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Pocket Parent-Child Interaction Therapy (PCIT) Online for Young Children With Disruptive Behaviors: Open Trial

Pocket Parent-Child Interaction Therapy (PCIT) Online for Young Children With Disruptive Behaviors: Open Trial

Descriptive statistics, correlation, chi-square, and t test analyses were completed in SPSS 29.0 (IBM Corporation). All regression analyses were conducted within Mplus 8.10 (Muthén & Muthén). Power analyses for the Pocket PCIT Online intervention were based on a similar self-directed, paper-based bibliotherapy version of PCIT, PCIT-Anticipatory Guidance [55].

Jason F Jent, Megan Golson, Abigail Peskin, William A Rothenberg, Hanan Salem, Allison Weinstein, Eileen Davis, Meaghan Parlade, Jocelyn Stokes, Tasha Brown, Michelle Berkovits, Dainelys Garcia

J Med Internet Res 2025;27:e69887

Optimizing Cardiovascular Risk Management in Primary Care Using a Personalized eCoach Solution Enhanced by an Artificial Intelligence–Driven Clinical Prediction Model: Protocol from the Coronary Artery Disease Risk Estimation and Early Detection Consortium

Optimizing Cardiovascular Risk Management in Primary Care Using a Personalized eCoach Solution Enhanced by an Artificial Intelligence–Driven Clinical Prediction Model: Protocol from the Coronary Artery Disease Risk Estimation and Early Detection Consortium

A paired sample t test will be performed for at least the 10-year ASCVD risk, assuming normality. Individual components, including systolic blood pressure, use of blood pressure medication, total cholesterol, HDL, use of lipid-modifying agents, smoking status, and moderate to vigorous physical activity, will be evaluated using the Mc Nemar test for dichotomous outcomes and the paired sample t test for continuous variables.

Rutger van Mierlo, Bart Scheenstra, Joost Verbeek, Anke Bruninx, Petros Kalendralis, Inigo Bermejo, Andre Dekker, Arnoud van 't Hof, Marieke Spreeuwenberg, Laura Hochstenbach

JMIR Res Protoc 2025;14:e66068

Federated Analysis With Differential Privacy in Oncology Research: Longitudinal Observational Study Across Hospital Data Warehouses

Federated Analysis With Differential Privacy in Oncology Research: Longitudinal Observational Study Across Hospital Data Warehouses

For quantitative variables, an implementation of the Student t test is used and from the result of this test, a P value is inferred. For qualitative variables, occurrence tables are computed (under the hood, the function table DP from DPPack [18] is used in each center and all the tables are summed) and then a chi-square or Fisher test is performed with the R functions “chisq.test” and “fisher.test.” Linear regression and Cox models were not implemented with DP.

Théo Ryffel, Perrine Créquit, Maëlle Baillet, Jason Paumier, Yasmine Marfoq, Olivier Girardot, Thierry Chanet, Ronan Sy, Louise Bayssat, Julien Mazières, Vincent Vuiblet, Julien Ancel, Maxime Dewolf, François Margraff, Camille Bachot, Jacek Chmiel

JMIR Med Inform 2025;13:e59685