Search Results (1,185)

This article explores strategies for integrating anti-racist approaches into university-level study of religion teaching on multiple levels, including curriculum design, selection of teaching materials, self-reflection practices, responses to concrete classroom situations and fostering environments that protect students of colour while encouraging “white” students to critically examine their own privileges. To contextualize this endeavour, the article first outlines the current situation and describes some challenges related to racism and anti-racism efforts within a Swiss university context, drawing on recent empirical studies. This is followed by an examination of the historical development of racial thought, culminating in contemporary discussions of neo-racism and its connection with the classification category religion. A working definition of racism suitable for academic teaching is then proposed. The article further investigates the relationship between racism and the study of religion, arguing that the discipline has a crucial role to play in addressing and combating racist ideologies. This argument is supported by some empirical data from the author’s doctoral research, as well as examples drawn from the author’s teaching experience at the University of Zurich. By combining historical analysis with practical teaching strategies, thearticle aims to provide a coherent framework for embedding anti-racist principles in higher education. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

We present a novel method to estimate blood cortisol concentration from sweat cortisol measurements, incorporating a kinetic model to simulate cortisol transport dynamics. Cortisol dysregulation is observed in conditions like Cushing’s syndrome, characterized by excessive cortisol production, and stress-related disorders, which can lead to metabolic disturbances, anxiety, and impaired overall health. Sweat-sensing technology offers a non-invasive and continuous alternative to blood sampling. However, the limited research exploring the sweat–blood cortisol relationship in patients shows a moderate correlation ($R<0.6$), hindering its clinical application for long-term monitoring. In this paper, we propose a novel kinetic model describing cortisol transport from blood to sweat. The model was validated using data from 44 patients before and after cardiac surgery. A high Pearson correlation coefficient of 0.95 (95% CI: 0.92–0.97) was observed between our model’s estimated and experimental blood cortisol concentrations. Moreover, the method enables personalized estimation of physiological parameters, accurately reflecting patients’ status under varying clinical conditions. The method paves the way for the clinical application of long-term, non-invasive monitoring of cortisol using sweat-sensing technology. Enabling the personalized estimation of physiological parameters could potentially support clinical decision-making, helping doctors diagnose and monitor patients with health conditions involving cortisol dysregulation. Full article

Although career choice is a kind of individual behavior, as the gatekeeper of the discipline, doctoral students’ academic career intention reflects the attractiveness of the academic labor market and determines the sustainable development of academic careers. An analysis of data (N = 1322) from a survey among Chinese doctoral students reveals that (1) environmental factors, such as departmental atmosphere and advisor support, cognitive factors like academic interest and research self-efficacy, as well as behavioral factors including research engagement and publication rates, significantly promote doctoral students’ academic career intentions; (2) female doctoral students and those from prestigious institutions show stronger academic career aspirations; (3) the influence of interest factors on doctoral students’ commitment to an academic career is particularly pronounced, especially in the field of fundamental science; (4) a clear understanding of career paths positively moderates the effect of interest on academic career intentions. Within increasingly severe competition in the global academic labor market, it is necessary to provide more support for doctoral students who are willing to engage in academic careers by enhancing career planning guidance for doctoral students and supporting them in making rational career plans and adequate preparations. Full article

This study investigates the complex relationship between levels of religiosity and attitudes toward secularization among individuals receiving higher religious education in Türkiye. Secularization is defined as the diminishing influence of religion in public life and the rise of critical attitudes toward religious norms, a process that accelerated particularly during the modernization period following the establishment of the Republic. The primary aim of the research is to analyze whether there is a significant relationship between secular attitudes and the perceived influence of Islam among theology faculty students. The study employs a quantitative, descriptive survey design and includes a sample of 380 undergraduate, graduate, and doctoral students from the faculties of theology at Kocaeli, Sakarya, Marmara, and Istanbul universities. Data were collected using the “Perceived Influence of Religion Scale” and the “Secular Attitude Scale,” both of which demonstrated acceptable reliability (Cronbach’s Alpha = 0.70). Demographic variables such as age, gender, marital status, parental education level, type of education (formal or distance), and economic status were also incorporated into the analysis. The findings revealed statistically significant differences based on marital status, parental education level, type of education program, and previous educational background. For instance, single students reported perceiving a higher influence of religion compared to their married counterparts, while students with fathers who held university degrees perceived a lower influence of religion. These results offer valuable insights into how modern social transformations influence religious attitudes and practices. Full article

Accurate detection of fractures in X-ray images is important to initiate appropriate medical treatment in time—in this study, an advanced combined attention CNN model with multiple attention mechanisms was developed to improve fracture detection by deeply representing features. Specifically, our model incorporates squeeze blocks and convolutional block attention module (CBAM) blocks to improve the model’s ability to focus on relevant features in X-ray images. Using computed tomography X-ray images, this study assesses the diagnostic efficacy of the artificial intelligence (AI) model before and after optimization and compares its performance in detecting fractures or not. The training and evaluation dataset consists of fractured and non-fractured X-rays from various anatomical locations, including the hips, knees, lumbar region, lower limb, and upper limb. This gives an extremely high training accuracy of 99.98 and a validation accuracy 96.72. The attention-based CNN thus showcases its role in medical image analysis. This aspect further complements a point we highlighted through our research to establish the role of attention in CNN architecture-based models to achieve the desired score for fracture in a medical image, allowing the model to generalize. This study represents the first steps to improve fracture detection automatically. It also brings solid support to doctors addressing the continued time to examination, which also increases accuracy in diagnosing fractures, improving patients’ outcomes significantly. Full article

Background/Objectives: Extracting meaningful medical information from chest X-ray images and transcribing it into text is a complex task that requires a high level of expertise and directly affects clinical decision-making processes. Automatic reporting systems for this field in Turkish represent an important gap in scientific research, as they have not been sufficiently addressed in the existing literature. Methods: A deep learning-based approach called Model-SEY was developed with the aim of automatically generating Turkish medical reports from chest X-ray images. The Swin Transformer structure was used in the encoder part of the model to extract image features, while the text generation process was carried out using the cosmosGPT architecture, which was adapted specifically for the Turkish language. Results: With the permission of the ethics committee, a new dataset was created using image–report pairs obtained from Elazıg Fethi Sekin City Hospital and Indiana University Chest X-Ray dataset and experiments were conducted on this new dataset. In the tests conducted within the scope of the study, scores of 0.6412, 0.5335, 0.4395, 0.4395, 0.3716, and 0.2240 were obtained in BLEU-1, BLEU-2, BLEU-3, BLEU-4, and ROUGE word overlap evaluation metrics, respectively. Conclusions: Quantitative and qualitative analyses of medical reports autonomously generated by the proposed model have shown that they are meaningful and consistent. The proposed model is one of the first studies in the field of autonomous reporting using deep learning architectures specific to the Turkish language, representing an important step forward in this field. It will also reduce potential human errors during diagnosis by supporting doctors in their decision-making. Full article

Phytohormones, representing a diverse group of molecules, are essential in orchestrating plant growth and development, ensuring the smooth progression of the entire life cycle from germination to senescence. Emerging research reveals that these compounds also exert biological effects in non-plant systems, including animals. Although some phytohormones can be harmful, their health-promoting potential is rapidly gaining attention. This has sparked a growing interest in exploring plant hormones as novel therapeutic agents, particularly in precision medicine. This review brings together a multidisciplinary team—plant physiologists, a pharmacist, and a medical doctor—to delve into the latest insight surrounding the health-related impacts of plant hormones on animal systems, with a particular emphasis on human health. We comprehensively analyze their effects, weighing both the benefits and potential risks. Key phytohormones—auxin, abscisic acid, cytokinins, jasmonates, ethylene, strigolactones, and gibberellins—are highlighted for their remarkable regulatory roles in animal physiology, with a special focus on their implications for human health. Our discussion reveals how phytohormones may help address critical health challenges, particularly those related to aging populations, including neurodegenerative diseases, diabetes, and cancers. These plant-derived molecules are emerging as promising candidates for future drug development and nutritional therapies. Hence, a deeper understanding of phytohormone action may not just revolutionize agriculture but also open new frontiers in medicine and human health. Full article

Achieving health equity for people with disabilities requires addressing the barriers that they face when accessing healthcare. Older adults with disabilities may experience compounded disparities, yet little research has explored their satisfaction with health facility personnel, including non-healthcare staff. This study examines differences in satisfaction with health facility personnel between younger (18–59 years) and older (60+) adults with disabilities in Chile. Data from the 2024 Disability and Citizenship (DISCA) survey were analysed using chi-square tests to examine differences between younger and older people with disabilities with regard to their satisfaction with health facility personnel. Ordered logistic regressions were employed to predict high satisfaction, given socioeconomic and health-related variables. Findings indicated that a higher percentage of older adults with disabilities reported high satisfaction with health facility personnel compared to younger adults. Ordered logistic regressions confirmed that older adults had greater odds of reporting high satisfaction with doctors (OR: 3.83), other health professionals (OR: 4.66), paramedical technicians (OR: 4.31), and administrative staff (OR: 3.13). These results suggest that age influences satisfaction levels among people with disabilities, potentially due to varying expectations, experiences, or interactions with health facility personnel. Understanding the underlying reasons for these age-related differences is essential to inform policies and practices that ensure equitable, person-centred care for people with disabilities across the life course. Full article

Introduction: Access of transgender and gender diverse (TGD) youth to gender-affirming medical care (GAMC) has become a contentious topic in the West, with many members of the general population, politicians, and even some experts and academic researchers voicing concerns about possible adverse effects of GAMC on the mental and physical health of TGD youth. Due to these concerns, recent years have seen a significant rise in legislation restricting TGD youth from accessing GAMC in countries such as the United States, the United Kingdom, and Canada. However, in this critical review of the literature on the psychological (e.g., anxiety, depression, suicide, and body satisfaction) and physical (e.g., bone health, cognitive function, and fertility) health outcomes associated with GAMC among TGD youth, we argue that, given the state of current research, youth should not be restricted from accessing GAMC. Conclusions: Our findings reinforce the importance of close monitoring by doctors, counselling for TGD youth with respect to potential risks, and increased studies on the topic, especially those focusing on reproductive health. Full article

Maternal mortality and morbidity are critical health challenges in the U.S., and building the perinatal workforce is a key to providing high-quality maternal medical care and services. Texas Southern University (TSU), home to a Doctor of Pharmacy program, launched the first Maternal Health Education and Research Training (MHERT) program to educate a cohort of high school, pharmacy, and health sciences students. Aiming to raise awareness of maternal health issues, build research skills, and promote action-based solutions. MHERT integrated online self-paced interactive lessons with hands-on research or community projects. Topics included maternal health epidemiology, causes of morbidity and mortality, research methods, literature reviews, and the development of action plans addressing maternal health challenges. Assessment tools included quizzes, open-ended reflection responses, training surveys, and course evaluations. Running from 3 June to 26 July 2024, the program enrolled 22 students. All participants completed both course components. Course evaluations showed strong and consistent satisfaction with the program, with teaching effectiveness rated at 95% and 96% for mid-program and final evaluations, respectively. MHERT enhanced participants’ understanding of maternal health, improved research skills, and encouraged community engagement and interdisciplinary collaboration. It offers a scalable model to strengthen public health education among high school, pharmacy, and health sciences students. Full article

Classification of thyroid images based on the Bethesda category using Diff-Quick stained images can assist in diagnosing thyroid cancer. This paper proposes a cross-domain approach that modifies the original deep learning network designed to classify X-ray images to classify stained thyroid images. Since the Diff-Quick stained images have large and high-quality sizes with tiny cells with essential characteristics that can help a doctor diagnose, resizing images is required to maintain this characteristic, which is significant. Thus, in this paper, we also research and evaluate the performance of different interpolation methods, including linear and cubic interpolation. The experiment results evaluated on a private dataset present promising results in the thyroid image classification of the proposed approach. Full article

The type of non-professional or professional support received affects the quality of life of the patient and their caregivers. Social support is the type of interaction that is taken by the patient and his caregivers in a problematic, difficult, stressful, or critical situation. Aim: The aim of the study was to assess the impact of social support on the functioning of patients under nursing home care. Material and methods: The study included 148 chronically ill patients under home nursing care. The study used the diagnostic survey method; the research technique was a questionnaire containing basic data about the respondent and the Social Support Scale (SWS) by Krystyna Kmiecik-Baran. Results: The need to continue the causal treatment at home means that the main source of support for care beneficiaries are nurses who provide medical services at the patient’s home, supported by doctors and family members of the patient. According to patients’ subjective assessment of the support they received from nurses, patients rated the informational support provided by nurses highest at 14.3 points and emotional support at 13.3 points (SD 1.776). on a scale where the maximum score was 16 points. In the opinion of the surveyed patients, the value-added support provided was the lowest-rated category by patients, 9.74 points (SD 2.505). Instrumental support was also rated very poorly by the respondents (10.17 points (SD 2.069). In each category, there was no statistically significant difference at the p < 0.05 level in the respondents’ evaluation, which means that the expressed opinion on each type of support from the highest to the lowest evaluation: informational, emotional, instrumental, and evaluative—overlapped in the patient group and the family group. Conclusions: Patients under home care highly appreciated the support provided to them by the nursing staff. Social support for a chronically ill person who requires constant care and care by the nursing staff is a form of direct impact that relieves stress and tension, minimizes the effects of the disease, directly affects the course of treatment and care, and prevents stigmatization. Full article

In recent years, Electronic Medical Record (EMR) sharing has played an indispensable role in optimizing clinical treatment plans, advancing medical research in biomedical science. However, existing EMR management schemes often face security risks and suffer from inefficient search performance. To address these issues, this paper proposes a secure EMR sharing scheme based on blockchain and searchable encryption. This scheme implements a decentralized management system with enhanced security and operational efficiency. Considering the scenario of EMRs requiring confirmation of multiple doctors to improve safety, the proposed solution leverages Shamir’s Secret Sharing to enable multi-party authorization, thereby enhancing privacy protection. Meanwhile, the scheme utilizes Bloom filter and vector operation to achieve efficient data search. The proposed method maintains rigorous EMR protection while improving the search efficiency of EMRs. Experimental results demonstrate that, compared to existing methodologies, the proposed scheme enhances security during EMR sharing processes. It achieves higher efficiency in index generation and trapdoor generation while reducing keyword search time. This scheme provides reliable technical support for the development of intelligent healthcare systems. Full article

Background/Objectives: The prevalence of people with incurable and progressive diseases in primary health care is high. Family doctors and nurses must be active agents in the early identification of palliative needs and the implementation of palliative approaches in cases of low to intermediate complexity. While there is a need for early referral of more complex palliative care (PC) cases to specialized teams, primary health care (PHC) professionals lack the confidence or skill to describe their role. This study sought to explore and describe (a) the practices of PHC professionals regarding their PC provision; (b) the barriers regarding access and referral of patients to specialized PC services; and (c) the strategies used or recommended to mitigate difficulties in accessing and referring to specialized PC. Methods: A descriptive qualitative study was carried out, using five focus groups conducted with nursing and medical staff at three local health units in the central region of Portugal. Semi-structured interviews were conducted, and then recorded, transcribed, and analyzed through a thematic analysis approach. The reporting of this research follows the COREQ checklist. Results: In total, 34 PHC professionals participated in this study. The majority of participants were women (n = 26) and family doctors (n = 24). Their mean age was 43.8 ± 11.9 (range: 29 to 65 years). The findings were organized into three core themes: (1) the contours of palliative action developed by PHC teams; (2) barriers to access and safe transition between PHC and specialized PC; and (3) ways to mitigate difficulties in accessing and referring to specialized PC. Conclusions: Our findings highlight the fundamental role of PHC professionals in providing primary PC, and in identifying PC needs and referring patients to PC early on, while exposing the systemic and interpersonal challenges that hinder these processes. To overcome these challenges, it is essential to invest in the development of integrated care models that promote practical, low-bureaucratic referral processes and capture the human resources necessary for the adequate follow-up of users. Full article