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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

All analyses were performed using the JJ Allaire R Studio software (version 4.2.1, 2022; Posit, PBC). The study was approved by the University of Michigan Institutional Review Board with the approval number HUM00205760. Informed consent and the ability to opt out of the study were provided to the participants, and they consented and signed before they could participate in the study. Anonymized data containing no identifiable personal information were collected from the participants.

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

Behavioral Factors Related to Participation in Remote Blood Pressure Monitoring Among Adults With Hypertension: Cross-Sectional Study

Behavioral Factors Related to Participation in Remote Blood Pressure Monitoring Among Adults With Hypertension: Cross-Sectional Study

All analyses were performed using the R Studio software, version 4.2.1 (JJ Allaire and Posit). A total of 507 people with hypertension meeting the study criteria were consented to the study and surveyed. The mean age for all participants was 60 (SD 14.7) years (Table 1). The respondents were mostly female (306/507, 60.4%), non-Hispanic (483/507, 95.3%), and White (429/507, 84.6%).

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

JMIR Form Res 2024;8:e56954

Correction: The Effect of an mHealth Self-Monitoring Intervention (MI-BP) on Blood Pressure Among Black Individuals With Uncontrolled Hypertension: Randomized Controlled Trial

Correction: The Effect of an mHealth Self-Monitoring Intervention (MI-BP) on Blood Pressure Among Black Individuals With Uncontrolled Hypertension: Randomized Controlled Trial

The reference has been revised to: Sallis J, Pinski R, Grossman R, Patterson T, Nader P. The development of self-efficacy scales for healthrelated diet and exercise behaviors. Health Educ Res. 1988;3(3):283-292. The correction will appear in the online version of the paper on the JMIR Publications website on August 6, 2024, together with the publication of this correction notice.

Lorraine R Buis, Junhan Kim, Ananda Sen, Dongru Chen, Katee Dawood, Reema Kadri, Rachelle Muladore, Melissa Plegue, Caroline R Richardson, Zora Djuric, Candace McNaughton, David Hutton, Lionel P Robert, Sun Young Park, Phillip Levy

JMIR Mhealth Uhealth 2024;12:e64632

Identifying Inequities in Video and Audio Telehealth Services for Primary Care Encounters During COVID-19: Repeated Cross-Sectional, Observational Study

Identifying Inequities in Video and Audio Telehealth Services for Primary Care Encounters During COVID-19: Repeated Cross-Sectional, Observational Study

All data cleaning and analyses were conducted using R statistical software [15]. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for reporting cross-sectional, observational studies was utilized to ensure robust reporting in this paper [16]. Primary Analysis Primary analysis focused on the status of each encounter, in terms of whether it was completed as scheduled, it was canceled, or the patient missed the encounter.

Lorraine R Buis, Lindsay K Brown, Melissa A Plegue, Reema Kadri, Anna R Laurie, Timothy C Guetterman, V G Vinod Vydiswaran, Jiazhao Li, Tiffany C Veinot

J Med Internet Res 2023;25:e49804

Predictors of Smartphone and Tablet Use Among Patients With Hypertension: Secondary Analysis of Health Information National Trends Survey Data

Predictors of Smartphone and Tablet Use Among Patients With Hypertension: Secondary Analysis of Health Information National Trends Survey Data

We accounted for the sampling weights and complex sample design features in all analyses to obtain population-level estimates for the United States using the R survey package by Thomas Lumley. Variance estimates were computed using the jackknife replication method, and specialized (unconditional) subpopulation analyses were not required when using this replication approach [24]. Descriptive statistics were used to analyze the characteristics of the respondents based on relevant demographics and covariates.

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

J Med Internet Res 2022;24(1):e33188

Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial

Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial

We anticipated a baseline mean of 53 minutes, a standard deviation of 28 minutes in both treatment groups, and r=0.46 correlation between baseline and 12 months. Because of the lengthy enrollment process, we expected up to 50% dropout during the consent and preparation phases, and assumed 25% dropout after enrollment during the 12-month program.

Laura J Damschroder, Lorraine R Buis, Felicia A McCant, Hyungjin Myra Kim, Richard Evans, Eugene Z Oddone, Lori A Bastian, Gwendolyn Hooks, Reema Kadri, Courtney White-Clark, Caroline R Richardson, Jennifer M Gierisch

J Med Internet Res 2020;22(8):e19216