Journal of Multidisciplinary Healthcare最新文献

Purpose: This scoping review aimed to explore the application of mobile health (mHealth) in prostate cancer (PC) care, focusing on how these interventions have been applied to promote self-management and patient empowerment.

Methods: A comprehensive search was performed across multiple databases, including CNKI, PubMed, Embase, Web of Science, and Cochrane Library. Studies were included if they involved mHealth interventions for prostate cancer patients and assessed self-management or empowerment outcomes. Data were extracted from randomized controlled trials, quasi-experimental studies, and mixed-methods studies.

Results: Among the 30 studies included, mHealth interventions were reported to support improvements in self-management and patient empowerment. Interventions ranged from remote monitoring systems and mobile apps to social media platforms, with generally high feasibility and patient satisfaction. However, the evidence remains heterogeneous, and challenges persist regarding data privacy, platform customization for older adults, and integration of theoretical frameworks.

Conclusion: mHealth interventions show promise in enhancing prostate cancer management by supporting patient empowerment and self-management. Nevertheless, evidence is still limited, and future research should prioritize personalized approaches and address privacy concerns to better establish their role and optimize impact.

Objective: As a non-invasive, convenient and real-time imaging tool, ultrasound has provided new imaging evidence for rehabilitation and scientific research in recent years. As the volume and scope of studies grow, analyzing the innovative applications and research trends of ultrasound in rehabilitation is essential. This study employs bibliometric methods to map global research collaboration networks in ultrasound for rehabilitation, explore research dynamics, and predict future research themes based on emerging trends.

Methods: We performed a bibliometric analysis of 8346 articles from the Web of Science (WoS) Core Collection (1990-2024) using CiteSpace and VOSviewer.

Results: A total of 8346 articles were included. Annual publication volumes have a surge in the past five years. Western countries dominate research output, while institutions in China are emerging as significant contributors. Levent Ozcakar and Paul W. Hodges lead in publication volume and citation impact, respectively. Musculoskeletal ultrasound, intelligent algorithms, and skill education are key citation clusters and emergent topics. High-frequency keywords include ultrasound examination, exercise and efficacy validation emerging recently.

Conclusion: Ongoing research is likely to continue focusing on the reliability of ultrasound for diagnosing various diseases, musculoskeletal quantification through novel ultrasound technologies in physical therapy, and ultrasound monitoring and biofeedback in respiratory and postpartum rehabilitation. Additionally, musculoskeletal examination evidence, real-time training monitoring, and systematic review evaluation are gaining increasing attention. These emerging areas may serve as guiding themes for future research, providing a foundation for continued innovation in the application of ultrasound in rehabilitation.

Background: Abnormal liver function has often been associated with epilepsy, but there is a lack of large-scale clinical evidence to support the potential correlation between liver function and post-stroke epilepsy.

Objective: We aimed to explore a real correlation between liver function and secondary epilepsy after stroke.

Methods: From the Dryad database, we retrospectively identified 21,459 patients who had experienced acute ischemic stroke. Multivariate regression was used to clarify the correlation between liver function and secondary epilepsy post-stroke via cross-sectional analysis.

Results: Our multivariate nonlinear analysis, adjusted for age and gender, suggested that a significant correlation exists between liver function (alanine aminotransferase [ALT] and aspartate aminotransferase [AST]) and the risk of secondary epilepsy post-stroke. Saturation effect analysis showed that a fold point (K) of blood AST level of 39.3 U/L was related to an epilepsy event. An increased AST level was related to a higher rate of epilepsy (1.2 [1.2-1.3], <0.001) among patients with AST levels of less than 39.3 U/L. Significance was weaker among patients with AST levels of more than 39.3 U/L. As for ALT, the fold point of blood ALT level revealed an association with epilepsy at 23.3 U/L. Similarly, elevated AST levels were related to a significantly higher risk of secondary epilepsy post-stroke (1.2 [1.1-1.2], <0.001) when they were less than 23.3 U/L. The significant correlation was weaker when blood AST levels were higher than 23.3 U/L. Importantly, ROC curve analysis displayed a high AUC value (0.8101) of blood AST in terms of detecting epilepsy risk, with a sensitivity of 0.7254 and specificity of 0.7997, respectively.

Conclusion: Our study provided potential evidence for the correlation between liver function and secondary epilepsy after acute stroke, indicating that early protection and management of liver dysfunction among post-stroke patients might be beneficial for reducing epileptic seizures. More studies with a high level of evidence are needed to confirm this finding, however.

Objective: This study aimed to examine the association between different obesity-related metabolic phenotypes, transitions in metabolic status over time, and cognitive function improvement among middle-aged and older adults in China.

Methods: Data were derived from the China Health and Retirement Longitudinal Study, a nationally representative longitudinal cohort involving urban and rural residents aged 45 years and older. Baseline data were collected in 2011, with follow-up assessments extending to 2020. Participants were classified into four body mass index (BMI)-metabolic phenotypes: Metabolically Healthy Normal Weight (MHNW), Metabolically Unhealthy Normal Weight (MUNW), Metabolically Healthy Overweight/Obesity (MHOO), and Metabolically Unhealthy Overweight/Obesity (MUOO). Cognitive function was evaluated through assessments of episodic memory, mental status, and overall cognitive performance. Statistical analyses were performed using R Studio 4.3.1. Cox regression analysis models were employed to estimate associations between metabolic phenotypes, their longitudinal transitions, and changes in cognitive function.

Results: In both the 2011 and 2015 surveys, MHOO demonstrated significantly higher scores in episodic memory, mental status, and overall cognitive function compared to other groups, while MUNW demonstrated significantly lower scores across all domains. In addition, cognitive outcomes varied by BMI-metabolic phenotypes: MHOO was positively associated with cognitive improvement, MUNW was usually associated with poorer cognitive outcomes, and MUOO had no significant association with cognitive changes. Moreover, individuals with stable MUNW status exhibited a lower likelihood of cognitive improvement relative to those with stable MHNW status. In contrast, individuals with stable MHOO status demonstrated a significantly greater likelihood of cognitive improvement. Furthermore, transitioning from MHNW to MUNW was associated with decreased likelihood of favorable cognitive outcomes.

Conclusion: Regardless of weight classification, metabolic health was associated with superior baseline cognitive function and a slower rate of cognitive decline. These findings underscore the significance of metabolic health in predicting cognitive aging trajectories among middle-aged and older individuals.

Background: The rising prevalence of mental disorders, coupled with limited access to mental health services, underscores the urgent need for innovative solutions. Artificial Intelligence (AI) offers transformative potential in managing mental health conditions through multimodal data analysis.

Objective: This study explores emerging applications of AI in early detection, personalized treatment, and the prevention of symptom escalation in mental disorders.

Methods: A narrative review was conducted using comprehensive searches of PubMed, Scopus, and IEEE Xplore databases (2015-2025). Selected sources included studies on natural language processing (NLP), deep learning, and the analysis of multimodal data (eg, voice, text, and biosensor inputs). A qualitative synthesis was employed to identify key patterns, challenges, and innovations.

Findings: AI enhances early detection through concepts such as a "psychological digital signature" and reports high performance in some studies (reported accuracies vary widely, eg, up to ~91% in selected cohorts). However, many high-accuracy reports derive from single-site or limited datasets with variable external validation; therefore, these figures should be interpreted cautiously. We discuss study-specific limitations (sample size, validation methods, and population diversity) in the Methods and Critical Appraisal sections.

Conclusion: AI provides a patient-centered, preventive framework for reimagining mental health care. However, its effective integration requires robust ethical standards and digital infrastructure. Ethical considerations are critically linked to clinical implementation, particularly regarding privacy, fairness, and transparency in AI-assisted decision-making.

Objective: This study aimed to examine the integration of artificial intelligence (AI) into nursing clinical education, with particular emphasis on enhancing the Mini-Clinical Evaluation Exercise (Mini-CEX). The study focused on the role of AI in improving the objectivity of clinical performance assessment and the quality of feedback provided.

Methods: A mixed-methods approach was used, involving 140 undergraduate nursing students randomly assigned to a control or intervention group. The intervention group received conventional clinical instruction supplemented by an AI-assisted Mini-CEX. The AI was integrated during the assessment process to provide automated performance analysis of video-recorded clinical skills and transcripts of patient interactions. This analysis generated structured, individualized feedback reports for learners, which were then used by instructors to guide the dissemination of results in post-assessment debriefing sessions.

Results: The AI-supported Mini-CEX demonstrated a significant enhancement in the consistency and objectivity of clinical evaluations. In this study, artificial intelligence was specifically applied through automated performance analysis, real-time feedback delivery, and its integration into Mini-CEX assessments, thereby clarifying the role of AI within the instructional process. Learners in the intervention group achieved more rapid acquisition of technical skills and exhibited increased engagement, which was attributed to the provision of immediate and personalized feedback.

Conclusion: The incorporation of AI into the Mini-CEX framework, specifically for automating aspects of performance analysis and feedback generation, contributed to real-time, standardized, and learner-centered assessments. This approach improved the objectivity of evaluations while maintaining the integral role of human mentorship for interpretive guidance.

Introduction: Community-based palliative care implementation faces challenges in terms of providing services to people living with terminal illness in remote and underserved areas. Integrating telehealth into palliative care has the potential to improve access to and effectiveness of palliative care by enabling remote interactions between people living with terminal illness, their caregivers, and healthcare providers. However, the models and outcomes of telehealth in the context of community palliative care remain poorly understood.

Objective: The aim of this systematic review was to investigate the benefits of integrating telehealth into community-based palliative care for people living with terminal illness and their caregivers.

Methods: A systematic search of studies was conducted using MEDLINE, PubMed, EBSCO, Cochrane Controlled Register of Trials (CENTRAL), Scopus, and Google Scholar. The inclusion criteria were primary quantitative studies on integrating telehealth into palliative care in community for adults living with terminal illness, published in between 2014 and 2024. The risk of bias was assessed using the revised Cochrane risk of bias tool for randomized controlled trials and the Newcastle-Ottawa scale for cohort studies. The data were analyzed using content analysis.

Results: Seven studies met the inclusion criteria. Telehealth interventions most commonly involve telephone or video consultations and phone calls. Evidence has shown consistent improvements in functional status, reduction in hospitalization rate, and reductions in psychological distress (anxiety, depression) among people living with terminal illness. For caregivers, the benefits included reduced psychological distress (stress, depressive symptoms) and care burden. Additionally, improvements in quality of life among caregivers has been inconsistent.

Conclusion: Integrating telehealth into community-based palliative care is associated with improved outcomes for people living with terminal illness and their caregivers. However, the lack of studies based in low- and middle-income countries limits the generalizability of the results and prevents conclusions as to whether similar interventions will have the same outcome outside high-income countries.

Background: Mechanically ventilated patients are at significant risk of malnutrition, a condition that not only prolongs ICU length of stay but also dramatically increases mortality risk. While existing studies have focused on clinical protocols, the global research landscape and knowledge gaps remain underexplored in terms of systematic synthesis. This study employs systematic bibliometric analysis to quantitatively trace publication trajectories, identify dominant research clusters, and propose evidence-based pathways for enhancing global research prioritization and improving clinical nutrition practices.

Methods: Studies published between January 1, 2000, and November 6, 2024, on enteral nutrition in mechanically ventilated patients were identified using the Web of Science platform. A comprehensive analysis of these studies was performed using VOSviewer, CiteSpace, and an online analysis tool(R-bibliometrix), assessing publication trends, contributions from countries/regions and institutions, institutional productivity, major funding agencies, journals and their co-citation networks, authors and their co-citation patterns, and keywords and emerging trends in the field.

Results: A total of 1164 studies were included in the analysis, which showed a general upward trend in publication volume over the 24 years. The USA, supported by robust financial resources and well-established research institutions, ranked first in terms of publication count, citation number, and h-index. The top three institutions in terms of publication volume were Harvard University, the University of Toronto, and Queen's University of Canada. The journals with the highest numbers of publications were the Journal of Parenteral and Enteral Nutrition, Critical Care Medicine, and Clinical Nutrition. The most prolific author was Dr. Daren K. Heyland. The top keywords were "nutrition", "malnutrition", and "prevalence".

Conclusion: Research in the field of enteral nutrition for mechanically ventilated patients continues to thrive, increasing the number of investigations. The present bibliometric analysis provides a summary of current research frontiers and hotspots in the field, offering a robust reference framework for researchers investigating enteral nutrition in mechanically ventilated critically ill patients.

Background: Visceral leishmaniasis (VL) is a severe, life-threatening public health concern in Ethiopia. Since early 2022, the outbreak of VL in the South Omo Zone, particularly among pastoralist communities, has resulted in multiple deaths.

Objective: To assess the risk factors contributing to the VL outbreak in South Omo Zone, southern Ethiopia.

Methods: A mixed-method study was conducted in Hammer, Nyangatom, and Selamago districts (areas with the highest case load). The study included a stakeholder consultative workshop and qualitative interviews with health workers, community leaders, and caregivers. A matched case-control study was also performed, and conditional logistic regression was used to analyze quantitative data.

Findings: The stakeholder consultation revealed 64 challenges linked to the outbreak. The top-ranked challenge was the high non-medical cost of VL diagnosis and treatment, followed by limited government and stakeholder commitment. Notably, the absence of governmental structure in the Mursi area (Selamago district) was identified as a significant barrier despite being ranked 11th. Qualitative data highlighted additional challenges: poor transportation, distant treatment services, low awareness, cultural treatment practices, and lengthy therapy duration. Quantitatively, family history of VL was a significant risk factor (AOR = 2.91, 95% CI: 1.73-4.87), while VL cases were more likely to have good knowledge of the disease than controls (AOR = 6.6, 95% CI: 2.34-18.42).

Conclusion: The findings highlight significant challenges in the control and management of visceral leishmaniasis (VL) in South Omo Zone, including high non-medical costs of care, limited government commitment, inadequate outbreak preparedness, and shortages of trained providers. Prioritized strategies emphasized strengthening health systems, mobilizing resources, and engaging political and community leaders. Addressing systemic gaps and strengthening community-based interventions are essential for effective VL outbreak control and timely treatment.

Purpose: Platinum-based chemotherapy and radiotherapy are cornerstone treatments for many cancers but carry a high risk of ototoxicity, leading to hearing loss, tinnitus, and balance dysfunction. Despite the benefits of monitoring in reducing long-term consequences, global uptake remains poor. This study provides the first national-level insight into ototoxicity monitoring for cancer patients in Saudi Arabia, aiming to identify service gaps and propose solutions to guide healthcare planning.

Methods: Twenty-five oncology centers were evaluated. Data were collected via phone interviews with oncologists and audiologists, providing a comprehensive understanding of monitoring in clinical practice.

Results: Findings highlight a concerning reality: institutions often fail to support even the most basic elements of ototoxicity monitoring. Practices varied considerably in the absence of formal policies, even within the same institution, depending on audiology service availability and oncologists' referral approaches. Adult referrals were rare, pediatric monitoring was inconsistent, and long-term follow-up was limited. Barriers included inadequate audiological resources, staff shortages, insufficient multidisciplinary coordination, limited audiologists' knowledge, and lack of guidelines.

Conclusion: As decision-makers seek reliable national data to guide policies aligned with Vision 2030 health transformation goals, this study proposes policy-based solutions to strengthen ototoxicity monitoring and expand access to hearing rehabilitation services in Saudi Arabia. The study has inspired a collaborative initiative-currently being explored by the author with audiologists and oncologists across health sectors-to promote internal monitoring protocols in capable institutions and lay the groundwork for a future national ototoxicity monitoring program.