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Join Tommy Shaughnessy from Delphi Ventures as he hosts Sam Lehman, Principal at Symbolic Capital and AI researcher, for a deep dive into the Reinforcement Learning (RL) renaissance and its implications for decentralized AI. Sam recently authored a widely discussed post, "The World's RL Gym", exploring the evolution of AI scaling and the exciting potential of decentralized networks for training next-generation models. The World's RL Gym: https://www.symbolic.capital/writing/the-worlds-rl-gym
Generalizability of Clinical Trials of Novel Weight Loss Medications to the US Adult Population - JAMA Intern Med---Nova Android & iOS app MGFamiliar - Link---Subscreva o Podcast MGFamiliar para não perder qualquer um dos nossos episódios. Além disso, considere deixar-nos uma revisão ou um comentário no Apple Podcasts ou no Spotify.---MusicHappy · MBB - Link
Host Roz is joined by Rene Bermea, MD and Gonzalo Sapisochin, MD, PhD to discuss the key articles of the April issue of the American Journal of Transplantation. Dr. Rene Bermea is an instructor at Harvard Medical School, and a transplant pulmonologist and intensivist. Dr. Gonzalo Sapisochin is an associate professor of surgery, abdominal transplant and surgical oncology at the University of Toronto, Canada. [04:31] Generalizability of kidney transplant data in electronic health records — The Epic Cosmos database vs the Scientific Registry of Transplant Recipients Editorial: Finding actionable information in the universe of data [14:17] High-dimensional profiling of immune responses to kidney transplant reveals heterogeneous T helper 1 and B cell effectors associated with rejection Editorial: Multimodal profiling of transplant rejection: Discerning the forest from the trees [23:02] The ability of an electronic nose to distinguish between complications in lung transplant recipients [34:58] The Rochester Protocol for living donor liver transplantation of unresectable colorectal liver metastasis: A 5-year report on selection, approval, and outcomes
Title: Episode 2- Study Design, Performance, Analysis and Generalizability Target Audience This activity is directed to physicians who take care of hospitalized children, medical students, nurse practitioners, and physician assistants working in the emergency room, intensive care unit, or hospital wards. Objectives: Upon completion of this activity, participants should be able to: Review Study design. Review Performance and analysis. Review generalizability vs internal validity. Course Directors: Tony R. Tarchichi MD — Associate Professor, Department of Pediatrics, Children's Hospital of Pittsburgh of the University of Pittsburgh Medical Center (UPMC.) Paul C. Gaffney Division of Pediatric Hospital Medicine. Jenna Carlson Ph.D. - University of Pittsburgh- Assistant Professor of Human Genetics and Biostatistics in school of Public Health Rebekah Miller MLIS - University of Pittsburgh School of Medicine - Research & Instruction Librarian Conflict of Interest Disclosure: No other planners, members of the planning committee, speakers, presenters, authors, content reviewers and/or anyone else in a position to control the content of this education activity have relevant financial relationships to disclose. Accreditation Statement: In support of improving patient care, the University of Pittsburgh is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. The University of Pittsburgh School of Medicine designates this enduring material activity for a maximum of 0.5 AMA PRA Category 1 CreditsTM. Physicians should only claim credit commensurate with the extent of their participation in the activity. Other health care professionals will receive a certificate of attendance confirming the number of contact hours commensurate with the extent of participation in this activity. Disclaimer Statement: The information presented at this activity represents the views and opinions of the individual presenters, and does not constitute the opinion or endorsement of, or promotion by, the UPMC Center for Continuing Education in the Health Sciences, UPMC / University of Pittsburgh Medical Center or Affiliates and University of Pittsburgh School of Medicine. Reasonable efforts have been taken intending for educational subject matter to be presented in a balanced, unbiased fashion and in compliance with regulatory requirements. However, each program attendee must always use his/her own personal and professional judgment when considering further application of this information, particularly as it may relate to patient diagnostic or treatment decisions including, without limitation, FDA-approved uses and any off-label uses. Released 1/23/2025, Expires 1/23/2028 The direct link to the course is provided below:
Today, Dr. Patrick Schloss, Professor in the Department of Microbiology and Immunology in the School of Medicine at the University of Michigan, joins the #QualityQuorum to discuss how the human microbiome is studied, possible pitfalls in such data analysis, and what tools he and his coworkers have developed to lead toward repeatable, hypothesis-driven science. Host: Mark O. Martin Guest: Patrick Schloss Subscribe: Apple Podcasts, Spotify Become a patron of Matters Microbial! Links for this episode An overview of how the gut microbiome is analyzed. One of the articles discussed by Dr. Schloss exploring reproducibility in microbiome studies: “Identifying and Overcoming Threats to Reproducibility, Replicability, Robustness, and Generalizability in Microbiome Research.” Another article discussed by Dr. Schloss, regarding the link between the microbiome and obesity: “Looking for a Signal in the Noise: Revisiting Obesity and the Microbiome.” An article from Dr. Schloss' research team that explores a link between the human microbiome and a type of colorectal cancer. A link to the MOTHUR project, used to analyze microbiome data. A link to a video by Dr. Schloss: “Understanding Disease Through the Lens of the Microbiome.” Dr. Schloss' YouTube channel about data analysis. Dr. Schloss' research group website. Dr. Schloss' faculty website. Intro music is by Reber Clark Send your questions and comments to mattersmicrobial@gmail.com
No Priors: Artificial Intelligence | Machine Learning | Technology | Startups
In this episode of No Priors, Dmitri Dolgov, Co-CEO of Waymo, joins Sarah and Elad to explore the evolution and advancements of Waymo's self-driving technology from its inception at Google to its current real-world deployment. Dmitri also shares insights into the technological breakthroughs and complexities of achieving full autonomy, the design innovations of Waymo's sixth generation driverless cars, and the broader applications of Waymo's advanced technology. They also discuss Waymo's strategic approach to scaling amidst regulation, deployment in cities like Phoenix and San Francisco, and the transformative potential of autonomous driving on car ownership and urban infrastructure. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Dmitri_Dolgov Shownotes: 00:00 Introduction 00:15 History of Self-Driving at Google 00:29 DARPA Challenges and Early Involvement 01:39 Formation of Waymo 01:53 Industry Lineage and Early Skepticism 03:05 Initial Goals and Milestones 4:33 Pivot to Full Autonomy 04:50 Scaling and Deployment 05:29 Generational Breakthroughs 06:59 Choosing Deployment Cities 09:26 Technological Advancements 11:01 Evaluating Safety 14:41 Regulatory Stance and Trust 16:52 Future of Autonomous Driving 23:19 Business Strategy and Partnerships 26:06 Changing Urban Mobility Trends 26:40 Challenges and Misconceptions in Self-Driving Timelines 28:43 The Role of Traditional OEMs in an Autonomous Future 30:54 Designing Cars for Autonomous Ride-Hailing 33:42 Scaling Responsibly 35:18 Generalizability and Future Applications of AI 37:10 The Complexity of Achieving Full Autonomy 42:58 The Importance of Data and Iteration in AI Development 46:13 Reflecting on the Journey and Future of Waymo
Dr. Breitbach has done a lot in his career and worked in many different settings prior to moving into academics. From there he has been a program director and now works as a vice dean and professor and his research focuses on interprofessional education and collaborative practice. Dr. Breitbach has been deeply involved with this area of research and education through the courses he teaches at Saint Louis University. In this episode we discuss what interprofessional education and collaborative practice are and how they can be applied to athletic training and building a healthcare team. As we have seen in my instances, a team is what can make a difference and help provide the highest level of care to the patients they serve. Dr. Breitbach provides an abundance of insight into these topics and a lot of takeaways about the importance of them and how to implement them in your daily practice. Please enjoy. In this Episode: +Interprofessional education and collaborative practice defined +Learn about, from and with +Generalizability in research: longer and wider +Common purpose, interprofessional identity (dual identity formation) +High impact practice +ATs need to own and share our unique skillsets +”It's your path, I just happen to be on it.” Connect LinkedIn: Anthony Breitbach LinkedIn: NATA IPEP Twitter: @BE_4_IPE Twitter: @NATA_IPEP IG: @anthonybreitbach FB: https://www.facebook.com/anthony.breitbach/ @: anthony.breitbach@health.slu.edu www.athletictrainingchat.com www.cliniallypressed.com SUBSCRIBE:https://www.youtube.com/channel/UCc3WyCs2lmnKK6shrL5A4hw?sub_confirmation=1#ATCchat #ATtwitter #complicatedsimple #atimpact #at4all #nata #boc #bocatc #athletictraining #athletictrainingchat #health #medicine #medical #careeverywhere #service #marketing #ATvalue --- Support this podcast: https://podcasters.spotify.com/pod/show/athletictrainingchat/support
On a special edition of the BioCentury This Week podcast, BioCentury's editors deliver their takeaways from the debut Grand Rounds conference, which focused on whether biotech can write a more successful playbook for translating from target to product. Weaving together takeaways from the panels, fireside chat and keynote at the conference, the editors assess the tensions between generalizability and fit-for-purpose models, between having control and capturing complexity, and, in human data, between scale and robustness/reliability, particularly for longitudinal readouts. The editors also discuss BioCentury's Q&A with USC Keck School's Patrick Lyden, who explained how high-quality, reproducible preclinical science can be feasible.View full story: https://www.biocentury.com/article/65363100:00 - Introduction02:56 - Generalizability vs. Fit for Purpose10:03 - Control vs. Complexity17:57 - Scale vs. Robustness in Human Data26:25 - Hypothesis-Driven vs. Unbiased Research28:50 - Grand Rounds 2025To submit a question to BioCentury's editors, email the BioCentury This Week team at podcasts@biocentury.com.Reach us by sending a text
The Brainy Business | Understanding the Psychology of Why People Buy | Behavioral Economics
In this episode of The Brainy Business podcast, host Melina Palmer welcomes Dr. Michael Hallsworth, a co-author of Behavioral Insights and a key figure in applying behavioral science to public policy. Dr. Hallsworth shares fascinating anecdotes from his extensive work, highlighting projects such as reducing antibiotic prescriptions in the UK and influencing food consumption habits to combat obesity. The discussion delves into the evolution of his team's approach, tackling bigger policy issues like economic mobility and social justice with support from major foundations. Lessons from both successful and unsuccessful trials are explored, underscoring the importance of sharing outcomes to refine interventions. Dr. Hallsworth also touches on the nuances of replicating behavioral strategies across different countries and contexts, emphasizing the need for a deep understanding of specific problems before proposing solutions. This episode is a treasure trove for anyone interested in how small nudges can lead to significant societal shifts and is packed with real-world applications of behavioral economics. In this episode: Maximize Business Impact: Harness the Power of Behavioral Insights in Decision-Making. Policy Design Precision: Unleashing the Impact of Behavioral Economics in Policy Formation. Optimize Antibiotic Prescribing: Strategies for Effective and Efficient Antibiotic Use. Elevate Economic Mobility: Leveraging Behavioral Insights for Greater Social Mobility. Health Impact Strategies: Designing Effective Sugar Drinks Tax for Public Health. Show Notes: 00:00:00 - Introduction The episode introduces Dr. Michael Hallsworth, managing director of the Behavioral Insights team, and his journey into behavioral science. He discusses the institute for government and the development of mindspace as a framework for applying behavioral science in practice. 00:06:48 - Flagship Project - Antibiotic Prescribing Michael shares a flagship project on antibiotic prescribing in the UK. By identifying prescribers who were outliers and sending them letters based on social norms, there was a substantial decline in antibiotic prescribing, equivalent to around 1% of England's total. This approach had a comparable effect to a massive financial incentive program, showing the effectiveness of alternative methods. 00:10:33 - Generalizability of Behavioral Insights The conversation delves into the generalizability of behavioral insights across different contexts. Michael emphasizes the complexity of generalizability, highlighting examples where similar interventions have had comparable results in different countries, while also acknowledging instances where interventions haven't worked as expected. 00:13:12 - Importance of Testing The discussion underscores the importance of rigorous testing and questioning the transferability of behavioral insights. Michael emphasizes the need for ongoing testing and the productive tension between retaining active ingredients that work and adapting interventions to different contexts. 00:14:02 - Applying Behavioral Insights Michael outlines a ten-step process for applying behavioral insights, emphasizing the importance of identifying the behavior in question, understanding the context, and diagnosing the underlying problem. 00:15:38 - The Behavioral Change Process Michael explains the common stages in behavioral change frameworks, from identifying factors to developing interventions and scaling the results. He emphasizes the importance of understanding the overall context and distinguishing between strategic and tactical use of behavioral science. 00:17:26 - Policy Impact of Behavioral Science Michael discusses the strategic and tactical use of behavioral science in influencing policy and structural changes. He shares an example of the behavioral effects of the sugar drinks tax in the UK and how it influenced reformulation rather than consumer behavior. 00:24:25 - Rapid Trials in Response to COVID-19 Michael talks about rapid trials conducted in the US with cities in response to COVID-19, focusing on messaging effectiveness for behaviors like staying home, social distancing, and mask use. He highlights the counterintuitive results and the importance of testing and implementing effective communication strategies. 00:27:34 - Urban Environment Design Michael discusses the potential for applying behavioral science to arrange urban environments to facilitate behaviors such as maintaining distance in crowded areas. He draws parallels to studies on choice architecture and redesigning traffic intersections, emphasizing the importance of making it easier for people to adhere to desired behaviors. 00:28:51 - Learning from Failed Interventions Michael emphasizes the importance of being transparent about interventions that did not work and the value of learning from those experiences to guide future initiatives. He explains how failures can lead to insights about the need for more intensive or structural changes in interventions. 00:30:45 - Exploring Bigger Policy Issues Michael discusses the idea that behavioral insights should be applied to more upstream and bigger policy issues instead of just downstream issues. This includes projects on economic mobility and social justice. 00:31:49 - Balancing Evidence and Pragmatism Michael highlights the tension between evidence and pragmatic needs when applying behavioral insights to upstream issues. He emphasizes the importance of finding a balance between knowing the evidence and being flexible in decision-making. 00:33:21 - Productive Balance in Applying Behavioral Insights Michael addresses the need for practitioners to find a balance between being knowledgeable about evidence and being flexible in strategic conversations. This balance is crucial for behavioral insights to fulfill its promise of transforming the way things are done. 00:34:49 - Conclusion, What stuck with you while listening to the episode? What are you going to try? Come share it with Melina on social media -- you'll find her as @thebrainybiz everywhere and as Melina Palmer on LinkedIn. Thanks for listening. Don't forget to subscribe on Apple Podcasts or Android. If you like what you heard, please leave a review on iTunes and share what you liked about the show. I hope you love everything recommended via The Brainy Business! Everything was independently reviewed and selected by me, Melina Palmer. So you know, as an Amazon Associate I earn from qualifying purchases. That means if you decide to shop from the links on this page (via Amazon or others), The Brainy Business may collect a share of sales or other compensation. Let's connect: Melina@TheBrainyBusiness.com The Brainy Business® on Facebook The Brainy Business on Twitter The Brainy Business on Instagram The Brainy Business on LinkedIn Melina on LinkedIn The Brainy Business on Youtube Connect with Michael: Dr. Michael Hallworth on the BI Team Website Michael on Twitter LinkedIn Learn and Support The Brainy Business: Check out and get your copies of Melina's Books. Get the Books Mentioned on (or related to) this Episode: Behavioral Insights, by Michael Hallsworth Engaged, by Amy Bucher Behavioral Science in the WIld, by Dilip Soman and Nina Mazar Designing for Behavior Change, by Stephen Wendel Nudge, by Richard Thaler & Cass Sunstein Top Recommended Next Episode: Michael Hallsworth Interview 2 (ep 218) Already Heard That One? Try These: Questions or Answers? (ep 4) Steve Wendell Interview (ep 116) The Most Important Step In Applying Behavioral Economics: Understanding the Problem (ep 126) Elina Halonen Interview (ep 188) Framing (ep 296) Other Important Links: Brainy Bites - Melina's LinkedIn Newsletter https://www.nature.com/articles/s41562-023-01555-3 Nudge vs. Superbugs: A Behavioural Economics Trial to Reduce the Overprescribing of Antibiotics Reductions in Portion Size and Energy Density of Foods are Additive and Lead to Sustained Decreases in Energy Intake
is with us today. She has done some amazing theory construct research using computational methods before this was really an accepted thing. We discuss which work she built her research around to give it legitimacy, what good stopping rules are for authors or reviewers to know when enough is enough, and how we can engage in humble generalizations of interesting and general regularities. References Miranda, S. M., Kim, I., & Summers, J. D. (2015). Jamming with Social Media: How Cognitive Structuring of Organizing Vision Facets Affects IT Innovation Diffusion. MIS Quarterly, 39(3), 591-614. Walsh, I., Holton, J. A., Bailyn, L., Fernandez, W. D., Levina, N., & Glaser, B. G. (2015). What Grounded Theory Is ... A Critically Reflective Conversation Among Scholars. Organizational Research Methods, 18(4), 581-599. Levina, N., & Vaast, E. (2015). Leveraging Archival Data from Online Communities for Grounded Process Theorizing. In K. D. Elsbach & R. M. Kramer (Eds.), Handbook of Qualitative Organizational Research: Innovative Pathways and Methods (pp. 215-224). Routledge. Berente, N., Seidel, S., & Safadi, H. (2019). Data-Driven Computationally-Intensive Theory Development. Information Systems Research, 30(1), 50-64. Miranda, S. M., Wang, D., & Tian, C. (2022). Discursive Fields and the Diversity-Coherence Paradox: An Ecological Perspective on the Blockchain Community Discourse. MIS Quarterly, 46(3), 1421-1452. Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2021). Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI. MIS Quarterly, 45(3), 1527-1556. Lindberg, A., Schecter, A., Berente, N., Hennel, P., & Lyytinen, K. (2024). The Entrainment of Task Allocation and Release Cycles in Open Source Software Development. MIS Quarterly, 48(1), 67-94. Sahaym, A., Vithayathil, J., Sarker, S., Sarker, S., & Bjørn-Andersen, N. (2023). Value Destruction in Information Technology Ecosystems: A Mixed-Method Investigation with Interpretive Case Study and Analytical Modeling. Information Systems Research, 34(2), 508-531. Miranda, S. M., Berente, N., Seidel, S., Safadi, H., & Burton-Jones, A. (2022). Computationally Intensive Theory Construction: A Primer for Authors and Reviewers. MIS Quarterly, 46(2), i-xvi. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1), 75-105. Adamic, L. A., & Glance, N. (2005). The Political Blogosphere and the 2004 U.S. Election: Divided They Blog. Paper presented at the 3rd International Workshop on Link Discovery, Chicago, Illinois. Pentland, B. T., Vaast, E., & Ryan Wolf, J. (2021). Theorizing Process Dynamics with Directed Graphs: A Diachronic Analysis of Digital Trace Data. MIS Quarterly, 45(2), 967-984. Sarker, S., Xiao, X., Beaulieu, T., & Lee, A. S. (2018). Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2). Journal of the Association for Information Systems, 19(8), 752-774. Lee, A. S., & Baskerville, R. (2003). Generalizing Generalizability in Information Systems Research. Information Systems Research, 14(3), 221-243. Tsang, E. W. K., & Williams, J. N. (2012). Generalization and Induction: Misconceptions, Clarifications, and a Classification of Induction. MIS Quarterly, 36(3), 729-748. Hume, D. (1748/1998). An Enquiry Concerning Human Understanding [Reprint]. In J. Perry & M. E. Bratman (Eds.), Introduction to Philosophy: Classical and Contemporary Readings (3rd ed., pp. 190-220). Oxford University Press. Exemplar Computationally-intensive Theory Construction Papers Bachura, E., Valecha, R., Chen, R., & Rao, H. R. (2022). The OPM Data Breach: An Investigation of Shared Emotional Reactions on Twitter. MIS Quarterly, 46(2), 881-910. Gal, U., Berente, N., & Chasin, F. (2022). Technology Lifecycles and Digital Innovation: Patterns of Discourse Across Levels of Abstraction: A Study of Wikipedia Articles. Journal of the Association for Information Systems, 23(5), 1102-1149. Hahn, J., & Lee, G. (2021). The Complex Effects of Cross-Domain Knowledge on IS Development: A Simulation-Based Theory Development. MIS Quarterly, 45(4), 2023-2054. Indulska, M., Hovorka, D. S., & Recker, J. (2012). Quantitative Approaches to Content Analysis: Identifying Conceptual Drift Across Publication Outlets. European Journal of Information Systems, 21(1), 49-69. Lindberg, A., Majchrzak, A., & Malhotra, A. (2022). How Information Contributed After an Idea Shapes New High-Quality Ideas in Online Ideation Contests. MIS Quarterly, 46(2), 1195-1208. Nan, N. (2011). Capturing Bottom-Up Information Technology Use Processes: A Complex Adaptive Systems Model. MIS Quarterly, 35(2), 505-532. Pentland, B. T., Recker, J., Ryan Wolf, J., & Wyner, G. (2020). Bringing Context Inside Process Research With Digital Trace Data. Journal of the Association for Information Systems, 21(5), 1214-1236. Vaast, E., Safadi, H., Lapointe, L., & Negoita, B. (2017). Social Media Affordances for Connective Action: An Examination of Microblogging Use During the Gulf of Mexico Oil Spill. MIS Quarterly, 41(4), 1179-1205.
Swarm Learning in Digital Pathology: Revolutionizing Cancer Histopathology Today on the Digital Pathology Podcast my guest is Oliver Saldana, the first author of a significant Nature Medicine paper published in 2022 on 'Swarm Learning for Decentralized Artificial Intelligence in Cancer Histopathology'. Oliver shares his journey from Mangalore, India, to Germany, where he pursued his master's and PhD, delving into histopathology and decentralized AI under the supervision of Professor Dr. Jakob Nicolas Kather. The discussion explores the concept of swarm learning as a novel method for deep learning in histopathology, its advantages over centralized learning including compliance with data protection laws like GDPR, and its potential for global collaboration in medical research without sharing sensitive data. Oliver emphasizes swarm learning's ease of setup and its alignment with the FAIR principles for scientific data management. The podcast aims to shed light on the groundbreaking work being done in the convergence of pathology and computer science, urging researchers and pathology centers to digitize their slides and contribute to global swarm learning projects.00:00 Introduction to Swarm Learning and Its Applications00:50 Intro01:17 Meet Oliver Saldana: A Trailblazer in Decentralized AI for Cancer Histopathology03:57 Exploring the Concept of Decentralized AI and Its Importance06:52 Understanding Centralized vs. Decentralized Learning08:47 The Revolutionary Approach of Swarm Learning10:38 Blockchain's Role in Enhancing Histopathology with Swarm Learning14:50 Addressing Preprocessing and Generalizability in Swarm Learning21:26 Swarm Learning's Compliance with GDPR and Data Protection25:05 Exploring Swarm Learning in Medical Data Analysis25:34 Prototype Study and Real Cohorts in Swarm Learning27:01 Comparing Swarm Learning with Centralized Models27:44 The Role of Bare Metal Servers in Swarm Learning30:01 Centralized Slide Repositories vs. Swarm Learning44:11 Commercializing Swarm Learning Models47:07 FAIR Principles and Swarm Learning51:11 Global Ambitions and the Future of Swarm LearningTHIS EPISODES RESOURCES
Clinics in the US are offering mammogram readings by both radiologists and artificial intelligence (AI) models. AI tools can speed up radiologists' work and detect breast cancer earlier than traditional mammograms alone. While experts are excited about improved accuracy, concerns remain about effectiveness across diverse patients and impact on breast cancer survival rates. AI models highlight suspicious areas on mammogram images and can reduce false positives. However, it is unclear whether AI analysis will reduce deaths from breast cancer or simply increase the number of earlier detections. Generalizability of European findings, potential limitations of AI, and lack of billing codes for insurers also pose challenges. --- Send in a voice message: https://podcasters.spotify.com/pod/show/tonyphoang/message
Rob Gray is an associate Professor at Arizona State University, host of The Perception & Action Podcast, and a Skill Acquisition Specialist for the Boston Red Sox. He's been studying movement and publishing research on it for 25 years. In this Part 1 of 2, Kris and Rob discuss the limitations and challenges of using sports science research for coaches and practitioners, as well as some ways both coaches and researchers could do it better. ____________________ EXPLORE FURTHER Our entire movement skills resource library Coaching for Mastery course mentioned in the episode Follow Rob on Instagram Check out The Perception & Action Podcast Check out Rob's books: How We Learn to Move: A Revolution in the Way We Coach & Practice Sports Skills Learning to Optimize Movement: Harnessing the Power of the Athlete-Environment Relationship ____________________ SUPPORT + CONNECT Help us keep the show sponsor-free when you join our Patreon Community for as little as $3. Get two or more bonus episodes every month on Patreon, Spotify, or Apple. Subscribe to THE CURRENT and get a monthly exploration of how we can all become better climbers. Share this episode with a friend who needs to hear it. ____________________ The Power Company Podcast is a proud founding member of the Plug Tone Audio Collective, a group of the best, most impactful podcasts in the outdoor industry. Find full episode transcripts and more at our website. ____________________ CHAPTERS (0:00) Intro (1:31) Guest Introduction (3:20) Topic Explanation (5:18) Accessibility (6:13) Impenetrability (7:33) Generalizability (8:43) ANNOTATION: Don't Discount Small Studies (10:49) Researchers Asking the Wrong Questions (11:49) How to Make it User Friendly (19:34) The Value of Case Studies (22:19) Studies Lack Real World Variables (24:23) ANNOTATION: Functional Movement Variability (26:44) What is it We Should be Looking For in Studies? (30:49) Coaches and Researchers Meeting in the Middle (33:48) Limitations of Using Studies From Other Sports (37:24) ANNOTATION: Constraints and Self Organization (40:54) ”Evidence-Based” Elitism (43:27) Wrap Up
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: GiveWell from A to Z, published by GiveWell on January 12, 2024 on The Effective Altruism Forum. Author: Isabel Arjmand, Special Projects Officer To celebrate the end of 2023, we're highlighting a few key things to know about GiveWell - from A to Z. These aren't necessarily the 26 most important parts of our work (e.g., we could include only "transparency" or "top charities" for T) but they do fit the alphabet, and we've linked to other pages where you can learn more. All Grants Fund. Our recommendation for donors who have a high level of trust in GiveWell and are open to programs that might be riskier than our top charities. Bar. We set a cost-effectiveness bar, or threshold, such that we expect to be able to fully fund all the opportunities above that level of cost-effectiveness. This bar isn't a hard limit; we consider qualitative factors in our recommendations, as discussed here. This post also discusses our bar in more detail. Cost-effectiveness. The core question we try to answer in our research is: How much good can you do by giving money to a certain program? This blog post describes how we approach cost-effectiveness estimates and use them in our work. Donors. Unlike a foundation, we don't hold an endowment. Our impact comes from donors choosing to use our recommendations. Effective giving organizations. Organizations like Effektiv Spenden, which fundraise for programs we recommend and provide tax-deductible donation options in a variety of countries. We're grateful to these national effective giving organizations and groups like Giving What We Can that recommend our work. Footnotes.[1] Generalizability. How well evidence generalizes to different settings, including variations in program implementation and the contexts where a program is delivered. Also called "external validity." Health workers and community distributors. The people who deliver many of the programs we support; includes both professional health workers and distributors who receive stipends to deliver programs in their local communities. For example, community distributors go from household to household to provide seasonal malaria chemoprevention to millions of children. Incubating new programs. We partner with the Evidence Action Accelerator and Clinton Health Access Initiative (CHAI) Incubator to scope, pilot, and scale up promising cost-effective interventions. Judgment calls. We aim to create estimates that represent our true beliefs. Our cost-effectiveness analyses are firmly rooted in evidence but also incorporate adjustments and intuitions that aren't fully captured by scientific findings alone. More in this post. Kangaroo mother care. A program to reduce neonatal mortality among low-birthweight babies through skin-to-skin contact to keep babies warm, breastfeeding instruction, home visits, and more. Leverage. How our funding decisions affect other funders, either by crowding in additional funding ("leverage") or by displacing funds that otherwise would have been used for a given program ("fungibility"). Mistakes. Transparency is core to our work. Read here about mistakes we've made and lessons we've learned. Nigeria. One of the countries where we most often fund work. (Our work is generally concentrated in Africa and South Asia.) New Incentives, one of our top charities, currently works exclusively in northern Nigeria, where low baseline vaccination rates make its work especially valuable. Oral rehydration solution + zinc. A low-cost way to prevent and treat dehydration caused by diarrhea. We've been interested in ORS/zinc for a long time (going back to 2006!), and recently funded the CHAI Incubator to conduct a randomized controlled trial in Bauchi State, Nigeria, studying the extent to which preemptively distributing free ORS/zinc directly to households increases usage by children u...
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After attending ASN Kidney Week, Bluestar Principal Jeff Fineberg sits down with Dr. Pietro Canetta to talk all things IgA nephropathy (IgAN). After Dr. Canetta provides a brief summary of his IgAN lecture at Kidney Week, Emerging Therapeutic Options in IgA Nephropathy, the two discuss the Filspari (sparsentan) data presented from both the PROTECT study, in IgAN, the DUPLEX study, in FSGS. From there, Dr. Canetta opines on the value of surrogate endpoints in predicting the three D's of CKD: death, dialysis, and doubling of serum creatinine (SCr). Dr. Canetta briefly discusses Novartis' press release announcing the positive Phase II data with atrasentan, another ETA RA, before the conversation shifts to other drug classes and therapeutic targets, including SGLT2 inhibitors, and B-cell activation (i.e., APRIL/BAFF). Finally, Jeff asks Dr. Canetta about whether the recent advancements in IgAN are generalizable to other glomerular diseases, and what might be the determinants of this. Jump to specific topics in the conversation: 00:00 Recap + guest intro/bio + Kidney Week lecture summary 05:05 Filspari (sparsentan) trial results from PROTECT (IgAN) and DUPLEX (FSGS) 12:25 Value of surrogate endpoints in predicting three D's - death, dialysis, and doubling of SCr - in glomerular disease 19:55 Atrasentan press release 23:05 The "four-hit" hypothesis of IgAN pathogenesis and SGLT2i 26:10 B-cell activation (APRIL/BAFF) as a therapeutic approach in IgAN 31:55 Generalizability (and lack thereof) of therapeutic approaches to other glomerular diseases 37:25 Where to learn more Helpful links: PROTECT Study (Filspari/sparsentan in IgAN) DUPLEX Study (Filspari/sparsentan in FSGS) Novartis press release (atrasentan in IgAN) ENVISION Study (sibeprenlimab in IgAN) Columbia Glomerular Center For more information about Bluestar BioAdvisors, please visit our website.
In this podcast I discuss five cognitive biases that are potentially harming your health - and no, this is not a clickbait title. We kick off by exploring the concept of cognitive biases - those systematic deviations in judgment that often lead us astray. Then, I dive into five specific cognitive biases that frequently sabotage health goals. From the Anchoring Bias, which makes us cling to initial information (like outdated fitness myths), to the Halo Effect, where we blindly trust attractive individuals as reliable sources of health advice. I also cover the Action Bias, the Empathy Gap, and the Fundamental Attribution Error, each offering a unique lens on why we often struggle with health and fitness endeavours. To wrap up, I provide practical tips for recognising and dismantling these biases, empowering you to make more informed decisions about your health, relationships, and life. Join me for a thought-provoking journey into the psychology behind our health choices, promising insights that can lead to real, positive changes in your life. Check out my website for more information about my training programmes: https://shonavertue.com/ Here is the study I refer to in the episode: Gabrieli, G., Lee, A., Setoh, P., & Esposito, G. (2021). An Analysis of the Generalizability and Stability of the Halo Effect During the COVID-19 Pandemic Outbreak. Frontiers in psychology, 12, 631871. https://doi.org/10.3389/fpsyg.2021.631871 I hope you enjoy this one as much as I enjoyed researching and recording it :) --- Send in a voice message: https://podcasters.spotify.com/pod/show/thevertuepodcast/message
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.26.550679v1?rss=1 Authors: Panela, R. A., Copelli, F., Herrmann, B. Abstract: Neural tracking of continuous, spoken speech is increasingly used to examine how the brain encodes speech and is considered a potential clinical biomarker, for example, for age-related hearing loss. A biomarker must be reliable (intra-class correlation [ICC] greater than 0.7), but the reliability of neural-speech tracking is unclear. In the current study, younger and older adults (different genders) listened to stories in two separate sessions while electroencephalography (EEG) was recorded in order to investigate the reliability and generalizability of neural speech tracking. Neural speech tracking was larger for older compared to younger adults for stories under clear and background noise conditions, consistent with a loss of inhibition in the aged auditory system. For both age groups, reliability for neural speech tracking was lower than the reliability of neural responses to noise bursts (ICC greater than 0.8), which we used as a benchmark for maximum reliability. The reliability of neural speech tracking was moderate (ICC ~0.5-0.75) but tended to be lower for younger adults when speech was presented in noise. Neural speech tracking also generalized moderately across different stories (ICC ~0.5-0.6), which appeared greatest for audiobook-like stories spoken by the same person. This indicates that a variety of stories could possibly be used for clinical assessments. Overall, the current data provide results critical for the development of a biomarker of speech processing, but also suggest that further work is needed to increase the reliability of the neural-tracking response to meet clinical standards. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC
Dr. John Vervaeke and Gregg Henriques continue their thought-provoking exploration of Transcendent Naturalism by examining extended naturalism, neoplatonism, and the dimensions of sacredness. They challenge conventional notions of sacredness by examining its connection with strong transcendence and discussing Spinoza's insights into nature, God's ultimate reality, and the universe's deterministic nature, aligning with the Neoplatonic framework. They discuss religious perspectives, comparing classical and common theism and their evolution, while addressing the interplay between energy, consciousness, and reality, highlighting the philosophical underpinnings of theism. They also intriguingly differentiate spirituality from religion, both rooted in the concept of the sacred, and discuss symbolic ideals, spiritual richness, consequential history, and the profound significance of consequential decisions in our lives. Resources: The Case for God - Karen Armstrong Religion and Nothingness - Keiji Nishitani Thinking Being: Introduction to Metaphysics in the Classical Tradition - Eric Pearl Consilience: The Unity of Knowledge - Edward Osborne Wilson Time-codes: [00:00:00] Dr. John Vervaeke outlines the episode's structure: extended naturalism, the meaning of sacredness within extended naturalism, the concept of strong transcendence, and three phenomena where people traditionally express a sense of transcendence: rituals, altered states of consciousness, and belonging to a worldview. [00:04:53] Dr. Vervaeke dives into the first topic, extended naturalism. He discusses the consilience between structural and content arguments in the context of neoplatonism. [00:07:36] Discussion of Spinoza's distinction between nature nurturing and nature being nurtured, a concept that explores the relationship between top-down and bottom-up processes in nature, bringing forward the idea of God not as a physical entity but as the source of all existence and understanding. [00:15:14] Dr. John Vervaeke discusses the features of common theism and its basis in classical theology, shares his perspective on the debates between theists and atheists, and the conception of God as a supreme being [00:18:00] The concept of God as the ground that supports continual self-transcendence, and a contemplative discussion on theism's classical and common forms, pushing the boundaries of philosophical exploration. [00:25:19] A deep dive into how truth can exist outside our understanding, challenging conventional beliefs. [00:30:20] Dr. Vervaeke delves into the concept of sacredness, describing it as an inexhaustible and paradoxical fountain of intelligibility. He also highlights the limitations of traditional propositional knowing in fully comprehending this concept. [00:37:23] The concepts of soul and spirit as ineffable aspects of human experience, with the soul, referring to the groundedness of our experiences and spirit pointing to our capacity for self-transcendence, and discussion on the connection between the symbolic ideal and the transcendent, [00:38:09] Symbolic Ideals & Transcendence: Gregg Henriques links symbolic ideals to deeper philosophical perspectives, enriching discourse. [00:41:20] Dr. John Vervaeke explains the concept of sacredness as a transjective experience, providing a new perspective on the understanding of sacredness. [00:44:53] Gregg Henriques introduces a proposes a new concept of inconsequential versus consequential history; viewing historical events based on their long-term impact. [00:55:00] Dr. John Vervaeke outlines his plan to explore the deep interconnections between an extended notion of rationality and ritual and their power, including an explanation of how and why we experience strong transcendence within ritual experiences, within the framework of extended naturalism. Qoutes: “Strong transcendence has epistemological and ontological import. The idea is that there are truths about reality that are disclosed only when one goes through a transcendence, which also gives you access to different levels of knowing.” - Dr. John Vervaeke “Generalizability in and of itself it's not really intelligibility. It's generalizability in relationship to the capacity for differentiation held in appropriate dialectic. There's a generalizable differentiation polarity where the poles between the two is going to afford intelligibility, and it's the right relationship of that t that is fundamentally key.” - Gregg Henriques
Commentary by Dr. Valentin Fuster
Dr. Breitbach has done a lot in his career and worked in many different settings prior to moving into academics. From there he has been a program director and now works as a vice dean and professor and his research focuses on interprofessional education and collaborative practice. Dr. Breitbach has been deeply involved with this area of research and education through the courses he teaches at Saint Louis University. In this episode we discuss what interprofessional education and collaborative practice are and how they can be applied to athletic training and building a healthcare team. As we have seen in my instances, a team is what can make a difference and help provide the highest level of care to the patients they serve. Dr. Breitbach provides an abundance of insight into these topics and a lot of takeaways about the importance of them and how to implement them in your daily practice. Please enjoy. In this Episode: +Interprofessional education and collaborative practice defined +Learn about, from and with +Generalizability in research: longer and wider +Common purpose, interprofessional identity (dual identity formation) +High impact practice +ATs need to own and share our unique skillsets +”It's your path, I just happen to be on it.” Connect LinkedIn: Anthony Breitbach LinkedIn: NATA IPEP Twitter: @BE_4_IPE Twitter: @NATA_IPEP IG: @anthonybreitbach FB: https://www.facebook.com/anthony.breitbach/ @: anthony.breitbach@health.slu.edu www.athletictrainingchat.com www.cliniallypressed.com SUBSCRIBE:https://www.youtube.com/channel/UCc3WyCs2lmnKK6shrL5A4hw?sub_confirmation=1#ATCchat #ATtwitter #complicatedsimple #atimpact #at4all #nata #boc #bocatc #athletictraining #athletictrainingchat #health #medicine #medical #careeverywhere #service #marketing #ATvalue --- Support this podcast: https://podcasters.spotify.com/pod/show/athletictrainingchat/support
In this episode, Nathan sits down with Tanishq Mathew Abraham, 19-year-old UC Davis grad and one of the youngest people in the world to receive a Ph.D, with a degree in biomedical engineering. Tanishq is the founder of the Medical AI Research Center (MedARC), and with his teammates, recently published a paper: Reconstructions of the Mind's Eye, which encompasses their breakthrough research on reconstructing visual perceptions from fMRI scans into images. In this episode, Nathan and Tanishq talk about the technology behind the fMRI-to-image project, developing the model, and future applications for this research. Part 2 with Tanishq will be released as the next episode. RECOMMENDED PODCAST: The HR industry is at a crossroads. What will it take to construct the next generation of incredible businesses – and where can people leaders have the most business impact? Hosts Nolan Church and Kelli Dragovich have been through it all, the highs and the lows – IPOs, layoffs, executive turnover, board meetings, culture changes, and more. With a lineup of industry vets and experts, Nolan and Kelli break down the nitty-gritty details, trade offs, and dynamics of constructing high performing companies. Through unfiltered conversations that can only happen between seasoned practitioners, Kelli and Nolan dive deep into the kind of leadership-level strategy that often happens behind closed doors. Check out the first episode with the architect of Netflix's culture deck Patty McCord. https://link.chtbl.com/hrheretics The Cognitive Revolution is a part of the Turpentine podcast network. To learn more: Turpentine.co TIMESTAMPS: (00:00) Episode Preview (05:43) The MindEye Project (09:06) Resemblance between AI reconstruction of mind's eye and visual presented (10:00) What is a voxel and which regions of the brain were studied? (10:23) What would the raw data of a voxel be? (11:44) Is there a time dimension to voxels? (15:00) Sponsor: Omneky (17:50) Goals for the MindEye project (25:57) What is the starting point of the model? (31:15) Aligning the model: reconstruction vs retrieval (40:34) Would doing a full end-to-end training be fine for the reconstruction? (42:15) The role of a limited data set (43:09) Training separate models per subject (45:07) Generalizability with a limited dataset (47:20) Mapping from one high-dimensional space to another (50:47) Stable Diffusion VAE encoding (1:00:50) How long does it take to train the model? (1:03:14) How similar or different are the subjects and their individual models? (1:05:59) The future of this research: custom models for your brain? (1:07:34) How much does this research contribute to brain research and wearables? (1:11:15) Fuzzing data and future research applications LINKS: MedARC: medarc.ai MindEye Paper: https://www.researchgate.net/publication/371136623_Reconstructing_the_Mind's_Eye_fMRI-to-Image_with_Contrastive_Learning_and_Diffusion_Priors MP3 of this episode: https://chrt.fm/track/993DGA/traffic.megaphone.fm/RINTP1584997572.mp3?updated=1687271014 TWITTER: @iScienceLuvr (Tanishq) @MedARC_AI (MedARC) @CogRev_Podcast @labenz (Nathan) @eriktorenberg (Erik) SPONSOR: Thank you Omneky (www.omneky.com) for sponsoring The Cognitive Revolution. Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work, customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off. MUSIC CREDIT: MusicLM
Dr. Srijan Kumar is an Assistant professor at Georgia Tech with research interests in combating misinformation and harmful content on online platforms, building robust AI models prone to adversarial attacks, and behavior modeling for more accurate recommender systems. Before joining Georgia Tech, he was a postdoctoral fellow at Stanford University and completed his Ph.D. in computer science from the University of Maryland. He has received multiple awards for his research work, including Forbes 30u30 and being named a Kavli Fellow by the National Academy of Sciences.Time stamps of the conversation00:01:00 Introductions00:01:45 Background and Interest in AI00:05:27 Current research interests00:09:50 What is misinformation?00:15:07 ChatGPT and misinformation00:23:40 How can AI help detect misinformation?00:39:15 Twitter's Birdwatch platform to detect fake/misleading news00:56:38 Detecting fake bots on Twitter01:03:39 Adversarial training to build robust AI models01:05:31 Robustness vs Generalizability in machine learning01:11:40 Navigating your interest in the field of AI/machine learning01:19:22 Doing a Ph.D. and working in Industry vs Academia01:24:22 Focusing on Quality of Research rather than Quantity01:31:23 Advice to young people interested in AIDr. Kumar's homepage: https://cc.gatech.edu/~srijan/Twitter: https://twitter.com/srijankediaLinkedin: https://www.linkedin.com/in/srijankrAbout the Host:Jay is a Ph.D. student at Arizona State University.Linkedin: https://www.linkedin.com/in/shahjay22/Twitter: https://twitter.com/jaygshah22Homepage: https://www.public.asu.edu/~jgshah1/ for any queries.Stay tuned for upcoming webinars!***Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***Checkout these Podcasts on YouTube: https://www.youtube.com/c/JayShahmlAbout the author: https://www.public.asu.edu/~jgshah1/
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.03.29.534696v1?rss=1 Authors: Goltermann, J., Winter, N. R., Gruber, M., Fisch, L., Richter, M., Grotegerd, D., Dohm, K., Meinert, S., Leehr, E. J., Böhnlein, J., Kraus, A., Thiel, K., Winter, A., Flinkenflügel, K., Leenings, R., Barkhau, C., Ernsting, J., Berger, K., Minnerup, H., Straube, B., Alexander, N., Jamalabadi, H., Stein, F., Brosch, K., Wroblewski, A., Thomas-Odenthal, F., Usemann, P., Teuteberg, L., Pfarr, J., Jansen, A., Nenadic, I., Kircher, T., Gaser, C., Opel, N., Hahn, T., Dannlowski, U. Abstract: Introduction: Statistical effect sizes are systematically overestimated in small samples, leading to poor generalizability and replicability of findings in all areas of research. Due to the large number of variables, this is particularly problematic in neuroimaging research. While cross-validation is frequently used in multivariate machine learning approaches to assess model generalizability and replicability, the benefits for mass-univariate brain analysis are yet unclear. We investigated the impact of cross-validation on effect size estimation in univariate voxel-based brain-wide associations, using body mass index (BMI) as an exemplary predictor. Methods: A total of n=3401 adults were pooled from three independent cohorts. Brain-wide associations between BMI and gray matter structure were tested using a standard linear mass-univariate voxel-based approach. First, a traditional non-cross-validated analysis was conducted to identify brain-wide effect sizes in the total sample (as an estimate of a realistic reference effect size). The impact of sample size (bootstrapped samples ranging from n=25 to n=3401) and cross-validation on effect size estimates was investigated across selected voxels with differing underlying effect sizes (including the brain-wide lowest effect size). Linear effects were estimated within training sets and then applied to unseen test set data, using 5-fold cross-validation. Resulting effect sizes (explained variance) were investigated. Results: Analysis in the total sample (n=3401) without cross-validation yielded mainly negative correlations between BMI and gray matter density with a maximum effect size of R2p=.036 (peak voxel in the cerebellum). Effects were overestimated exponentially with decreasing sample size, with effect sizes up to R2p=.535 in samples of n=25 for the voxel with the brain-wide largest effect and up to R2p=.429 for the voxel with the brain-wide smallest effect. When applying cross-validation, linear effects estimated in small samples did not generalize to an independent test set. For the largest brain-wide effect a minimum sample size of n=100 was required to start generalizing (explained variance greater than 0 in unseen data), while n=400 were needed for smaller effects of R2p=.005 to generalize. For a voxel with an underlying null effect, linear effects found in non-cross-validated samples did not generalize to test sets even with the maximum sample size of n=3401. Effect size estimates obtained with and without cross-validation approached convergence in large samples. Discussion: Cross-validation is a useful method to counteract the overestimation of effect size particularly in small samples and to assess the generalizability of effects. Train and test set effect sizes converge in large samples which likely reflects a good generalizability for models in such samples. While linear effects start generalizing to unseen data in samples of n greater than 100 for large effect sizes, the generalization of smaller effects requires larger samples (n greater than 400). Cross-validation should be applied in voxel-based mass-univariate analysis to foster accurate effect size estimation and improve replicability of neuroimaging findings. We provide open-source python code for this purpose (https://osf.io/cy7fp/?view_only=a10fd0ee7b914f50820b5265f65f0cdb). Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC
Dr. Breitbach has done a lot in his career and worked in many different settings prior to moving into academics. From there he has been a program director and now works as a vice dean and professor and his research focuses on interprofessional education and collaborative practice. Dr. Breitbach has been deeply involved with this area of research and education through the courses he teaches at Saint Louis University. In this episode we discuss what interprofessional education and collaborative practice are and how they can be applied to athletic training and building a healthcare team. As we have seen in my instances, a team is what can make a difference and help provide the highest level of care to the patients they serve. Dr. Breitbach provides an abundance of insight into these topics and a lot of takeaways about the importance of them and how to implement them in your daily practice. Please enjoy. LINK: https://www.athletictrainingchat.com/2023/02/ep-126-dr-anthony-brietbach.html In this Episode: +Interprofessional education and collaborative practice defined +Learn about, from and with +Generalizability in research: longer and wider +Common purpose, interprofessional identity (dual identity formation) +High impact practice +ATs need to own and share our unique skillsets +”It's your path, I just happen to be on it.” Connect LinkedIn: Anthony Brietbach LinkedIn: NATA IPEP Twitter: @BE_4_IPE Twitter: @NATA_IPEP IG: @anthonybreitback FB: https://www.facebook.com/anthony.breitbach/ @: anthony.breitbach@health.slu.edu www.athletictrainingchat.com www.cliniallypressed.com SUBSCRIBE:https://www.youtube.com/channel/UCc3WyCs2lmnKK6shrL5A4hw?sub_confirmation=1 #ATCchat #ATtwitter #complicatedsimple #atimpact #at4all #nata #boc #bocatc #athletictraining #athletictrainingchat #health #medicine #medical #careeverywhere #service #marketing #ATvalue --- Support this podcast: https://podcasters.spotify.com/pod/show/athletictrainingchat/support
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2022.12.06.519290v1?rss=1 Authors: Conessa, A., Debarnot, U., Siegler, I., Boutin, A. Abstract: Sleep benefits the consolidation of motor skills learned by physical practice, mainly through periodic thalamocortical sleep spindle activity. However, motor skills can be learned without overt movement, either through motor imagery or action observation. Here, we investigated whether sleep spindle activity also supports the consolidation of non-physically learned movements. Forty-five electroencephalographic sleep recordings were collected during a daytime nap after motor sequence learning by physical practice, motor imagery or action observation. Our findings revealed that irrespective of the modality of practice, spindles tend to cluster in trains on a low-frequency time scale of about 50 seconds, and during which spindles iterate every 3-4 seconds. However, despite this apparent modality-unspecific temporal organization of sleep spindles, different behavioral outcomes were elicited. We show that a daytime nap offers an early sleep window that promotes the retention of the learned motor skill following PP and MI practice, and its generalizability towards the transfer of skill from one effector to another after AO practice. Altogether, we demonstrated that the temporal cluster-based organization of sleep spindles may be a general mechanism for effective memory reprocessing. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC
CME credits: 1.25 Valid until: 23-11-2023 Claim your CME credit at https://reachmd.com/programs/cme/generalizability-of-the-victoria-trial-and-the-us-fda-label-for-vericiguat-to-patients-hospitalized-for-heart-failure-in-the-united-states/14369/ In this program, expert faculty review and discuss real-world applications of the latest, practice-changing data across different therapeutic areas within cardiovascular medicine presented at the American Heart Association Scientific Session 2022.
John Vervaeke joins me for a deep conversation exploring his work as a cognitive scientist and his YouTube lecture series "Awakening from the Meaning Crisis."Be sure to check out NYDIG, one of the most important companies in Bitcoin: https://nydig.com/GUESTJohn's twitter: https://twitter.com/vervaeke_johnJohn's Patreon: https://www.patreon.com/johnvervaekeJohn's Lecture Series “Awakening from the Meaning Crisis”: https://www.youtube.com/watch?v=54l8_ewcOlY PODCASTPodcast Website: https://whatismoneypodcast.com/Apple Podcast: https://podcasts.apple.com/us/podcast/the-what-is-money-show/id1541404400Spotify: https://open.spotify.com/show/25LPvm8EewBGyfQQ1abIsE?si=wgVuY16XR0io4NLNo0A11A&nd=1RSS Feed: https://feeds.simplecast.com/MLdpYXYITranscript:OUTLINE00:00:00 “What is Money?” Intro00:00:05 NYDIG00:01:23 The Mind as a Map of the Universe00:05:29 The Recurrent Patterns in Nature00:06:58 “Agency All The Way Down”00:11:28 Serving What's True, Good, and Beautiful00:12:19 Synchronicity: The Acausal Principle00:16:44 The Flow State: An Optimization of Adaptivity00:17:52 Circumambulation00:23:18 A Causes B; B Values Precondition A00:24:45 Emergence and Emanation: Matter and Principles00:27:31 Possibility and Actuality are Co-Determining00:29:46 Homemaking vs. House-Building00:33:37 Material Engagement Theory00:34:54 Software and Hardware: Multiple Realizability00:37:05 Human and Tool Reciprocity; The Stroop Effect00:41:17 Mimesis, Self-Reflection, and Mindfulness00:42:57 Distributed Cognition and Captaining the Ship00:43:33 Social Institutions: Psychotechnologies Externalized?00:46:06 Price Signals and Mead's “Generalized Other”00:50:45 The Generalizability and Discrimination Tradeoff00:53:02 Does the Corruption of Money Corrupt Humanity?00:59:22 The Social Utility of Religion and Institutions01:03:10 Money as the Base Layer Protocol for Human Action01:05:47 Central Banking Twists Distributed Cognition01:07:25 Hyperbolic Discounting, Time Preference, and Consumerism01:09:36 Central Banking Causes Capital Destruction and Politicization01:13:22 Psychotechnological Disruption of Social Institutions01:15:16 Politics as the Ethics of Distributed Cognition01:18:04 Politics as Imposable Opinion01:21:37 Bitcoin Moves Markets Away from the Threat of Force01:27:41 Bitcoin: The Incorruptible Game of Money01:29:59 “Parable of the Winemaker”: A Corruption of Money and Morality01:36:04 Exploring the Languages of Value and Cognition01:38:13 “Words are the Coinage of Thought”01:41:12 Industrial Revolution and the Abolition of Slavery01:45:55 Corruption of Money and the Meaning Crisis01:55:39 Humans are “Natural-Born Cyborgs”SOCIALBreedlove Twitter: https://twitter.com/Breedlove22WiM? Twitter: https://twitter.com/WhatisMoneyShowLinkedIn: https://www.linkedin.com/in/breedlove22/Instagram: https://www.instagram.com/breedlove_22/TikTok: https://www.tiktok.com/@breedlove22?lang=enAll My Current Work: https://linktr.ee/breedlove22WRITTEN WORKMedium: https://breedlove22.medium.com/Substack: https://breedlove22.substack.com/WAYS TO CONTRIBUTEBitcoin: 3D1gfxKZKMtfWaD1bkwiR6JsDzu6e9bZQ7Sats via Strike: https://strike.me/breedlove22Sats via Tippin.me: https://tippin.me/@Breedlove22Dollars via Paypal: https://www.paypal.com/paypalme/RBreedloveDollars via Venmo: https://venmo.com/code?user_id=1784359925317632528The "What is Money?" Show Patreon Page: https://www.patreon.com/user?u=32843101&fan_landing=trueRECOMMENDED BUSINESSESWorldclass Bitcoin Financial Services: https://nydig.com/Join Me At Bitcoin 2022 (10% off if paying with fiat, or discount code BREEDLOVE for Bitcoin): https://www.tixr.com/groups/bitcoinconference/events/bitcoin-2022-26217Put your Bitcoin to work. Earn up to 12% interest back on Bitcoin with Tantra: https://bit.ly/3CFcOmgIBAC assists central banks and sovereign wealth funds succeed in their digital asset investments: https://www.ibac.io/Automatic Recurring Bitcoin Buying: https://www.swanbitcoin.com/breedlove/
Yash Sharma is a Ph.D. student at the International Max Planck Research School for Intelligent Systems. He previously studied electrical engineering at Cooper Union and has spent time at Borealis AI and IBM Research. Yash's early work was on adversarial examples and his current research interests span a variety of topics in representation disentanglement. In this episode, we discuss robustness to adversarial examples, causality vs. correlation in data, and how to make deep learning models generalize better.
Ask yourself these true or false questions: Generalizability and transportability and external validity are all the same thing Generalizability is a secondary concern to internal validity We spend too much time in epi training programs teaching internal validity and not enough teaching external validity Worrying about external validity is largely and academic exercise that doesn’t really have much in the way of real-world impact. In this episode of SERious Epi we discuss these questions and more with Dr. Megha Mehrotra. While internal and external validity are familiar to nearly all epidemiologists, the concept of transportability is less familiar. Listen in to this episode for a clear description of how concepts related to validity, generalizability, and transportability are similar, and different, from each other.
Hydrocephalus is a neurological condition where fluid builds up in the brain which cannot drain. In babies, it's as common as Down's Syndrome. But it's an affliction far fewer have heard about. Hydrocephalus Association funds research into a cure and offers support and education to those affected. Find out how your donation can help young scientists improve countless lives by saving patients from repeated brain surgery. Want to support Organization? https://www.hydroassoc.org/ Find the episode on Great.com: https://great.com/great-talks-with/why-surgeons-still-use-a-50-year-old-procedure-to-treat-hydrocephalus
This is Episode 23 of PsychCrunch, the podcast from the British Psychological Society’s Research Digest. In this episode, Emily Reynolds, staff writer at Research Digest, explores modern psychology’s relationship with race and representation. It’s well-known that psychology has a generalisability problem, with studies overwhelmingly using so-called “WEIRD” participants: those who are Western and educated and from industrialised, rich and democratic societies. But how does that shape the assumptions we make about participants of different racial identities or cultures? And how can top-tier psychology journals improve diversity among not only participants but also authors and editors? Our guests, in order of appearance, are Dr Bobby Cheon, Assistant Professor at Nanyang Technological University, Singapore, and Dr Steven O. Roberts, Assistant Professor of Psychology at Stanford University. Episode credits: Presented and produced by Emily Reynolds. Script edits by Matthew Warren. Mixing and editing by Jeff Knowler. PsychCrunch theme music by Catherine Loveday and Jeff Knowler. Art work by Tim Grimshaw. Research mentioned in this episode includes: How USA-Centric Is Psychology? An Archival Study of Implicit Assumptions of Generalizability of Findings to Human Nature Based on Origins of Study Samples Racial Inequality in Psychological Research: Trends of the Past and Recommendations for the Future Toward a psychology of Homo sapiens: Making psychological science more representative of the human population
Dr. Leo Celi discusses various problems involving bias, fairness and generalizability that continue to affect the adoption of artificial intelligence models in hospitals and clinics. Dr. Celi also makes a number of recommendations for improving relationships between health care organizations and the private sector as AI research moves forward. Articles that Dr. Celi mentions in the podcast are: Futoma J, Simons M, Panch T, Doshi-Velez F, Celi L. The myth of generalizability in clinical research and machine learning in health care. Lancet Digital Health 2020; 2:e489-92. At: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30186-2/fulltext. Stuppe A, Singerman D, Celi L. The reproducibility crisis in the age of digital medicine. NPJ Digital Medicine January 29, 2019. At https://www.nature.com/articles/s41746-019-0079-z. Vyas D, Eisenstein L, Jones D. Hidden in plain sight—reconsidering the use of race correction in clinical algorithms. The New England Journal of Medicine August 27, 2020; 383(9):874-882. At: https://www.nejm.org/doi/full/10.1056/NEJMms2004740.
There has been several headlines lately expressing that not sleeping enough can affect how well the flu vaccine keeps you protected. Reviewing the article where much of these headlines come from - we find that as usual, there’s nothing of substance, and nothing to worry about!Do you have trouble sleeping? Can’t sleep? Have questions about insomnia or sleep? Please leave a comment or send an email:questions@thesleepcoachschool.comI will be happy to share my thoughts as a video reply in an Ask Daniel episode.If you want to connect elsewhere I’m on Twitter @ErichsenDaniel, Instagram @Erichsen.Daniel, Facebook as Daniel Erichsen.Would you like to work with me? Awesome! I would love a chance to help you sleep fantastic. There are three ways we can work together:- The Self Coaching Master Program www.thesleepcoachschool.com- BedTyme, a sleep coaching app for iOS and Android.- Buy my book Set it & Forget it on Amazon. It includes a cell phone number where you can send questions.The self coaching program is perfect if you like learning through video and also if have mental wellness goals besides such has being less anxious.BedTyme is ideal if you like to learn via text and have a sleep coach in your pocket.Not sure where to start? Check out these playlists!This is natto - the perfect place to start learning! https://www.youtube.com/playlist?list...Success stories - if you need hope and inspiration, this is for you. https://www.youtube.com/playlist?list...Insomnia insight - a list of every single episode. https://www.youtube.com/playlist?list...Talking insomnia - guests with trouble sleeping or experts share their stories / tips. https://www.youtube.com/playlist?list...Hypnic jerks, hypnic awareness and other common issues. https://www.youtube.com/playlist?list...Fatal insomnia - for those concerned about ffi and sfi. https://www.youtube.com/playlist?list...The self coaching model https://www.youtube.com/playlist?list...Best!This content does not constitute medical advice, diagnosis, or treatment, and should never replace any advice given to you by your physician or other qualified healthcare providers.
Welcome back to Let's Chat, Myths! This week is the first part out of two all about the myths of age in regards to health and fitness. We start with the older generation. We've all heard it "I'm getting old" "I'm too old for any of that" etc etc. While there is evidence to suggest a decline it can be mitigated if individuals take action and in some cases, this mitigation can get to a point where other factors cause improvement with age. We break down today's episode into multiple parts. First up was exploring the impacts of age on strength, power & mass. We discuss type 2 muscle fibres, the peak age for elite athletes and something that can affect us all with age, sarcopenia. Sarcopenia is an age-related deterioration in skeletal muscle. Once again if individuals take action as we discuss on the pod then you can mitigate its effects and as the data suggests "older pop" can get similar % of strength gains compared to "younger pop" when participating in a resistance program. The worst thing you can do in terms of sarcopenia is giving up and let it get worse. Take action, keep active and keep on top of diet and you'll reap the benefits going forward. Endurance. We start by establishing that type 1 muscle fibres like those used in endurance events are not impacted as much by age like in type 2. However due to max heart decreasing over time our ability to utilise oxygen technically decreases. So we asked the question why are seeing older champions/record breakers? Apart from the cynicism of Tom jumping straight to performance-enhancing drugs, we looked at individuals. One sportsman made the point that with age his training and diet has improved due to knowledge gained over the years and that his mental/physical robustness "I don't feel pain as much" has improved. Recovery. "It takes me ages to recover now" We've all heard it from "older pop" and we are not saying those individuals are lying however it can be mitigated to the point of being negligible. We looked at two sets of data from trained athletes looking at 24hr recovery and HR recovery after a bout of intense exercise. Both concluded that essentially age didn't impact their recovery. We suggested that as these "trained" older pop participants have kept up with exercise they have perhaps with experience learnt how to recover optimally for their age so that in data it looks no different. Metabolism. This is a common one. Once you hit 30 your metabolism tanks and after eating a pringle you'll blow up like a balloon. Of course, this statement was made in jest as it simply isn't the case. Yes, your metabolism does slow with age however multiple factors come into play. Your basal metabolic rate (BMR) is impacted by things such as muscle. If sarcopenia takes hold and you stop any physical activity and have a poor diet (minimal protein etc) then due to low muscle mass your metabolism will slow further. More important to note is that this is a very slow gradual process. (data suggests 1-2% per decade) One set of data compared 90+ participants to 20-34 in terms of metabolism and worse case taking no account of gender, muscle etc found 90+ burned 422 calories fewer. 20-34 compared to 60-74 was even less at 122 fewer. These numbers are not that big so to blame sudden "ballooning" on metabolism when you're in your 40s/50s is just passing the blame. Keep active as you age and you should be ok. If you decide in your older years you don't want to exercise as much then just be aware you may want to cut down on a few things to keep those calories lower. Lifestyle. Tom's favourite buzzword makes a comeback. Socioeconomics. As we get older we tend to have more life responsibilities. Moving higher up in the work chain, house, kids all these things accumulate to offer more barriers to consistent physical exercise and good life choices. This final part of the episode offered some real honest discussion about the impacts of "life" as we get older. This part alone is worth a listen. If you want some more advice/help then get in touch. Remember if you want us "on tap" then head over to trainprimal.co and sign up to any of our training programmes and you'll be invited to join our exclusive Facebook group where you can chat to us whenever. Apologies if it's inundated with conspiracy theories it was part of the deal when we asked Tom to join the group. New to the show? Head back to episode 1 "Let's Chat, Covid & Fitness" where we give an introduction into who we are and talk about the current state of ourselves and the fitness industry during this covid pandemic Find us on Instagram @cf_bill @coachtomreardon @a_new_man87 Website: www.chatshitgetfit.com Emai: csgfpodcast@gmail.com Studies Mentioned Muscle changes in ageing: understanding sarcopenia Age-related changes in skeletal muscle Age Differences, Age Changes, and Generalizability in Marathon Running by Master Athletes Peak Age and Performance Progression in World-Class Weightlifting and Powerlifting Athlete Periodization resistance training program in college-aged and middle-aged men Effect of Age on Muscle Hypertrophy Induced by Resistance Training Dose-Response Relationships of Resistance Training in Healthy Old Adults: A Systematic Review and Meta-Analysis Age-related changes in cardio-respiratory responses and muscular performance following an Olympic triathlon in well-trained triathletes Effects of age and training status on heart rate recovery after peak exercise Ageing, Resting Metabolic Rate, and Oxidative Damage Age-dependent changes in different components of energy expenditure (EE) Nutrition and Aging: Changes in the Regulation of Energy Metabolism With Aging Bouncing Back! Counteracting Muscle Aging With Plyometric Muscle Loading How Old Is too Old to Strength Train?
In this episode, I answer a listener question about generalizability. I provide helpful tips for determining if the results of the study apply to you or the population of interest. I define population and explain why researchers generally rely on samples when carrying out research studies.
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.07.08.193664v1?rss=1 Authors: David O'Connor, Evelyn M.R. Lake, Dustin Scheinost, R. Todd Constable Abstract: It is a long-standing goal of neuroimaging to produce reliable generalized models of brain behavior relationships. More recently data driven predicative models have become popular. Overfitting is a common problem with statistical models, which impedes model generalization. Cross validation (CV) is often used to give more balanced estimates of performance. However, CV does not provide guidance on how best to apply the models generated out-of-sample. As a solution, this study proposes an ensemble learning method, in this case bootstrap aggregating, or bagging, encompassing both model parameter estimation and feature selection. Here we investigate the use of bagging when generating predictive models of fluid intelligence (fIQ) using functional connectivity (FC). We take advantage of two large openly available datasets, the Human Connectome Project (HCP), and the Philadelphia Neurodevelopmental Cohort (PNC). We generate bagged and non-bagged models of fIQ in the HCP. Over various test-train splits, these models are evaluated in sample, on left out HCP data, and out-of-sample, on PNC data. We find that in sample, a non-bagged model performs best, however out-of-sample the bagged models perform best. We also find that feature selection can vary substantially within-sample. A more considered approach to feature selection, alongside data driven predictive modeling, is needed to improve cross sample performance of FC based brain behavior models.Competing Interest StatementThe authors have declared no competing interest.View Full Text Copy rights belong to original authors. Visit the link for more info
Generalizability of randomized trials is always limited because of the super-selectivity of the patients enrolled in these trials and the very controlled conditions in which clinical care is delivered. Pragmatic trials are performed in order to provide guidance for how to best deliver clinical care in situations that more closely resemble actual clinical scenarios. Hal Sox, MD, director of peer review for the Patient-Centered Outcomes Research Institute (PCORI), explains how these trials work and what clinical questions they answer. Related: Pragmatic Trials: Practical Answers to “Real-world” Questions
Podcasting legend Yoel Inbar (from Two Psychologists Four Beers (https://fourbeers.fireside.fm)) joins us to break down Tal Yarkoni's "The Generalizability Crisis,” the paper that launched a thousand Twitter wars. Psychologists make verbal claims about the world, then conduct studies to test these claims - but are the studies actually providing evidence for those claims? Do psychological experiments generalize beyond the the strict confinments of the lab? Are psychologists even using the right statistical models to be able to claim that they do? Does this debate boil down to fundamental differences in the philosophy of science - induction, Popper, and hypothetico-deductive models and so forth? Will David and Tamler ever be able to talk about a psych study again without getting into a fight? Plus ahead of tonight's New Hampshire primary, expert political analysis about what went down in Iowa. Special Guest: Yoel Inbar.
Yoel and Mickey discuss a new paper by Tal Yarkoni suggesting that quantitative research in psychology is suffering from a generaliozability crisis. Do the numbers and statistics that psychological scientists present in their papers correspond to their verbal claims? What would psychological science look like if psychologists made fewer general statements? Should psychologists conduct more qualitative and descriptive research? Did Tal Yarkoni himself use a quantitative argument to prop up very old verbal claims about the problem of induction? Bonus: Before discussing generalizability, Yoel and Mickey discuss Contrapoints and her new video on cancel-culture.
Cardiac Consult: A Cleveland Clinic Podcast for Healthcare Professionals
Luke Laffin, MD, cardiologist in the Section of Preventive Cardiology at Cleveland Clinic discusses his recently published paper with Stephanie Besser, MSA, MSPA, and Francis Alenghat, MD, PhD, from the University of Chicago which dove into the results of the SPRINT and ACCORD-BP trials to answer the question if trial results looking at a specific population of patients can apply to specific patients in clinic. The team developed a tool to answer this question.
A recent publication reported preoperative Patient-Reported Outcomes Measurement Instrumentation System (PROMIS) scores to be highly predictive in identifying patients who would and would not benefit from foot and ankle surgery. Their applicability to other patient populations is unknown. The aim of this study was to assess the validation and generalizability of previously published preoperative PROMIS physical function (PF) and pain interference (PI) threshold t scores as predictors of postoperative clinically meaningful improvement in foot and ankle patients from a geographically unique patient population. PROMIS PF threshold scores from published data were successful in classifying patients from a different patient and geographic population who would improve with surgery. If functional improvement is the goal, these thresholds could be used to help identify patients who will benefit from surgery and, most important, those who will not, adding value to foot and ankle health care. To view the article, click here.
On this episode, Dr. Mary Ellen Dello Stritto is joined by Dr. Mary Kite. Mary Kite received her B.A., M.S., and Ph.D. from Purdue University. A social psychologist, she is currently Professor of Social Psychology at Ball State University. Strongly committed to psychology education at all levels, she is Past-President of The Society for the Teaching of Psychology (STP, APA Division 2); she has held a number of other leadership roles for STP. She also chaired the APA Presidential Task Force on Diversity Education Resources and is Past President of the Midwestern Psychological Association. She is a Fellow of APA Divisions 2, 8, 9, 35, & 44 and of the Association for Psychological Science and the Midwestern Psychological Association. She maintains an active research program in the area of stereotyping and prejudice, including co-authoring The Psychology of Prejudice and Discrimination (3e) with Bernard Whitley, Jr.; Kite and Whitley also co-authored Principles of Research in Behavioral Science (4e). Recognitions include the Charles L. Brewer Award for Distinguished Teaching in Psychology from the American Psychological Foundation (2014) and a Presidential Citation from the Society for the Teaching of Psychology (2011). She was selected as a G. Stanley Hall Lecturer for the American Psychological Association in 2009 and was named a Minority Access National Role Model in 2007. Segment 1: External Validity [00:00-08:03] In this first segment, Dr. Kite discusses the importance of external validity in experimental research. Segment 2: Sampling [08:04-18:12] In segment two, Dr. Kite discusses sampling issues in quantitative research methods. Segment 3: Meta-analysis [18:13-31:20] In segment three, Dr. Kite describes the statistical technique of meta-analysis and shares finding from a recent meta-analysis. Bonus Clip [00:00-04:39]: Generalizability and Representative Samples To share feedback about this podcast episode, ask questions that could be featured in a future episode, or to share research-related resources, contact the “Research in Action” podcast: Twitter: @RIA_podcast or #RIA_podcast Email: riapodcast@oregonstate.edu Voicemail: 541-737-1111 If you listen to the podcast via iTunes, please consider leaving us a review. The views expressed by guests on the Research in Action podcast do not necessarily represent the views of Oregon State University Ecampus or Oregon State University.
Bonus Clip [00:00-04:39]: Generalizability and Representative Samples To share feedback about this podcast episode, ask questions that could be featured in a future episode, or to share research-related resources, contact the “Research in Action” podcast: Twitter: @RIA_podcast or #RIA_podcast Email: riapodcast@oregonstate.edu Voicemail: 541-737-1111 If you listen to the podcast via iTunes, please consider leaving us a review. The views expressed by guests on the Research in Action podcast do not necessarily represent the views of Oregon State University Ecampus or Oregon State University.
Author Bryan Sykes discusses his article, "The Problem of “Cameo Appearances” in Mixed-methods Research: Implications for Twenty-first-century Ethnography,” co-authored by Back Hawk Hancock and Anjuli Verma. The article is published in the April 2018 issue of Sociological Perspectives.
Commentary by Dr. Valentin Fuster
Background: Careful observation of the longitudinal course of bipolar disorders is pivotal to finding optimal treatments and improving outcome. A useful tool is the daily prospective Life-Chart Method, developed by the National Institute of Mental Health. However, it remains unclear whether the patient version is as valid as the clinician version. Methods: We compared the patient-rated version of the Lifechart (LC-self) with the Young-Mania-Rating Scale (YMRS), Inventory of Depressive Symptoms-Clinician version (IDS-C), and Clinical Global Impression-Bipolar version (CGI-BP) in 108 bipolar I and II patients who participated in the Naturalistic Follow-up Study (NFS) of the German centres of the Bipolar Collaborative Network (BCN; formerly Stanley Foundation Bipolar Network). For statistical evaluation, levels of severity of mood states on the Lifechart were transformed numerically and comparison with affective scales was performed using chi-square and t tests. For testing correlations Pearson's coefficient was calculated. Results: Ratings for depression of LC-self and total scores of IDS-C were found to be highly correlated (Pearson coefficient r = -.718; p < .001), whilst the correlation of ratings for mania with YMRS compared to LC-self were slightly less robust (Pearson coefficient r = .491; p = .001). These results were confirmed by good correlations between the CGI-BP IA (mania), IB (depression) and IC (overall mood state) and the LC-self ratings (Pearson coefficient r = .488, r = .721 and r = .65, respectively; all p < .001). Conclusions: The LC-self shows a significant correlation and good concordance with standard cross sectional affective rating scales, suggesting that the LC-self is a valid and time and money saving alternative to the clinician-rated version which should be incorporated in future clinical research in bipolar disorder. Generalizability of the results is limited by the selection of highly motivated patients in specialized bipolar centres and by the open design of the study.