A program manual to assist with implementation of a volunteer health and wellness program

Based on the success of a community health and wellness program, Wellness in the City, delivered in Dallas County by trained volunteers, Texas Cooperative Extension (TCE) decided to pilot the program in 16 counties in North and East Texas. Before implementing the program, TCE wanted the Dallas County program to be reviewed and revised as needed to meet the diverse community needs in the pilot counties. TCE also asked for an implementation manual to be developed for the county agents to utilize. ^ To achieve these objectives, I first reviewed literature on other volunteer-implemented health interventions in the U.S. to see how they were planned, disseminated, implemented, and evaluated. Next, I reviewed the Wellness in the City program and materials. I applied all the information I gathered up to that point to the program development committee meetings (committee included seven TCE county agents, a TCE regional program director, and me). The program structure and training materials were revised based on our research and program implementation experience. These changes were made to ensure adequate training for the volunteers and to create a program that is applicable in the communities it will be piloted in. ^ With the program structure and training presentations developed, next I focused on compiling the implementation manual, which includes program details and volunteer recruitment, training, and management materials. The goal was to create a manual with everything the county agents will need to implement the program, so they can focus their efforts on putting the manual to use and recruiting and managing the volunteers. The final step was developing a program evaluation form for the agents to complete. It includes questions to assess the agents' thoughts about the training content, the feasibility of implementing the program using the manual, and the challenges of the program. ^

Statistical Methods for Differential Expressions of Genes Detected in Multiple-Condition Experiment of Microarray

Most studies of differential gene-expressions have been conducted between two given conditions. The two-condition experimental (TCE) approach is simple in that all genes detected display a common differential expression pattern responsive to a common two-condition difference. Therefore, the genes that are differentially expressed under the other conditions other than the given two conditions are undetectable with the TCE approach. In order to address the problem, we propose a new approach called multiple-condition experiment (MCE) without replication and develop corresponding statistical methods including inference of pairs of conditions for genes, new t-statistics, and a generalized multiple-testing method for any multiple-testing procedure via a control parameter C. We applied these statistical methods to analyze our real MCE data from breast cancer cell lines and found that 85 percent of gene-expression variations were caused by genotypic effects and genotype-ANAX1 overexpression interactions, which agrees well with our expected results. We also applied our methods to the adenoma dataset of Notterman et al. and identified 93 differentially expressed genes that could not be found in TCE. The MCE approach is a conceptual breakthrough in many aspects: (a) many conditions of interests can be conducted simultaneously; (b) study of association between differential expressions of genes and conditions becomes easy; (c) it can provide more precise information for molecular classification and diagnosis of tumors; (d) it can save lot of experimental resources and time for investigators.^