Enhancing Student Gerocompetencies: Evaluation of an Intergenerational Service Learning Course

This article describes the development and evaluation of an intergenerational service-learning course designed to promote social work gerocompetencies. Service-learning opportunities were structured into the course, including an optional evidence-based falls prevention program, for older adults, entitled A Matter of Balance (MOB). Significant differences between pre- and posttest scores on the Geriatric Social Work Competency Scale (GSWCS) were noted for students in the service learning course (n = 13). Once MOB was introduced as an independent variable, the MOB participants scored the highest mean posttest scores for 2 GSWCS domains: values, ethics, and theoretical perspectives; and intervention. The benefits of utilizing social work gerocompetencies to guide course objectives, content, and student outcomes are discussed.     

Use of propensity score matching to evaluate a national smoking cessation media campaign

Sustained mass media campaigns have been recommended to stem the tobacco epidemic in the United States. Propensity score matching (PSM) was used to estimate the effect of awareness of a national smoking cessation media campaign (EX) on quit attempts and cessation-related cognition. Participants were 4,067 smokers and recent quitters aged 18-49 in targeted U.S. media markets. Controlling for potential confounders through PSM and regression analysis, confirmed awareness of EX was not significantly associated with either outcome at 6-month follow-up. Matched analyses excluding 217 quitters resulted in a significant effect of EX on both outcomes.     

Does IO Economics Really Make the Case for Investments in IT: A Rejoinder

The preceding critique [1] of the paper “The Information Problems in Organizations: A Research Model for the Value of Information and Information Systems” [3], reaches general conclusions with respect to the original paper and the applicability of economics to MIS research. These conclusions are based on arguments developed at a different level of analysis than that used in the original paper, and without considering the goals and intent of the original paper. The differences between the critique and the original paper are highlighted.     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

Deriving Behavior Model Parameters from Survey Data: Self‐Protective Behavior Adoption During the 2009–2010 Influenza A(H1N1) Pandemic

In this paper, we demonstrate how public opinion surveys can be designed to collect information pertinent to computational behavior modeling, and we present the results of a public opinion and behavior survey conducted during the 2009–2010 H1N1 influenza pandemic. The results are used to parameterize the Health Belief Model of individual health‐protective decision making. Survey subjects were asked questions about their perceptions of the then‐circulating influenza and attitudes towards two personal protective behaviors: vaccination and avoidance of crowds. We empirically address two important issues in applying the Health Belief Model of behavior to computational infectious disease simulation: (1) the factors dynamically influencing the states of the Health Belief Model variables and (2) the appropriateness of the Health Belief Model in describing self‐protective behavior in the context of pandemic influenza.     

Ambulance allocation for maximal survival with heterogeneous outcome measures

This paper proposes new models for locating emergency medical services (EMS) by incorporating survival functions for capturing multiple-classes of heterogeneous patients. The Maximal Expected Survival Location Model for Heterogeneous Patients (MESLMHP) aims to maximize the overall expected survival probability of multiple-classes of patients, whereby different classes could be defined according to agreed patient categories based on response time targets, or by capturing differing medical conditions each with a corresponding survival function. Furthermore, we propose and demonstrate an approximation approach to solving the extended stochastic version of MESLMHP, which utilizes queuing theory to permit the modeling of congestion and utilization at each ambulance station, and does not require assumptions to be made on the utilization of ambulances. Both models are demonstrated using data from the ambulance service in Wales. We show that our multiple outcome measures and survival-maximizing approach, rather than one based on average response time targets alone or a single patient class provides more effective EMS ambulance allocations.     

Leadership and emotion management for complex tasks: Different emotions,different strategies

Emotions in the workplace influence a number of critical cognitive tasks including information processing and decision-making. Moreover, the effect of emotion on these operations is often emotion-specific. Given these unique effects, leaders may need to learn how to manage subordinates' discrete emotions, and not just general affect. This laboratory experiment examined the effects of leaders suggesting different regulation strategies after subordinates experienced anger or pessimism. Effects of these emotions under different leader-facilitated regulation strategies were evaluated with respect to planning, a critical organizational task, and perceptions of leader effectiveness. Results demonstrated that the type of leader-facilitated regulation strategy moderates the relationships of anger and pessimism to planning. The findings imply that leaders should understand the differential effects of discrete emotions, and be prepared to help subordinates manage emotions accordingly.     

Supply Chain Inventory Replenishment: The Debiasing Effect of Declarative Knowledge

Previous experimental research demonstrates that inefficient replenishment decision making in the supply chain can be caused by specific judgment and decision biases. Based on the literature we use controlled experiments involving both student subjects and supply chain managers to test debiasing interventions that provide declarative knowledge, which is theorized to enhance the acquisition of procedural knowledge. We first investigate the effects of three debiasing components in a single‐echelon setting: knowledge of bullwhip, inventory position (IP), and use of a target order‐up‐to quantity. Experiment 1 (N = 1,608 decisions by 67 student subjects) using a 2 × 2 × 2 factorial design for the three components finds that the conceptual understanding of IP is salient for efficient replenishment decisions. We next examine the effects of the components in a simulated, multi‐echelon, serial supply chain, which introduces the additional complexity of coordination risk. Experiment 2 (N = 3,072 decisions by 128 student subjects) using a 2 × 2 × 2 factorial design finds that although subjects benefit from training components, there is evidence of cognitive overload with an increased quantity of information. Finally we test whether these debiasing components may be an effective training program for practicing supply chain managers who can be expected to have higher levels of procedural knowledge through experience gained in the field. Experiment 3 (N = 864 decisions by 36 supply chain managers) using a 2 × 1 design investigates the effects of an instructional training intervention which includes all three debiasing components and finds the intervention to reduce costs by 14%. We provide avenues for future research and successful practice.