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OBJECTIVES: To describe the strategies adopted to maintain high level participation throughout a community based clinical trial, and the reasons given by participants for why they participated in the study. DESIGN: Observational study. SETTING: Community based clinical trial in Melbourne, Australia that ran for 68 weeks and involved 2811 community based individuals from 600 families. A high level of commitment was required of the families; each participant completed a Health Diary each week of the 68 week study, as well as answering numerous other questionnaires, and providing faecal and blood samples. MAIN RESULTS: Only 41 of the 600 families withdrew from the study; the majority of these families withdrew because they sold their home and moved from the study area. The completion rate of Health Diaries averaged 90.7% over the 68 weeks of data collection. Of the 559 families who completed the study, 524 (93.7%) completed the Participation Questionnaire. The statement that received the highest rating for why families enrolled in the study was they thought the study was researching an important community issue. The statements that received the highest ratings for why families continued to participate in the study was the family being kept well informed about the study's progress and that the study was well run. CONCLUSIONS: The low numbers of withdrawals and the high level of participation throughout the study suggests the strategies of (a) having a non-aggressive recruitment method, (b) maintaining regular contact with the participants and (c) ensuring participants were kept well informed of the study's progress and constantly encouraged to continue participation were successful. The results also suggest people involve themselves in research because they perceive it to be of value to the community, not simply for personal gain. They indicated that they maintained their participation because it was a well run study and they were kept well informed throughout the study. [ABSTRACT FROM AUTHOR]

Abstract Background Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. Results Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. Conclusion Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring.