Analysis of the Impact of Johnson's Behavioral Model on Anxiety of Mothers of Children with Cancer

Background: Nowadays, cancer is one of the most critical health problems. The present study aimed to investigate the impact of the Johnson Behavioral Model on the anxiety of mothers of children with cancer. Methods: This empirical study was done on 66 mothers of children with cancer in the centers covered by children with cancer in 2020. The samples were selected using simple random sampling. Data were collected using the Spielberger demographic and anxiety inventory. After data collection, data analysis was done in SPSS18 using descriptive statistics and independent t-test, paired t-test, chi-square test, fisher, and covariance test. The significant level was set at 0.05. Results: The anxiety level was equal to 112.39±18.22 and 111±20.07 before intervention and equal to 81.21±6012 and 108.42±18.37 after the intervention in the intervention and control group, respectively. The independent t-test showed no significant difference between the two groups before the intervention (Pvalue=0.769). However, the difference was significant after the intervention (Pvalue<0.01). The paired t-test showed a significant difference between the two groups before and after the intervention in the intervention (Pvalue=0.001) and control (Pvalue<0.001) groups. Conclusions: The results obtained from this study showed that the Johnson theory plays a key role in reducing the anxiety of mothers of children with cancer. Keywords: Johnson Behavioral Model, Anxiety, Mothers of children, Cance

Can we Use the “Script Concordance” Test As a Valid Alternative Method to Evaluate Clinical Reasoning Skills in Nursing Students?

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Analysis of the Impact of Johnson's Behavioral Model on Anxiety of Mothers of Children with Cancer: Analysis of the Impact of Johnson's Behavioral Model on Anxiety of Mothers of Children with Cancer

Background: Nowadays, cancer is one of the most critical health problems. The present study aimed to investigate the impact of the Johnson Behavioral Model on the anxiety of mothers of children with cancer. Methods: This empirical study was done on 66 mothers of children with cancer in the centers covered by children with cancer in 2020. The samples were selected using simple random sampling. Data were collected using the Spielberger demographic and anxiety inventory. After data collection, data analysis was done in SPSS18 using descriptive statistics and independent t-test, paired t-test, chi-square test, fisher, and covariance test. The significant level was set at 0.05. Results: The anxiety level was equal to 112.39±18.22 and 111±20.07 before intervention and equal to 81.21±6012 and 108.42±18.37 after the intervention in the intervention and control group, respectively. The independent t-test showed no significant difference between the two groups before the intervention (Pvalue=0.769). However, the difference was significant after the intervention (Pvalue<0.01). The paired t-test showed a significant difference between the two groups before and after the intervention in the intervention (Pvalue=0.001) and control (Pvalue<0.001) groups. Conclusions: The results obtained from this study showed that the Johnson theory plays a key role in reducing the anxiety of mothers of children with cancer. Keywords: Johnson Behavioral Model, Anxiety, Mothers of children, Cance

Mixed convection heat transfer and pressure drop characteristics of the copper oxide-heat transfer oil (CuO-HTO) nanofluid in vertical tube

In this paper, the mixed natural-forced convection is experimentally investigated for the heat transfer oil-copper oxide (HTO-CuO) nanofluid flow upward in a vertical tube. The flow regime is laminar and the temperature of the tube surface is constant. The effect of the nanoparticles concentration on the heat transfer rate and the pressure drop is studied as Richardson number varies between 0.1 and 0.7. It is observed that the mixed convection heat transfer rate increases with both the nanoparticles concentration and Richardson number. New correlations are proposed to predict the Nusselt number of the nanofluid flow with the reasonable accuracy. As the heat transfer enhancement methods usually accompany with increment in the pressure drop, the figure of merit is evaluated experimentally. As such the maximum figure of merit of 1.31 is achieved using the 1.5% concentration of the nanoparticles in Richardson number of 0.7. This study provides a platform to design next generation of low flow rate nanofluid-based heat exchangers and may improve the accuracy of predicting the mixed convection characteristics of nanofluid flows