2 resultados para Designs Qualitative

em Boston University Digital Common


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BACKGROUND: Biomonitoring studies can provide information about individual and population-wide exposure. However they must be designed in a way that protects the rights and welfare of participants. This descriptive qualitative study was conducted as a follow-up to a breastmilk biomonitoring study. The primary objectives were to assess participants' experiences in the study, including the report-back of individual body burden results, and to determine if participation in the study negatively affected breastfeeding rates or duration. METHODS: Participants of the Greater Boston PBDE Breastmilk Biomonitoring Study were contacted and asked about their experiences in the study: the impact of study recruitment materials on attitudes towards breastfeeding; if participants had wanted individual biomonitoring results; if the protocol by which individual results were distributed met participants' needs; and the impact of individual results on attitudes towards breastfeeding. RESULTS: No participants reported reducing the duration of breastfeeding because of the biomonitoring study, but some responses suggested that breastmilk biomonitoring studies have the potential to raise anxieties about breastfeeding. Almost all participants wished to obtain individual results. Although several reported some concern about individual body burden, none reported reducing the duration of breastfeeding because of biomonitoring results. The study literature and report-back method were found to mitigate potential negative impacts. CONCLUSION: Biomonitoring study design, including clear communication about the benefits of breastfeeding and the manner in which individual results are distributed, can prevent negative impacts of biomonitoring on breastfeeding. Adoption of more specific standards for biomonitoring studies and continued study of risk communication issues related to biomonitoring will help protect participants from harm.

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Attributing a dollar value to a keyword is an essential part of running any profitable search engine advertising campaign. When an advertiser has complete control over the interaction with and monetization of each user arriving on a given keyword, the value of that term can be accurately tracked. However, in many instances, the advertiser may monetize arrivals indirectly through one or more third parties. In such cases, it is typical for the third party to provide only coarse-grained reporting: rather than report each monetization event, users are aggregated into larger channels and the third party reports aggregate information such as total daily revenue for each channel. Examples of third parties that use channels include Amazon and Google AdSense. In such scenarios, the number of channels is generally much smaller than the number of keywords whose value per click (VPC) we wish to learn. However, the advertiser has flexibility as to how to assign keywords to channels over time. We introduce the channelization problem: how do we adaptively assign keywords to channels over the course of multiple days to quickly obtain accurate VPC estimates of all keywords? We relate this problem to classical results in weighing design, devise new adaptive algorithms for this problem, and quantify the performance of these algorithms experimentally. Our results demonstrate that adaptive weighing designs that exploit statistics of term frequency, variability in VPCs across keywords, and flexible channel assignments over time provide the best estimators of keyword VPCs.