2 resultados para single-case A-B-fase design

em DigitalCommons@The Texas Medical Center


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Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

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This research study offers a critical assessment of NIH's Consensus Development Program (CDP), focusing upon its historical and valuative bases and its institutionalization in response to social and political forces. The analysis encompasses systems-level, as well as interpersonal factors in the adoption of consensus as the mechanism for resolving scientific controversies in clinical practice application. Further, the evolution of the CDP is also considered from an ecological perspective as a reasoned adaptation by NIH to pressures from its supporters and clients for translating biomedical research into medical practice. The assessment examines federal science policy and institutional designs for the inclusion of the public interest and democratic deliberation.^ The study relies on three distinct approaches to social research. Conventional historical methods were utilized in the interpretation of social and political influences across eras on the evolution of the National Institutes of Health and its response to demands for accountability and relevance through its Consensus Development Program. An embedded single-case study was utilized for an empirical examination of the CDP mechanism through five exemplar conferences. Lastly, a sociohistorical approach was taken to the CDP in order to consider its responsiveness to the values of the eras which created and shaped it. An exploration of organizational behavior with considerations for institutional reform as a response to continuing political and social pressure, it is a study of organizational birth, growth, and response to demands from its environment. The study has explanatory import in its attempt to account for the creation, timing, and form of the CDP, relative to political, institutional, and cultural pressures, and predictive import thorough its historical view which provides a basis for informed speculation on the playing out of tensions between extramural and intermural scientists and the current demands for health care reform. ^