WebEase: Development of a Web-Based Epilepsy Self-Management Intervention

People with epilepsy must adopt many self-management behaviors, especially regarding medication adherence, stress management, and sleep quality. In response to the need for theory-based self-management programs that people with epilepsy can easily access, the WebEase Web site was created and tested for feasibility, acceptability, and usability. This article discusses the theoretical background and developmental phases of WebEase and lessons learned throughout the development process. The WebEase research team developed content for the Web site on the basis of social cognitive theory, the transtheoretical model of behavior change, and motivational interviewing. Formative research and development of the WebEase program included a literature search, computer use survey, a focus group, and review by content experts and consumers. The program has 2 main components: 1) the modules, which provide a tailored opportunity for learning, reflection, and goal setting, and 2) MyLog, a place to enter daily information

Detecting and explicating interactions in categorical data

Detecting and explicating interactions in categorical data analyses using cross tabulation and the [chi] 2 statistic can provide salient tests of hypotheses concerning the relationship between two variables measured at the nominal or ordinal levels. For example, researchers usually employ categorical analysis when they are interested in whether members of one group (e.g., males vs. females) differ in the proportion falling into two or more levels of a dependent variable (e.g., in favor of or opposed to sex education in public schools). In this case, the data can be expressed as a two-way table and hypotheses tested with the [chi] 2 statistic. Interpretation of this simplest of two-way tables is straightforward. However, research questions are often more complex than this simple example both in the number of predictor variables and the number of levels of each variable. Researchers typically include other predictor variables (e.g., race, academic status, marital status) to gain a better understanding of more complex relationships among predictors and outcomes. In addition, researchers often employ measures that have more than two levels (e.g., income, race, treatment type, academic status), and they often choose to combine levels in one or more variables to simplify the analyses, meet assumptions, or clarify the results. The inclusion of more than one predictor leads to a model with multiway tables that can provide the researcher with thorny problems of analysis and interpretation. For example, suppose the previous model is expanded by including race (e.g., African American, Hispanic, and White). While the data could be analyzed using two separate two-way tables (one analysis for gender and one for race), this approach does not provide an opportunity to test for a possible race gender interaction. Here, interaction means that the effects of one predictor variable are not the same at all levels of a second predictor variable There are several approaches to testing for possible interactions in categorical data. One solution is to use logistic regression with race, gender, and the race x gender interaction term as predictors of the dichotomous outcome variabl

Updated Research Priorities For Neuroscience Nursing

In 2007, the Neuroscience Nursing Foundation (NNF) convened a research panel to update NNF\u27s research priorities used to guide funding. The research panel identified leaders in neuroscience nursing and conducted a review of neuroscience nursing research literature and an American Association of Neuroscience Nurses membership survey on research priorities. A workgroup of leaders in neuroscience nursing was then convened to draft and set priorities on the basis of the review of the literature and the membership survey. The updated priorities were submitted to the NNF Board of Trustees for approval. The revised document reviews the mission of NNF and outlines six strategies and five program areas (including specific subareas) that represent priorities for NNF research funding. The purpose of the updated priority document is to provide guidelines for the systematic development of knowledge in neuroscience nursing through the encouragement of selected neuroscience nursing research activities. © 2011 American Association of Neuroscience Nurses

Adherence, Sexual Risk, and Viral Load in HIV-Infected Women Prescribed Antiretroviral Therapy

The purpose of this study was to determine if there was a connection between adherence to antiretroviral therapy (ART) and use of risk reduction behaviors (RRB) in HIV-infected women who were prescribed antiretroviral therapy. The sample consisted of 193 predominately African American women with an average age of 44 who had been on ARV for approximately 9 years and had low annual incomes. All women were participating in a behavioral clinical trial focused on these dual outcomes. Using a risk index developed for this study, we examined the relationship of a composite of risk behaviors to electronically measured and self-reported adherence over the approximately 13-month study period. Women were categorized based on levels of adherence and risky behaviors, and we sought to determine if these classifications were associated with clinical outcomes of HIV viral load and CD4 counts. High levels of adherence were correlated with low risk behaviors (abstinence, consistent use of condoms, etc.). Those classified as high adherence and low-risk behavior (HALR) as well as those classified as high adherence and high-risk behavior (HAHR) had lower mean viral loads and higher CD4 counts than those in the other categories. Women in the low adherence and high-risk category (LAHR) had detectable viral loads and the lowest CD4 counts and are at higher risk for transmitting HIV to partners and unborn children. Our findings underscore the importance of addressing adherence to both ART and RRB in HIV clinical settings to improve clinical outcomes and reduce HIV transmission