32 research outputs found

    A Theory of Aesthetic Justice

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    Theories of distributive justice give us the appropriate determination of who ought to have what, where ?who? are the members of society and ?what? are social goods and burdens. Traditionally, social goods have taken the form of rights and privileges, as well as more tangible economic goods. However, it is not clear that these are the only kinds of social goods relevant to justice. There is a substantial body of literature showing that environmental benefits and burdens can and should be thought of as social goods. In this paper, I will argue that we ought to make a comparable extension for aesthetic benefits and burdens. Specifically, I will show that aesthetic goods are objects of significant public interest, and therefore must be subject to our principles of justice. I begin by explaining and evaluating a theory of aesthetic justice offered by Monroe Beardsley. I will expand this theory by showing its broad applicability to myriad examples, especially to aesthetic objects in nature. Then I will show that this theory is compatible with two leading conceptions of justice: John Rawls?s liberal conception and Michael Walzer?s communitarian conception. In doing so, I will show that the theory of aesthetic justice must be taken seriously by those who have these philosophical commitments

    A Psychometric Analysis of Patient-Reported Outcomes in Chronic Kidney Disease

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    ABSTRACT OF THE DISSERTATIONA Psychometric Analysis of Patient-Reported Outcomes in Chronic Kidney DiseasebyJohn Devin PeipertDoctor of Philosophy in Public HealthUniversity of California, Los Angeles, 2017Professor Donald Morisky, ChairBackground: Survival is a critical outcome in chronic kidney disease (CKD), but it provides a limited view of how well patients are doing. Many aspects of patients’ health can only be obtained by patient reported measures (PRMs), such as health-related quality of life (HRQOL). This dissertation examines the psychometric properties of currently used PRMs in chronic kidney disease (CKD) and make recommendations for how collection and reporting of PRMs can be systematized in the CKD field.Methods: This dissertation used data from three separate sources, each containing kidney patients’ responses to PRMs: treatment decision-making, medication adherence, and HRQOL. The treatment decision-making PRMs examined include patients’ Decisional Balance (perceived Pros and Cons) and Self-Efficacy to pursue both living and deceased donor kidney transplant (LDKT, DDKT; 6 measures in total). The 8-item Morisky Medication Adherence Scale (MMAS-8) was examined as a measure of medication adherence. Finally, the Kidney Disease Quality of Life (KDQOL)-36 was examined as a measure of HRQOL. For each measure, internal consistency reliability was estimated. Dimensional structure was examined with exploratory and confirmatory factor analysis (EFA, CFA) and item-scale correlations, corrected for item overlap. To determine the dimensionality suggested by the exploratory factor analysis, several criteria were used, including the scree “elbow” test, parallel analysis, and the Tucker-Lewis reliability coefficient. For CFA models, model fit was determined with the Satorra-Bentler chi-square, the comparative fit index (CFI), Tucker-Lewis Index (TLI) and root mean square error of approximation (RMSEA). Good model fit is evidenced by a non-significant Satorra-Bentler chi-square, CFI and TLI values of above 0.95, and RMSEA of 0.06 or less. Next, the measurement invariance for each measure was examined between Black and White patients. Finally, recommendations for improvements to each measure were made, including calculations to determine the number of items needed to achieve good (>0.80) and excellent (>0.90) reliability (reliability of >0.70 is considered adequate). Generally, excellent reliability is required for use with individuals.Summary of Results: For both the LDKT and DDKT Pros and Cons measures, 2 correlated factors CFA models fit the data well, verifying the original dimensional structures for these measures. Additionally, the LDKT and DDKT Self-Efficacy measures were supported by single factor CFA models, also supporting their original dimensional structure. However, several of these scales only evidenced adequate internal consistency reliability (LDKT Pros, LDKT Cons, DDKT Cons). These scales would require the addition of up to 15-17 parallel items to achieve excellent reliability (>0.90). Regarding the MMAS-8, the original factor structure was not supported by EFA and CFA models. One item, “Did you take your medicine yesterday?,” was weakly correlated (r<0.243) with the others, and did not load highly (λ<0.40) in EFA models. A CFA model with this item removed fit the data well (RMSEA = 0.06; CFI = 0.99; TLI = 0.98). The internal consistency reliability of the modified scale was 0.78, and 18 items would need to be added to achieve excellent reliability. Finally, regarding the KDQOL-36, the original factor structure was supported, and the internal consistency reliability for each KDQOL-36 scale exceeded the criterion for “good” reliability (>0.80), though the addition of up to 11 items would be required to increase reliability to “excellent” (Symptoms/Problems scale). For all scales in the dissertation, recommendations were made for increasing reliability using classical test theory and item response theory

    Between-group minimally important change versus individual treatment responders.

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    PurposeEstimates of the minimally important change (MIC) can be used to evaluate whether group-level differences are large enough to be important. But responders to treatment have been based upon group-level MIC thresholds, resulting in inaccurate classification of change over time. This article reviews options and provides suggestions about individual-level statistics to assess whether individuals have improved, stayed the same, or declined.MethodsReview of MIC estimation and an example of misapplication of MIC group-level estimates to assess individual change. Secondary data analysis to show how perceptions about meaningful change can be used along with significance of individual change.ResultsMIC thresholds yield over-optimistic conclusions about responders to treatment because they classify those who have not changed as responders.ConclusionsFuture studies need to evaluate the significance of individual change using appropriate individual-level statistics such as the reliable change index or the equivalent coefficient of repeatability. Supplementing individual statistical significance with retrospective assessments of change is desirable
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