e.g. mhealth
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Skip search results from other journals and go to results- 2 JMIR Formative Research
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To improve the effectiveness and adherence to PA, just-in-time adaptive interventions (JITAIs) are being investigated to tailor personalized and contextualized digital health support, often enabled by mobile health technologies such as wearable sensing devices and smartphones [8,9].
JMIR Mhealth Uhealth 2025;13:e57255
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Reference 15: Gestating bodies: sensing foetal movement in first-time pregnancysensing
Asian Pac Isl Nurs J 2024;8:e57128
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Reference 26: Digital phenotyping, behavioral sensing, or personal sensing: names and transparency insensing
JMIR Form Res 2023;7:e44323
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Although current approaches to medication adherence can implement static routines or idealized behavior, this study can inform the development of sensing, persuasive, and other technologies that meaningfully leverage users’ current behaviors and adapt to changing needs. The most substantial limitation is that the collected user sentiments were based on previous behavior, preference, and perception of hypothetical technologies, not on actual use.
JMIR Hum Factors 2023;10:e40173
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sensing remote sensing technology
J Med Internet Res 2023;25:e44352
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Relevant to depression in people with MS, clinicians could use this digital passive sensing approach to potentially identify patients who require urgent health interventions.
Past research has leveraged passively generated data from personal digital devices (eg, smartphones and fitness trackers) to capture human behavior and predict health outcomes.
JMIR Ment Health 2022;9(8):e38495
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These surveys are prompted based on recorded information about a participant’s current and prior locations, measured using the phone’s location-sensing system. At the end of each day, a density-based clustering algorithm clusters that day’s location measurements [35,36]. When clusters are found, they are inserted into a master cluster list for the participant.
JMIR Res Protoc 2022;11(7):e36666
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Answers to this question defined our outcome of interest; that is, the perceived helpfulness of mobile sensing apps. The concept of mobile sensing apps was introduced through multiple examples of what type of sensors might be used in mobile sensing apps and what behavioral insights might be obtained from these sensor data. In particular, we asked participants to rate the likeability and comfort with different mobile sensing features (Multimedia Appendix 1).
JMIR Form Res 2021;5(4):e24180
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Others had questions about efficacy:
I think with the sensing, I guess what’s the most effective. I mean with floor mats or bed mats, do you really just get someone’s movement that’s just normal movement, just restless or getting up and it’s not necessarily an emergency? We don’t want to install cameras, but I don’t know without a camera how you would know that.
J Med Internet Res 2018;20(2):e66
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