Protocol for the development of a reporting guideline for causal and counterfactual prediction models in biomedicine by Yi Guo, Hua Xu, Fei Wang, Jie Xu, Jiang Bian, Robert Lucero, Mattia Prosperi

“…In stage 3, a computer-based, real-time Delphi survey will be performed to consolidate the PRECOG checklist, involving experts in causal inference, epidemiology, statistics, machine learning, informatics and protocols/standards. …”
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Herpes zoster vaccine and the risk of stroke: a population-based cohort study using linked data from the Clinical Practice Research Datalink by Fawziah Marra, Kathryn Richardson, Helen I McDonald, Yoon Kong Loke, Helen Mary Parretti

“…Our study illustrates the importance of robust sensitivity analyses and testing the suitability of causal inference tools for observational vaccine studies.…”
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Impact of Comprehensive Health Insurance affiliation on mortality in children under one year: an analysis of the Demographic and Health Survey 2010–2022 in Peru by Marcos Espinola-Sánchez, Marcos Espinola-Sánchez, Andres Campaña-Acuña, Diego Urrunaga-Pastor, Diego Urrunaga-Pastor, Jorge L. Maguiña, Manuel Jumpa, Oscar Ugarte-Ubillus

“…Additionally, the study evaluated how CHI affects infant mortality according to wealth quintiles in the Peruvian population.MethodsA causal inference analysis with observational data was applied, employing propensity score matching. …”
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Effect of trace elements and nutrients on 21 autoimmune diseases: a Mendelian randomization study by Ming-Jie Jia, Hua-Fang Yin, Ying-Chao Liang, Feng Jiang, Hui-Lin Li, Hui-Lin Li

“…MR was employed to explore the causal relationships between 9 trace elements and 6 vitamins and autoimmune diseases. Causal inference was performed using inverse variance weighted methods, MR Egger, and weighted median methods. …”
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Fingolimod and risk of skin cancer among individuals with multiple sclerosis: a population-based cohort study protocol by Lisa Kuramoto, Larry D Lynd, Amir Khakban, Jacquelyn J Cragg, Anthony Traboulsee, Jiwon Oh, Analisa Jia, Weng Sut Sio, M A De Vera, Jonathan Loree, Roger Tam

“…Introduction Long-term population-based safety studies, applying advanced causal inference techniques, including an active comparator with new-user design, are needed to investigate skin cancer outcomes among individuals with multiple sclerosis (MS) treated with fingolimod. …”
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Atopic dermatitis in childhood and pubertal development: A nationwide cohort studyCapsule Summary by Camilla Lomholt Kjersgaard, MD, Andreas Ernst, MD, PhD, Pernille Jul Clemmensen, MD, PhD, Lea Lykke Harrits Lunddorf, MD, PhD, Linn Håkonsen Arendt, MD, PhD, Nis Brix, MD, PhD, Onyebuchi A. Arah, MD, PhD, Mette Deleuran, MD, PhD, Cecilia Høst Ramlau-Hansen, MHSc, PhD

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Evaluation of variation in special educational needs provision and its impact on health and education using administrative records for England: umbrella protocol for a mixed-method... by Stuart Logan, Ruth Gilbert, Tamsin Ford, Johnny Downs, Jugnoo Rahi, Ania Zylbersztejn, Katie Harron, Kate Boddy, Bianca De Stavola, Vincent Nguyen, Isaac Winterburn, Kate Lewis, Lucy Karwatowska, Lorraine Dearden, Sarah Barnes, Jacob Matthews, Matthew Lilliman, Jennifer Saxton, Antony Stone, Kristine Black-Hawkins

“…WP3 assesses the impact of SEN provision on health and education outcomes for specific health phenotypes using a range of causal inference methods to account for confounding factors and possible selection bias. …”
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Potential drug targets for asthma identified through mendelian randomization analysis by Xingxuan Chen, Yu Shang, Danting Shen, Si Shi, Zhe Wen, Lijuan Li, Hong Chen

“…Bidirectional Mendelian randomization analysis, Steiger filtering, colocalization, and phenotype scanning were employed for reverse causal inference detection, further substantiating the Mendelian randomization results. …”
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Supervised Injecting Room Cohort Study (SIRX): study protocol by Lisa Maher, Thomas Kerr, Matthew Hickman, Alexander Thompson, Peter Higgs, Paul Dietze, Paul A Agius, Nick Scott, Daniel O’Keefe, Mark A Stoové, Jack Stone, Dylan Vella-Horne, Ashleigh C Stewart, Amanda Roxburgh, Sione Crawford, Josephine Norman, Zachary Lloyd, Nico Clark

“…Primary outcomes are aligned to the legislated aims of the Melbourne MSIR, including ambulance-attended non-fatal overdoses and all-cause and drug-related mortality. Using causal inference methods, analyses will estimate the effect of MSIR exposure (frequent use/infrequent use/no use) on these primary outcomes. …”
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What is the near-natural catchment? An application of hydrological signatures assessment by Huan Xu, Hao Wang, Pan Liu, Xiaojing Zhang, Weibo Liu, Chutian Zhou, Hao Ye, Hongxuan Lei, Yang Liu

“…The sensitivity of the eight signatures to HA are calculated using a causal inference method instead of directly calculating linear correlation coefficients to avoid spurious relationships. …”
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Editorial by Michael Rose, Jonathan M. Hoffmann

“…Discussing different arguments and methods of causal inference, Thomas Bontly (Storrs, CT) employs a difference-making perspective and shows that there is indeed a highly significant non-identity effect of climate change policies. …”
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Cohort profile: the multigeneration Respiratory Health in Northern Europe, Spain and Australia (RHINESSA) cohort by Thorarinn Gislason, Torben Sigsgaard, Vivi Schlünssen, Joachim Heinrich, Jesús Martínez-Moratalla, Øistein Svanes, Mathias Holm, Bertil Forsberg, Dan Norbäck, Rain Jogi, Kjell Torén, Deborah Jarvis, Magnus Ekström, Adrian Lowe, Caroline J Lodge, Michael Abramson, Shyamali Dharmage, Kathrine Pape, Cecilie Svanes, Gita Mishra, Caroline Lodge, Lyle Gurrin, Bruce Thompson, Eva Lindberg, Christer Janson, Simone Accordini, Ane Johannessen, Bryndis Benediktsdottir, Karl Franklin, Andrei Malinovschi, Anna Oudin, Francisco Gómez Real, José Luis Sánchez-Ramos, Lennart Bråbäck, Torgeir Storaas, Shanshan Xu, Julia Dratva, John Holloway, Jorunn Kirkeleit, Christine Cramer, Gro Tjalvin, Anne Mette Lund Würtz, Randi Jacobsen Bertelsen, Oskar Jõgi, Signe Timm, Francisco Javier Callejas, Raúl Godoy, Trude Duelien Skorge, Christine Drengenes, Nils Oskar Jõgi, Maryia Khomich, Toril Mørkve Knudsen, Ingrid Kuiper, Juan Pablo López-Cervantes, Marianne Lønnebotn, Shokouh Makvandi-Nejad, Antonio Pérez, Anders Røsland, Rajesh Shigdel, Svein Magne Skulstad, Kai Triebner, Hilde Vindenes, Jose Luis Sanchez, Jose Maldonado, David Martino, Jennifer Perret, Lucia Calciano, William Horsnell, Susanne Krauss-Etchmann

“…Statistical analyses developed to approach causal inference suggest that these associations may be causal. …”
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The Mongol empire’s expansion and rethinking research trends in Chinese historical climatology by Ka wai Fan

“…Through critical analysis of the history of the Mongol Empire, this study contributes to a deeper understanding of the complex relationships between climate change and human history, advocating for prudence in drawing causal inferences.…”
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The digital age students: Exploring leadership, freedom, and ethical online behavior: A quantitative study by Mohamed Mekheimer, Walid Mohamed Abdelhalim

“…While acknowledging the limitations of our cross-sectional design, which precludes causal inferences, and the need for further research across diverse contexts, this study provides a valuable framework for future longitudinal investigations into the complex dynamics of digital responsibility.…”
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Economic instruments for population diet and physical activity behaviour change: a systematic scoping review. by Ian Shemilt, Gareth J Hollands, Theresa M Marteau, Ryota Nakamura, Susan A Jebb, Michael P Kelly, Marc Suhrcke, David Ogilvie

“…Future research should include measurement of people's actual behavioural responses using study designs capable of generating reliable causal inferences regarding intervention effects. Policy implementation needs to be carefully aligned with evaluation planning and design.…”
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Evaluating the Effectiveness of Patient-Centered Standardized Prophylaxis Processes in Enhancing Patient Satisfaction and Return Intentions by Wen Tao, Tingfang Liu

“…However, the findings should be interpreted with caution due to the study’s cross-sectional nature, which limits causal inferences, and the specific demographic characteristics that may affect the general applicability of the results. …”
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Opening a career door!: The role of ChatGPT adoption in digital entrepreneurial opportunity recognition and exploitation by Cong Doanh Duong, Thi Thanh Hoa Phan, Bich Ngoc Nguyen, Thanh Van Pham, Ngoc Diep Do, Anh Trong Vu

“…While this study offers valuable contributions, its reliance on self-reported data and a cross-sectional design may limit causal inferences and generalizability. Future research should consider longitudinal designs and diverse samples, such as established entrepreneurs or non-Asian populations, to explore ChatGPT adoption in broader contexts.…”
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