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iCogCA to Promote Cognitive Health Through Digital Group Interventions for Individuals Living With a Schizophrenia Spectrum Disorder: Protocol for a Nonrandomized Concurrent Controlled Trial

iCogCA to Promote Cognitive Health Through Digital Group Interventions for Individuals Living With a Schizophrenia Spectrum Disorder: Protocol for a Nonrandomized Concurrent Controlled Trial

Monte Carlo simulations computed in R (R Foundation for Statistical Computing) were used to estimate the required sample size for our proposed models. Our analyses, based on simulated data, suggest that a total sample size of 300 provides enough statistical power (up to 90%) to detect anticipated effect sizes on primary outcomes of cognitive capacity and cognitive bias based on values from our group and those reported in the literature (CR: d=0.50 and MCT: g=0.27) [9,20,27,31].

Christy Au-Yeung, Helen Thai, Michael Best, Christopher R Bowie, Synthia Guimond, Katie M Lavigne, Mahesh Menon, Steffen Moritz, Myra Piat, Geneviève Sauvé, Ana Elisa Sousa, Elisabeth Thibaudeau, Todd S Woodward, Martin Lepage, Delphine Raucher-Chéné

JMIR Res Protoc 2025;14:e63269

Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

The PMIS (Pearson r=−0.76; P As we examined the sensitivity and specificity data to choose cut scores, we chose to favor sensitivity to minimize missing individuals with true disease in this sample of patients considered high risk because of their cognitive concerns. The cut scores for a positive result on the 5-Cog components were as follows: PMIS ≤6 (range 0-8), Symbol Match ≤25 (range 0-65), and s MCR >5 (range 0-7).

Rachel Beth Rosansky Chalmer, Emmeline Ayers, Erica F Weiss, Nicole R Fowler, Andrew Telzak, Diana Summanwar, Jessica Zwerling, Cuiling Wang, Huiping Xu, Richard J Holden, Kevin Fiori, Dustin D French, Celeste Nsubayi, Asif Ansari, Paul Dexter, Anna Higbie, Pratibha Yadav, James M Walker, Harrshavasan Congivaram, Dristi Adhikari, Mairim Melecio-Vazquez, Malaz Boustani, Joe Verghese

JMIR Res Protoc 2025;14:e60471

Conversion of Sensitive Data to the Observational Medical Outcomes Partnership Common Data Model: Protocol for the Development and Use of Carrot

Conversion of Sensitive Data to the Observational Medical Outcomes Partnership Common Data Model: Protocol for the Development and Use of Carrot

For example, assume a field “Sex” is provided with the value “M,” and this has previously been manually mapped to the OMOP concept 8507 “Male” in one scan R=report. In the case where a later scan report is uploaded with another field “Gender” and the value “M,” the system automatically applies the previous mapping rule to this value in this field in the new scan report.

Samuel Cox, Erum Masood, Vasiliki Panagi, Calum Macdonald, Gordon Milligan, Scott Horban, Roberto Santos, Chris Hall, Daniel Lea, Simon Tarr, Shahzad Mumtaz, Emeka Akashili, Andy Rae, Esmond Urwin, Christian Cole, Aziz Sheikh, Emily Jefferson, Philip Roy Quinlan

JMIR Res Protoc 2025;14:e60917