2 resultados para Measurement Variability

em DigitalCommons@The Texas Medical Center


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The objective of this longitudinal study, conducted in a neonatal intensive care unit, was to characterize the response to pain of high-risk very low birth weight infants (<1,500 g) from 23 to 38 weeks post-menstrual age (PMA) by measuring heart rate variability (HRV). Heart period data were recorded before, during, and after a heel lanced or wrist venipunctured blood draw for routine clinical evaluation. Pain response to the blood draw procedure and age-related changes of HRV in low-frequency and high-frequency bands were modeled with linear mixed-effects models. HRV in both bands decreased during pain, followed by a recovery to near-baseline levels. Venipuncture and mechanical ventilation were factors that attenuated the HRV response to pain. HRV at the baseline increased with post-menstrual age but the growth rate of high-frequency power was reduced in mechanically ventilated infants. There was some evidence that low-frequency HRV response to pain improved with advancing PMA.

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Research has shown that physical activity serves a preventive function against the development of several major chronic diseases. However, studying physical activity and its health benefits is difficult due to the complexity of measuring physical activity. The overall aim of this research is to contribute to the knowledge of both correlates and measurement of physical activity. Data from the Women On The Move study were used for this study (n = 260), and the results are presented in three papers. The first paper focuses on the measurement of physical activity and compares an alternate coding method with the standard coding method for calculating energy expenditure from a 7-day activity diary. Results indicate that the alternative coding scheme could produce similar results to the standard coding in terms of total activity expenditure. Even though agreement could not be achieved by dimension, the study lays the groundwork for a coding system that saves considerable amount of time in coding activity and has the ability to estimate expenditure more accurately for activities that can be performed at varying intensity levels. The second paper investigates intra-day variability in physical activity by estimating the variation in energy expenditure for workers and non-workers and identifying the number of days of diary self-report necessary to reliably estimate activity. The results indicate that 8 days of activity are needed to reliably estimate total activity for individuals who don't work and 12 days of activity are needed to reliably estimate total activity for those who work. Days of diary self-report required by dimension for those who don't work range from 6 to 16 and for those who work from 6 to 113. The final paper presents findings on the relationship between daily living activity and Type A behavior pattern. Significant findings are observed for total activity and leisure activity with the Temperament Scale summary score. Significant findings are also observed for total activity, household chores, work, leisure activity, exercise, and inactivity with one or more of the individual items on the Temperament Scale. However, even though some significant findings were observed, the overall models did not reveal meaningful associations. ^