Objectives: This study aimed to fill the gap between Vietnamese diabetic patients' needs and care through a qualitative study asking about their experiences with diabetes and quality of care. -/- Methods: Interviews with five diabetic patients were conducted at a tertiary general hospital located in southern Vietnam. The transcribed data were first subjected to quantitative text analysis using KH Coder to identify major categories of frequently used words, followed by a qualitative analysis of selected cases using the Steps for Coding (...) and Theorization (SCAT) method. -/- Results: The major categories of frequently used words were chronic health conditions, services, facilities, insurance, patient-doctor communication, and medication. SCAT analysis of three selected cases identified six themes: “Disregarding the disease at the early stage,” “Fear of complications,” “Satisfaction with hospital services and medical staff,” “Insurance-related problems,” “Long waiting times,” and “Communication barriers between patients and doctors.” Patients were satisfied with improved hospital facilities and services; however, the overloading of one hospital led to long waiting times and communication difficulties with doctors. Difficulties with health insurance were also observed, and patients were rather passive in disease management and needed to be empowered through improved communication with doctors and other care providers. -/- Conclusion: These findings from our trial of introducing a qualitative study into service evaluation suggest that listening to patients can help health providers learn their perspectives and be more responsive to their needs. (shrink)

Dear Colleagues, -/- Recently, for an article submitted to the European Journal of Therapeutics, it was reported that the paper may have been written with artificial intelligence support at a rate of more than 50% in the preliminary examination made with Turnitin. However, the authors did not mention this in the article’s material method or explanations section. Fortunately, the article’s out-of-date content and fundamental errors in its methodology allowed us no difficulty making the desk rejection decision. -/- On the other (...) hand, similar situations that we may encounter later caused us to discuss how we would decide when the artificial intelligence support of the articles was written. The general opinion that we have adopted and currently available in the literature is that if artificial intelligence is used while writing an article, how artificial intelligence is used in the methodology should be written in detail. -/- Moreover, we encountered a much more exciting situation during our evaluation. In a few academic studies, we have seen that artificial intelligence is added as a co-author. On July 06, 2023, in the Web of Science, using the advanced search, we found four articles with the author name ChatGPT [1]. We have determined that ChatGPT is the author in one of these articles [2] and the Group Author in three [3-5]. -/- Lee [6] stated that although artificial intelligence tools are much more advanced than search engines, they cannot be an author regarding research ethics because they cannot take responsibility for what they write. Similarly, Goto and Katanoda [7] stated that it is the author’s responsibility to confirm that the texts written by ChatGPT are correct. However, Pourhoseingholi et al. [8] reported that keeping up with technology is inevitable. Additionally, they said that“this action will be more fruitful and practical in extended dimensions when international institutes like ICMJE or COPE come up with the appropriate adjustments and establish robust criteria to scheme the AI authorship”. -/- Most probably, the use of artificial intelligence applications in scientific articles and whether it can be a co-author in these papers will be discussed soon. -/- We encourage interested authors to submit their ideas to our journal as a letter to the editor. -/- Yours sincerely,. (shrink)