Physician's adherence to CDC standards for physical activity counseling of older women in a cardiology practice in Texas---An exploratory study

Physical activity is an important health-promoting behavior to prevent and control chronic disease. Interventions to increase physical activity are vitally needed. Women are not meeting the recommended goals for physical activity - a behavior that has been shown to effectively reduce the incidence of chronic disease and the medical costs associated with treating it. Among many factors predicting physical activity and the different forms of interventions that have been applied, physician counseling is one potentially cost-effective approach that may produce at least modest effects on women's behavior. The Centers for Disease Control and Prevention has published standards for physician counseling of patients regarding physical activity. This study used a short questionnaire to assess the degree to which a group practice of cardiology physicians in Texas queried and discussed physical activity recommendations to older women that they treat and whether they are meeting the physical activity counseling goals of the Centers for Disease Control and Prevention. The majority of this group of physicians counseled patients without benefit of exploring patient behavior. Although these physicians "agreed" that physical activity delayed or prevented disease, the outcome suggests that low self-efficacy hampered efforts to counsel older women on this. Physicians' perceptions that counseling may be ineffective could explain the lower rate of physical activity counseling that does not meet the goals of the Centers for Disease Control and Prevention. ^

An exploratory analysis of variance and volatility in epileptic electroencephalograms

The electroencephalogram (EEG) is a physiological time series that measures electrical activity at different locations in the brain, and plays an important role in epilepsy research. Exploring the variance and/or volatility may yield insights for seizure prediction, seizure detection and seizure propagation/dynamics.^ Maximal Overlap Discrete Wavelet Transforms (MODWTs) and ARMA-GARCH models were used to determine variance and volatility characteristics of 66 channels for different states of an epileptic EEG – sleep, awake, sleep-to-awake and seizure. The wavelet variances, changes in wavelet variances and volatility half-lives for the four states were compared for possible differences between seizure and non-seizure channels.^ The half-lives of two of the three seizure channels were found to be shorter than all of the non-seizure channels, based on 95% CIs for the pre-seizure and awake signals. No discernible patterns were found the wavelet variances of the change points for the different signals. ^