e.g. mhealth
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Skip search results from other journals and go to results- 33 JMIR mHealth and uHealth
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The questionnaires popped up on the participants’ smartphones whenever an NFC tag was scanned that indicated the end of an activity (eg, end of rounds, leaving a patient room, end of a meeting, end of speaking with a patient or his or her relatives) and asked, for example, “How stressed do you feel right now?” with a continuous slider from 0% to 100%, labeled in increments of 20%. In addition, the questionnaire could also be accessed at any time by scanning a designated NFC tag called “open questionnaire.”
JMIR Res Protoc 2025;14:e63549
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Over 80% (15/19) of participants had access to smart devices, defined as either smartphones, smartwatches, computers, and tablets.
Most participants, over 70% (13/19), disclosed annual household incomes below US $50,000. Hemoglobin A1c (Hb A1c) was self-reported (mean 6.77, SD 1.93). Ages ranged from 35 years old to 72 years old (mean age 58.79, SD 19.54). Approximately half (10/19, 52%) of participants did not pursue higher education (neither partially nor completed a college degree).
JMIR Form Res 2025;9:e65893
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Adolescent Emoji Use in Text-Based Messaging: Focus Group Study
smartphones
JMIR Form Res 2025;9:e59640
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Mobile Apps and Wearable Devices for Cardiovascular Health: Narrative Review
Smartphones equipped with photoplethysmography technology can detect atrial fibrillation and assess cardiovascular health by measuring blood volume changes using infrared light, this technique provides insights into heart rate and variability, offering a cost-effective and noninvasive method for evaluating cardiovascular fitness [9].
Wearable devices, typically worn on the wrist, arms, chest, or hips, can also be effective tools for managing CVD risks [10].
JMIR Mhealth Uhealth 2025;13:e65782
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For example, EMA prompts could be used to deliver real-time feedback or motivational messages when a participant is detected to be sedentary or transitioning to PA, leveraging data from wearable devices synced with smartphones. This adaptability positions EMA as a promising tool for both preventive health strategies and rehabilitation programs aimed at improving PA behaviors.
J Med Internet Res 2025;27:e59878
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Positive and negative affect surveys were deployed to participants’ smartphones once every 2 weeks via an abbreviated form of the Positive and Negative Affect Schedule (PANAS) [41,42]. The abbreviated PANAS consisted of 5 items assessing negative affect and 5 items assessing positive affect. Example items include “indicate to what extent you have felt afraid over the past few days” (negative affect) and “indicate to what extent you have felt inspired over the past few days” (positive affect).
J Med Internet Res 2025;27:e64965
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Leveraging the ubiquity of smartphones, ECHAS aims to be a scientifically validated and regulatory-approved digital medicine technology. The app is modeled on the “history and examination” of a neurologist or cardiologist by asking a series of evidence-based questions about the user’s medical history and symptoms, as well as a finger-tapping test designed to detect unilateral weakness.
JMIR Form Res 2025;9:e60465
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