Is maternal diabetes during pregnancy associated with neurodevelopmental, cognitive and behavioural outcomes in children? Insights from individual participant data meta-analysis in... by Rachelle A. Pretorius, Demetris Avraam, Mònica Guxens, Jordi Julvez, Jennifer R. Harris, Johanna Thorbjornsrud Nader, Tim Cadman, Ahmed Elhakeem, Katrine Strandberg-Larsen, Hanan El Marroun, Serena Defina, Tiffany C. Yang, Rosie McEachan, John Wright, Jesús Ibarluzea, Loreto Santa-Marina, Juana Mari Delgado, Marisa Rebagliato, Marie-Aline Charles, Chloe Vainqueur, Silvia Maritano, Daniela Zugna, Wen Lun Yuan, Barbara Heude, Rae-Chi Huang

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Practice patterns among early-career primary care (ECPC) physicians and workforce planning implications: protocol for a mixed methods study by Richard J Gibson, Tara Sampalli, Tara Kiran, Richard H Glazier, Agnes Grudniewicz, Kimberlyn McGrail, David Snadden, Ian Scott, M Ruth Lavergne, Laurie J Goldsmith, David Rudoler, Emily Gard Marshall, Megan Ahuja, Doug Blackie, Fred Burge, Steve Hawrylyshyn, Lindsay Hedden, Jacalynne Hernandez-Lee, Kathleen Horrey, Mike Joyce, Adrian MacKenzie, Maria Mathews, Rita McCracken, Madeleine McKay, Charmaine McPherson, Goldis Mitra, Gail Tomblin Murphy, Sabrina T Wong

“…We will also analyse linked administrative health data within each province. Mixed methods integration both within the study and as an end-of-study step will inform how practice intentions, choices and patterns are interrelated and inform policy recommendations.Ethics and dissemination This study was approved by the Simon Fraser University Research Ethics Board with harmonised approval from partner institutions. …”
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Acute pain pathways: protocol for a prospective cohort study by Christine Lee, Joseph S Ross, Molly Moore Jeffery, Nilay D Shah, David B Page, Nancy Chang, Fernanda Bellolio, Sam Torbati, Jessica D Ritchie, Gregg H Gilbert, Lindsay Emanuel, Mitra Ahadpour, Summer Allen, Richardae Araojo, Laura Ciaccio, Jonathan Fillmore, Patricia Koussis, Heather Lipkind, Celeste Mallama, Tamra Meyer, Megan Moncur, Teryl Nuckols, Michael A Pacanowski, Elektra Papadopoulos, Mat Soukup, Christopher O St. Clair, Stephen Tamang, Douglas W Wallace, Yueqin Zhao, Rebekah Heckmann

“…Participants will be followed for 6 months with the aid of a patient-centred health data aggregating platform that consolidates data from study questionnaires, electronic health record data on healthcare services received, prescription fill data from pharmacies, and activity and sleep data from a Fitbit activity tracker. …”
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Safety of a co-designed cognitive behavioural therapy intervention for people with type 1 diabetes and eating disorders (STEADY): a feasibility randomised controlled trialResearch... by Marietta Stadler, Natalie Zaremba, Amy Harrison, Jennie Brown, Divina Pillay, Jacqueline Allan, Rachael Tan, Salma Ayis, Emmanouela Konstantara, Janet Treasure, David Hopkins, Khalida Ismail

“…Main outcome at 6 months post-randomisation was feasibility. Baseline mental health data (Structured Clinical Interview for DSM-5, SCID-5RV), and secondary biomedical outcomes (HbA1c; glucose time in range; TIR) and person-reported outcome measures (PROM: Diabetes Eating Problems Survey-Revised, DEPS-R; Eating Disorder Examination Questionnaire Short, EDE-QS; Type 1 Diabetes Distress Scale, T1DDS; Generalised Anxiety Disorder Assessment, GAD-7; Patient Health Questionnaire, PHQ-9; Impact of Diabetes Profile, DIDP) were collected. …”
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Real-world effectiveness and causal mediation study of BNT162b2 on long COVID risks in children and adolescentsResearch in context by Qiong Wu, Bingyu Zhang, Jiayi Tong, L. Charles Bailey, H. Timothy Bunnell, Jiajie Chen, Elizabeth A. Chrischilles, Dimitri A. Christakis, Stephen M. Downs, Kathryn Hirabayashi, Aaron D. Mishkin, Abu S.M. Mosa, Nathan M. Pajor, Suchitra Rao, Hanieh Razzaghi, Hayden T. Schwenk, Marion R. Sills, Huiyuan Wang, Linbo Wang, Yudong Wang, Dazheng Zhang, Ting Zhou, Ravi Jhaveri, Eric J. Tchetgen Tchetgen, Jeffrey S. Morris, Christopher B. Forrest, Yong Chen

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TAME 2.0: expanding and improving online data science training for environmental health research by Alexis Payton, Alexis Payton, Alexis Payton, Elise Hickman, Elise Hickman, Elise Hickman, Jessie Chappel, Jessie Chappel, Jessie Chappel, Kyle Roell, Kyle Roell, Lauren E. Koval, Lauren E. Koval, Lauren A. Eaves, Lauren A. Eaves, Chloe K. Chou, Chloe K. Chou, Chloe K. Chou, Allison Spring, Allison Spring, Sarah L. Miller, Sarah L. Miller, Sarah L. Miller, Oyemwenosa N. Avenbuan, Oyemwenosa N. Avenbuan, Oyemwenosa N. Avenbuan, Rebecca Boyles, Rebecca Boyles, Paul Kruse, Cynthia V. Rider, Grace Patlewicz, Caroline Ring, Cavin Ward-Caviness, David M. Reif, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Rebecca C. Fry, Rebecca C. Fry, Rebecca C. Fry, Julia E. Rager, Julia E. Rager, Julia E. Rager, Julia E. Rager

“…Though data science training resources are expanding, they are still limited in terms of public accessibility, user friendliness, breadth of content, tangibility through real-world examples, and applicability to the field of environmental health science.MethodsTo fill this gap, we developed an environmental health data science training resource, the inTelligence And Machine lEarning (TAME) Toolkit, version 2.0 (TAME 2.0).ResultsTAME 2.0 is a publicly available website that includes training modules organized into seven chapters. …”
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