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Ali Mohammadzadeh, Majid Vahedi, Karim Ghorbani, Esa Jafari,
Volume 15, Issue 1 (6-2016)
Abstract

Background: Given that Tabriz Shohada hospital is the place of admitting emergency patients including accident victims, Nurses are exposed to double stress at hospital. This study conducted to predict nursing stress based on personality traits and job engagement among nurses in Shohada hospital of Tabriz.

Materials and Methods: The current study was a correlational one. Randomly selected 105 nurses from Tabriz Shohada hospital sections such as sixth general sections including Rehabilitation, ICU & Emergency Department participated. Contributors answered to Nursing Stress Scale, Eysenck Personality Questionnaire Revised (EPQ-R) and Job Engagement Scale. Data were analyzed using stepwise multiple regression analysis.

Results: The study results indicated that nursing stress was more strongly associated with the neuroticism; there were no relationships among nursing stress and extraversion or psychoticism. Also, nursing stress revealed a positive relationship with job engagement. Using the multivariate regression analysis showed that the neuroticism trait (p< 0.001, F=10.68) and job engagement (p= 0.004, F=10.12) were suitable predictors for nursing stress among three personality factors and job engagement.

Conclusions: Nursing stress influenced by internal factors more than demographic variables and two important predictive variables (neuroticism trait and job engagement) had more important roles in nursing stress prediction.


Neda Vahedi Nezhad, Farzad Firouzi Jahantigh,
Volume 20, Issue 1 (5-2021)
Abstract

Introduction and purpose: Risk assessment is a necessity in high-risk work environments like hospitals. During epidemics, the need to maintain the health of healthcare staff increases as they are effective people in controlling the spread of the disease. The purpose of this study was to assess the occupational safety of healthcare staff against coronavirus using FMEA in infectious diseases ward of Bu-Ali Hospital in Zahedan.
Methodology: Failure modes were identified using brainstorming technique. After scoring them with S, O and D, they were prioritized by calculated RPN. To improve the traditional FMEA, failure modes were prioritized with weighted FMEA and MCDM techniques. After identifying the critical failure modes, the root causes of them were identified and categorized.  Finally, corrective solutions were provided to handle them.
Results: Three processes including emergency admission, patient visit, and sampling were identified as priority processes. 58 failure modes and their effects were identified in 6 categories. 13 critical failures modes (RPN above 100) equivalent to 22% were identified. Then 42 root causes of them were identified by brainstorming technique and their classifications were done by Eindhoven. Finally, 49 corrective strategies were presented to handle critical risks.
Conclusion: Identifying 58 risks and their effects, identifying and classifying root causes and providing corrective solutions indicate the capability of the FMEA to assess the risk of critical departments such as hospitals. As a result, the FMEA is able to detect risks, reduce their consequences and improve quality. Risk assessment techniques along with the commitment of managers and the renewal of organizational policies can ensure the effectiveness of these activities.


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