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Children’s Improvement After Language and Rhythm Training With the Digital Medical Device Poppins for Dyslexia: Single-Arm Intervention Study

Children’s Improvement After Language and Rhythm Training With the Digital Medical Device Poppins for Dyslexia: Single-Arm Intervention Study

In March 2022, Collège Français d’Orthophonie (French College of Speech Therapy [CFO]) [1] published its recommendations for best practices in written language. These best practice recommendations were developed using the formal consensus recommendation method described in the scientific rationale published by the Haute Autorité de Santé [24] and include a section on the management of SLD reading.

Charline Grossard, Melanie Descamps, Hugues Pellerin, François Vonthron, David Cohen

JMIR Serious Games 2025;13:e76435

Framework for Race-Specific Prostate Cancer Detection Using Machine Learning Through Gene Expression Data: Feature Selection Optimization Approach

Framework for Race-Specific Prostate Cancer Detection Using Machine Learning Through Gene Expression Data: Feature Selection Optimization Approach

Identifying significant genes is based on the set threshold of base Mean≥10 and p-adj The second and third scenarios were developed by introducing additional thresholds to the DEG results. The additional scenarios further narrowed down the outlier genes by applying log2 Fold Change>0.35 and >0.4, respectively. For the fourth scenario, ROC analysis was performed using the scikit-learn metrics library (version 1.5.1; scikit-learn developers) to isolate genes with high predictive impact [38,39].

David Agustriawan, Adithama Mulia, Marlinda Vasty Overbeek, Vincent Kurniawan, Jheno Syechlo, Moeljono Widjaja, Muhammad Imran Ahmad

JMIR Bioinform Biotech 2025;6:e72423

eHealth Literacy and Participation in Remote Blood Pressure Monitoring Among Patients With Hypertension: Cross-Sectional Study

eHealth Literacy and Participation in Remote Blood Pressure Monitoring Among Patients With Hypertension: Cross-Sectional Study

With 47.3% adult population with hypertension in the United States in 2021 [29], using 5% type 1 error (P=.05), the minimum sample size required to estimate participation in RBPM was 383 participants [30]. A minimum of 500 sample size has been recommended for detecting differences between the sample estimates and the population in observational studies involving logistic regression [31]. We stopped recruitment as soon as possible when we reached a sample size of 500.

Chinwe E Eze, Michael P Dorsch, Antoinette B Coe, Corey A Lester, Lorraine R Buis, Karen B Farris

J Med Internet Res 2025;27:e71926

The Impact of Vision Impairment on Self-Reported Falls Among Older US Adults: Cross-Sectional and Longitudinal Study

The Impact of Vision Impairment on Self-Reported Falls Among Older US Adults: Cross-Sectional and Longitudinal Study

All variables with a P value of A total of 38,835 respondents contributed to 117,834 participant-observations (see Tables 1 and 2). The total number of observations in which participants reported a total of 40,477 falls and 13,471 serious falls. The weighted proportion of participants who reported any falls was OR 37.9% (95% CI 37.7%‐40.1%), while the proportion reporting serious falls was OR 30.9% (95% CI 30.7%‐31.1%).

Kasem Seresirikachorn, Rachasak Somyanonthanakul, Matthew Johnson, Panisa Singhanetr, Jiraporn Gatedee, David Friedman, Nazlee Zebardast

JMIR Aging 2025;8:e68771

Large Language Model Symptom Identification From Clinical Text: Multicenter Study

Large Language Model Symptom Identification From Clinical Text: Multicenter Study

With an overall α of .05, a Bonferroni adjustment for 12 comparisons (11 symptoms plus no symptoms) set the threshold at P ICD-10 codelists (Multimedia Appendix 2) [4] for each symptom were compiled by 3 experts at BCH using online resources [43,44]. The panel collaboratively reviewed whether each candidate code met the inclusion or exclusion criteria defined in the symptom annotation guidelines. ICD-10 codes recorded at the time of ED discharge were matched against the final symptom codelists.

Andrew J McMurry, Dylan Phelan, Brian E Dixon, Alon Geva, Daniel Gottlieb, James R Jones, Michael Terry, David E Taylor, Hannah Callaway, Sneha Manoharan, Timothy Miller, Karen L Olson, Kenneth D Mandl

J Med Internet Res 2025;27:e72984

Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial

Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial

Reach-Accept testing in the Chatbot arm was lower than in SMS text messaging (174/1051, 16.6% vs 555/1066, 52.1%; a RR 0.317, 98.33% CI 0.27‐0.38; P Reach-Accept testing was higher among participants messaged every 10 days vs every 30 days (860/15,717, 5.5% vs 752/15,722, 4.8%; a RR 1.144, 97.5% CI 1.03‐1.28; P=.01; Table 2), and lower if the participants were offered access to PN compared with those in the no PN condition (680/15,718, 4.3% vs 932/15,721, 5.9%; a RR 0.729, 97.5% CI 0.65‐0.81; P Out of 2117 participants

Guilherme Del Fiol, Tatyana V Kuzmenko, Brian Orleans, Jonathan J Chipman, Tom Greene, Ray Meads, Kimberly A Kaphingst, Bryan Gibson, Kensaku Kawamoto, Andy J King, Tracey Siaperas, Shlisa Hughes, Alan Pruhs, Courtney Pariera Dinkins, Cho Y Lam, Joni H Pierce, Ryzen Benson, Emerson P Borsato, Ryan C Cornia, Leticia Stevens, Richard L Bradshaw, Chelsey R Schlechter, David W Wetter

J Med Internet Res 2025;27:e74145