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An Exergames Program for Adolescents With Type 1 Diabetes: Qualitative Study of Acceptability

An Exergames Program for Adolescents With Type 1 Diabetes: Qualitative Study of Acceptability

I just wanna be, you know, the healthiest I can...the healthiest in terms of like blood sugar especially, and that could be helped a lot by, being physically active, so I think...having good blood sugar is, is what motivates me. I feel like when I exercise my blood sugars are more stable throughout the day, so exercise usually is a part of my daily routine.

Selene S Mak, Laura M Nally, Juanita Montoya, Rebecca Marrero, Melissa DeJonckheere, Kevin L Joiner, Soohyun Nam, Garrett I Ash

JMIR Diabetes 2025;10:e65665

Smart Wearable Technologies for Balance Rehabilitation in Older Adults at Risk of Falls: Scoping Review and Comparative Analysis

Smart Wearable Technologies for Balance Rehabilitation in Older Adults at Risk of Falls: Scoping Review and Comparative Analysis

Reference 16: Global strategy on digital health 2020-2025(https://www.who.int/publications/i/item/9789240020924 Reference 17: Classification of digital health interventions v10(https://www.who.int/publications/i/item

Brooke Nairn, Vassilios Tsakanikas, Becky Gordon, Efterpi Karapintzou, Diego Kaski, Dimitrios I Fotiadis, Doris-Eva Bamiou

JMIR Rehabil Assist Technol 2025;12:e69589

Evaluating the Accuracy and Reliability of Real-World Digital Mobility Outcomes in Older Adults After Hip Fracture: Cross-Sectional Observational Study

Evaluating the Accuracy and Reliability of Real-World Digital Mobility Outcomes in Older Adults After Hip Fracture: Cross-Sectional Observational Study

MREs and mean absolute relative errors (MAREs) were calculated by dividing the (absolute) errors per WB by the corresponding estimates from the reference system, expressed in percentage, as shown in the following formulas (SWD refers to the single wearable device, and RS refers to the reference system): Mean error = (1 / n) × Σ from i=1 to n ([DMO_SWDi– DMO_RSi]) MRE = (1 / n) × Σ from i=1 to n ([(DMO_SWDi– DMO_RSi)/DMO_RSi] × 100) Mean absolute error = (1 / n) × Σ from i=1 to n (|DMO_SWDi – DMO_RSi|) MARE =

Martin A Berge, Anisoara Paraschiv-Ionescu, Cameron Kirk, Arne Küderle, Encarna Micó-Amigo, Clemens Becker, Andrea Cereatti, Silvia Del Din, Monika Engdal, Judith Garcia-Aymerich, Karoline B Grønvik, Clint Hansen, Jeffrey M Hausdorff, Jorunn L Helbostad, Carl-Philipp Jansen, Lars Gunnar Johnsen, Jochen Klenk, Sarah Koch, Walter Maetzler, Dimitrios Megaritis, Arne Müller, Lynn Rochester, Lars Schwickert, Kristin Taraldsen, Beatrix Vereijken

JMIR Form Res 2025;9:e67792

Cocreating the Visualization of Digital Mobility Outcomes: Delphi-Type Process With Patients

Cocreating the Visualization of Digital Mobility Outcomes: Delphi-Type Process With Patients

[White female participant with MS aged 51-60 y] “Very Faint” and “Too Pale” [White male participant with PD aged 71-80 y] “The information is good, I like the idea of being able to compare times of day, however I think the nighttime slot is too short and should be at least 10 hours. The evening slot is too long and shouldn’t go past 10pm. A better distribution would be Morning 7am-12pm; afternoon 12pm-5pm; evening 5pm-10pm, night 10pm to 7am.”

Jack Lumsdon, Cameron Wilson, Lisa Alcock, Clemens Becker, Francesco Benvenuti, Tecla Bonci, Koen van den Brande, Gavin Brittain, Philip Brown, Ellen Buckley, Marco Caruso, Brian Caulfield, Andrea Cereatti, Laura Delgado-Ortiz, Silvia Del Din, Jordi Evers, Judith Garcia-Aymerich, Heiko Gaßner, Tova Gur Arieh, Clint Hansen, Jeffrey M Hausdorff, Hugo Hiden, Emily Hume, Cameron Kirk, Walter Maetzler, Dimitrios Megaritis, Lynn Rochester, Kirsty Scott, Basil Sharrack, Norman Sutton, Beatrix Vereijken, Ioannis Vogiatzis, Alison Yarnall, Alison Keogh, Alma Cantu

JMIR Form Res 2025;9:e68782