مجله اطلاع رسانی پزشکی نوین
سال هفتم شماره 1 (پیاپی 15، بهار 1400)

Due to the development of the Internet, banks are rapidly moving towards providing an online banking platform for their customers. One of the most widely used aspects of such platforms is the use of mobile banking. The aim of the present study was to determine the factors affecting the acceptance of mobile banking based on Social Cognitive Theory by Bank Mellat customers in Bandar Abbas.

This descriptive study was conducted from March 2016 to August 2017 on the customers of 15 branches of Bank Mellat in Bandar Abbas. The required number of samples was estimated to be 384 who were selected using the convenience sampling method. A researcher-made questionnaire was used to collect the data, which was then analyzed using SPSS 22 and Smart PLS 2 statistical softwares.

Social features, trust, ease of use and online customer services had a significant effect on customerschr('39') intentions to adopt mobile banking with t-value of 4/71, 7/24, 9/05 and 4/31 respectively. However, compatibility with lifestyle did not have a significant relationship with the customerschr('39') intentions to adopt mobile banking (t-value =1/78).

Mobile-banking is utilized willingly by Mellat Bank Customers in Bandar Abbas and is influenced by social features, trust, ease of use and online customer services.

Childbirth, as women’s most special experience, is associated with negative understandings of mothers, which would be a reason for increasing the rate of cesarean section. Role training is a new educational method that facilitates the visualization of childbirth. The present study was conducted to determine the effect of role-playing training on the expectation of childbirth experience of primiparous pregnant women in Ilam.

In this quasi-experimental study that was conducted in 2019, 82 mothers who met the criteria were randomly divided into intervention (n = 41) and control (n = 41) groups in comprehensive health centers of Ilam. The training in the intervention group was provided in a role-playing manner during three 40-minute plays. The control group received routine prenatal care. Evaluation of the expectation of delivery experience before the intervention, immediately after the last intervention session, and also one week after delivery, was performed with the Vijma Waiting Experience Examination Questionnaire (WDE-Q) in two groups. Data analysis was performed using SPSS software and an independent t-test, and one-way analysis of variance.

Comparison of scores for the two groups before and immediately after the intervention (P <0.001) and also after delivery and before the intervention (P = 0.001) were significant. The reduction of expectation scores of delivery experience in the intervention group was significantly greater than the control group.
 

Applying the role-playing training method led to improving the delivery experience. This method can be used during pregnancy to encourage mothers and reduce their stress from childbirth.

Education and technology are the key indicators that should be taken into account during the infectious pandemic of human society with Covid-19. Preventing scientific and educational gaps requires recognition of the present problems, modifying necessary conditions and improving the quality of education, which lead to the durability and consistency of the countrychr('39')s scientific strength.

The present study was a cross-sectional quantitative research in terms of applied purpose, descriptive method and the nature of the data.  The statistical sample consisted of 10 professors familiar with virtual education with at least ten years of experience in Hormozgan University of Medical Sciences. They were selected through purposeful sampling in the form of snowballs. A DANP-based questionnaire was used to collect the data. The incompatibility rate of the questionnaires was 0.03 and their reliability was confirmed. The collected data were analyzed by Excel software.

The results revealed that the most effective factors of improving the quality of virtual education in Hormozgan University of Medical Sciences are activists of electronic knowledge and skills with a weight of 0.12, organizational support with a weight of 0.105, and infrastructure and system quality with a weight of 0.103.

Organizational factors, education and technology are more important than individual factors. Therefore, managers’ and decision-makers’ efforts in this area can play a significant role to achieve the desired goals.

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.

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.

From the nurseschr('39') 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).

Considering the viewpoints of infectious and non-infectious nurses about the same supportive measures taken by the hospitals, managerschr('39') attention to the needs of hospitals’ nursing groups, especially during the crisis time, is suggested to increase job satisfaction.

Managing stress and proper communication with clients is a key element in patient-care. Study stress is very common among nursing students during Covid-19 crisis and has weakened traineeschr('39') relationship with patients. The aim of this study was to develop stress management training and communication skills of nursing students during Covid-19 crisis based on augmented reality.

In this quasi-experimental study, 46 nursing students undergoing internship at Farabi Hospital in Bastak in 2020 were randomly divided into experimental and control groups. The experimental group participants received augmented reality-based education, and in the control group, education was conducted in the traditional way. The effectiveness of the training was assessed with a researcher-made questionnaire and the data were analyzed using SPSS software and independent t-test.

Augmented reality training was more effective than traditional training and independent t-test showed a significant difference between the experimental and control groups (P-Value=0.001). The mean scores of communication skills factors and stress management factors increased in the post-test compared to the pre-test. The mean scores of behavioral stress management, positive thinking, time management and relaxation techniques also increased in the post test.

Training of stress management and communication skills to nursing students based on augmented reality can improve learning and increase the effectiveness of training in a stressful hospital environment, especially during COVID-19 conditions.

Awareness of the nature of the field of study makes students act purposefully along the path of education and anticipate career prospects. This study aimed to investigate the knowledge and attitude of health information technology students towards their field of study and career prospects at Hormozgan University of Medical Sciences.

This was an applied descriptive-analytical study in 2018. All the 68 Health Information Technology undergraduate students whose entrance date was 2015-2018 were interviewed. A valid and reliable researcher-made questionnaire was used with Likert scale to record studentschr('39') opinions in four areas of knowledge and attitude towards the field of study, knowledge and attitude towards the career prospects. The data were analyzed using SPSS26 with descriptive/analytical statistics such as Independent T-Test and ANOVA.

In the four areas, the highest score was related to attitude towards career prospects and the lowest was related to knowledge of the field of study. Considering the variables of knowledge and attitude towards the field of study and career prospects based on demographic variables, there was a significant relationship between diploma mean grade and the knowledge about the field of study (p-value= 0.039). There was also a significant correlation between knowledge and attitude towards the field of study with a correlation coefficient of 0.657(p-value<0.001).

With the significant relationship between knowledge and attitude, acquiring the right knowledge based on actual capabilities of the field can improve the students’ level of attitude.

The world has recently faced COVID-19 pandemic. Phobia or panic has been considered as one of the most common mental disorders during various infectious pandemics. Therefore, the present study aimed to determine the psychometric properties of the Covid-19 phobic scale in an Iranian population.

The present study was a descriptive cross-sectional correlational research which was performed on 402 Iranian participants in Tehran (191 females, 211 males). The participants were selected through convenience sampling method by an online survey form. They completed a battery of scales, including the Corona Anxiety Scale (CDAS), the Corona Phobia Scale (C19P-S) and the Corona Virus Anxiety Scale by online Google Form. The data were analyzed using SPSS-25 and LISREL software with descriptive statistics, Cronbachchr('39')s alpha, Pearson correlation coefficient, and confirmatory factor analysis to describe the data, internal consistency, validity, and construct validity, respectively.

The results showed that Cronbachchr('39')s alpha methodchr('39')s internal consistency for the Corona phobia scale was 0.91. Cronbachchr('39')s alpha was reported for psychological, psychosomatic, economic, and social subscales repeated 0.85, 0.83, 0.79 and 0.8, respectively. In order to evaluate the validity, the correlation between the C19P-S questionnaire and its subscales with CDAS and Corona Virus Anxiety Scale was evaluated. The results showed that all correlations were positive and significant (P-value <0.05). The confirmatory factor analysis (CFA) results showed that the four-factor model has a good fit.

COVID-19 Phobia Scale can be used to assess levels of panic in therapeutic settings and identify candidates in need of clinical intervention.

Accurate and timely diagnosis of COVID-19 using artificial intelligence and machine learning technologies will play an important role in improving the disease indicators, optimal utilization of limited hospital resources and reducing the burden on pandemic healthcare providers. Therefore, this study aimed to evaluate the efficiency of selected data mining algorithms based on their performance for COVID-19 diagnosis.

The present study was a retrospective applied-descriptive study that was conducted in 2020. In this study, the data of patients admitted with a definitive diagnosis of Covid-19 from March 17, 2020 to December 10, 2020 were extracted from the Electronic Medical Record (EMR) database in Ayatollah Taleghani Hospital in Abadan. After applying the inclusion and exclusion criteria to identify the samples, 400 records were entered into the data mining software. The data were compared using chi-square criterion to determine the variables of teach algorithms and their performance based on different evaluation criteria in the turbulence matrix.

Comparing the performance from data mining algorithms based on different evaluation criteria in the turbulence matrix revealed that the J-48 algorithm with the sensitivity, precision, and Matthews Correlation Coefficient (MCC) of 0.85, 0.85 and 0.68 respectively had better performance than the other data mining algorithms for the disease diagnosis. The 3 variables of lung lesion existence, fever, and history of contact with suspected COVID-19 patients, by considering Gini Index to determine the point of division, with Gini index of 0.217, 0.205 and 0.188 respectively were considered as the most important diagnostic indicators of COVID-19.

Using selected data mining methods, particularly J-48 algorithm will greatly aid the timely and effective diagnosis of COVID-19 in the form of clinical decision support systems.