Meta-analysis as a tool for understanding existing research literature

This article describes the rationale for and methods used in conducting meta-analyses in rehabilitation research. Advantages and disadvantages of meta-analysis, vis a vis the narrative and quantitative literature reviews described in previous articles, are discussed. Hypothetical and actual examples from the rehabilitation and related health sciences fields are used to illustrate points throughout the text.     

Development of a screen for ongoing intimate partner violence

A five-question Ongoing Abuse Screen (OAS) was developed to evaluate ongoing intimate partner violence. Our hypothesis was that the OAS was more accurate and more likely to reflect ongoing intimate partner violence than the AAS when compared to the Index of Spouse Abuse (ISA). The survey included the ISA, the OAS, and the AAS. During the busiest emergency department hours, a sampling of 856 patients completed all aspects of the survey tool. Comparisons were made between the two scales and the ISA. The accuracy, positive predictive value, and positive likelihood ratio were 84%, 58%, and 6.0 for the OAS and 59%, 33%, and 2.0 for the AAS. The OAS was more accurate, had a better positive predictive value, and was three times more likely to detect victims of ongoing intimate partner violence than the AAS. Because the OAS was still not accurate enough, we developed a new screen, based on the ISA, titled the Ongoing Violence Assessment Tool (OVAT).     

Doctors, lawyers evaluate each other in new study

Asking doctors and lawyers what they like and dislike about each other brings strong, often negative results. Take a look at the level of trust between doctors and lawyers and learn how both sides view one another. And discover ways to patch up the rocky relationships.     

Critical phases among adoptees and their families: Implications for therapy

A growing body of literature indicates that families with adopted children seek mental health care for the adoptive and other family members more frequently and for different reasons than biologically-bound families. This paper addresses the struggles and corrective strategies for adoptive families at various levels of their development.     

Opportunity for Childcare: The Impact of Government Initiatives in England upon Childcare Provision

This paper considers the impact of recent government initiatives upon childcare provision for children under the age of five. It is based upon interviews with parents and providers from two contrasting wards in Liverpool. The aim of the research was to identify key issues and concerns with regard to childcare, and perceptions about the impact of developments within social security and education provision. Government policies have concentrated on supporting working parents who need to pay for formal childcare, and on providing an earlier start to the formal education of young children. There is a fear that this focus may be failing to recognize and support the diversity of families and their childcare needs.     

A Bayesian Approach in Estimating Transition Probabilities of a Discrete-time Markov Chain for Ignorable Intermittent Missing Data

This article focuses on data analyses under the scenario of missing at random within discrete-time Markov chain models. The naive method, nonlinear (NL) method, and Expectation-Maximization (EM) algorithm are discussed. We extend the NL method into a Bayesian framework, using an adjusted rejection algorithm to sample the posterior distribution, and estimating the transition probabilities with a Monte Carlo algorithm. We compare the Bayesian nonlinear (BNL) method with the naive method and the EM algorithm with various missing rates, and comprehensively evaluate estimators in terms of biases, variances, mean square errors, and coverage probabilities (CPs). Our simulation results show that the EM algorithm usually offers smallest variances but with poorest CP, while the BNL method has smaller variances and better/similar CP as compared to the naive method. When the missing rate is low (about 9%, MAR), the three methods are comparable. Whereas when the missing rate is high (about 25%, MAR), overall, the BNL method performs slightly but consistently better than the naive method regarding variances and CP. Data from a longitudinal study of stress level among caregivers of individuals with Alzheimer’s disease is used to illustrate these methods.     

An exploratory study of drug-exposed infants: case substantiation and subsequent child maltreatment

This study explores factors related to drug-exposed infants' case substantiation and subsequent child maltreatment. Child protective services computerized administrative data (from January 1998 to October 2001) were obtained from an urban Nevada county. The data included 457 drug-exposed infant cases. Chi-square, t-test, one-way ANOVA, and logistic regression were used to analyze the data. Results indicate that: (1) drug-exposed infant case substantiation was related to the type of drug exposure and the unit to which the case was assigned, but not to the mother's ethnicity; and (2) subsequent maltreatment among drug-exposed infants was related to the mother's age and prior parental alcohol abuse, but not to the type of drug exposure, nor to the initial drug-exposed infant status of case substantiation. Implications for child welfare practice and research are discussed.     

Computing continuous core/periphery structures for social relations data with MINRES/SVD

When diagonal values are missing or excluded, MINRES is a natural continuous model for the core/periphery structure of a symmetric social network matrix. Symmetric models, however, are not so useful when dealing with asymmetric data. Singular value decomposition (SVD) is a natural choice to model asymmetry, but this method also requires the presence of diagonal values. In this paper we offer an alternative, more general, approach to continuous core/periphery structures, the minimum residual singular value decomposition (MINRES/SVD), where each node in the network receives two indices, an “in-coreness” and an “out-coreness.” The algorithm for computing these coreness vectors is a least squares computation similar to, but distinct from the SVD, again because of the missing diagonal values. And in contrast to the standard, symmetric MINRES algorithm, we can more accurately model asymmetric matrices. This allows us to distinguish, for example, countries in the world economy that are more in the exporting core than they are in the importing core. We propose two nested PRE (proportional reduction of error) measures of fit: (1) the PRE from the MINRES vector with respect to the data and (2) the PRE of the product of the two MINRES/SVD vectors. Applying the resulting method to citations between journals and to international trade in clothing, we illustrate insights gained from being able to model asymmetrical flow patterns. Finally, two permutation tests are introduced to test independently for the MINRES and MINRES/SVD results.