مجله اطلاع رسانی پزشکی نوین
سال هشتم شماره 2 (پیاپی 20، تابستان 1401)

Information systems are used in healthcare centers of Iran for more than three decades, but the successful cases of these systems are usually low. This study aims to determine the success and failure factors of the integrated health system (SIB) from the perspective of the users of this system in comprehensive health care centers of Torbat Heydariyeh, Iran.

This is a descriptive-analytical study that was conducted in 2017. The study population consist of all users of the SIB system in the comprehensive health care centers in Torbat Heydariyeh county. Of these, 100 were selected using random and convenience sampling methods. The data were collected by a questionnaire. The, they were analyzed in SPSS v. 18 software.

The highest mean scores of success factors were related to economic (2.1±98.25), political (2.97±0.91) and ethical (2.91±0.91) factors, respectively, while the lowest mean scores were related to cultural (2.43±0.61), organizational (2.52±0.57) and educational factors (2.59±0.68).

The most important factor for the SIB system’s success is economic factor or cost-effectiveness. Appropriate policy making for the implementation and use of such systems is of particular importance.

Teaching health information seeking skills to pregnant women can improve their health knowledge, self-care ability, and preventive behaviors. This study aims to survey the health information seeking behaviors of pregnant women referred to health centers in Bushehr, Iran. 

This descriptive-analytical study with cross-sectional design was conducted in 2020 on 306 pregnant women referred to health centers in Bushehr, Iran who were selected using stratified random sampling method. Data were collected using a Health Information seeking Behavior Questionnaire and analyzed in SPSS v. 24 software using Chi-square test and Fisher’s exact test.

The findings showed that 25% of pregnant women had favorable health information seeking behavior, and 75% had unfavorable information seeking behavior. There was a significant relationship between the educational level of pregnant women and their health information seeking behaviors (P=0.04). The rate of unfavorable information seeking behavior in women with no history of abortion was 72.1%; in women with a history of abortion, it was 77%; and in women with a history of more than one abortion was 93.3% (P=0.039).

The most of pregnant women in Bushehr has unfavorable health information seeking behaviors. Since inappropriate information-seeking behavior leads to incorrect information or lack of access to information, it is recommended to teach information seeking skills and consequently empower pregnant women to seek health information.

Due to the large amount of data for people with diabetes, it is very difficult to extract the predictors of diabetes. Data mining science can discover the predictors of diseases and help physicians and medical staff in predicting and diagnosing diseases.

This is an applied survey study conducted in 2020 using the dataset used by Mirsharif et al. The study population includes 105 cases with data registered from 2011 to 2014 in a specialized women’s medical center in Tehran, of which 80 were for healthy women and 25 were for women with gestational diabetes. MATLAB software was used to analyze and evaluate the results.

The results and comparisons showed the high efficiency of the proposed method in predicting gestational diabetes. The accuracy of the proposed method was 93%, which was more accurate than the method proposed by Mirsharif et al. 

The proposed prediction method has good performance and high accuracy compared to previous methods. Therefore, this intelligent and unsupervised method can be used to predict gestational diabetes.

Organizational portals play a key role in increasing the efficiency of Non-Governmental Organizations (NGOs). Considering that education can affect the perception of their usefulness, acceptance and adoption, this study aims to assess the effect of education on the adoption of patient portals by health-related NGOs using the technology acceptance model.

The is an applied study. The statistical population consists of all employees of health-related NGOs in Tabriz, Iran in 2019. Of these, 32 were selected by a random sampling method. The data collection tool was a questionnaire assessing factors affecting the adoption of technology with acceptable validity and reliability. Data analysis was performed using paired t-test, Pearson correlation test, and linear regression in SPSS v. 22 software.

The mean age of participants was 46 years; 59.38% had moderate computer skills and familiarity with information technology, formation technology, formation technology, formation technology, and 68.75% were not familiar with the portals. There was a significant difference in the adoption of portal technology before and after the education (P=0.05).

The educational intervention has a positive impact on improving the patient portal adoption in health-related NGOs. Therefore, the planners need to consider the effect of this method in their policies.

During the Covid-19 pandemic, quality of services provided by medical centers are importance. The present study aims to investigate the quality of diagnostic services provided by medical centers in Zanjan, Iran during the Covid-19 pandemic using Parasuraman’s quality model.

This is a descriptive correlational survey. The study population consists of all patients referred to medical centers in Zanjan province in 2020. Of these, 370 were selected using a convenience sampling method. The sample size was determined using Cochran’s formula. The data collection tool was a standard service quality questionnaire whose validity was assessed by experts, and a Cronbach’s reliability coefficient >0.7 showed its acceptable reliability. Its convergent validity was confirmed using the partial least squares (PLS) model with Average variance extracted > 0.5). Data analysis was performed in PLS and SPSS v. 21 Software. Hypotheses and model fitting were evaluated by structural equation modeling, PLS method, and importance-performance map analysis (IPMA).

There was a high gap between the perceived and expected status of the quality in terms of empathy. Regarding the dimension of tangibility, the services had good quality compared to other dimensions, since there was a small gap between the perceived and expected status. Based on the results of IPMA, the highest coefficient belonged to the assurance dimension, while the lowest coefficient belonged to the reliability dimension.

There is a gap between the current status and desired status in all dimensions of health service quality in Zanjan, Iran. People’ expectations are more than their perceptions; they expect to receive better quality health services during the Covid-19 pandemic.

Building clinical decision support models to automatically extract knowledge from data helps physicians in early diagnosis of disease. Interpretability of the diagnostic rules of these models for understanding how they make decisions and increasing confidence in their output is a key indicator in determining their efficacy.

In this retrospective study, an automated hybrid rule extraction model is proposed for type 2 diabetes. In order to evaluate the model, the PIMA Diabetes dataset including 768 records and 9 variables was used. After removing the missing and outlier data in the data preprocessing stage, a proposed fuzzy-genetic hybrid model was implemented using MATLAB software to extract the rules. A self-organizing chromosomal structure was used to eliminate the complexity of setting genetic algorithm operators and facilitate the re-implementation of the model in other applications.

The accuracy of the proposed model on the PIMA dataset was 79.05%. This accuracy was obtained by two fuzzy rules, each of which contained only two independent variables. In addition, two single diagnostic rules for diabetic and non-diabetic individuals were presented with accuracy of 70.83% and 81.48%, respectively. The number of pregnancies, body mass index, diastolic blood pressure, diabetes pedigree function, plasma glucose concentration, and triceps skinfold thickness were the most effective factors in having or not having diabetes in the extracted rules.

The proposed model with high accuracy and interpretability is quite suitable in producing an accurate and highly interpretable set of rules as well as single rules for diagnosing diabetes or absence of diabetes. Due to its self-organizing ability, it can also be used for other binary classification purposes.

Internet is a source of information for students. The information seeking behaviors on the web is related to several factors. One of these factors is the critical thinking. The present study aims to survey the information seeking behaviors on the web and its relation with critical thinking in postgraduate and doctoral students.

This is a descriptive survey study conducted in 2020. The study population consists of 230 students of postgraduate studies in Ahvaz Jondishapur University of Medical Sciences who were selected by stratified random sampling method. A researcher-made information seeking behavior questionnaire and the Persian version of California Critical Thinking Test: Form B were used to collect data. Data analysis was done in SPSS v. 26 using correlation test, linear regression, and independent t-test, and ANOVA.

The postgraduate students (Mean=3.40) spend more time and effort searching on the web for health information than doctoral students (Mean=2.96). The mean critical thinking scores of postgraduate (7.54) and doctoral students (7.14) were very low, and there was a significant difference between them (P=0.001). There was a significant relationship between critical thinking and information seeking behavior on the web (P=0.027). Based on the results of linear regression analysis, critical thinking could explain 15.7% of the changes in information seeking behaviors on the web.

Critical thinking in college students has direct relationship with their information seeking behavior on the web. Therefore, strengthening this skill can help students to better analyze the information retrieved from the web, evaluate them properly, and differentiate between valid and invalid information.

COVID-19 was identified on December 31, 2019 in Wuhan, China. As a pandemic, it caused people unable to regulate their emotions and created anxiety in many people worldwide. The present study aimed to investigate the role of emotion regulation strategies in mental health during the COVID-19 pandemic.

This is a systematic review study conducted in 2021. A search was conducted in Google Scholar, PubMed, Springer, Web of Science, Scopus, and Science Direct databases using the keywords: COVID-19, Psychological Implications, Mental Health, Emotion Regulation Strategies, and Pandemic for the related studies published in English from 2020 (February) to 2021 (December) in reputable journals. 
Selection methods for study: The search yielded 538 articles. By checking the full texts of these articles, 23 articles were finally selected for the review.

Studies showed that the use of adaptive emotion regulation strategies such as positive reappraisal and positive refocusing on planning led to increased mental health. In contrast, using maladaptive emotion management strategies such as catastrophizing, rumination, and blaming others led to anxiety, depression, and stress.

  Given the role of emotion regulation strategies in the management of anxiety caused by COVID-19, it is necessary to take effective measures to inform people about the role of emotion regulation strategies in reducing their anxiety.