Iranian Journal of Medical Ethics and History of Medicine

The concept of Islamic medicine, which differs from traditional medicine and even Muslims’ medicine, has become more and more popular in recent years in Iran, especially in religious cities. In the present article, we have addressed the extremist approach of the claimants of Islamic medicine (which considers itself a competitor of modern medicine and traditional medicine).Our theoretical basis for the ethical criticism of this approach has been the principlism of "Beauchamp and Childers". Thereby, we have attempted to challenge the clinical position and medical performances of extremists in the Islamic medicine on the basis of four principles of "justice, autonomy, beneficence, and non-maleficence". Then, we have concluded that the claim of the Islamic medicine cannot, in the present circumstances, satisfy the principle of distributive justice. It also violates patients' autonomy by making unfair judgments and fears about modern medicine. It is very prone to harm clients by refusing scientific evaluation of medicines and therapies and lacking a valid certification system.  Accordingly, we  particularly challenged the attribution of this process to Islam.  This attribution may cause serious damage to the religious beliefs of the clients.

Increased patient satisfaction can promote patient’s compliance with prescribed treatments and improve patients’ health. The aim of this study was to determine the patients’ satisfaction with nurses in surgical departments of Imam, Razi, and Golestan hospitals of Ahvaz city in 2018. In this descriptive-analytic study, patients over 18 years of age with at least 3 days of hospitalization were studied. Data including age, sex, marriage status, level of education, type of illness, hospitalization time, number of hospital admissions, and health status were collected through a demographic form. Patients’ satisfaction with nurses was obtained by the satisfaction questionnaire of nursing services. Chi-square, one-way analysis of variance, Kruskal-Wallis analysis, Mann-Whitney test, and Spearman correlation coefficient were used to analyze by SPSS software. Patients’ satisfaction in Imam, Razi and Golestan hospitals were 78.25±12.09, 68.30±11.24, and 58.09±17.42, respectively. Highest level of patients’ satisfaction was with Razi hospital nurses (P-value<0.05).There were no significant difference between patients of different hospitals regarding age, marriage status, place of residence, hospitalization history, and education level (P-value>0.05).With increasing age, having a history of admission, an increase in the duration of hospitalization, the patients’ satisfaction score decreased significantly (P-value<0.05), but there was no significant difference between the patients’ satisfaction by marriage status, place of residence and level of education (P-value>0.05). It is suggested that effective strategies for increasing patients’ satisfaction be applied through more care and attention of more sensitive people. Also, increasing awareness of  the community about the duties of patients, nurses, and medical staff is recommended.

With the onset of the COVID-19 pandemics, a huge flood of people rushed to medical centers, which severely affected working conditions of the medical staff. In this article, we are going to evaluate the reaction of health care workers to the rise of traffic, social gatherings, non-observance of mask use protocols and physical distance which lead to an increasing number of infected persons and death rate. Here, we address the impact of community’s indifference on medical staff which seems to decrease the quality of medical staff practice gradually

Human is spiritual dimensions that has legal status in health and disease. The purpose of this study was to evaluate the knowledge of nursing and midwifery students about patient rights in Iran Universities of Medical Sciences teaching hospitals’ in 2017. This study was a descriptive cross-sectional study in 2017 with convenience sampling method. Data was collected by a three-part questionnaire including demographic information, Knowledge about the Patient Rights Charter, and strategies for student information to deal with patient rights. Mann-Whitney and Spearman tests were used for data analysis. A total of 1219 undergraduate students participated in this study. The mean score of students' awareness of the Patient Rights Charter was 13.54±4.45 out of 29 points. 1007 students (82.61%) reported that education about patient right was sufficient. Direct correlation was between patient knowledge awareness score with pre-internship training (r = 0.461) and learning from instructor information (r = 0.512) and there was a negative correlation between self-education (r = -0.151) and other methods of information acquisition (r = -0.067). Given that most students did not consider the educational content taught in the field of patient rights to be effective, it can be concluded that these methods were ineffective and failed to convey the correct information. Therefore, revising of the Patient Rights Curriculum for Nursing and Midwifery students is recommended

Journals have begun publishing articles in which chatbots, such as Bard, Bing, and ChatGPT, have been utilized, with some even listing chatbots as co-authors. The legal status of authorship varies by country, but under most jurisdictions, an author must be a legal person. Chatbots do not meet the International Committee of Medical Journal Editors (ICMJE) authorship criteria, particularly requirements such as giving “final approval of the version to be published” and being “accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.” No AI tool can “understand” a conflict-of-interest statement or sign it, nor do chatbots have independent affiliations apart from their developers. Since authors submitting a manuscript must ensure that all listed authors meet the required criteria, chatbots cannot be considered authors. Authors should disclose the use of chatbots and provide detailed information about how they were employed. The extent and type of chatbot usage in journal publications should be clearly indicated, in line with the ICMJE recommendation to acknowledge writing assistance and detail the study's methods and results. When chatbots or AI tools are used to draft new text, authors must note such use in the acknowledgments. All prompts employed to generate text, convert text into tables or illustrations, or draft figures should be specified. If an AI tool was used for analytical work, reporting results (e.g., generating tables or figures), or writing computer codes, this should be explicitly stated in the paper’s Abstract and Methods sections. For transparency and reproducibility, authors should include the complete prompt used to generate results, the query’s time and date, and details of the AI tool, including its version. Authors remain fully responsible for material generated by a chatbot, including its accuracy and the absence of plagiarism. They must also ensure appropriate attribution of all sources, including original sources for content produced by the chatbot. Authors must confirm that the work reflects their data and ideas and is free from plagiarism, fabrication, or falsification. Otherwise, submitting such material for publication constitutes scientific misconduct. Proper attribution of quoted material, with full citations, is essential, and cited sources must align with the chatbot’s claims. Since chatbots may omit sources opposing the viewpoints in their output, it is the author’s responsibility to identify, review, and include such counterviews in their articles. (It is worth noting that biases are not exclusive to AI; human authors are also subject to them.) Editors and peer reviewers should disclose any use of chatbots in manuscript evaluation or correspondence. If they employ chatbots in communications with authors or colleagues, they must clarify how the chatbot was used. Editors and reviewers are responsible for any content and citations generated by chatbots. They should also be mindful that chatbots may retain the prompts and manuscript content provided to them, which could breach the confidentiality of submitted manuscripts. Authors must specify the chatbot used and the exact prompts (query statements) employed. They should detail steps taken to mitigate the risks of plagiarism, provide balanced perspectives, and ensure the accuracy of all references. Editors require effective tools to detect content generated or modified by AI. These tools should be universally accessible, regardless of financial constraints, to uphold scientific integrity and minimize the risk of misinformation that could adversely affect public health. Many medical journal editors currently rely on manuscript evaluation approaches that are not designed to address AI-related challenges, such as manipulated or plagiarized text, fabricated images, and papermill-generated documents. This puts them at a disadvantage when distinguishing legitimate from fabricated content, and the emergence of chatbots exacerbates these challenges. Access to advanced tools that enable efficient and accurate content evaluation is particularly vital for editors of medical journals, where misinformation can have severe consequences, including harm to patients.