Design of long-term animal bioassay for low-dose extrapolation using a multistage model

Conventional designs of animal bioassays allocate the same number of animals into control and dose groups to explore the spontaneous and induced tumor incidence rates, respectively. The purpose of such bioassays are (a) to determine whether or not the substance exhibits carcinogenic properties, and (b) if so, to estimate the human response at relatively low doses. In this study, it has been found that the optimal allocation to the experimental groups which, in some sense, minimize the error of the estimated response for low dose extrapolation is associated with the dose level and tumor risk. The number of dose levels has been investigated at the affordable experimental cost. The pattern of the administered dose, 1 MTD, 1/2 MTD, 1/4 MTD,....., etc. plus control, gives the most reasonable arrangement for the low dose extrapolation purpose. The arrangement of five dose groups may make the highest dose trivial. A four-dose design can circumvent this problem and has also one degree of freedom for testing the goodness-of-fit of the response model.^ An example using the data on liver tumors induced in mice in a lifetime study of feeding dieldrin (Walker et al., 1973) is implemented with the methodology. The results are compared with conclusions drawn from other studies. ^

Establishing occupational and environmental health design requirements for Lunar and Mars settlements

In a study of Lunar and Mars settlement concepts, an analysis was made of fundamental design assumptions in five technical areas against a model list of occupational and environmental health concerns. The technical areas included the proposed science projects to be supported, habitat and construction issues, closed ecosystem issues, the "MMM" issues--mining, material-processing, and manufacturing, and the human elements of physiology, behavior and mission approach. Four major lessons were learned. First it is possible to relate public health concerns to complex technological development in a proactive design mode, which has the potential for long-term cost savings. Second, it became very apparent that prior to committing any nation or international group to spending the billions to start and complete a lunar settlement, over the next century, that a significantly different approach must be taken from those previously proposed, to solve the closed ecosystem and "MMM" problems. Third, it also appears that the health concerns and technology issues to be addressed for human exploration into space are fundamentally those to be solved for human habitation of the earth (as a closed ecosystem) in the 21st century. Finally, it is proposed that ecosystem design modeling must develop new tools, based on probabilistic models as a step up from closed circuit models. ^

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

THE DESIGN AND DEVELOPMENT OF A SURVEY INSTRUMENT FOR THE ASSESSMENT OF OCCUPATIONAL STRESS

Using stress and coping as a unifying theoretical concept, a series of five models was developed in order to synthesize the survey questions and to classify information. These models identified the question, listed the research study, described measurements, listed workplace data, and listed industry and national reference data.^ A set of 38 instrument questions was developed within the five coping correlate categories. In addition, a set of 22 stress symptoms was also developed. The study was conducted within two groups, police and professors, on a large university campus. The groups were selected because their occupations were diverse, but they were a part of the same macroenvironment. The premise was that police officers would be more highly stressed than professors.^ Of a total study group of 80, there were 37 respondents. The difference in the mean stress responses was observable between the two groups. Not only were the responses similar within each group, but the stress level of response was also similar within each group. While the response to the survey instrument was good, only 3 respondents answered the stress symptom survey properly. It was determined that none of the 37 respondents believed that they were ill. This perception of being well was also evidenced by the grand mean of the stress scores of 2.76 (3.0 = moderate stress). This also caused fewer independent variables to be entered in the multiple regression model.^ The survey instrument was carefully designed to be universal. Universality is the ability to transcend occupational or regional definitions as applied to stress. It is the ability to measure responses within broad categories such as physiological, emotional, behavioral, social, and cognitive functions without losing the ability to measure the detail within the individual questions, or the relationships between questions and categories.^ Replication is much easier to achieve with standardized categories, questions, and measurement procedures such as those developed for the universal survey instrument. Because the survey instrument is universal it can be used as an analytical device, an assessment device, a basic tool for planning and a follow-up instrument to measure individual response to planned reductions in occupational stress. (Abstract shortened with permission of author.) ^

Design of a systematic approach to workplace exposure medical surveillance protocols

Current toxic tort cases have increased national awareness of health concerns and present an important avenue in which public health scientists can perform a vital function: in litigation, and in public health initiatives and promotions which may result. This review presents a systematic approach, using the paradigm of interactive public health disciplines, for the design of a matrix framework for medical surveillance of workers exposed to toxic substances. The matrix framework design addresses the required scientific bases to support the legal remedy of medical monitoring for workers injured as a result of their exposure to toxic agents. A background of recent legal developments which have a direct impact on the use of scientific expertise in litigation is examined in the context of toxic exposure litigation and the attainment of public health goals. The matrix model is applied to five different workplace exposures: dental mercury, firefighting, vinyl chloride manufacture, radon in mining and silica. An exposure matrix designed by the Department of Energy for government nuclear workers is included as a reference comparison to the design matrix. ^

CATCH across Texas: Building a model for the diffusion of effective school-based health promotion programs

The impact of health promotion programs is related to both program effectiveness and the extent to which the program is implemented among the target population. The purpose of this dissertation was to describe the development and evaluation of a school-based program diffusion intervention designed to increase the rate of dissemination and adoption of the Child and Adolescent Trial for Cardiovascular Health, or CATCH program (recently renamed the Coordinated Approach to Child Health). ^ The first study described the process by which schools across the state of Texas spontaneously began to adopt the CATCH program after it was tested and proven effective in a multi-site randomized efficacy trial. A survey of teachers and administrator representatives of all schools on record that purchased the CATCH program, but were not involved in the efficacy trial, was used to find out who brought CATCH into the schools, how they garnered support for its adoption, why they decided to adopt the program, and what was involved in deciding to adopt. ^ The second study described how the Intervention Mapping framework guided the planning, development and implementation of a program for the diffusion of CATCH. An iterative process was used to integrate theory, literature, the experience of project staff and data from the target population into a meaningful set of program determinants and performance objectives. Proximal program objectives were specified and translated into both media and interpersonal communication strategies for program diffusion. ^ The third study assessed the effectiveness of the diffusion program in a case-comparison design. Three of the twenty Education Service Center regions in Texas were chosen, selected based on similar demographic criteria, and were followed for adoption of the CATCH curriculum. One of these regions received the full media and interpersonal channel intervention; a second received a reduced media-only intervention, and a third received no intervention. Results suggested the use of the interpersonal channels with media follow-up is an effective means to facilitate program dissemination and adoption. The media-alone condition was not effective in facilitating program adoption. ^

Mixed effects model in negative exponential curve

Despite many researches on development in education and psychology, not often is the methodology tested with real data. A major barrier to test the growth model is that the design of study includes repeated observations and the nature of the growth is nonlinear. The repeat measurements on a nonlinear model require sophisticated statistical methods. In this study, we present mixed effects model in a negative exponential curve to describe the development of children's reading skills. This model can describe the nature of the growth on children's reading skills and account for intra-individual and inter-individual variation. We also apply simple techniques including cross-validation, regression, and graphical methods to determine the most appropriate curve for data, to find efficient initial values of parameters, and to select potential covariates. We illustrate with an example that motivated this research: a longitudinal study of academic skills from grade 1 to grade 12 in Connecticut public schools. ^