Food Safety in the Domestic Environment: An Interdisciplinary Investigation of Microbial Hazards During Food Preparation

It has been established that, to a considerable extent, the domestic hygiene practices adopted by consumers can result in a greater or lesser microbial load in prepared meals. In the research presented here, an interdisciplinary study is reported in which interviews, observations of consumers preparing a recipe, and microbial contamination of the finished meals were compared. The results suggest that, while most consumers are knowledgeable about the importance of cross-contamination and heating in preventing the occurrence of foodborne illness, this knowledge is not necessarily translated into behavior. The adoption of habitual cooking practices may also be important. Potentially risky behaviors were, indeed, observed in the domestic food preparation environment. Eighteen of the participants made errors in food preparation that could potentially result in cross-contamination, and seven participants allowed raw meat juices to come in contact with the final meal. Using a tracer microorganism the log reduction as a result of consumer preparation was estimated at an average of log 4.1 cfu/salad. When combining these findings, it was found that cross-contamination errors were a good predictor for log reduction. Procedural food safety knowledge (i.e., knowledge proffered after general open questions) was a better predictor of efficacious bacterial reduction than declarative food safety knowledge (i.e., knowledge proffered after formal questioning). This suggests that motivation to prepare safe food was a better indicator of actual behavior than knowledge about food safety per se.     

Career development interventions for transition-age youths with disabilities

Youths with disabilities are often precluded from participating in career exploration and planning activities that prepare them for meaningful employment. They do not always have the same opportunities as their non-disabled peers to learn about different career options and to develop important work-related skills. This article presents experientially-based career development interventions that can be incorporated into the transition planning process to guide these youths in (a) career exploration and decision-making, (b) career planning, (c) job development and placement, and (e) career maintenance.     

Parity-Specific and two-sex utility models of reproductive intentions

This paper uses married couples’ anticipated consequences of having a (another) child to predict their reproductive intentions. Parity-specific models identify different variables as predictors of reproductive behavior at different parities but do not yield interpretable patterns of difference by parity. Parity-specific models are not significantly stronger predictors of reproductive behavior. Generally, wife-only models are distinctly superior to husband-only models. Two-sex models are usually better predictors than one-sex models but not enough better to justify the additional cost.     

Consideration of future consequences and unprotected anal intercourse among men who have sex with men

This study of men who have sex with men (MSM) examined whether tendencies to consider the future consequences of one's actions were associated with sexual behaviors that place oneself at risk for HIV infection. A total of 339 HIV-negative MSM responded to the Consideration of Future Consequences Scale (CFC; Strathman et al., 1994) and to questions about their anal intercourse practices in the past year. In bivariate analyses, men with a stronger future orientation were less likely to engage in anal intercourse unprotected by a condom (p < .05). Multivariate analyses revealed that CFC accounted for significant variance in three of four measures of unprotected anal sex after statistically controlling for demographic covariates (education, income, ethnicity, age). CFC was a better predictor of sexual behavior and accounted for more unique variance than any of the demographic factors. Additional research is needed to confirm that CFC is an antecedent of behavior and to examine the feasibility and efficacy of focusing on CFC in HIV prevention interventions.     

Disaggregated spatial modelling for areal unit categorical data

Summary.  We consider joint spatial modelling of areal multivariate categorical data assuming a multiway contingency table for the variables, modelled by using a log-linear model, and connected across units by using spatial random effects. With no distinction regarding whether variables are response or explanatory, we do not limit inference to conditional probabilities, as in customary spatial logistic regression. With joint probabilities we can calculate arbitrary marginal and conditional probabilities without having to refit models to investigate different hypotheses. Flexible aggregation allows us to investigate subgroups of interest; flexible conditioning enables not only the study of outcomes given risk factors but also retrospective study of risk factors given outcomes. A benefit of joint spatial modelling is the opportunity to reveal disparities in health in a richer fashion, e.g. across space for any particular group of cells, across groups of cells at a particular location, and, hence, potential space–group interaction. We illustrate with an analysis of birth records for the state of North Carolina and compare with spatial logistic regression.     

Maximum likelihood methods for complex sample data: logistic regression and discrete proportional hazards models

To estimate model parameters from complex sample data. we apply maximum likelihood techniques to the complex sample data from the finite population, which is treated as a sample from an i nfinite superpopulation. General asymptotic distribution theory is developed and then applied to both logistic regression and discrete proportional hazards models. Data from the Lipid Research Clinics Program areused to illustrate each model, demonstrating the effects on inference of neglecting the sampling design during parameter estimation. These empirical results also shed light on the issue of model-based vs. design-based inferences.     

Development of a Prediction Model for Hospital Closure Using Financial Accounting Data*

Numerous research studies have examined the use of financial accounting data in the prediction of corporate bankruptcy. Partly due to a lack of available data, however, little work has been done in developing a closure prediction model specifically for hospitals. Using cost reports from the Health Care Financing Administration and a sample of 71 closed hospitals and a matched sample of 71 open hospitals, the current study examines the relationship between 21 financial accounting ratios and hospital closure. Univariate logit results indicate that hospital closure is significantly related to 17 of the 21 ratios one year prior to closure. Results are also presented using a multivariate model, and for the relationships two years prior to closure. The current study provides information helpful to users in identifying financial variables which may be important indicators of hospital closure.