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Effects of Missing Data on Heart Rate Variability Measured From A Smartwatch: Exploratory Observational Study

Effects of Missing Data on Heart Rate Variability Measured From A Smartwatch: Exploratory Observational Study

Many commercial off-the-shelf (COTS) wearable sensors provide data on important physiological information, particularly wrist-worn devices used to measure heart rate [7,8]. Wrist-worn devices most often use embedded photoplethysmography sensors that detect changes in light intensity on the skin surface due to changes in blood volume during the cardiac cycle to estimate heart rate [9].

Hope Davis-Wilson, Meghan Hegarty-Craver, Pooja Gaur, Matthew Boyce, Jonathan R Holt, Edward Preble, Randall Eckhoff, Lei Li, Howard Walls, David Dausch, Dorota Temple

JMIR Form Res 2025;9:e53645

Exploring the Use of a Length AI Algorithm to Estimate Children’s Length from Smartphone Images in a Real-World Setting: Algorithm Development and Usability Study

Exploring the Use of a Length AI Algorithm to Estimate Children’s Length from Smartphone Images in a Real-World Setting: Algorithm Development and Usability Study

In total, 7 (88%) of 8 investigators indicated that they would be likely or very likely to use a digital tool that could automatically measure a child’s length from an image, if available for clinical use (Multimedia Appendix 2). A similar proportion (7/8, 88% investigators) reported that they would be likely or very likely to recommend a digital length measurement tool to parents for home use, if available.

Mei Chien Chua, Matthew Hadimaja, Jill Wong, Sankha Subhra Mukherjee, Agathe Foussat, Daniel Chan, Umesh Nandal, Fabian Yap

JMIR Pediatr Parent 2024;7:e59564

Clinician-Prioritized Measures to Use in a Remote Concussion Assessment: Delphi Study

Clinician-Prioritized Measures to Use in a Remote Concussion Assessment: Delphi Study

The sensitivity, specificity, and additional considerations for the administration of each measure (eg, equipment needed or time for administration) identified in the review of the literature were presented. The clinicians were then asked to rerank the identified measures from most to least relevant to their in-person clinical practice. Mean rankings were calculated by summing the product of the weight and frequency count for each measure and dividing by the total number of responses.

Keely Barnes, Heidi Sveistrup, Mark Bayley, Mary Egan, Martin Bilodeau, Michel Rathbone, Monica Taljaard, Shawn Marshall

JMIR Form Res 2024;8:e47246

Development and Validation of a Mobile-Centered Digital Health Readiness Scale (mDiHERS): Health Literacy and Equity Scale

Development and Validation of a Mobile-Centered Digital Health Readiness Scale (mDiHERS): Health Literacy and Equity Scale

Additionally, because existing health literacy scales rely on subjective measurements, it is impossible to know how an individual’s responses relate to actual skill level, whereas objective tests can directly measure an individual’s skills [9,10]. Motivated by this, our study endeavors to construct and validate a scale measuring digital health readiness consisting of subjective and objective questions.

Hana Kim, Rebecca Schnall, Nagyeom Yoon, Seong-Joon Koh, Jisan Lee, Jae Hee Cheon

J Med Internet Res 2024;26:e58497

A Multidimensional Approach for Evaluating Reality in Social Media: Mixed Methods Study

A Multidimensional Approach for Evaluating Reality in Social Media: Mixed Methods Study

Given the pervasiveness of misinformation [1-3], our goal was to offer a general measure that can be used in diverse public health domains. These efforts aim to inform and enhance public health misinformation–countering efforts using digital media literacy. Toward this end, 2 studies were conducted. First, qualitative focus group research examined salient themes in social media realism judgments among users.

HyunYi Cho, Wenbo Li, Rachel Lopez

J Med Internet Res 2024;26:e52058

Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study

Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study

To address this gap, it is crucial to develop tools that comprehensively measure AI researchers' knowledge, attitudes, and practices of ethics implementation. The Knowledge-Attitude-Practice (KAP) model is widely used in medical research as the most commonly used model [31-33], proposed that knowledge was the basis of behavior change, and attitude and practice are the driving force of behavior change.

Xiaobo Zhang, Ying Gu, Jie Yin, Yuejie Zhang, Cheng Jin, Weibing Wang, Albert Martin Li, Yingwen Wang, Ling Su, Hong Xu, Xiaoling Ge, Chengjie Ye, Liangfeng Tang, Bing Shen, Jinwu Fang, Daoyang Wang, Rui Feng

JMIR Form Res 2023;7:e42202

Blood Pressure Measurement Based on the Camera and Inertial Measurement Unit of a Smartphone: Instrument Validation Study

Blood Pressure Measurement Based on the Camera and Inertial Measurement Unit of a Smartphone: Instrument Validation Study

This equation model was implemented in the Always BP app and used to measure blood pressure at the initial visit and at follow-up. The test blood pressure measurement software was installed and used in a Galaxy S10 smartphone (Samsung Electronics) throughout this study. The test software has yet to be released on the app market for commercial use.

Yong-Hoon Yoon, Jongin Kim, Kwang Jin Lee, Dongrae Cho, Jin Kyung Oh, Minsu Kim, Jae-Hyung Roh, Hyun Woong Park, Jae-Hwan Lee

JMIR Mhealth Uhealth 2023;11:e44147

Assessing the Well-Being at Work of Nurses and Doctors in Hospitals: Protocol for a Scoping Review of Monitoring Instruments

Assessing the Well-Being at Work of Nurses and Doctors in Hospitals: Protocol for a Scoping Review of Monitoring Instruments

Instruments to measure well-being at work vary in specific professions [14] and specific settings [15] or include only one or two aspects of well-being at work [12,16]. This study is part of a program of the Netherlands Federation of University Medical Hospitals (NFU) about finding ways to improve and monitor health care professionals’ well-being in Dutch hospitals. Strikingly, there is often a substantial gap and mismatch between employer perceptions of well-being and well-being interventions [8].

Amber Boskma, Kim van der Braak, Neda Ansari, Lotty Hooft, Götz Wietasch, Arie Franx, Maarten van der Laan

JMIR Res Protoc 2023;12:e43692