This article describes the issues and challenges that are inherent in conducting cost-quality outcomes research related to the advanced practice nurse role. As consumers of this research, nurse administrators need to be aware of these issues in order to make informed, organizationally rational decisions. Following discussion of the issues, recommendations are offered for factors to consider when using results of published research findings.

ALINE is a pedagogical model developed to aid nursing faculty transition from passive to active learning. Based on the constructionist theory, ALINE serves as a tool for organizing curriculum for online and classroom-based interaction and positioning the student as the active player and the instructor as the facilitator of nursing competency.

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Tinnitus is a common, yet poorly understood problem. This symptom has many causes, both benign as well as serious. Patients can experience significant changes in quality-of-life related to symptom severity and duration. This article explores causes of tinnitus, evaluation in a primary care setting, and management strategies.

This study examined the association between pressure injuries and complexity of abdominal temperature measured in residents of a nursing facility. The temperature served as a proxy measure for skin thermoregulation. Refined multiscale sample entropy and bubble entropy were used to measure the irregularity of the temperature time series measured over two days at 1-min intervals. Robust summary measures were derived for the multiscale entropies and used in predictive models for pressure injuries that were built with adaptive lasso regression and neural networks. Both types of entropies were lower in the group of participants with pressure injuries (n=11) relative to the group of non-injured participants (n=15). This was generally true at the longer temporal scales, with the effect peaking at scale τ=22 min for sample entropy and τ=23 min for bubble entropy. Predictive models for pressure injury on the basis of refined multiscale sample entropy and bubble entropy yielded 96% accuracy, outperforming predictions based on any single measure of entropy. Combining entropy measures with a widely used risk assessment score led to the best prediction accuracy. Complexity of the abdominal temperature series could therefore serve as an indicator of risk of pressure injury.