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Skip search results from other journals and go to results- 4 Journal of Medical Internet Research
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While all participants reviewed a total of 15 additional snippets, when they initiated the survey, they were randomly assigned to either read a set of snippets that included more risk items (called “survey A”) or more procedural items (called “survey B”). The random assignment resulted in 41 (52%) participants receiving survey A and 38 (48%) participants receiving survey B.
J Med Internet Res 2025;27:e63349
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Tutorial for Using Control Systems Engineering to Optimize Adaptive Mobile Health Interventions
Classic tailoring uses if-then structures, such as if stage of change=X then Intervention=A; if stage of change=Y then intervention=B [9,10]. Although controllers can use if-then structures, they can use other structures, particularly mathematical equations and optimization algorithms that can account for multiple tailoring variables, intervention options, and responses of the person simultaneously.
One can think of this like accounting. The controller keeps a ledger of measurements.
J Med Internet Res 2018;20(6):e214
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To be included, the primary caretaker (hereafter referred to as the parent) of an OW/OB preschooler aged 3 through 5 years had to (a) have a preschooler with a medical diagnosis of OW/OB, defined as a BMI percentile of 85% or above; (b) possess an active mobile phone with text-messaging capability; (c) be between the ages of 18 and 45 years; and (d) give consent for participation.
JMIR Mhealth Uhealth 2016;4(1):e21
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Spearman rank order correlationsa (ρ) between raw Acti Graph and raw phone counts for the laboratory study (N=15).
a The Spearman correlations are between counts/min derived for the Acti Graph and the 3 Android smartphones (Motorola Cliq, HTC My Touch, and Google/HTC Nexus One).
b The different models correspond to different filters (ie, no bike & standing excludes bicycling and standing; hip-only excludes measures whereby the phones were in the pocket).
JMIR Mhealth Uhealth 2015;3(2):e36
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In the model whereby only word count was added to the model, results found that word count alone did not predict weight (ie, B=–0.000009, SE 0.000063, P=.13).
J Med Internet Res 2014;16(12):e254
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