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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].
JMIR Res Protoc 2025;14:e63269
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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).
JMIR Res Protoc 2025;14:e60471
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Statistical analyses were conducted using SAS (SAS Institute) [46] and R software (R Foundation for Statistical Computing) [47], and significance was determined at a P value of .05.
Following transcription, 3 members of the research team (SS, SM, and TC) conducted a double-coding process on the transcripts from 52% (12/23) intervention group participants and 48% (11/23) control group participants.
JMIR Form Res 2025;9:e67997
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