency of perception and cognition scores among nurses on the clinical ladders I, II and ≧III and pre-acquisition nurses. The group on Ladder I was the most sensitive to the ECG’s alarm (p < .05). The group ≧III was more observant than the other groups, not only to the sound of the alarm, but also the waveform of the ECG (p < .01). The pre-acquisition group thought that if they responded to an alarm, it would affect the work of other groups. Furthermore, they were unable to concentrate on other work if disturbed by the alarm (p < .05). Subsequently, t test was conducted to examine the tendency of scores score based on experience of accidents or incidents related to ECG. The results showed that the experienced group had more confidence in alarms than the non-experienced group (p < .01). On the other hand, the experienced group believed felt that if alarm frequencies were high, and they could not concentrate on other work and this would have an adverse effect on their performance (p < .05).

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References

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Correspondence to Yasuyo Kasahara .

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Kasahara, Y. (2019). Nurses’ Perception and Cognition of Electrocardiogram Monitoring Alarms. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 818. Springer, Cham. https://doi.org/10.1007/978-3-319-96098-2_89

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