A pilot intervention to promote walking and wellness and to improve the health of college faculty and staff

There is a need to investigate novel interventions that promote worksite physical activity and wellness. OBJECTIVE: The authors' purpose in this study was to evaluate the effectiveness of a 12-week walking program supplemented with a pedometer, computer educational program, and weekly e-mails. METHODS: College faculty and staff participated in a one-group pre-posttest study to determine whether the 12-week walking intervention had an effect on body mass index (BMI), blood pressure, blood glucose, and cholesterol. The authors also determined participant-perceived wellness effects. RESULTS: The authors observed differences between baseline and follow-up in BMI (p = .024), blood glucose (p = .06), and total cholesterol (p = .09). The program had a moderate effect on fitness, mood, health awareness, nutrition, and health. CONCLUSIONS: It is incumbent that experts develop innovative worksite physical activity and wellness programs. A pedometer-monitored walking program is one way that a worksite health initiative can improve the health and wellness of its employees and simultaneously reduce health-care costs.     

Spirit of aging rising: cross-cutting thematic modules to enrich foundation graduate social work courses

To enrich an urban generalist MSW program serving a diverse aging community, an innovative approach was initiated. A team of students, faculty and a field instructor collaborated in creating and evaluating 3 sets of cross-cutting thematic modules. An overview of the thematic modules (addressing elder abuse, family caregiving, and mental health), integrated across multiple curriculum areas (Human Behavior and the Social Environment, Macro/Policy, Practice and Research), is presented along with results of a faculty focus group evaluating the process of coordinating module content for one full week of class per foundation area (one topic per quarter).     

The Research Environment Norm Inventory (RENI): a study of integrity in research administrative systems

University research administrators have been generally ignored in basic studies of research integrity. Hensley noted that research administrators are "essential... to the achievement of the specific missions of postsecondary institutions... and to science and the academic infrastructure". The following study sought to extend the scope of research on research integrity to research administrative structures with a new instrument called the Research Environment Norm Inventory or RENI. University research administrators and their professional association were targeted for data collection. Evidence suggested that research administration in the United States supports integrity in the research environment through: (1) respect for community; (2) respect for institutional boundaries; (3) professionalism; (4) respect for authority structures; (5) sensitivity to system conflicts. The study suggested that integrity structures are dictated largely by the institutional settings and environments.     

What clients of couple therapy model developers and their former students say about change, part II: model-independent common factors and an integrative framework

Proponents of the common factors movement in marriage and family therapy (MFT) suggest that, rather than specific models of therapy, elements common across models of therapy and common to the process of therapy itself are responsible for therapeutic change. This article-the second of two companion articles-reports on a study designed to further investigate common factors in couple therapy. We used grounded theory techniques to analyze data from interviews with MFT model developers Dr. Susan M. Johnson, Dr. Frank M. Dattilio, Dr. Richard C. Schwartz, former students of Dr. Johnson and Dr. Schwartz, and each of their clients who had been successful in couple therapy. This article reports model-independent variables, that is, general aspects of therapy that are not directly related to the therapist's model. Model-independent categories include client variables, therapist variables, the therapeutic alliance, therapeutic process, and expectancy and motivational factors, each with several subcategories. We also present a conceptual framework that outlines how model-dependent and model-independent common factors may interact to produce change. We discuss our findings and proposed framework in relation to the current common factors literature in psychology and MFT. We also discuss clinical, training, and research implications.     

Modeling Demand For Unionization With Nontraditional Data Analysis Methods

Upon reviewing the extant literature on determinants of unionism, it becomes clear that many areas that have had a plethora of research attention do not converge upon singularly directional findings. This study explores a potential cause of such an apparent anomaly: nonlinearity of data. An exploratory examination of correlation coefficients among typical union determinant variables seems to show different patterns of relationships at different levels of union demand. Thus, a break from traditional linear data analysis techniques is explored in the interest of explaining more variance with typical, theoretically derived variables by using neural network analysis. Results of analyses on industry level data reveal that using neural network analysis to model union demand explained over four times as much variance as multiple regression analysis.     

The Impact of Learning and Labor Attrition on Worker Flexibility in Dual Resource Constrained Job Shops

This study investigates the impact of worker learning, worker flexibility, and labor attrition on the system performance of a dual resource constrained (DRC) job-shop. The effects of learning and labor attrition have not been previously addressed in DRC literature. Results from the study, consistent with previous literature, show that the greatest benefits are achieved when inter-departmental worker flexibility is incrementally introduced into the system. In addition, the learning environment, which depends on the initial processing time of jobs and the learning rates of workers, is shown to impact the acquisition of flexibility. The study also shows that the impact of labor attrition on system performance under certain shop conditions may be significant.     

The functional patterns of adolescent mothers leaving foster care: Results from a cluster analysis

Few studies have explored the outcomes of adolescent mothers leaving foster care, especially using person‐oriented methods. The current study employed a cluster analysis to identify unique patterns of functioning among adolescent mothers aged 19 (n = 777). Data from the National Youth in Transition Database and the Adoption and Foster Care Analysis and Reporting System were utilized. Findings revealed five subpopulations characterized by distinct constellations of outcomes at age 19. The largest group (43%) exhibited competent functioning across all the domains studied—its members were connected to school and/or employment and did not experience homelessness, substance abuse referrals, or incarceration during the past 2 years (i.e., “resilient”). A relatively small group (12%) exhibited challenges across all the above‐referenced domains, whereas the remaining groups presented challenges in some domains, but not in others. Follow‐up analyses revealed that adolescent mothers classified as resilient at age 19 had the lowest rates of congregate care placements and the highest rates of nonrelative foster care placements at age 17. Moreover, they had lower placement instability and higher rates of extended foster care as compared with members of the other clusters. Implications for practice, policy, and research are discussed.     

Capturing temporal dynamics of fear behaviors on a moment‐to‐moment basis

Identifying patterns of fearful behaviors early and accurately is essential to identify children who may be at increased risk for psychopathology. Previous work focused on the total amount of fear by using composites across time. However, considering the temporal dynamics of fear expression might offer novel insights into the identification of children at risk. One hundred and twenty‐five toddlers participated in high‐ and low‐fear tasks. Data were modeled using a novel two‐step approach. First, a hidden Markov model estimated latent fear states and transitions across states over time. Results revealed children's behavior was best represented by six behavioral states. Next, these states were analyzed using sequence clustering to identify groups of children with similar dynamic trajectories through the states. A four‐cluster solution found groups of children varied in fear response and regulation process: “external regulators” (using the caregiver as a regulation tool), “low reactive” (low reaction to stimulus), “fearful explorers” (managing their own internal state with minimal assistance from the caregiver), and “high fear” (fearful/at‐caregiver state regardless of task). The combination of analytic tools enabled fine‐grained examination of the processes of fearful temperament. These insights may help prevention programs target behaviors that perpetuate anxious behavior in the moment.     

Sensitivity Analysis in Linear Programming Models with Common Inputs

The importance of sensitivity analysis information in linear programming has been stressed in the management science literature for some time. Indeed, Gal [3] has devoted an entire text to just this issue. Linear programs with common inputs (cost coefficients or right-hand-side values) present a problem in that classical sensitivity analysis does not allow for the simultaneous changes required to determine the sensitivity of these models to common inputs. We first survey the approaches previously developed for simultaneous-change sensitivity analysis and cast them in the framework of the special common input case. These general techniques are compared to a simple aggregate variable technique that has not received attention in the literature.