4 resultados para dietary outcome measures

em DigitalCommons@The Texas Medical Center


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Intensive Family Preservation Services seek to reflect the values of focusing on client strengths and viewing clients as colleagues. To promote those values, Intensive Family Preservation Programs should include a systematic form of client self monitoring in their packages of outcome measures. This paper presents a model of idiographic self-monitoring used in time series, single system research design developed for Family Partners, a family preservation program of the School for Contemporary Education in Annandale, Virginia. The evaluation model provides a means of empowering client families to utilize their strengths and promote their status as colleague in determining their own goals, participating in the change process, and measuring their own progress.

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The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

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Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^

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Background: As obesity increases among U.S. workers, employers are implementing programs to increase physical activity and improve diets. Although programs to address individual determinants of obesity have been evaluated, less is known about the effects of workplace programs that change environmental factors, because most reviews have not isolated environmental programs; the one that did was published in 2005. ^ Objective: To update the 2005 review to determine the effectiveness of workplace environmental interventions. ^ Methods: The Medline database was searched for published English language reports (2003-2011) of randomized controlled (RCTs) or quasi-experimental trials (NRCTs) that evaluated strategies to modify physical activity opportunities or food services, targeting employees at least 18 years, not including retirees and that provided data for at least one physical activity, dietary, or health risk indicator. Three coders independently extracted study characteristics and scored the quality of study methods. Program effectiveness was determined using the 2005 review's best evidence approach. ^ Results: Seven studies represented in nine reports met eligibility criteria; three focused on diet and the remainder targeted diet and physical activity interventions. All but one study received a high quality score for internal validity. The evidence for the effectiveness of workplace environmental interventions was at best, inconclusive for diet and physical activity and limited for health risk indicators. The outcome constructs were inconsistent across the studies. ^ Conclusions: Limitations in the methods of the 2005 review made it challenging to draw conclusions about findings for this review that include: variation in outcome measures, reliance on distal measures without proximal behavior change measures, no distinction between changes at the workplace versus outside the workplace, and inappropriate analyses of cluster designs that biased findings toward statistical significance. The best evidence approach relied on vote-counting, using statistical significance alone rather than effect size and confidence intervals. Future research should address these limitations and use more rigorous methods; systematic reviews should use methods of meta-analysis to summarize study findings. These recommendations will help employers to better understand how environmental modifications in the workplace can support their efforts to combat the effects of obesity among employees.^