The Impact of Transformational Leadership Style on the Success of Global Virtual Teams

Organizations in the age of modern technology have a diverse workforce, who are spread around the globe, and the business leaders of the 21st century need to understand how best to manage, overcome new challenges, and know the various skills of team members to capitalize on their differences and unique skills. To allow those geographically dispersed workers to reach their full potential and facilitate team success. Global virtual teams (GVTs) operate in complex environments characterized by diverse cultural and organizational elements. The primary purpose of this correlational and nonexperimental quantitative research was to examine the impact of transformational leadership on GVTs, their productivity, and job satisfaction with leadership effectiveness. Using the Multifactor Leadership Questionnaire (MLQ) and the Job Satisfaction Survey (JSS), data analyzes were completed through SurveyMonkey.com and SPSS software. The study measured transformational leadership, the independent variable, by the leader\u27s ability to motivate workers to be satisfied and productive, and by the leader\u27s effectiveness in the organization. Data were assessed by frequency analysis, moderation analyzes, and multiple regression analysis on the dependent variables of job satisfaction, leadership effectiveness, and productivity. The findings from this study reinforced the positive relationships found between transformational leadership, employee productivity, and leadership effectiveness in GVTs. Results also showed that motivated employees increase productivity and help in the organization\u27s growth. Implications for positive social change included improvements in GVT interactions to increase the exchange of diverse ideas that lead to increased productivity and job satisfaction

Use of Social Media for Patient Education in Dermatology: Narrative Review

BackgroundSocial media has rapidly become one of the main avenues for news and communication among those with access to technology. Nearly 60% or 4.7 billion people worldwide use social media. Different social media networks provide users with a barrage of posts, opinions, and transformations. With this noticeable uptick in physician and patient education usage of social media, exploration of the impacts of social media on patient education in dermatology is crucial. ObjectiveThe goal of this narrative review was to evaluate existing peer-reviewed literature examining the use of social media for patient education in dermatology and to establish trends and implications. Additional attention was given to different social media sites, and potential differences in modalities of posts such as short-form videos on TikTok and Instagram Reels, long-form videos on YouTube, and infographics on Twitter, Instagram, and Facebook. MethodsPubMed, Access DermatologyDxRx, and Scopus searches of peer-reviewed publications were performed to discover articles with social media and patient education keywords in combination with other health care–relevant or dermatology-relevant keywords. Subsequently, the screening of these studies was performed by the author who has experience with education and research experience in health care, dermatology, social media, and telehealth. Ultimately, the selected articles were summarized through qualitative analysis of key points and presented for further discussion. ResultsThrough this narrative review, the researcher was able to identify several publications focusing on dermatology and social media. Some common subject areas included the use of social media for the promotion of private dermatology practices, residency programs, and research journals. So long as providers, such as dermatologists, take ethical considerations into account, these platforms can provide patients with curated educational content. In addition, several publications emphasized the use of social media as a form of patient education on dermatologic conditions but also as a source of misinformation. ConclusionsThis narrative review illuminated the use of social media as a form of patient education for dermatology, with its applications addressed across many demographics and situations. As social media platforms continue to update their algorithms, content filters, and posts, social media may become a reputable form of patient education in dermatology. Future studies and innovations should continue to explore innovations in this space, the efficacy of different modalities of posts, and longitudinal differences in patient outcomes and health literacy

On Human-Robot Co-manipulation for Handling Tasks: Modeling and Control Strategy

International audienceIn this paper, we address the co-manipulation problem for the handling tasks through a viewpoint that we do not think sufficiently explored, even it employs classical tools of robotics. Usually, this problem is tackled through the control objective based on impedance control. We consider that this force is the only exchanged physical signal, showing the robot how to move according to the willingness of the human operator. Indeed, this force gives the desired direction of displacement at every moment, a displacement that should remain under the operator's authority. Moreover, for safety purposes, the velocity of displacement should be imposed to avoid hazardous behavior. As a result, dealing with co-manipulation consists in realizing two functions in order to perform a controlled power amplification. The first is the online trajectory generation of an appropriate trajectory. The other lies in the design of a control structure allowing a good trajectory tracking. The overall strategy is illustrated with the co-manipulation problem of a robot that handles a pendulous load

Artificial intelligence in rare disease diagnosis and treatment

Abstract Artificial intelligence (AI) utilization in health care has grown over the past few years. It also has demonstrated potential in improving the efficiency of diagnosis and treatment. Some types of AI, such as machine learning, allow for the efficient analysis of vast datasets, identifying patterns, and generating key insights. Predictions can then be made for medical diagnosis and personalized treatment recommendations. The use of AI can bypass some conventional limitations associated with rare diseases. Namely, it can optimize traditional randomized control trials, and may eventually reduce costs for drug research and development. Recent advancements have enabled researchers to train models based on large datasets and then fine‐tune these models on smaller datasets typically associated with rare diseases. In this mini‐review, we discuss recent advancements in AI and how AI can be applied to streamline rare disease diagnosis and optimize treatment