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Showing 3 results for Support
Hospital support measures from the perspective of infectious and non-infectious nurses caring for patients with COVID-19
Somayeh Fazaeli, Mahdi Yousefi, Ali Khorsand Vakilzaeh, Zahra Ebrahimi,
Volume 7, Issue 1 (5-2021)
Abstract
Aim: As the functions of hospitals change during COVID-19 outbreak and due to lack of nurses’ experience, the development and implementation of special support programs in this regard seems necessary. The present study intended to assess the experienced nurses’ viewpoints in infectious and non-infectious wards regarding hospital support measures.
Methods: This cross-sectional descriptive study was performed in IMAMREZA hospital in Mashhad. All together 230nurses caring for COVID-19 patients working in infectious (group 1) and non-infectious (group 2) wards were selected through stratified random sampling. The research tool was a researcher-made questionnaire whose validity and reliability were examined and confirmed. The Data were analyzed by SPSS with Chi-square and Pearson correlation coefficients.
Results: From the nurses' viewpoint, the highest satisfaction score was related to the reorganization of the hospital and the allocation of new ward (87.8%). The lowest was related to providing suitable accommodation for the medical staff (26.4%). Statistically significant differences were observed between the level of satisfaction with supportive measures in groups 1 and 2 in the areas related to education and information(P-Value=0.014), training on safety and care of coronary patients(P-Value=0.017) Possibility of receiving counseling and screening and timely dispatch of manpower(P-Value=0.018), supply and timely dispatch of manpower in the ward(P-Value=0.002) and reorganization of the hospital in accordance with the crisis (P-Value=0.002).
Conclusion: Considering the viewpoints of infectious and non-infectious nurses about the same supportive measures taken by the hospitals, managers' attention to the needs of hospitals’ nursing groups, especially during the crisis time, is suggested to increase job satisfaction.

Relationship Between Turnover Intention and Perceived Organizational Support in Nurses of Hospitals in Gorgan, Iran
Alireza Heidari, Sakine Beygom Kazemi, Mohammad Javad Kabir, Zahra Khatirnamani, Abbas Badakhshan, Mansoureh Lotfi, Sajad Moeini, Ameneh Kamal Gharibi, Abdi Kor,
Volume 9, Issue 3 (10-2023)
Abstract
Objective High perceived organizational support can make employees feel that they belong to the organization and have less intention to leave their jobs. This study aims to determine the relationship between turnover intention and perceived organizational support in nurses working in hospitals in Gorgan, Iran.
Methods This cross-sectional study was conducted in 2021 on 293 nurses from 16 hospitals affiliated to Golestan University of Medical Sciences who were selected by stratified sampling method, proportional to the population. The data collection tool was a three-part questionnaire including demographic/occupational form, Kim et al.’s turnover intention questionnaire (TIQ), and Eisenberger et al.’s Perceived Organizational Support Questionnaire (POSQ). The data were analyzed using SPSS software, version 16. 
Results The mean scores of TIQ was 39.91±12.18 and the mean score of POSQ was 23.66±6.6. There was a negative significant relationship between turnover intention and perceived organizational support (P<0.001).
Conclusion The turnover intention and perceived organizational support of nurses in Gorgan are at a moderate level. As the nurses’ perceptions of organizational support decrease, their turnover intention can increase. It is necessary to create a supportive environment for nurses, in such a way that this support be tangible and understandable to them and can cause job satisfaction and prevent them from leaving the job.

An Explainable Algorithm for Survival Prediction in Gastric Cancer Patients
Ms Leila Alaei, Dr Ali Broumandnia, Dr Amin Golabpour, Dr Sina Dami,
Volume 10, Issue 5 (12-2024)
Abstract

Introduction: One of the main causes of cancer-related mortality globally is gastric cancer, which is more common in developing nations.  Physicians can make better clinical decisions and plan treatments if they can accurately forecast the survival time of patients with stomach cancer.
Methods: This retrospective study was conducted on data from 384 patients diagnosed with gastric cancer over a 20-year period. To predict survival time, a Support Vector Regression (SVR) model with an RBF kernel was applied. SVR was selected due to its strong capability in modeling complex nonlinear relationships in continuous data. To enhance the interpretability of the results, the LIME algorithm was employed to analyze the influence of individual variables. Model performance was evaluated using the C-index, mean absolute error (MAE), and mean squared error (MSE).
Results: The SVR model achieved a C-index of 0.87, MAE of 45.3 days, and MSE of 56.7. LIME analysis showed that while addiction, family history of gastric cancer, and cause of death had negative effects on survival prediction, factors like combination therapy, adenocarcinoma histology, education level, and age at diagnosis had a substantial beneficial impact.
Conclusion: A dependable and understandable model for forecasting survival time in patients with stomach cancer was made possible by the combination of SVR and LIME.The model's interpretability makes it appropriate for clinical settings, where decision-making procedures require openness and trust


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