Journal of Multidisciplinary Healthcare最新文献

Background: The Theoretical Domains Framework (TDF) is among the most extensively utilised foundational frameworks in implementation science. It was developed from 33 psychological theories, with the latest version identifying 14 domains encompassing 84 theoretical constructs. These domains and constructs capture the complexity of factors that affect behaviours, making the framework a valuable tool for designing and implementing interventions within health and social care settings.

Objective: To summarise the development, hot topics, and future trends in TDF-related research and provide implementation practitioners with more information on the application of TDF.

Methods: We used TDF as the topic and searched the ISI Web of Science Core Collection, identifying 1382 relevant publications. We used analytical tools such as Excel, Tableau, VOSviewer, and Citespace to conduct a bibliometric analysis of the relevant publication.

Results: We identified the United Kingdom as the primary contributor, with University College London as the key institution. Susan Michie ranked highest in total citations. The analysis highlighted cancer and stroke as primary clinic medicine-related topics using TDF. Emerging themes encompass abuse, violence, maternal health, antenatal care, patient involvement, and trauma-informed care et al. "Nurse" and "qualitative research" emerged as recent and enduring hotspots, possibly indicating future research trends.

Conclusion: This article represents the first attempt to summarise the TDF using bibliometric analysis. We suggest this method can be used to analyse other theoretical frameworks in scientific implementation of its objectivity and quantifiability. Overall, the application scope of TDF is shifting from public health towards more specialised clinical directions, although its application in the field of public health is continuously expanding. In the future, the number of users of TDF is also expected to expand from implementation scientists to professional technical personnel.

Introduction: Stroke is one of the leading causes of death and disability globally, and low-income countries such as Malawi bear a heavy burden. Tailored, high-quality research is essential for bridging existing gaps and improving the healthcare provided in low-resource settings while maximizing available resources.

Aim: This mapping study aimed to synthesize the current state of stroke research in Malawi.

Methods: Six databases were thoroughly searched: CINAHL complete, Ovid MEDLINE and EMBASE, Web of Science Core Collection, PubMed, and Google Scholar.

Results: The search retrieved 598 references and identified 20 studies published between 2005 and 2023. Of these, 70% were conducted at Queen Elizabeth Central Hospital only; open-access journals published 95% of the studies. Cross-sectional studies were the most common (50%), followed by case-control studies (20%). The Malawi-Liverpool-Wellcome Trust Clinical Research Program authors contributed the most articles as main authors (25%). The number of citations per article ranged from 0 to 168 on Google Scholar, and the number of authors per article ranged from 1 to 15. Authors from thirty-five different institutions from 11 other countries partnered with Malawi on stroke articles, and England contributed 45.7% of the institutions. Most articles focused on pathophysiology (30%), followed by diagnosis (20%) and stroke management (15%). The highest number of participants included in the analysis was 739 and the highest number of stroke participants was 222. The identified challenges included the need for more infrastructure and under-utilization of available services. The Wellcome Trust has emerged as the primary funding agency for stroke research in Malawi.

Conclusion: The study found limited collaboration among local institutions in Malawi, with most research focused in Blantyre District. There is a critical need for increased interdisciplinary teamwork to boost nationwide research.

Purpose: This study aimed to explore the combined effects of caffeine intake and listening to music on walking parameters, and its relationship with psychological variables (fatigue and exercise enjoyment) in middle-aged women.

Patients and methods: Sixteen healthy middle-aged women, aged between 50 and 60 years old, participated in this study. Their walking parameters (distance, number of steps, steps number/minute, cadence and walking speed) were assessed using the 6-minute walking test (6MWT) in four task conditions: in no-music/no-caffeine, no-music/with caffeine, with music/no-caffeine, and with music/with caffeine conditions. Besides, exercise enjoyment and fatigue were evaluated using the Physical Activity Enjoyment Scale (PACES-8) and rating of perceived exertion (RPE) questionnaires, respectively.

Results: As a result, we found that 100 mg of caffeine intake significantly (p < 0.05) improved walking parameters such as distance, cadence and number of steps during both simple (p < 0.05) and dual-task, while listening to preferred music, where optimal results were found (p < 0.01) with a large effect size (η2p >0.14). Listening to music was sufficient to significantly improve the distance (p < 0.001), cadence (p < 0.001), and walking speed (p < 0.05) values. Besides, both caffeine intake and/or listening to music significantly (p < 0.05 with large effect size (η2p >0.14)) decreased the feeling of fatigue and increased exercise enjoyment while walking in healthy middle-aged women.

Conclusion: In conclusion, caffeine intake seems to positively influence gait capacities, and its combined effects with listening to music, mainly preferred ones, would boost these beneficial effects in middle-aged women.

Purpose: The pressure on professionals within the healthcare workforce is increasing due to staffing shortages, economic demands and changing care models. Through boundary work theories, our study explores how task-shifting in hand osteoarthritis (OA) care impacts the professional boundaries and division of labor between rheumatologists and occupational therapists (OTs) in Norwegian specialist healthcare.

Methodology: Seventeen semi-structured qualitative interviews were conducted at two hospitals in Norway. Participants included ten rheumatologists and five OTs. Data were analyzed using reflexive thematic analysis.

Results: The analysis resulted in three themes (1) Forms of responsibility and task transfers, (2) Circumventing the rules to ensure efficient practices and appropriate patient care, (3) Broadening and specializing; movement of professional demarcations. Overall, we found that medical tasks in hand OA care are increasingly delegated to, and adopted by, OTs, blurring the rheumatologist-OT boundary. Some of the task delegations skirted Norwegian legal boundaries, in efforts to streamline clinic operations. OTs expanded their scope of practice by adopting new tasks, whereas rheumatologist increased their specialist status by shedding unwanted tasks.

Conclusion: Task shifting between rheumatologists and OTs in hand OA care was characterized by boundary blurring activities. The results support a shift in hand OA management from rheumatologists to OTs.

Background: Artificial Intelligence (AI) holds transformative potential for the healthcare industry, offering innovative solutions for diagnosis, treatment planning, and improving patient outcomes. As AI continues to be integrated into healthcare systems, it promises advancements across various domains. This review explores the diverse applications of AI in healthcare, along with the challenges and limitations that need to be addressed. The aim is to provide a comprehensive overview of AI's impact on healthcare and to identify areas for further development and focus.

Main applications: The review discusses the broad range of AI applications in healthcare. In medical imaging and diagnostics, AI enhances the accuracy and efficiency of diagnostic processes, aiding in early disease detection. AI-powered clinical decision support systems assist healthcare professionals in patient management and decision-making. Predictive analytics using AI enables the prediction of patient outcomes and identification of potential health risks. AI-driven robotic systems have revolutionized surgical procedures, improving precision and outcomes. Virtual assistants and chatbots enhance patient interaction and support, providing timely information and assistance. In the pharmaceutical industry, AI accelerates drug discovery and development by identifying potential drug candidates and predicting their efficacy. Additionally, AI improves administrative efficiency and operational workflows in healthcare, streamlining processes and reducing costs. AI-powered remote monitoring and telehealth solutions expand access to healthcare, particularly in underserved areas.

Challenges and limitations: Despite the significant promise of AI in healthcare, several challenges persist. Ensuring the reliability and consistency of AI-driven outcomes is crucial. Privacy and security concerns must be navigated carefully, particularly in handling sensitive patient data. Ethical considerations, including bias and fairness in AI algorithms, need to be addressed to prevent unintended consequences. Overcoming these challenges is critical for the ethical and successful integration of AI in healthcare.

Conclusion: The integration of AI into healthcare is advancing rapidly, offering substantial benefits in improving patient care and operational efficiency. However, addressing the associated challenges is essential to fully realize the transformative potential of AI in healthcare. Future efforts should focus on enhancing the reliability, transparency, and ethical standards of AI technologies to ensure they contribute positively to global health outcomes.

Objective: To describe our methodology and share the practical tools we have developed to operationalize a multidisciplinary Long COVID clinic that incorporates progressive, personalized exercise prescription as a cornerstone feature.

Background: There is a lack of evidence-based guidance regarding optimal rehabilitation strategies for people with Long COVID. Existing guidelines lack precision regarding exercise dosage. As one of Australia's few established multidisciplinary Long COVID clinics, we describe our novel approach to safely incorporating exercise of both peripheral and respiratory muscles, with essential monitoring and management of post-exertional symptom exacerbation.

Methods: Working closely with primary health-care providers, our multidisciplinary team screens referrals for people aged 16 and older with Long COVID. Staff apply a three tier model of triage, dependent on the consumer's presenting problems. Exercise-based interventions necessitate detailed monitoring for post-exertional symptom exacerbation both in the clinic and at home. Personalized exercise prescription includes resistance training at a submaximal threshold (4-6 exercises, 3 days/week); whole-body endurance exercise titrated to the individual's progress, at an intensity 4-6/10 (Rate of Perceived Exertion); and for those limited by dyspnoea, high-intensity inspiratory muscle training using a threshold-based handheld device (30 repetitions per day, ≥50% of their maximum inspiratory pressure).

Discussion: We have used these approaches for the past 2 years in 250 consumers with no serious adverse events and promising consumer feedback. Our exercise prescription is less conservative than the methods advocated in international guidelines for people with Long COVID, and these more progressive tools may be valuable in other contexts.

Conclusion: In our experience, a multidisciplinary clinic-based approach to safely prescribing progressive exercise in Long COVID is feasible. Both peripheral and inspiratory muscle exercise can be effectively titrated to each individual's symptoms, and careful monitoring for post-exertional symptom exacerbation is crucial.