e.g. mhealth
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Skip search results from other journals and go to results- 3 Journal of Medical Internet Research
- 2 JMIR Formative Research
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While statistical tests did not indicate that the measurements obtained across devices are systematically nonequivalent, we cannot rule out that this finding may be due to high variability, different average disease severity, or, for a few comparisons, a small sample size.
J Med Internet Res 2025;27:e63090
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Reference 3: Measuring heart rate variability using commercially available devices in healthy children Reference 26: Validity of the Polar H10 sensor for heart rate variability analysis during resting statevariability
JMIR Mhealth Uhealth 2025;13:e54871
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Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium
A wide range was observed, stretching from 25.56% to 94.70%, reflecting significant variability among institutions within this department, as evidenced by an IQR of 31.77%. Conversely, the pediatrics department presented a mean completeness of 60.11% with an even larger IQR of 73.10%, suggesting a more pronounced discrepancy in recording practices. Here, data completeness varied from a minimum of 11.29% to a maximum of 97.26%.
JMIR Med Inform 2024;12:e60244
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This variability is likely attributed to insufficient methodological quality and diverse study designs, making it challenging to derive a single reliable estimate of the diagnostic outcomes. A total of 5 (Cochrane) systematic reviews ascribe this heterogeneity to a variety of other factors, including variations in study characteristics, such as the complexity in the detection of certain skin lesion types [8-12].
JMIR Dermatol 2024;7:e60346
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This is why some studies have reported significant tester variability [20].
The primary aim of this study was to investigate the impact of tester variability on the accuracy of outcome of SCs, using clinical vignettes. The secondary aim was to identify the methodology to measure isolated aspects of SC performance using clinical vignettes. We investigated the following two isolated aspects: (1) SC data and algorithm quality using adjusted accuracy metrics and (2) SC symptom comprehension.
JMIR Form Res 2024;8:e49907
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We first examined the relationship between mean and day-to-day sleep efficiency variability using the Pearson r correlation coefficient and a scatterplot. Thereafter, using cutoffs from previous studies [12], we plotted the distribution of sleep efficiency variability stratified by normal versus low (≥0.85 vs
We first examined univariable associations between sleep efficiency variability and DSST, CERAD-WL, and AFT scores.
JMIR Aging 2024;7:e54353
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Specifically, within-person variability in affective response associated with identification versus contrast may help to explain these differences. Greater (vs. lesser) affect variability is associated with poorer mental health outcomes, such as lower self-esteem, worse depressive symptoms, and more neuroticism [14], as well as more frequent alcohol use [15].
JMIR Form Res 2022;6(5):e36541
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Home BP variability values were calculated by SD, coefficient of variation (CV), and average real variability (ARV) [19]. Home BP variability was calculated in 14-day (2-week) intervals: baseline values were derived from days 1 to 14, weeks 3-4 values from days 15 to 28, weeks 5-6 values from days 29 to 42, and weeks 7-8 values from days 43 to 56. Calculations were conducted in the same manner for SBP and DBP data.
J Med Internet Res 2022;24(1):e22957
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There are several possible factors that affect the variability of MEP amplitude, which vary depending on internal and external factors [9,10]. Furthermore, there are many factors involved, such as changes in body temperature, blood pressure, the atmosphere in the laboratory, and the participant’s posture. It is thus difficult to identify the factors that affect MEP fluctuations. If the fluctuation of the MEP amplitude can be suppressed, this suppression method could be applied in a wide range of fields.
JMIR Biomed Eng 2021;6(2):e28902
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The emotion variability in depression described above has predominantly been operationalized in two ways. First, variability may be operationalized as within-individual variability as i SD, an individual’s SD of emotion expression. Like the mean, variability may best be viewed as a trait-like measure of emotion expression, as it provides a single number that summarizes the overall variability in affect for an individual across their recording period but ignores time-structured information [29].
J Med Internet Res 2018;20(5):e168
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