Search Results (227)

With the arrival of an aging society and the continuous extension of the human lifespan, the quality of life has not improved in a corresponding manner. People’s demand for happiness and health is increasing. As a result, a model emerged that integrates tourism and medical services, which is health tourism. This growing demand has prompted many service providers to see it as a business opportunity and enter the market. Tourism can help travelers release work stress and restore physical and mental balance; meanwhile, health check-ups and disease treatment can help them regain health. Consumers have long favored health and medical tourism because it helps relieve stress and promotes overall well-being. As people age, some consumers experience a gradual decline in physical functions, making it difficult for them to participate in regular travel services provided by traditional travel agencies. Therefore, this study aims to explore the service needs of health and medical tourism customers (tourists/patients) and the interrelationships among these service needs, so that health and medical tourism service providers can develop more customized and diversified services. This study identifies four key drivers of medical tourism services: medical services, medical facilities, tour planning, and hospitality facilities. This study uses the APA (attention and performance analysis) method to assess each dimension and criterion and utilizes the DEMATEL method with the NRM (network relationship map) to identify network relationships. By combining APA and NRM techniques, this study develops the APA-NRM technique to evaluate adoption strategies and identify suitable paths for health tourism services, providing tailored development strategies and recommendations for service providers to enhance the service experience. Full article

During the coronavirus 2019 pandemic, sports activities were restricted, raising concerns about their impact on the physical condition of adolescent athletes, which remained largely unquantified. This study was designed with two primary objectives: first, to precisely quantify and elucidate the differences in the physical condition of adolescent athletes before and after activity restrictions due to the pandemic; and second, to innovatively develop and validate a non-contact medical checkup application. Medical checks were conducted on 563 athletes designated for sports enhancement. Participants were junior high school students aged 13 to 15, and the sample consisted of 315 boys and 248 girls. Furthermore, we developed a smartphone application and compared self-checks using the application with in-person checks by orthopedic surgeons to determine the challenges associated with self-checks. Statistical tests were conducted to determine whether there were statistically significant differences in range of motion and flexibility parameters before and after the pandemic. Additionally, items with discrepancies between values self-entered by athletes using the smartphone application and values measured by specialists were detected, and application updates were performed. Student’s t-test was used for continuous variables, whereas the chi-square test was used for other variables. Following the coronavirus 2019 pandemic, athletes were stiffer than during the pre-pandemic period in terms of hip and shoulder joint rotation range of motion and heel–buttock distance. The dominant hip external rotation decreased from 53.8° to 46.8° (p = 0.0062); the non-dominant hip external rotation decreased from 53.5° to 48.0° (p = 0.0252); the dominant shoulder internal rotation decreased from 62.5° to 54.7° (p = 0.0042); external rotation decreased from 97.6° to 93.5° (p = 0.0282), and the heel–buttock distance increased from 4.0 cm to 10.4 cm (p < 0.0001). The heel–buttock distance and straight leg raising angle measurements differed between the self-check and face-to-face check. Although there are items that cannot be accurately evaluated by self-check, physical condition can be improved with less contact by first conducting a face-to-face evaluation under appropriate guidance and then conducting a self-check. These findings successfully address our primary objectives. Specifically, we demonstrated a significant decline in the physical condition of adolescent athletes following pandemic-related activity restrictions, thereby quantifying their impact. Furthermore, our developed non-contact medical checkup application proved to be a viable tool for monitoring physical condition with reduced contact, although careful consideration of measurable parameters is crucial. This study provides critical insights into the long-term effects of activity restrictions on young athletes and offers a practical solution for health monitoring during infectious disease outbreaks, highlighting the potential for hybrid checkup approaches. Full article

Background: Cancer survivors may continue to experience health issues that affect their quality of life and raise the risk of other chronic diseases. Methods: This study aimed to assess adherence to general health check-ups, cancer-specific screenings, and chronic disease management among five-year cancer survivors using nationally representative data from the Korea National Health and Nutrition Examination Survey (KNHANES) conducted between 2013 and 2021. A total of 2597 cancer survivors and 2458 matched non-cancer controls were selected via 1:1 propensity score matching based on demographic and lifestyle characteristics. We analyzed health behaviors (smoking and alcohol use), participation in general and cancer-specific screenings, and medication adherence for hypertension, diabetes, and dyslipidemia. Results: Compared to controls, cancer survivors, especially those diagnosed more than five years ago, were significantly less likely to participate in recommended cancer screenings (adjusted OR: 0.82, p = 0.014) and had lower adherence to treatment for hypertension (adjusted OR: 1.84, p = 0.004) and dyslipidemia (adjusted OR: 1.42, p = 0.026). However, cancer survivors were less likely to smoke or consume alcohol. Conclusions: These findings underscore the need for comprehensive survivorship care policies that integrate both cancer surveillance and chronic disease management. Full article

Objectives: Scarce data are available regarding preventive medicine in forcibly displaced populations especially regarding non-communicable diseases like neoplasia, while even more limited data are available on Ukrainian refugees in Romania. To address this research gap, the present analysis was performed to investigate Ukrainian refugee women’s beliefs, attitudes, and opinions towards the Romanian and Ukrainian healthcare system in a comparison model while focusing on the HPV immunization rates and factors influencing the uptake for themselves and their children. Methods: Participants were recruited using the snowball sampling method through their General Practitioner (GP) and a health mediator. Results: In total, 105 women completed the online or physical survey. The mean age was 50 years. In total, 40% of women had not been to a gynecological check-up in 3 or more years, and more than 56% had never been screened. Only four were vaccinated against HPV, and none remembered which type of vaccine was dispensed or how many doses were utilized. The primary hindrances to accessing health services or immunization programs were language barriers, financial burdens, and a lack of information. Respondents’ general distrust of health systems and healthcare workforces were recurrent themes. Relationship status, living arrangements, and previous engagement in screening practices influenced immunization rates. Perceiving the healthcare officials as proactive concerning optional vaccination programs such as HPV immunization and actively receiving recommendations drove respondents to pursue vaccination. Conclusions: This analysis offers a foundational insight into the specific needs of refugee women. It can guide the development of effective public health interventions to improve health outcomes and vaccination rates among Ukrainian refugees in Romania. Tailored preventive campaigns with adequate native language information and prompts from medical experts in designated centers should be deployed to ensure inclusive tactics for vulnerable populations. Full article

Background: The aim of this study was to assess the experiences and attitudes of dentists toward treating patients with mental disorders and to investigate how these attitudes correlate with factors such as sex, age, and years of clinical experience. Methods: A cross-sectional pilot study was conducted from March to July 2021 via an online questionnaire. The questionnaire consisted of four sections: demographic information, self-assessment of experiences and attitudes toward treating patients with mental disorders, knowledge of psychotropic drugs and their interactions, and personal experiences with patient care. Results: Overall, 101 dentists, mostly females (78.22%), completed the questionnaire, of which 65.35% consistently checked whether their patients were taking psychotropic drugs and 48.51% inquired about mental disorders when taking medical history. Still, 39.60% reported unpleasant experiences when treating such patients—mostly female dentists—and as many as 14.85% of all dentists refused to treat them. More than 94% of dentists recognized that patients with mental disorders are at greater risk for poor oral health and in need of early referral and professional support. Older dentists demonstrated better knowledge of oral manifestations and drug interactions relevant to dental treatment. Conclusions: Our findings highlight the need for improved training, an interdisciplinary approach, and greater dissemination of new scientific evidence for managing patients with mental disorders in dental practice. Considering that this is a pilot study using a combination of non-probabilistic convenience and snowball sampling method, the findings should be considered preliminary and interpreted with caution, as the sampling method limits the ability to make statistical inferences. Full article

Background and Objectives: Physical activity represents a cornerstone in the management of diabetes mellitus; however, the majority of persons with diabetes remain insufficiently active. Current guidelines emphasise the need to educate individuals with diabetes on physical activity at each clinical visit. The aim of the study was to develop an adequate instrument and test diabetologists’ knowledge on physical activity and related guidelines in diabetes, as well as investigate their prescribing habits. Materials and Methods: The instrument was developed with four diabetologists using Delphi and RAND appropriateness methods, then distributed to diabetologist societies in 12 Southeast European countries for anonymous completion by their members. Data were analysed using Mann–Whitney U test and Pearson ${ x}^2$ test. Results: Out of 302 analysed respondents, 123 (41%) worked at university hospitals, at average four days a week in outpatient departments, mean number of patients was 16 a day; 95 (32%) had a PhD, and 105 (35%) university teaching positions. Median overall knowledge was 15 (Q1–Q3, 13–17) out of 22 maximum points. 26% diabetologists knew recommended level of physical activity for people with diabetes. Physical activity goals were discussed during check-ups in 53.0% of cases; re-education and goal adjustments were provided in 33.4% when health status changed; and clear instructions were documented in 25.5% of medical records. Conclusions: Diabetologists’ overall knowledge of physical activity was found to be at least satisfactory in 90% of participants. Knowledge of the guidelines is insufficient in 75% of participants. The prescribing habits are inadequate in half of the participants. Full article

Large language models (LLMs) are transforming the capabilities of medical chatbots by enabling more context-aware, human-like interactions. This review presents a comprehensive analysis of their applications, technical foundations, benefits, challenges, and future directions in healthcare. LLMs are increasingly used in patient-facing roles, such as symptom checking, health information delivery, and mental health support, as well as in clinician-facing applications, including documentation, decision support, and education. However, as a study from 2024 warns, there is a need to manage “extreme AI risks amid rapid progress”. We examine transformer-based architectures, fine-tuning strategies, and evaluation benchmarks specific to medical domains to identify their potential to transfer and mitigate AI risks when using LLMs in medical chatbots. While LLMs offer advantages in scalability, personalization, and 24/7 accessibility, their deployment in healthcare also raises critical concerns. These include hallucinations (the generation of factually incorrect or misleading content by an AI model), algorithmic biases, privacy risks, and a lack of regulatory clarity. Ethical and legal challenges, such as accountability, explainability, and liability, remain unresolved. Importantly, this review integrates broader insights on AI safety, drawing attention to the systemic risks associated with rapid LLM deployment. As highlighted in recent policy research, including work on managing extreme AI risks, there is an urgent need for governance frameworks that extend beyond technical reliability to include societal oversight and long-term alignment. We advocate for responsible innovation and sustained collaboration among clinicians, developers, ethicists, and regulators to ensure that LLM-powered medical chatbots are deployed safely, equitably, and transparently within healthcare systems. Full article

Clinical documentation, particularly the hospital discharge report (HDR), is essential for ensuring continuity of care, yet its preparation is time-consuming and places a considerable clinical and administrative burden on healthcare professionals. Recent advancements in Generative Artificial Intelligence (GenAI) and the use of prompt engineering in large language models (LLMs) offer opportunities to automate parts of this process, improving efficiency and documentation quality while reducing administrative workload. This study aims to design a digital system based on LLMs capable of automatically generating HDRs using information from clinical course notes and emergency care reports. The system was developed through iterative cycles, integrating various instruction flows and evaluating five different LLMs combined with prompt engineering strategies and agent-based architectures. Throughout the development, more than 60 discharge reports were generated and assessed, leading to continuous system refinement. In the production phase, 40 pneumology discharge reports were produced, receiving positive feedback from physicians, with an average score of 2.9 out of 4, indicating the system’s usefulness, with only minor edits needed in most cases. The ongoing expansion of the system to additional services and its integration within a hospital electronic system highlights the potential of LLMs, when combined with effective prompt engineering and agent-based architectures, to generate high-quality medical content and provide meaningful support to healthcare professionals. Hospital discharge reports (HDRs) are pivotal for continuity of care but consume substantial clinician time. Generative AI systems based on large language models (LLMs) could streamline this process, provided they deliver accurate, multilingual, and workflow-compatible outputs. We pursued a three-stage, design-science approach. Proof-of-concept: five state-of-the-art LLMs were benchmarked with multi-agent prompting to produce sample HDRs and define the optimal agent structure. Prototype: 60 HDRs spanning six specialties were generated and compared with clinician originals using ROUGE with average scores compatible with specialized news summarizing models in Spanish and Catalan (lower scores). A qualitative audit of 27 HDR pairs showed recurrent divergences in medication dose (56%) and social context (52%). Pilot deployment: The AI-HDR service was embedded in the hospital’s electronic health record. In the pilot, 47 HDRs were autogenerated in real-world settings and reviewed by attending physicians. Missing information and factual errors were flagged in 53% and 47% of drafts, respectively, while written assessments diminished the importance of these errors. An LLM-driven, agent-orchestrated pipeline can safely draft real-world HDRs, cutting administrative overhead while achieving clinician-acceptable quality, not without errors that require human supervision. Future work should refine specialty-specific prompts to curb omissions, add temporal consistency checks to prevent outdated data propagation, and validate time savings and clinical impact in multi-center trials. Full article

Firefighters experience high noise levels from various sources, such as sirens, alarms, pumps, and emergency vehicles. Unlike industrial workers who experience continuous noise exposure, firefighters are subject to intermittent high-intensity noise, increasing their risk of noise-induced hearing loss (NIHL). Despite global concerns regarding firefighters’ auditory health, research on Korean firefighters remains limited. This study aimed to assess personal noise exposure among Korean firefighters across three primary job roles—fire suppression, rescue, and emergency medical services (EMS)—and to predict worst-case noise exposure scenarios. This study included 115 firefighters from three fire stations (one urban, two suburban). We measured personal noise exposure using dosimeters attached near the ear following the Korean Ministry of Employment and Labor (MOEL) and International Organization for Standardization (ISO) criteria. Measurements included threshold levels of 80 dBA, exchange rates of 5 dB (MOEL) and 3 dB (ISO), and a peak noise criterion of 140 dBC. We categorized firefighters’ activities into routine tasks (shift handovers, equipment checks, training) and emergency responses (fire suppression, rescues, EMS calls). We performed statistical analyses to compare noise levels across job roles, vehicle types, and specific tasks. The worst-case exposure scenarios were estimated using 10th percentile recorded noise levels. The average 8 h time-weighted noise exposure levels varied significantly by job role. Rescue personnel exhibited the highest mean noise exposure (MOEL: 71.4 dBA, ISO: 81.2 dBA; p < 0.05), whereas fire suppression (MOEL: 66.5 dBA, ISO: 74.2 dBA) and EMS personnel (MOEL: 68.6 dBA, ISO: 73.0 dBA) showed no significant difference. Peak noise levels exceeding 140 dBC were most frequently observed in rescue operations (33.3%), followed by fire suppression (30.2%) and EMS (27.2%). Among vehicles, noise exposure was the highest for rescue truck occupants. Additionally, EMS personnel inside ambulances had significantly higher noise levels than drivers (p < 0.05). Certain tasks, including shift handovers, equipment checks, and firefighter training, recorded noise levels exceeding 100 dBA. Worst-case scenario predictions indicated that some work conditions could lead to 8 h average exposures surpassing MOEL (91.4 dBA) and ISO (98.7 dBA) limits. In this study, Korean firefighters exhibited relatively low average noise levels. However, when analyzing specific tasks, exposure was sufficiently high enough to cause hearing loss. Despite NIHL risks, firefighters rarely used hearing protection, particularly during routine tasks. This emphasizes the urgent need for hearing conservation programs, including mandatory hearing protection during high-noise activities, noise exposure education, and the adoption of communication-friendly protective devices. Future research should explore long-term auditory health outcomes and assess the effectiveness of noise control measures. Full article

Background: Reusable, machine-processable clinical decision support system (CDSS) rules have not been widely achieved in the medical informatics field. This study introduces the process, results, challenges faced, and lessons learned while converting the United States of America Centers for Disease Control and Prevention (CDC)-recommended immunization schedules (2022) to machine-processable CDSS rules. Methods: We converted the vaccination schedules into tabular, charts, MS Excel, and clinical quality language (CQL) formats. The CQL format can be automatically converted to a machine-processable format using existing tools. Therefore, it was regarded as a machine-processable format. The results were reviewed, verified, and tested. Results: We have developed 465 rules for 19 vaccines in 13 categories, and we have shared the rules via GitHub to make them publicly available. We used cross-review and cross-checking to validate the CDSS rules in tabular and chart formats. The CQL files were tested for syntax and logic with hypothetical patient HL7 FHIR resources. Our rules can be reused and shared by the health IT industry, CDSS developers, medical informatics educators, or clinical care institutions. The unique contributions of our work are twofold: (1) we created ontology-based, machine-processable, and reusable immunization recommendation rules, and (2) we created and shared multiple formats of immunization recommendation rules publicly which can be a valuable resource for medical and medical informatics communities. Conclusions: These CDSS rules can be important contributions to informatics communities, reducing redundant efforts, which is particularly significant in resource-limited settings. Despite the maturity and concise presentation of the CDC recommendations, careful attention and multiple layers of verification and review are necessary to ensure accurate conversion. The publicly shared CDSS rules can also be used for health and biomedical informatics education and training purposes. Full article

Background/Objectives: To evaluate the role of temporomandibular disorder (TMD)-related diagnostics in orthodontic treatment routines and investigate what consequences are drawn from symptoms concerning orthodontic treatment planning and therapy. Methods: All officially listed orthodontists in Germany were surveyed about their professional background, TMD-related specialization, and concrete clinical procedures. Anonymized responses were systematized, manually checked, and statistically analyzed. Differences in reported TMD-related procedures depending on orthodontists’ professional experience and specialization were determined using Fisher’s exact tests. Results: A total of 2359 questionnaires were sent out, of which 630 could be evaluated. The majority of the orthodontists surveyed stated that they perform either a brief TMD screening or a complete functional analysis. In total, 21.1% of the respondents base their examination on the patient’s medical history. A second complete functional analysis is performed by 33% of the responding orthodontists during the course of orthodontic therapy, and by 56.6% only in the case of an initial pathological finding. For 60.1% of the respondents, pre-therapeutically diagnosed, non-painful temporomandibular joint clicking has an influence on orthodontic treatment planning. Only 4.3% of respondents take no further action prior to orthodontic therapy in the case of TMD symptoms. There is an indication that professional experience has no influence on the procedure, whereas a specialization in the field of TMDs does. Conclusions: A discrepancy between the current state of research and standard procedures in German orthodontic practices may lead to an overly detailed examination. However, this has no health disadvantages for the patient. Full article

Background: the purpose of this study was to explore the effect of 10 weeks of yoga intervention on the mental health outcomes (stress, anxiety, and depression), quality of life, emotional regulation, and quality of sleep of medical students. Method: In the current experimental study, 220 medical students, with a mean age of 21.36 ± 2.20 years, participated in a 10-week yoga intervention at the University of Pécs. Data were collected before and after the intervention using the validated questionnaires DASS-21, WHOQOL-BREF, PSQI, and DERS. The distribution of data was checked using the Kolmogorov–Smirnov test. A paired sample T-test was used to compare the mean of the continuous variable. Stepwise linear regression was used to assess the association between mental health outcomes and quality-of-life variables. Results: The present study shows a significant reduction in (p < 0.001), depression (p < 0.001), and anxiety (p < 0.001) for participants, and overall quality of life (p < 0.001), quality of sleep (p < 0.001), and emotional regulation (p < 0.001) significantly improved after the intervention. The stepwise linear regression shows a strong association between higher levels of anxiety (β = 0.608, R² = 0.366) and depression (β = 0.608, R² = 0.392), with higher stress levels and improvement in environmental conditions being associated with a decrease in stress levels (β = −0.392, R² = 0.087). Conclusions: the current study shows that yoga significantly improved the mental health and well-being of medical students, improving quality of life, quality of sleep, and emotional regulation. Registered Clinical Trial: NCT06661603. Full article

Objective: This study intends to evaluate simulated experiences provided to pharmacy students that directly compare the perspective of patients managing chronic disease states through traditional means without compliance aids to those using compliance aids, such as continuous glucose monitors (CGMs) and other devices. Methods: This simulation was conducted with third-year pharmacy students enrolled in the ambulatory care elective course at the University of Florida College of Pharmacy. It was designed to simulate a patient responsible for self-administering an array of medications for multiple chronic diseases that the students are likely to encounter during clinical practice. For the first week, students were tasked with adhering to a complex medication schedule from their associated pill bottles without the use of compliance aids (pill organizers, alarms, etc.) and checking their blood glucose twice daily using a traditional glucometer. In the second week, students continued the role of the patient; however, they were provided with compliance aids and encouraged to set alarms and use CGMs. Using a questionnaire developed based on the traditional Likert scale model, the students were able to quantify their experiences in a way that allowed the investigators to observe any changes. Results: Regarding the overall implications of this experience, most participants (>80%) agreed that this project increased their understanding of the value of compliance aids and devices and encouraged them to not only incorporate them into their future patient care plans but also advocate for accessibility to improve health outcomes. Conclusion: Students who completed this experience reported better adherence to chronic disease state control using compliance aids and, in turn, the applicability of the use of compliance aids in managing those with complex medication regimens. This simulation may encourage future pharmacists to incorporate compliance aids with their patients to improve health outcomes. Full article

Objective: To investigate the association between coffee consumption and visceral obesity (VO). Methods: We conducted a retrospective, cross-sectional, observational study using data from 45,630 participants who underwent a general health check-up program at a medical center in Japan between 2015 and 2018. After excluding participants with missing data or duplicated visits, 19,253 subjects were included in the final analysis. Visceral fat area (VFA) was measured using computed tomography (CT), and data on metabolic disorders, history of lifestyle-related diseases, coffee consumption, and other lifestyle factors were collected via a self-administered questionnaire. Results: The mean ± SD VFA was 74.0 ± 49.7 cm², and the mean ± SD age was 53.3 ± 9.8 years. The prevalence of VO (VFA ≥ 100 cm²) was 25.5%. The mean coffee consumption was 1.7 ± 1.3 cups per day. In multivariate logistic regression analysis, coffee consumption was significantly inversely associated with VO. Compared to non-coffee drinkers, the odds ratios (ORs) for VO were as follows: 1 or 2 cups/day (OR: 0.75, 95% confidence interval [CI]: 0.68–0.83), 3 or 4 cups/day (OR: 0.67, 95% CI: 0.59–0.75), and ≥5 cups/day (OR: 0.65, 95% CI: 0.53–0.80). In multiple linear regression analysis, coffee consumption was significantly associated with lower VFA (Model 3: β = −1.86, SE = 0.230, p < 0.05). Conclusions: Coffee consumption was significantly associated with lower VO. Full article

In this paper, we present a comprehensive survey on the pervasive issue of medical misinformation in social networks from the perspective of information technology. The survey aims at providing a systematic review of related research and helping researchers and practitioners navigate through this fast-changing field. Research on misinformation spans multiple disciplines, but technical surveys rarely focus on the medical domain. Existing medical misinformation surveys provide broad insights for various stakeholders but lack a deep dive into computational methods. This survey fills that gap by examining how fact-checking and fake news detection techniques are adapted to the medical field from a computer engineering perspective. Specifically, we first present manual and automatic approaches for fact-checking, along with publicly available fact-checking tools. We then explore fake news detection methods, using content, propagation features, or source features, as well as mitigation approaches for countering the spread of misinformation. We also provide a detailed list of several datasets on health misinformation. While this survey primarily serves researchers and technology experts, it can also provide valuable insights for policymakers working to combat health misinformation. We conclude the survey with a discussion on the open challenges and future research directions in the battle against health misinformation. Full article