Showing papers by "José E Cavazos published in 2012"
TL;DR: These 13 brief measures of self-reported QOL are reliable and show preliminary evidence of concurrent validity inasmuch as they differentiate people based upon number of reported health conditions and whether those reported conditions impede normal function.
Abstract: Objective: To address the need for brief, reliable, valid, and standardized quality of life (QOL) assessment applicable across neurologic conditions. Methods: Drawing from larger calibrated item banks, we developed short measures (8–9 items each) of 13 different QOL domains across physical, mental, and social health and evaluated their validity and reliability. Three samples were utilized during short form development: general population (Internet-based, n = 2,113); clinical panel (Internet-based, n = 553); and clinical outpatient (clinic-based, n = 581). All short forms are expressed as T scores with a mean of 50 and SD of 10. Results: Internal consistency (Cronbach α) of the 13 short forms ranged from 0.85 to 0.97. Correlations between short form and full-length item bank scores ranged from 0.88 to 0.99 (0.82–0.96 after removing common items from banks). Online respondents were asked whether they had any of 19 different chronic health conditions, and whether or not those reported conditions interfered with ability to function normally. All short forms, across physical, mental, and social health, were able to separate people who reported no health condition from those who reported 1–2 or 3 or more. In addition, scores on all 13 domains were worse for people who acknowledged being limited by the health conditions they reported, compared to those who reported conditions but were not limited by them. Conclusion: These 13 brief measures of self-reported QOL are reliable and show preliminary evidence of concurrent validity inasmuch as they differentiate people based upon number of reported health conditions and whether those reported conditions impede normal function.
459 citations
Patent•
05 Jul 2012
TL;DR: In this paper, a method and apparatus for detecting seizures with motor manifestations including detecting EMG signals, isolating from the EMG signal spectral data for a plurality of frequency bands, and calculating a T-squared value there from.
Abstract: A method and apparatus for detecting seizures with motor manifestations including detecting EMG signals, isolating from the EMG signals spectral data for a plurality of frequency bands, and calculating a T-squared value there from. The T-squared values may be detected in real time, such as in a patient's home environment, and the T-squared data may be compared to a threshold T-squared value to determine whether an alarm is sent.
56 citations