This article discusses XBRL, its impacts on users and on the characteristics of financial information, and provides an impacts framework for XBRL. XBRL will both simplify disclosure and ease the communication of financial information to users, analysts, and regulators via the Internet. The potential impacts that XBRL is expected to have on users, accountants, regulators, and the financial communication process are addressed. Research on XBRL is examined and future research directions and priorities are identified. A more rigorous look at the myriad range of potential impacts of XBRL is needed.

Nearly half of Americans are employed by small businesses, and future projections suggest that the number of those employed by small businesses will rise. Despite this, there is relatively little small business intervention research on the integration of health protection and health promotion, known as Total Worker Health® (TWH). We first discuss the importance of studying small businesses in TWH research and practice. Second, we describe an example of a small business TWH intervention, Health Links™ plus TWH owner/senior manager leadership training, that we are evaluating via the Small+Safe+Well (SSWell) study. Key features of the intervention and the SSWell study include attention to multi-level influences on worker health, safety and well-being; organizational change; and dissemination and implementation science strategies via the RE-AIM model. We offer several considerations for future small business TWH research and practice both in terms of the small business context as well as intervention development and evaluation. Our goal is to provide TWH researchers and practitioners with a framework and an example of how to approach small business TWH interventions. Ultimately, through the SSWell study, we aim to provide small businesses with strong evidence to support the use of TWH strategies that are practical, effective and sustainable.

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Experts claim that artificial neural network (ANN) technology can outperform standard statistical methods when applied to examine actual financial data.Researchers have used ANNs to analyze bankruptcy prediction, bond rating and the going-concern problem. Financial firms have employed ANNs commercially to predict commercial bank failures, detect credit card fraud and verify signatures. For accounting and auditing problems, however, application of ANN technology has been limited. Preliminary experiments tested whether an ANN offered improved performance in recognizing material misstatements during the analytical review process of auditing. Four years of audited financial data from a medium-sized distributor were input as data streams to calibrate the ANN across fifteen financial accounts. Researchers compared a presumed lack of actual errors and certain seeded material errors with signals from the ANN analytical review process to evaluate performance. Results were compared to analyses where financial ratios and regression methods were employed as analytical review techniques. Results tentatively suggest that the ANN method recognized patterns within financial accounts more effectively than did financial ratio and regression methods. ANNs applied as a forecasting tool seem useful for identifying patterns that can indicate potential investigations of a firm's unaudited financial data in the current year.