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A Mobile App for the Self-Management of Type 1 Diabetes Among Adolescents: A Randomized Controlled Trial

A Mobile App for the Self-Management of Type 1 Diabetes Among Adolescents: A Randomized Controlled Trial

The primary research site (The Hospital for Sick Children) used a high-performance liquid chromatography assay (Bio-Rad Laboratories, Inc, Waterloo, ON, Canada) or an enzymatic assay (Abbott Laboratories, Ltd, North York, ON, Canada) to measure Hb A1c, with internal quality control demonstrating excellent agreement among samples assayed by both methods (r>.99).

Shivani Goyal, Caitlin A Nunn, Michael Rotondi, Amy B Couperthwaite, Sally Reiser, Angelo Simone, Debra K Katzman, Joseph A Cafazzo, Mark R Palmert

JMIR Mhealth Uhealth 2017;5(6):e82

Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial

Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial

Given these instructions instead of a recommended number of uses per day, engagement levels were assessed based on frequency of using the app to log foods per week categorized as high (logging ≥2 meals per week), medium (logging ≥1 meal every 2 weeks but Statistical analysis for the pilot randomized controlled trial was conducted using R (version 3.6.0) statistical software.

Jeffrey E Alfonsi, Elizabeth E Y Choi, Taha Arshad, Stacie-Ann S Sammott, Vanita Pais, Cynthia Nguyen, Bryan R Maguire, Jennifer N Stinson, Mark R Palmert

JMIR Mhealth Uhealth 2020;8(10):e22074

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study

Pearson correlation (r) of compliance in the nonblinded (below the diagonal) and blinded sets (above the diagonal). Similar to wearable compliance, phone agent compliance was calculated in half-hour time windows. However, the phone agent was intended to run without any user input or action apart from the initial installation and updates. This presented several challenges for researchers, as participants used 112 different models of mobile devices from 14 manufacturers throughout the study.

Gonzalo J Martinez, Stephen M Mattingly, Pablo Robles-Granda, Koustuv Saha, Anusha Sirigiri, Jessica Young, Nitesh Chawla, Munmun De Choudhury, Sidney D'Mello, Gloria Mark, Aaron Striegel

JMIR Mhealth Uhealth 2021;9(11):e22218

The Development of the Military Service Identification Tool: Identifying Military Veterans in a Clinical Research Database Using Natural Language Processing and Machine Learning

The Development of the Military Service Identification Tool: Identifying Military Veterans in a Clinical Research Database Using Natural Language Processing and Machine Learning

The second study, by Mark et al [10], on which this study is based, systematically searched for veterans using a military-related search term strategy on free-text clinical documents using a manual approach. Although this approach could identify veterans, it was time consuming as searches were performed manually.

Daniel Leightley, David Pernet, Sumithra Velupillai, Robert J Stewart, Katharine M Mark, Elena Opie, Dominic Murphy, Nicola T Fear, Sharon A M Stevelink

JMIR Med Inform 2020;8(5):e15852

Understanding Mental Health App Use Among Community College Students: Web-Based Survey Study

Understanding Mental Health App Use Among Community College Students: Web-Based Survey Study

The software environment R (R Foundation for Statistical Computing) was used for statistical analysis, and the R package lavaan was used for the structural equation models, bootstrapping, and confirmatory factor analysis [43]. Of the 500 participants, 189 (37.8%) reported that they had experienced a mental illness; 219 (43.8%) of participants reported mental health concerns related to stress.

Judith Borghouts, Elizabeth V Eikey, Gloria Mark, Cinthia De Leon, Stephen M Schueller, Margaret Schneider, Nicole Stadnick, Kai Zheng, Dana B Mukamel, Dara H Sorkin

J Med Internet Res 2021;23(9):e27745

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