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The Application of Artificial Neural Network in Evaluating the Relationship between Nurses' Empathy, Accountability and Responsibility with Patient Relaxation in Emergency Wards
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Alireza Mosavi *   , Jamaleddin Alvani |
| Professor, Islamic azad university - - Department of management , alimosavi1396468@yahoo.com |
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Abstract: (3824 Views) |
Background and aim: Facing difficult situations have happened to all of us. One of these difficult situations is being informed about having a specific disease which can be extremely shocking and as a result, may cause mental illnesses. The purpose of this study was to investigate the effect of artificial neural network on the effect of nurses 'empathy, responsiveness and responsibility on the patients' sense of hospitalization in emergency wards.
Methods: This descriptive-correlational study was conducted in January 2020. The statistical population included the patients in the emergency wards of Namazi Hospital of Shiraz. The sample size was calculated using 195 Cochran formula. Samples were selected using available random sampling method. The tool used in this study was a standard questionnaire with a confirmed validity and reliability. Also, the artificial neural networks have been used for data analysis.
Results: The mean scores of patients' evaluation of nurses' empathy were 4.42 out of 5, responsibility was 4.48, responsiveness was 4.44 and patients' sense of calm was 4.52. The normalized significance level of the independent variables on the dependent variable according to the ANN spend was calculated as: Empathy 100, Accountability 68.6 and Accountability 59.5.
Conclusion: In the hospital environment, different behaviors of nurses can have a great impact on the morale of frustrated patients. By creating a sense of empathy in patients with proper and timely responsiveness and good accountability (quality of services), respected nurses can develop a sense of comfort in their patients. |
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| Keywords: Artificial Neural Networks, Empathy, Accountability, Responsibility, Patient Relaxation, Quality of Services |
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Full-Text [PDF 692 kb]
(724 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2019/11/11 | Accepted: 2020/01/27 | Published: 2020/02/18
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