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The study aims to survey information-seeking behavior of the Iranian medical faculty members and to identify the reasons and obstacles of their usage via the internet, scientific databases and online social networks.

In this cross-sectional study, a structured questionnaire used to collect data. The research population includes faculty members of four faculties of Hamadan University of Medical Sciences in Iran, including health, nursing – midwifery, paramedicine and rehabilitation. SPSS software was used to analyze data in descriptive and analytical levels.

Low internet speed, network traffic and lack of time were the main barriers and difficulties. Gender was significantly related with familiarity with databases, problems and barriers to accessing information, barriers to using social network, as well as purpose and motivation of using social network. Search for educational and research resources and use of social network to increase their general information were the main goals of participants to using the internet and databases. A negative significant relationship was observed between usage of social network with age (r = −0.204, P = 0.047) and experience (r = −0.239, P = 0.019).

The usage of faculty members of various digital resources is growing ever more. This study examines the use of faculty members of the internet, scientific databases and online social networks simultaneously.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

The Iranian patients’ rights charter defines patient rights as a reflection of fundamental human rights in the field of medicine and incorporates all elements of patient rights accepted in international texts. The purpose of this paper is to study the way in which diabetes patients’ rights are being exercised in everyday hospital practice in Birjand, Iran.

A cross-sectional study design was used in 2014. The sample size was estimated 150 patients, out of which 108 diabetes patients completed questionnaire. The questionnaire of diabetes patients’ perspectives on the patients’ rights was used to collect data. The questionnaire consists of 22 questions. Data entry and analysis were carried out using SPSS software (version 22). Descriptive and inferential statistics were calculated with all survey items and total scores, as well as demographic data.

The response rate was 72 percent. Overall, the mean score percentage of diabetes patients’ perspectives on the patients’ rights was 74.04± 8.4. Furthermore, statistical significant differences were found among diabetes patients in relation to patients’ perspectives on the patients’ rights according to highest level of education (F=16.52, p=0.002), their habitat(t=3.49, p=0.001), age groups (F=18.70, p=0.0001) and the duration of the disease (F=5.16, p=0.007). The results showed that no statistically significant differences were observed among diabetes patients in relation to diabetes patients’ perspectives on the patients’ rights according to their gender (F=1.57, p=0.12) and marital status (F=1.56, p=0.09).

Clinicians can provide care based on patients’ rights, and their knowledge of patients’ rights needs to be evaluated. Educational courses, leaflets, booklets and posters can be helpful in this regard. In addition, professional organizations and the Ministry of Health need to be more sensitive to this issue.

The purpose of this paper is to explore oncology nurses’ barriers to empathy-based care perceptions.

The authors used a descriptive qualitative method. In total, 18 oncology nurses were selected via purposive sampling. Data were collected through in-depth interviews and qualitative content analysis using an inductive approach.

Three main categories emerged from the data analysis: barriers related to nursing including: lacking compassion; disinterest in oncology nursing and self-criticism; psychological distress; barriers related to healthcare: job strain; task-centeredness; no formal training; poor manager support; nurse-patient gender imbalance; and barriers related to cancer care including: difficulty maintaining empathy with cancer patients; and inappropriate cancer patient

Oncology nurses provided insights into barriers to empathy-based care and the challenges they encountered while caring for cancer patients. Understanding these barriers is the first step to overcoming obstacles and creating an open and caring environment to provide an empathic care culture.

Given that oncology nurses experience several emotions, positive coping strategies for these distresses should be adopted. Healthcare systems should change cancer-caring culture from task-centered to patient-centered care. Compassion and empathy should become patient care values.

This study aims to identify the effect of strawberry supplementation on some metabolic, inflammatory and oxidative parameters in adults with cardiovascular (CV) risk factors.

A systematic literature search was performed up to November 2020 using PubMed, Embase, Cochrane, Web of Sciences and Scopus databases. The pooled mean difference (MD) with 95% confidence interval (CI) was used to analyze the data by random-effects model. I² statistics and Cochrane risk of bias tool were used for investigating heterogeneity and quality of included studies, respectively.

In total, 13 randomized controlled trials with 488 participants were included. Strawberry supplementation significantly reduced diastolic blood pressure (MD = −2.1, 95% CI [−3.7, −0.42], P = 0.01), low-density lipoprotein cholesterol (−0.16, −0.30, −0.02, P = 0.03), high-sensitivity C-reactive protein (CRP) (−0.76, −1.4, −0.05, P < 0.001) and CRP (−0.31, −0.43, −0.18, P = 0.04). Leptin levels were raised in control group compared with participants who had received strawberry (0.65, 0.09 and 1.2, P = 0.02). The results of subgroup analysis based on the follow-up duration and supplementation dose showed that consumption of strawberry for more than eight weeks and 50 g day⁻¹ can significantly decrease some other CV risk factors compared to control group. Further, both higher follow-up duration and supplementation dose were more effective in increasing leptin levels of control group compared to intervention group.

The use of some useful plant foods such as strawberries by the pharmaceutical industry and the community health sector can greatly help improve people’s CV and metabolic health.

Failure modes and effects analysis (FMEA) is a practical tool to evaluate risks, discover failures in a proactive manner and propose corrective actions to reduce or eliminate potential risks. The purpose of this paper is to apply FMEA technique to examine the hazards associated with the process of service delivery in intensive care unit (ICU) of a tertiary hospital in Yazd, Iran.

This was a before-after study conducted between March 2013 and December 2014. By forming a FMEA team, all potential hazards associated with ICU services – their frequency and severity – were identified. Then risk priority number was calculated for each activity as an indicator representing high priority areas that need special attention and resource allocation.

Eight failure modes with highest priority scores including endotracheal tube defect, wrong placement of endotracheal tube, EVD interface, aspiration failure during suctioning, chest tube failure, tissue injury and deep vein thrombosis were selected for improvement. Findings affirmed that improvement strategies were generally satisfying and significantly decreased total failures.

Application of FMEA in ICUs proved to be effective in proactively decreasing the risk of failures and corrected the control measures up to acceptable levels in all eight areas of function.

Using a prospective risk assessment approach, such as FMEA, could be beneficial in dealing with potential failures through proposing preventive actions in a proactive manner. The method could be used as a tool for healthcare continuous quality improvement so that the method identifies both systemic and human errors, and offers practical advice to deal effectively with them.

This paper aims to evaluate the association between carbohydrate quality index (CQI) and nutrient adequacy in Iranian adults.

A total of 268 men and women with ages ranged from 18 to 70 years were evaluated in a cross-sectional study. The CQI was calculated by adding together the three components, namely, the ratio of solid to total carbohydrate, dietary fiber and glycemic index. The scores of three components were summed to calculate the CQI, with a higher score indicating a higher dietary carbohydrate quality. The odds ratios (ORs) of nutrient adequacy ratio (NAR), defined as the ratio of intake of a nutrient to the age- and gender-specific recommended dietary allowance, for the intake of energy and 10 nutrients across quartiles of the CQI were calculated by logistic regression analysis and expressed with 95% confidence intervals (CIs).

CQI ranged between 3 to 15 (mean ± SD: 9 ± 1.9). Being in top versus bottom quartile of the CQI was associated with a higher NAR of folic acid (OR: 3.20, 95% CI: 1.06–9.62; P-trend: <0.001), vitamin A (OR: 3.66; 95% CI: 1.46–9.17; P-trend: <0.001), magnesium (OR: 5.94; 95% CI; 1.71–20.53; P-trend: <0.001), vitamin C (OR: 7.85; 95% CI; 2.99–20.59; P-trend: <0.001).

A higher CQI was associated with greater micronutrient consumption adequacy in Iranian adults. The results suggest that increasing the consumption of total fiber and solid carbohydrates and decreasing the glycemic index of the diet and liquid carbohydrates can improve micronutrient intake adequacy.

The purpose of this paper is to introduce a new tactile array sensor into the medical field to enhance current robotic minimally invasive surgery (RMIS) procedures that are still limited in scope and versatility. In this paper, a novel idea is proposed in which a tactile sensor array can measure rate of displacement in addition to force and displacement of any viscoelastic material during the course of a single touch. To verify this new array sensor, several experiments were conducted on a diversity of tissues from which it was concluded that this newly developed sensory offers definite and significant enhancements.

The proposed array sensor is capable of extracting force, displacement and displacement rate in the course of a single touch on tissues. Several experiments have been conducted on different tissues and the array sensor to verify the concept and to verify the output of the sensor.

It is shown that this new generation of sensors are required to distinguish the difference in hardness degrees of materials with viscoelastic behavior.

In this paper, a new generation of tactile sensors is proposed that is capable of measuring indentation time in addition to force and displacement. This idea is completely unique and has not been submitted to any conference or journal.