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Effects of ankle joint mobilization on dynamic balance muscle activity and dynamic balance in persons with chronic ankle instability - Feasibility of a cross-over study
Full text linkIntroduction
Studies with focus on effects of manual therapy techniques on postural control and muscle activity in patients with chronic ankle instability (are lacking. The purpose of this study was to evaluate the feasibility of a planned cross-over study to assess efficacy of manual therapy techniques applications in patients with chronic ankle instability.
Methods
This feasibility study used a randomized controlled, blinded assessor cross-over design. Criteria of success under evaluation were adherence and attrition rates and adverse events. while preliminary treatment effects of manual therapy techniques on muscular activity (measured by surface electromyography) and on dynamic balance (measured by time to stabilization test) were secondary aims.
Results
Thirteen participants (mean age: 24.4 ± 3.8 years) with chronic ankle instability volunteered in this feasibility study. Success criteria showed a high adherence (98.7%) and low attrition (0%). No missing data were reported but four out of 26 data sets could not be used for statistical analysis because of non-readability of the recorded data. Preliminary treatment effect showed divergent results for surface electromyography and time to stabilization. One significant result (p = 0.03, ES = 1.48) in peroneus longus muscle activity after jump landing between 30 and 60 ms could be determined.
Conclusions
This study showed that the study protocol is feasible but should be modified by offering participants the opportunity to familiarize to the jumps and to the test repetitions. This study generates better understanding of manual therapy techniques for patients with chronic ankle instabilit
Advanced Midwifery Practice in Switzerland: Development and challenges
Full text linkMidwifery is undergoing increasing complexity attributed to global epidemiological, socio-economic and technological shifts. Coupled with a shortage of workforce and the imperative for cost-effectiveness and high-quality care, there is an ongoing international discourse and establishment of new care models and specialized roles, notably Advanced Midwifery Practice (AMP). While countries like the UK and Ireland have embraced AMP roles, Switzerland lags behind with only a few pioneering roles. The absence of regulatory frameworks for AMP within the Swiss legal and healthcare system, hinders the evolution of APM roles necessary to address contemporary needs in perinatal healthcare provision. To effectively harness the midwifery workforce and mitigate premature attrition, Switzerland must formulate distinct career trajectories for postgraduate midwives, particularly for Advanced Practice Midwives (APM). This involves establishing legal standards for educational and clinical prerequisites, delineating guidelines for APM responsibilities and competencies, and devising compensation schemes that mirror the autonomy and leadership competencies integral to these advanced roles within inpatient and outpatient perinatal care models. The incorporation of evaluation and research into AMP is indispensable, contributing to improved patient outcomes and the ongoing professionalization of midwifery. In conjunction with the Swiss Federation of Midwives, all Universities of Applied Sciences in Switzerland have collaboratively drafted a national position paper underscoring the significance of developing APM roles to ensure the provision of high-quality perinatal care. This article aims to elucidate current developments in perinatal care within the Swiss context, providing a comprehensive definition for AMP, delineating its contribution to enhancing and sustaining the quality of care
Potential of Large Language Models in Health Care: Delphi Study
Full text linkBackground:
A large language model (LLM) is a machine learning model inferred from text data that captures subtle patterns of language use in context. Modern LLMs are based on neural network architectures that incorporate transformer methods. They allow the model to relate words together through attention to multiple words in a text sequence. LLMs have been shown to be highly effective for a range of tasks in natural language processing (NLP), including classification and information extraction tasks and generative applications.
Objective:
The aim of this adapted Delphi study was to collect researchers’ opinions on how LLMs might influence health care and on the strengths, weaknesses, opportunities, and threats of LLM use in health care.
Methods:
We invited researchers in the fields of health informatics, nursing informatics, and medical NLP to share their opinions on LLM use in health care. We started the first round with open questions based on our strengths, weaknesses, opportunities, and threats framework. In the second and third round, the participants scored these items.
Results:
The first, second, and third rounds had 28, 23, and 21 participants, respectively. Almost all participants (26/28, 93% in round 1 and 20/21, 95% in round 3) were affiliated with academic institutions. Agreement was reached on 103 items related to use cases, benefits, risks, reliability, adoption aspects, and the future of LLMs in health care. Participants offered several use cases, including supporting clinical tasks, documentation tasks, and medical research and education, and agreed that LLM-based systems will act as health assistants for patient education. The agreed-upon benefits included increased efficiency in data handling and extraction, improved automation of processes, improved quality of health care services and overall health outcomes, provision of personalized care, accelerated diagnosis and treatment processes, and improved interaction between patients and health care professionals. In total, 5 risks to health care in general were identified: cybersecurity breaches, the potential for patient misinformation, ethical concerns, the likelihood of biased decision-making, and the risk associated with inaccurate communication. Overconfidence in LLM-based systems was recognized as a risk to the medical profession. The 6 agreed-upon privacy risks included the use of unregulated cloud services that compromise data security, exposure of sensitive patient data, breaches of confidentiality, fraudulent use of information, vulnerabilities in data storage and communication, and inappropriate access or use of patient data.
Conclusions:
Future research related to LLMs should not only focus on testing their possibilities for NLP-related tasks but also consider the workflows the models could contribute to and the requirements regarding quality, integration, and regulations needed for successful implementation in practice
Transgenerationalität am Beispiel des Schweigens und Sprechens im Kontext fürsorgerischer Zwangsmassnahmen in der Schweiz: eine qualitative Studie mit Nachkommen Betroffener
No full textCitizen Assembly: "Zukunft der Demokratie": Werkstattbericht und Ergebnisse einer im Rahmen des «Demokratie Labor Basel» durchgeführten Bürger:innen-Versammlung
Full text linkGestimmtes Sterben: Ein Perspektivenwechsel zwischen Sterbeliteratur und zukunftsweisendem End-of-Life Care Design
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