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A key feature of human rights in health is access to safe, effective and affordable medicines. Pharmacovigilance is advocated for monitoring intended/unintended effects of medicines to assure their safety. The purpose of this paper is to synthesize knowledge about supply chain impediments to safe medicines in developing nations and contribute to future development of research in this field.

This paper conducts a structured literature review based on Preferred Reporting Items for the Systematic Reviews and Meta-Analyses guidelines. It aims at profiling supply chain impediments to safe medicines in developing nations by reviewing 46 recent pharmacovigilance-specific papers published between 2005 and 2020.

Analysis of reviewed articles identified criticality of supply chain impediments that affect constituents across pharmaceutical in developing nations, which still struggle to maintain robust national pharmacovigilance systems due to lack of awareness, policy and practices.

Research results can be applied by pharmaceutical industry decision-makers and drug safety professionals in developing nations. Because the review is qualitative in nature, its implication ought to be tested after actual implementation.

This review can help identify underinvestigated impediments and methods to aid in developing new pharmacovigilance knowledge areas in developing nation context.

The review uncovers gaps in global health equity dialogue in developing nations. It also recognizes that macrolevel supply chain impediments exist due to unfair disease burden and health inequities in developing nations.

The paper examines supply chain impediments to safe medicines in developing nations with insights for future pharmacovigilance research. Identifying and classifying supply chain impediments through this review is the first step toward creating effective interventions for these impediments to safe medicines.

In the state of Hawaii, it has been shown that certain ethnic minority groups, such as Filipinos and Pacific Islanders, suffer disproportionally high rates of cardiovascular disease, evidence that local health-care systems and governing bodies fail to equally extend the human right to health to all. This study aims to examine whether these ethnic health disparities in cardiovascular disease persist even within an already globally disadvantaged group, the houseless population of Hawaii.

A retrospective chart review of records from Hawaii Houseless Outreach and Medical Education Project clinic sites from 2016 to 2020 was performed to gather patient demographics and reported histories of type II diabetes, obesity, hyperlipidemia, hypertension and other cardiovascular disease diagnoses. Reported disease prevalence rates were compared between larger ethnic categories as well as ethnic subgroups.

Unexpectedly, the data revealed lower reported prevalence rates of most cardiometabolic diseases among the houseless compared to the general population. However, multiple ethnic health disparities were identified, including higher rates of diabetes and obesity among Native Hawaiians and other Pacific Islanders and higher rates of hypertension among Filipinos and Asians overall. The findings suggest that even within a generally disadvantaged houseless population, disparities in health outcomes persist between ethnic groups and that ethnocultural considerations are just as important in caring for this vulnerable population.

To the best of the authors’ knowledge, this is the first comprehensive study focusing on ethnic health disparities in cardiovascular disease and the structural processes that contribute to them, among a houseless population in the ethnically diverse state of Hawaii.

Evidence of overprescribing of psychotropic medicines to manage challenging behaviour in people with intellectual disabilities has led to national programmes within the UK to promote deprescribing, such as stopping the overprescribing of medication in people (with learning disabilities, autism or both). To successfully implement deprescribing initiatives, we need to understand how to engage stakeholders in the process.

In a published systematic review, we reported evidence about the process of deprescribing psychotropic medicines for people of all ages with intellectual disabilities and challenging behaviour. As a part of the original review, we searched for evidence about stakeholders’ experiences of the psychotropic deprescribing process, which was synthesised and reported within the current study.

Six studies were identified. Involving carers and people with intellectual disabilities, providing ongoing support and improving access to non-pharmacological interventions, including positive behaviour support, may contribute to successful outcomes, including reducing or stopping psychotropic medicines and improving quality of life. Implementing psychotropic deprescribing requires a multidisciplinary collaborative care approach and education for stakeholders.

There have been no previous reviews of stakeholder experiences of deprescribing psychotropic medications for people with intellectual disabilities and challenging behaviour. The existing literature is scant, and further research is needed.

Under the background of open science, this paper integrates altmetrics data and combines multiple evaluation methods to analyze and evaluate the indicators' characteristics of discourse leading for academic journals, which is of great significance to enrich and improve the evaluation theory and indicator system of academic journals.

This paper obtained 795,631 citations and 10.3 million altmetrics indicators data for 126,424 published papers from 151 medicine, general and internal academic journals. In this paper, descriptive statistical analysis and distribution rules of evaluation indicators are first carried out at the macro level. The distribution characteristics of evaluation indicators under different international collaboration conditions are analyzed at the micro level. Second, according to the characteristics and connotation of the evaluation indicators, the evaluation indicator system is constructed. Third, correlation analysis, factor analysis, entropy weight method and TOPSIS method are adopted to evaluate and analyze the discourse leading in medicine, general and internal academic journals by integrating altmetrics. At the same time, this paper verifies the reliability of the evaluation results.

Six features of discourse leading integrated with altmetrics indicators are obtained. In the era of open science, online academic exchanges are becoming more and more popular. The evaluation activities based on altmetrics have fine-grained and procedural advantages. It is feasible and necessary to integrate altmetrics indicators and combine the advantages of multiple methods to evaluate the academic journals' discourse leading of which are in a diversified academic ecosystem.

This paper uses descriptive statistical analysis to analyze the distribution characteristics and distribution rules of discourse leading indicators of academic journals and to explore the availability of altmetrics indicators and the effectiveness of constructing an evaluation system. Then, combining the advantages of multiple evaluation methods, The author integrates altmetrics indicators to comprehensively evaluate the discourse leading of academic journals and verify the reliability of the evaluation results. This paper aims to provide references for enriching and improving the evaluation theory and indicator system of academic journals.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

Many refugees and asylum seekers in Germany experience a high disease burden and low health literacy. The current study aims to focus on assessing these issues among African refugees and asylum seekers in Bavaria, Germany. The authors evaluated their self-perceived health status and health literacy, and identified barriers and gaps in health care utilization, intending to improve health care services for this group.

The authors conducted a cross-sectional, questionnaire-based study involving 69 refugees and asylum seekers from Ethiopia, Eritrea and Nigeria. The authors performed descriptive and exploratory statistical analyses.

The authors found a substantial disease burden in the early stages of resettlement in Germany, particularly mental health symptoms (53.6%) and musculoskeletal problems (47.8%). Challenges in health literacy were observed, such as difficulties in understanding health information and managing emergency situations. Access to interpreters was limited, and understanding treatment certificates was more challenging than using electronic health cards, with 18.2% of participants reporting denial of medical treatment.

These findings highlight the need for early and tailored health support for refugees, with a particular focus on mental health. Efforts should be made to reduce language barriers and improve navigational skills within the health-care system, particularly in emergency situations. Addressing the restricted access to health care and bureaucratic obstacles is crucial for improved health outcomes among refugees.

To the best of the authors’ knowledge, this research is the first to specifically explore the self-reported health status and health literacy of African refugees and asylum seekers in Bavaria, Germany, providing valuable insights into the unique healthcare challenges of this often underrepresented and overlooked population.

This study aims to measure the perception of the residents regarding peer assisted learning in emergency medicine residency program as well as assessing the psychometric properties of the questionnaire used as the research tool.

A descriptive cross-sectional study was conducted at King Abdullah Medical City, Saudi Arabia, Makkah on a Convenience sample of Emergency Medicine residents who completed peer assisted learning sessions. Data were collected through a questionnaire evaluating the residents’ perception of Peer Assisted Learning. Descriptive statistics were used and statistical significance was set at p < 0.05. The Peer Assisted Learning (PAL) satisfaction questionnaire was tested for construct validity and reliability. Exploratory Factor Analysis (EFA) was conducted. The reliability of the used questionnaire was assessed using Cronbach’s coefficient alpha.

The study showed that the PAL questionnaire yielded four factors. The four factors are labeled as the following: Factor 1: Cognitive congruence, Factor 2: Social congruence; Factor 3: Teaching skills in Peer Assisted Learning (PAL) session; and Factor 4: Professional development. These results indicated that questionnaire has a good structure validity. In addition, the study showed high internal consistency of the questionnaire. Cronbach’s alpha coefficient value for the total scale was 0.88. The perception of residents was assessed and results revealed residents’ satisfaction regarding Peer Assisted Learning.

Up to the authors’ knowledge, this is the first study which assessed the psychometric properties of a questionnaire measuring the residents’ perceptions regarding Peer Assisted Learning. The study contributed to improving information regarding the psychometric properties and usefulness of PAL questionnaire.

The purpose of this study is to explore the lived experiences of the constraints of older adult family caregivers with chronic diseases in caring for and accessing health services during the COVID-19 pandemic.

This study used the descriptive phenomenology qualitative method. The sampling method was purposive sampling involving 16 older adult family caregivers.

The results of this study showed three themes such as difficulties in health services in hospitals during the COVID-19 pandemic (complaints of services provided by doctors, older adult treatment control problems and difficulty getting to hospital health facilities); difficulties accompanying taking older adult medicine (older adult non-compliance response to taking medication and older adult medicine assistance); and psychosocial complaints caring for and accompanying the older adult (negative emotions for the older adult, difficulty interacting with the older adult and the economic burden of caring for the older adult).

Barriers to family caregivers in caring for older adults with chronic diseases can help health-care service providers understand and support families caring for and assisting older adults, which may contribute to the quality of life and care for both family caregivers and older adults.

This study showed that Indonesian family caregivers faced difficulties caring for and living with older adults with chronic diseases during the pandemic. Family caregivers’ experiences are essential when developing an intervention to support and manage health care for older adults with chronic illnesses.

Studies show that economic sanctions have had major negative impacts on health systems during the past years. The aim of this study is to identify the impacts of US sanctions on the performance of public hospitals in Iran.

A qualitative research study was conducted between October 2019 and September 2020 in Kermanshah Province, Iran. Semi-structured, face-to-face interviews, lasting between 25 and 90 min, were carried out with 20 participants in seven public hospitals affiliated to the authors’ institution in Kermanshah Province. Inductive thematic analysis was used to identify themes in the data.

Five main themes emerged from the analysis: resource management challenges; financial restrictions; interruptions in planning; reductions in the quality of service delivery; and changes in organizational relationships.

The results of the present study demonstrate that US economic sanctions have considerably reduced access to necessary medical equipment and medicines for public hospitals in Iran. Policymakers should monitor the distribution of equipment and pharmaceutical products within public hospitals in Iran and take actions to ameliorate shortages during times of economic sanctions.

The research on structure function recognition mainly concentrates on identifying a specific part of academic literature and its applicability in the multidiscipline perspective. A specific part of academic literature, such as sentences, paragraphs and chapter contents are also called a level of academic literature in this paper. There are a few comparative research works on the relationship between models, disciplines and levels in the process of structure function recognition. In view of this, comparative research on structure function recognition based on deep learning has been conducted in this paper.

An experimental corpus, including the academic literature of traditional Chinese medicine, library and information science, computer science, environmental science and phytology, was constructed. Meanwhile, deep learning models such as convolutional neural networks (CNN), long and short-term memory (LSTM) and bidirectional encoder representation from transformers (BERT) were used. The comparative experiments of structure function recognition were conducted with the help of the deep learning models from the multilevel perspective.

The experimental results showed that (1) the BERT model performed best, with F1 values of 78.02, 89.41 and 94.88%, respectively at the level of sentence, paragraph and chapter content. (2) The deep learning models performed better on the academic literature of traditional Chinese medicine than on other disciplines in most cases, e.g. F1 values of CNN, LSTM and BERT, respectively arrived at 71.14, 69.96 and 78.02% at the level of sentence. (3) The deep learning models performed better at the level of chapter content than other levels, the maximum F1 values of CNN, LSTM and BERT at 91.92, 74.90 and 94.88%, respectively. Furthermore, the confusion matrix of recognition results on the academic literature was introduced to find out the reason for misrecognition.

This paper may inspire other research on structure function recognition, and provide a valuable reference for the analysis of influencing factors.