Editor’s Choice Articles

Background: Bronchopulmonary dysplasia (BPD) is the most common serious pulmonary morbidity in preterm infants with high disability and mortality rates. Early identification and treatment of BPD is critical. Objective: This study aimed to develop and validate a risk scoring tool for early identification of preterm infants that are at high-risk for developing BPD. Methods: The derivation cohort was derived from a systematic review and meta-analysis of risk factors for BPD. The statistically significant risk factors with their corresponding odds ratios were utilized to construct a logistic regression risk prediction model. By scoring the weights of each risk factor, a risk scoring tool was established and the risk stratification was divided. External verification was carried out by a validation cohort from China. Results: Approximately 83,034 preterm infants with gestational age < 32 weeks and/or birth weight < 1500 g were screened in this meta-analysis, and the cumulative incidence of BPD was about 30.37%. The nine predictors of this model were Chorioamnionitis, Gestational age, Birth weight, Sex, Small for gestational age, 5 min Apgar score, Delivery room intubation, and Surfactant and Respiratory distress syndrome. Based on the weight of each risk factor, we translated it into a simple clinical scoring tool with a total score ranging from 0 to 64. External validation showed that the tool had good discrimination, the area under the curve was 0.907, and that the Hosmer–Lemeshow test showed a good fit (p = 0.3572). In addition, the results of the calibration curve and decision curve analysis suggested that the tool showed significant conformity and net benefit. When the optimal cut-off value was 25.5, the sensitivity and specificity were 0.897 and 0.873, respectively. The resulting risk scoring tool classified the population of preterm infants into low-risk, low-intermediate, high-intermediate, and high-risk groups. This BPD risk scoring tool is suitable for preterm infants with gestational age < 32 weeks and/or birth weight < 1500 g. Conclusions: An effective risk prediction scoring tool based on a systematic review and meta-analysis was developed and validated. This simple tool may play an important role in establishing a screening strategy for BPD in preterm infants and potentially guide early intervention. Full article

The consolidation of telerehabilitation for the treatment of many diseases over the last decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises and proper corporal movements online should also be mentioned. The focus of this paper is on a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and other less accessible locations. A full-stack is presented using big data frameworks that facilitate communication between the patient and the occupational therapist, the recording of each session, and real-time skeleton identification using artificial intelligence techniques. Big data technologies are used to process the numerous videos that are generated during the course of treating simultaneous patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for automated evaluation of corporal exercises, which is of immense help to the therapists in charge of the treatment programs. Full article

Life as a couple, and their ability to solve problems or not, can result in the relationship being satisfactory and functional or unsatisfactory and dysfunctional, which increases the risk of violence with serious implications. For that reason, it is important to isolate the risk factors to prevent and treat unsatisfactory and dysfunctional relationships. The qualitative interpretive exploratory method was used, analysing 50 sessions of group psychotherapy with patients from a reproductive health institution whose relationships faced violent problems. The identified factors were the lack of autonomy in one of the partners, unresolved internal factors, a combination of external factors and factors caused by their interaction; symmetrical and asymmetrical violence, subjugation of one before the other, intergenerational violence, family violence during childhood and normalisation of violence. Isolating factors to understand relationship problems at risk of manifesting violence opens the possibility of effective, specific and preventive treatments of family and intimate partner violence. Full article

During the great life-altering challenges brought by Coronavirus 2019, school closures and lack of access to exercise and social interactions may have increased students’ negative emotions. The current research acts as a follow-up study to the development of the EXSEM-SC, using the Repeated Measures Panel Analysis Framework (RMPAF) to examine the stability of the model in revealing the relationship between physical activity, self-compassion, and mental well-being among Hong Kong adolescents. It is also aimed at examining the changes in physical activity, self-compassion, and mental well-being among Hong Kong adolescents between, before, and after the peak of COVID-19 using the EXSEM-SC Model. The RMPAF has involved 572 (60% Female, Mage = 13.63, SD =1.31) Hong Kong secondary school students. Furthermore, using the abductive qualitative approach, a total of 25 (Mage = 14.84, SD = 1.40) students were involved in the in-depth interviews to further investigate the relationships within the EXSEM-SC. The quantitative results showed that the relationship between physical activity and self-compassion could be demonstrated by the EXSEM-SC, with a satisfactory goodness-of-fit index in the SEMs, as well as satisfying model construct consistency. Moreover, it showed no significant differences in the level of physical activity, self-compassion, and mental well-being during and after the peak of COVID-19. The qualitative results demonstrated two new categories within the EXSEM-SC variables, which are personality traits and injuries experiences. With the stability of the EXSEM-SC model among adolescents, it is expected that the physical activity intervention, which is based on the EXSEM-SC model, could also aim at easing Hong Kong adolescent’s mental health issues. In addition, in terms of generating a long-term impact among students, the physical activity and self-compassionate intervention should be promoted among schools. However, the quantitative properties of the two new categories in the qualitative outcomes should be involved in future investigation. Full article

Physicians are required to move and manipulate equipment to achieve motor tasks such as surgical operations, endotracheal intubations, and intravenous cannulation. Understanding how movements are generated allows for the analysis of performance, skill development, and methods of teaching. Ecological-Dynamics (ECD) is a theoretical framework successfully utilized in sports to explain goal-directed actions and guide coaching and performance analysis via a Constraint-Led Approach (CLA). Its principles have been adopted by other domains including learning music and mathematics. Healthcare is yet to utilize ECD for analyzing and teaching practical skills. This article presents ECD theory and considers it as the approach to understand skilled behavior and developing training in medical skills. Full article

We report a rare case of severe COVID-19-associated pulmonary aspergillosis presenting as invasive pulmonary aspergillosis and subsequently invasive tracheobronchial aspergillosis during hospitalization in a critically ill patient who developed a further Aspergillus infection after home discharge. He needed readmission to the ICU and mechanical ventilation. We therefore strongly encourage a high degree of attention to fungal complications, even after viral recovery and ICU discharge. Full article

(1) Background: Palliative and end-of-life care services are increasingly gaining centre stage in health and social care contexts in the UK and globally. Death and dying need are relational processes. Building personal and community capacity along with resilience is vital to support families and communities to normalise death and dying. Last Aid Training (LAT) is one such innovative educational initiative which teaches the general public about the fundamentals of palliative care and promotes public discussion about death and dying. The Highland Hospice [HH] in Scotland has pioneered delivery of LAT in face-to-face settings since March 2019 and online since March 2020 to accommodate pandemic restrictions. (2) Methods: This study used a mixed-methods approach, combining an online survey with LAT participants followed by individual semi-structured qualitative interviews with both LAT participants and facilitators. The primary aim of this study was to investigate the impacts of LAT for participants at the individual, family, and community levels, as well as explore participant and facilitator experiences and perspectives of LAT in an online environment. (3) Results: Overall, this evaluation demonstrates that provision of foundational death literacy education in social contexts enhances the personal knowledge, skills, and confidence of individual community members and supports the notion that this personal growth could lead to strengthened community action. (4) Conclusions: Findings from this study concluded that there is potential to include LAT as the foundational core training to promote death literacy in communities with further exploration to integrate/align LAT with other national/global end-of-life care frameworks. Full article

Digital contact tracing apps have been introduced by governments as a strategy to limit the spread of the COVID-19 pandemic. Digital contact tracking is an alternative to traditional contact tracing performed by human tracers who have to reconstruct each contact an infected person had in the recent past by means of interviews. The Italian government proposed the Immuni digital contact tracking app as a solution. Immuni uses Bluetooth technology to anonymously register all close contacts a person had: if she tests positive for COVID-19 then all registered contacts are notified. The main aim of the paper is to propose a cluster analysis of some factors concerning the possible acceptance of the Immuni app to build behaviour profiles that explain and predict the possible behaviours of the respondents. The factors considered referred to three different pillars: the technological pillar, investigated by considering factors from the technology acceptance models family; the health pillar, where variables of the health belief model were used; and the sociopolitical pillar, where some values of the respondents were considered as possible barriers to or facilitators of the acceptance of this technology. As a result of the cluster analysis, three behavioural profiles were built: the ProApp profile, the Hesitant profile, and the AntiApp profile. The first is the profile grouping the respondents who intend to use the contact tracing app; the second is more about people who are favourable of the use of the app, but some issues such as privacy reduce the strength of their intention; the last profile is about people who are less favourable to use the app. We are confident that the behaviour profiles found would be useful to build more tailored communication campaigns to help promote the use of the app by managing factors that could either be facilitators or barriers. Full article

Identification and re-identification are two major security and privacy threats to medical imaging data. De-identification in DICOM medical data is essential to preserve the privacy of patients’ Personally Identifiable Information (PII) and requires a systematic approach. However, there is a lack of sufficient detail regarding the de-identification process of DICOM attributes, for example, what needs to be considered before removing a DICOM attribute. In this paper, we first highlight and review the key challenges in the medical image data de-identification process. In this paper, we develop a two-stage de-identification process for CT scan images available in DICOM file format. In the first stage of the de-identification process, the patient’s PII—including name, date of birth, etc., are removed at the hospital facility using the export process available in their Picture Archiving and Communication System (PACS). The second stage employs the proposed DICOM de-identification tool for an exhaustive attribute-level investigation to further de-identify and ensure that all PII has been removed. Finally, we provide a roadmap for future considerations to build a semi-automated or automated tool for the DICOM datasets de-identification. Full article

Background: The application of Context Aware Computing (CAC) can be an effective, useful, feasible, and acceptable way to advance medical research and provide health services. Methods: This review was conducted in accordance with the principles of the development of a mixed methods review and existing knowledge in the field via the Synthesis Framework for the Assessment of Health Information Technology to evaluate CAC implemented by Evidence-Based Health Informatics (EBHI). A systematic search of the literature was performed during 18 November 2021–22 January 2022 in Cochrane Library, IEEE Xplore, PUBMED, Scopus and in the clinical registry platform Clinicaltrials.gov. The author included the articles in the review if they were implemented by EBHI and concerned with CAC technologies. Results: 29 articles met the inclusion criteria and refer to 26 trials published between 2011 and 2022. The author noticed improvements in healthcare provision using EBHI in the findings of CAC application. She also confirmed that CAC systems are a valuable and reliable method in health care provision. Conclusions: The use of CAC systems in healthcare is a promising new area of research and development. The author presented that the evaluation of CAC systems in EBHI presents positive effects on the state of health and the management of long-term diseases. These implications are presented in this article in a detailed, clear, and reliable manner. Full article

The pandemic outbreak of COVID-19 has posed several questions about public health emergency risk communication. Due to the effort required for the population to adopt appropriate behaviors in response to the emergency, it is essential to inform the public of the epidemic situation with transparent data sources. The COVID-19ita project aimed to develop a public open-source tool to provide timely, updated information on the pandemic’s evolution in Italy. It is a web-based application, the front end for the eponymously named R package freely available on GitHub, deployed both in English and Italian. The web application pulls the data from the official repository of the Italian COVID-19 outbreak at the national, regional, and provincial levels. The app allows the user to select information to visualize data in an interactive environment and compare epidemic situations over time and across different Italian regions. At the same time, it provides insights about the outbreak that are explained and commented upon to yield reasoned, focused, timely, and updated information about the outbreak evolution. Full article

Family members of intensive care unit patients are often experience high anxiety and require more information about the patients. However, most Taiwanese healthcare institutions currently face manpower shortages due to the COVID-19 pandemic. Therefore, the task of providing additional services to meet family members’ needs and relieve their stress was deferred by some healthcare institutions. The self-service system, known to be effective and efficient in other industries, was recommended for use in the healthcare industry. This study aims to explore an intensive care unit self-service system (ICU-SSS) designed for the family members of ICU patients. This study investigates the feasibility of the system by following a mixed method approach, including qualitative interviews and a quantitative survey. Firstly, interviews with five family members and five ICU staff members of a case hospital were conducted to identify the need to develop an ICU-SSS for the family member. Secondly, a survey was completed by 30 family members to evaluate the system. The interview results reveal nine categories of family members’ needs and the survey results show that the ICU family members assigned acceptable scores to all the ICU-SSS functions, except the importance of “Logistical information”. Based on these findings, the scientific and practical implications are discussed. Full article

Background: A high-volume center with a multidisciplinary team is regarded as the optimal place for providing extracorporeal membrane oxygenation (ECMO). We hypothesize that an ECMO center can also be successfully created and subsequently developed entirely by intensivists in a mid-size mixed intensive care unit (ICU). Methods: A model was created for setting up a new ECMO referral center within the structure of an existing mixed ICU in a tertiary hospital. A retrospective analysis was carried out of the first 33 patients treated in the initial period of the center’s activity, from mid 2018 to the end of 2020. Results: An ECMO center was established and developed entirely based on the resources of an existing mixed ICU. Thirty-three patients were treated. They had an overall survival rate at 90 days of 60.6%. In veno-venous (VV) mode ECMO duration, ICU length of stay, and SOFA score were significantly higher than in veno-arterial mode. No significant differences in clinical characteristics were observed between survivors and non-survivors on VV-ECMO. Conclusions: A regional ECMO center can be set up as an integral part of a mixed ICU in a tertiary hospital. Extracorporeal therapy, such as continuous renal replacement therapy and mechanical ventilation can be managed entirely by intensivists. Further studies are needed to show that the ICU-based approach to setting up a new ECMO center is no less effective than the multidisciplinary approach. Full article

COVID-19, or SARS-CoV-2, is considered as one of the greatest pandemics in our modern time. It affected people’s health, education, employment, the economy, tourism, and transportation systems. It will take a long time to recover from these effects and return people’s lives back to normal. The main objective of this study is to investigate the various factors in health and food access, and their spatial correlation and statistical association with COVID-19 spread. The minor aim is to explore regression models on examining COVID-19 spread with these variables. To address these objectives, we are studying the interrelation of various socio-economic factors that would help all humans to better prepare for the next pandemic. One of these critical factors is food access and food distribution as it could be high-risk population density places that are spreading the virus infections. More variables, such as income and people density, would influence the pandemic spread. In this study, we produced the spatial extent of COVID-19 cases with food outlets by using the spatial analysis method of geographic information systems. The methodology consisted of clustering techniques and overlaying the spatial extent mapping of the clusters of food outlets and the infected cases. Post-mapping, we analyzed these clusters’ proximity for any spatial variability, correlations between them, and their causal relationships. The quantitative analyses of the health issues and food access areas against COVID-19 infections and deaths were performed using machine learning regression techniques to understand the multi-variate factors. The results indicate a correlation between the dependent variables and independent variables with a Pearson correlation R²-score = 0.44% for COVID-19 cases and R² = 60% for COVID-19 deaths. The regression model with an R²-score of 0.60 would be useful to show the goodness of fit for COVID-19 deaths and the health issues and food access factors. Full article

Forensic medicine has always held the human environment, either seen as a source for pathological agents or the background of judicial events, in great consideration. The concept of the environment has evolved through time, expanding itself to include all the physical and virtual sub-spaces in which we exist. We can nowadays talk of technoenvironmental reality; virtual spaces exploded because of the COVID-19 pandemic making us come to terms with the fact that those are the places where we work, where we socialize and, even, where we meet our doctors and can be cured. Artificial Intelligence (AI) has contributed to shaping new virtual realities that have got their own rules yet to be discovered, carved and respected. We already fight a daily battle to save our natural environment: along with the danger of green crimes, comes the need for environmental justice and environmental forensic medicine that will probably develop a forensic branch and an experimental branch, to implement our technical culture leading to definition of the real dimension of the risk itself to improve the role of legal medicine in the Environmental Risk Management. While green criminology addresses widespread green crimes, a virtual environment criminology will also develop, maybe with a contribution of AI in the justice field. For a sustainable life, the environmental revolution must rapidly take place, and there is the need for a new justice, a new forensic medicine and a new criminology too. Full article

Cardiovascular diseases (CVDs) carry significant morbidity and mortality and are associated with substantial economic burden on healthcare systems around the world. Coronary artery disease, as one disease entity under the CVDs umbrella, had a prevalence of 7.2% among adults in the United States and incurred a financial burden of 360 billion US dollars in the years 2016–2017. The introduction of artificial intelligence (AI) and machine learning over the last two decades has unlocked new dimensions in the field of cardiovascular medicine. From automatic interpretations of heart rhythm disorders via smartwatches, to assisting in complex decision-making, AI has quickly expanded its realms in medicine and has demonstrated itself as a promising tool in helping clinicians guide treatment decisions. Understanding complex genetic interactions and developing clinical risk prediction models, advanced cardiac imaging, and improving mortality outcomes are just a few areas where AI has been applied in the domain of coronary artery disease. Through this review, we sought to summarize the advances in AI relating to coronary artery disease, current limitations, and future perspectives. Full article

Mantle cell lymphoma (MCL) is a subtype of mature B-cell non-Hodgkin lymphoma characterized by a poor prognosis. First, we analyzed a series of 123 cases (GSE93291). An algorithm using multilayer perceptron artificial neural network, radial basis function, gene set enrichment analysis (GSEA), and conventional statistics, correlated 20,862 genes with 28 MCL prognostic genes for dimensionality reduction, to predict the patients’ overall survival and highlight new markers. As a result, 58 genes predicted survival with high accuracy (area under the curve = 0.9). Further reduction identified 10 genes: KIF18A, YBX3, PEMT, GCNA, and POGLUT3 that associated with a poor survival; and SELENOP, AMOTL2, IGFBP7, KCTD12, and ADGRG2 with a favorable survival. Correlation with the proliferation index (Ki67) was also made. Interestingly, these genes, which were related to cell cycle, apoptosis, and metabolism, also predicted the survival of diffuse large B-cell lymphoma (GSE10846, n = 414), and a pan-cancer series of The Cancer Genome Atlas (TCGA, n = 7289), which included the most relevant cancers (lung, breast, colorectal, prostate, stomach, liver, etcetera). Secondly, survival was predicted using 10 oncology panels (transcriptome, cancer progression and pathways, metabolic pathways, immuno-oncology, and host response), and TYMS was highlighted. Finally, using machine learning, C5 tree and Bayesian network had the highest accuracy for prediction and correlation with the LLMPP MCL35 proliferation assay and RGS1 was made. In conclusion, artificial intelligence analysis predicted the overall survival of MCL with high accuracy, and highlighted genes that predicted the survival of a large pan-cancer series. Full article

The global burden of chronic kidney disease (CKD) is rising. A superior strategy to advance global kidney health is required to prevent and treat CKD early. Kidney development can be impacted during the first 1000 days of life by numerous factors, including malnutrition, maternal illness, exposure to chemicals, substance abuse, medication use, infection, and exogenous stress. In the current review, we summarize environmental risk factors reported thus far in clinical and experimental studies relating to the programming of kidney disease, and systematize the knowledge on common mechanisms underlying renal programming. The aim of this review is to discuss the primary and secondary prevention actions for enhancing kidney health from pregnancy to age 2. The final task is to address the potential interventions to target renal programming through updating animal studies. Together, we can enhance the future of global kidney health in the first 1000 days of life. Full article

Background: Moral distress has frequently been investigated in single healthcare settings and concerning a single type of professional. This study aimed to describe the experience of moral distress in all the types of professionals providing daily care to elderly patients and residents. Methods: The Grounded Theory approach, developed by Corbin and Strauss, was used. This study included participants from hospital and nursing homes of northern Italy. Purposive and theoretical sampling was used. Between December 2020 and April 2021, semi-structured interviews were conducted. Results: Thirteen participants were included in the study. Four categories were derived from the data: talking and listening, care provider wellbeing, decision making, protective factors, and potential solutions. The core category identified was “sharing daily”. Interviewees confirm how hard it may be to communicate to the elderly, but at the same time, how adequate communication with the leader is a protective factor of moral distress. They also confirm how communication is key to managing or downsizing misunderstandings at all levels. Findings highlight the scarcity of operators as a fundamental trigger of moral distress. Conclusions: Many determinants of this phenomenon lie behind the direct control of professionals, but education can help them learn how to prevent, manage, or downsize the consequences. Full article

Technologies play an essential role in monitoring, managing, and self-management of chronic diseases. Since chronic patients rely on life-long healthcare systems and the current COVID-19 pandemic has placed limits on hospital care, there is a need to explore disease monitoring and management technologies and examine their acceptance by chronic patients. We systematically examined the use of smartphone applications (apps) in chronic disease monitoring and management in databases, namely, Medline, Web of Science, Embase, and Proquest, published from 2010 to 2020. Results showed that app-based weight management programs had a significant effect on healthy eating and physical activity (p = 0.002), eating behaviours (p < 0.001) and dietary intake pattern (p < 0.001), decreased mean body weight (p = 0.008), mean Body Mass Index (BMI) (p = 0.002) and mean waist circumference (p < 0.001). App intervention assisted in decreasing the stress levels (paired t-test = 3.18; p < 0.05). Among cancer patients, we observed a high acceptance of technology (76%) and a moderately positive correlation between non-invasive electronic monitoring data and questionnaire (r = 0.6, p < 0.0001). We found a significant relationship between app use and standard clinical evaluation and high acceptance of the use of apps to monitor the disease. Our findings provide insights into critical issues, including technology acceptance along with regulatory guidelines to be considered when designing, developing, and deploying smartphone solutions targeted for chronic patients. Full article

Background: The COVID-19 pandemic has resulted in a major influx of intensive care unit (ICU) admissions. Currently, there is limited knowledge on the long-term outcomes of COVID-19 ICU-survivors and the impact on family members. This study aimed to gain an insight into the long-term physical, social and psychological functioning of COVID-19 ICU-survivors and their family members at three- and six-months following ICU discharge. Methods: A single-center, prospective cohort study was conducted among COVID-19 ICU-survivors and their family members. Participants received questionnaires at three and six months after ICU discharge. Physical functioning was evaluated using the MOS Short-Form General Health Survey, Clinical Frailty Scale and spirometry tests. Social functioning was determined using the McMaster Family Assessment Device and return to work. Psychological functioning was assessed using the Hospital Anxiety and Depression Scale. Results: Sixty COVID-19 ICU-survivors and 78 family members participated in this study. Physical functioning was impaired in ICU-survivors as reflected by a score of 33.3 (IQR 16.7–66.7) and 50 (IQR 16.7–83.3) out of 100 at 3- and 6-month follow-ups, respectively. Ninety percent of ICU-survivors reported persistent symptoms after 6 months. Social functioning was impaired since 90% of COVID-19 ICU-survivors had not reached their pre-ICU work level 6 months after ICU-discharge. Psychological functioning was unaffected in COVID-19 ICU-survivors. Family members experienced worse work status in 35% and 34% of cases, including a decrease in work rate among 18.3% and 7.4% of cases at 3- and 6-months post ICU-discharge, respectively. Psychologically, 63% of family members reported ongoing impaired well-being due to the COVID-19-related mandatory physical distance from their relatives. Conclusion: COVID-19 ICU-survivors suffer from a prolonged disease burden, which is prominent in physical and social functioning, work status and persisting symptoms among 90% of patients. Family members reported a reduction in return to work and impaired well-being. Further research is needed to extend the follow-up period and study the effects of standardized rehabilitation in COVID-19 patients and their family members. Full article

The physical and psychological consequences of critical illness may affect intensive care unit survivors for up to five years, and hence, health-related quality of life has emerged as an important measure of outcome in this population. We aimed at investigating the quality of life, the presence of anxiety and depression symptoms, and the correlations of clinical and psychological parameters with the quality of life scores in survivors of critical illness one year after discharge from intensive care. Widely used scales that have been validated for the Greek population were used. One thousand two hundred and seventy (1270) patients were assessed for eligibility. Inclusion criteria were age between 18 and 68 years and the presence of critical illness requiring endotracheal intubation and mechanical ventilation for more than three days. One hundred and four (104) patients were included in the final analysis; forty-nine age and sex-matched healthy volunteers were included for comparison. One year following intensive care unit discharge, survivors of critical illness had impaired quality of life scores, as measured with the WHOQOL-Bref, compared to healthy subjects (p < 0.001 for the physical and psychological domains, and p = 0.006 for the domain of social relationships). In addition, we found that quality of life scores were significantly lower in patients with comorbidities (p < 0.01), and correlated with the duration of ICU stay (r = −0.19, p = 0.04) and with the presence of symptoms suggestive of depression (r = −0.66, p < 0.0001) and post-traumatic stress disorder (r = −0.61, p < 0.0001). Approximately one-third of our patients scored high in the CES-D scale for depression, while the majority of them scored high in the STAI scale for anxiety symptoms. Full article

Several preventive measures have been applied to limit the COVID-19 pandemic, including successful the development and introduction of vaccines. The aim of this study was to investigate adherence to preventive measures and vaccination intentions among nursing students in three European countries and the factors associated with vaccination intention and advising vaccination. A cross-sectional study using convenience/snow-ball sampling strategy was performed in Slovenia, Poland, and Serbia between 12 February and 5 March 2021. Data from 872 eligible respondents were analyzed (mean age 23.5 ± 6.5 years, 89% female). Higher adherence to preventive behavior was declared by those working in healthcare (p < 0.001), engaged in COVID-19 departments (p < 0.001), had not had the disease yet (p < 0.001), and had children (p = 0.01). Those groups also expressed higher vaccination intention and advised vaccination to others. Higher vaccination intention and advising vaccination were mostly associated with belief in benefits of vaccine, trust in institutions, perceived effectiveness of vaccine, influence of social environment, protection of patients and perceived health care professionals’ duty. Fear of side effects and general refusal of vaccines are the main reasons for vaccination hesitancy. The results of the study indicate how higher education institutions can support the development of appropriate professional attitudes and behaviors among nursing students. Full article

(1) Background: There are persistent racial/ethnic disparities in cesarean delivery in the United States (U.S.), yet the causes remain unknown. One factor could be provider bias. We examined medical indications for cesarean delivery that involve a greater degree of physician discretion (more subjective) versus medical indications that involve less physician discretion (more objective) to better understand factors contributing to the higher rate among Micronesian, one of the most recent migrant groups in the state, compared to White women in Hawai‘i. (2) Methods: A retrospective chart review was conducted to collect data on 620 cesarean deliveries (N = 296 White and N = 324 Micronesian) at the state’s largest maternity hospital. Multivariate regression models were used to examine associations between maternal and obstetric characteristics and (1) subjective indication defined as non-reassuring fetal heart tracing (NRFHT) and arrest of labor disorders, and (2) objective indication defined as all other indications (e.g., malpresentation). (3) Results: We found that Micronesian women had significantly higher odds of cesarean delivery due to a subjective indication compared to White women (aOR: 4.17; CI: 2.52-6.88; P < 0.001; N = 619) after adjusting for multiple covariates. (4) Conclusion: These findings suggest unmeasured factors, possibly provider bias, may influence cesarean delivery recommendations for Micronesian women in Hawai‘i. Full article

With the rapid increase in the ageing population (60+) in China since 1999, the problem of supporting the aged is facing increasingly severe challenges. Based on the 2072 valid samples from the Chinese General Social Survey (CGSS) of 2017, a non-sequential multinomial logistic regression model was established to analyse the changing trends and micro-influencing factors of Chinese people’s cognition of old-age care responsibility (COACR). The result shows that offspring responsibility still is a common COACR, but this concept has been gradually weakened and been replaced by the responsibility of the government and the aged. Individual characteristics and relationships with relatives in the models all significantly affect people’s COACR. It is obviously unrealistic for China to completely rely on government and society to provide for the aged. The traditional ethical role of inter-generational responsibility in providing for the aged should be brought into play. Reshaping the inter-generational responsibility ethics of old-age care requires the joint efforts of government, society, families, individuals and other responsible subjects to construct a diversified old-age care service system. Full article