5 resultados para measurement scale

em DigitalCommons@The Texas Medical Center


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Research has shown that physical activity serves a preventive function against the development of several major chronic diseases. However, studying physical activity and its health benefits is difficult due to the complexity of measuring physical activity. The overall aim of this research is to contribute to the knowledge of both correlates and measurement of physical activity. Data from the Women On The Move study were used for this study (n = 260), and the results are presented in three papers. The first paper focuses on the measurement of physical activity and compares an alternate coding method with the standard coding method for calculating energy expenditure from a 7-day activity diary. Results indicate that the alternative coding scheme could produce similar results to the standard coding in terms of total activity expenditure. Even though agreement could not be achieved by dimension, the study lays the groundwork for a coding system that saves considerable amount of time in coding activity and has the ability to estimate expenditure more accurately for activities that can be performed at varying intensity levels. The second paper investigates intra-day variability in physical activity by estimating the variation in energy expenditure for workers and non-workers and identifying the number of days of diary self-report necessary to reliably estimate activity. The results indicate that 8 days of activity are needed to reliably estimate total activity for individuals who don't work and 12 days of activity are needed to reliably estimate total activity for those who work. Days of diary self-report required by dimension for those who don't work range from 6 to 16 and for those who work from 6 to 113. The final paper presents findings on the relationship between daily living activity and Type A behavior pattern. Significant findings are observed for total activity and leisure activity with the Temperament Scale summary score. Significant findings are also observed for total activity, household chores, work, leisure activity, exercise, and inactivity with one or more of the individual items on the Temperament Scale. However, even though some significant findings were observed, the overall models did not reveal meaningful associations. ^

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Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

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Two studies among college students were conducted to evaluate appropriate measurement methods for etiological research on computing-related upper extremity musculoskeletal disorders (UEMSDs). ^ A cross-sectional study among 100 graduate students evaluated the utility of symptoms surveys (a VAS scale and 5-point Likert scale) compared with two UEMSD clinical classification systems (Gerr and Moore protocols). The two symptom measures were highly concordant (Lin's rho = 0.54; Spearman's r = 0.72); the two clinical protocols were moderately concordant (Cohen's kappa = 0.50). Sensitivity and specificity, endorsed by Youden's J statistic, did not reveal much agreement between the symptoms surveys and clinical examinations. It cannot be concluded self-report symptoms surveys can be used as surrogate for clinical examinations. ^ A pilot repeated measures study conducted among 30 undergraduate students evaluated computing exposure measurement methods. Key findings are: temporal variations in symptoms, the odds of experiencing symptoms increased with every hour of computer use (adjOR = 1.1, p < .10) and every stretch break taken (adjOR = 1.3, p < .10). When measuring posture using the Computer Use Checklist, a positive association with symptoms was observed (adjOR = 1.3, p < 0.10), while measuring posture using a modified Rapid Upper Limb Assessment produced unexpected and inconsistent associations. The findings were inconclusive in identifying an appropriate posture assessment or superior conceptualization of computer use exposure. ^ A cross-sectional study of 166 graduate students evaluated the comparability of graduate students to College Computing & Health surveys administered to undergraduate students. Fifty-five percent reported computing-related pain and functional limitations. Years of computer use in graduate school and number of years in school where weekly computer use was ≥ 10 hours were associated with pain within an hour of computing in logistic regression analyses. The findings are consistent with current literature on both undergraduate and graduate students. ^

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Background/significance. Mental illness stigma is a matter of great concern to family caregivers. Few research studies have been conducted in the Arab World on family caregivers' perception of stigma associated with caring for a mentally ill relative. Review of the literature on measurement of the concept of stigma related to caring for a mentally ill relative yielded no instrument appropriate for use in a Jordanian sample. Reliable and valid instruments to measure stigma perception among family caregivers are needed for research and practice, particularly in Arabic speaking populations. ^ Purpose. The purposes of this study were: (1) translate the Stigma-Devaluation scale (SDS) into Arabic, modifying it to accurately reflect the cultural parameters specific to Jordan, and (2) test the reliability, the content and construct validity of the Arabic version of the SDS for use among a sample of family members of mentally ill relatives in Jordan. ^ Design. Methodologic, cross-sectional. ^ Methods. The SDS was translated into Arabic language, modified and culturally adapted to the Jordanian culture by a translation model which incorporates a cultural adaptation process. The Arabic SDS was evaluated in a sample of 164 family caregivers in the outpatient mental health clinic in Irbid-Jordan. Cronbach's alpha estimation of internal consistency was used to assess the reliability of the SDS. Construct validity was determined by confirmatory factor analysis (CFA). Measurements of content validity and reading level of the Arabic SDS were included. ^ Findings. Content Validity Index was determined to be 1.0. Reading level of the Arabic SDS was considered at a 6th grade or lower Cronbach's alpha coefficient of the modified Arabic SDS total scale was .87. Initial results of CFA did not fully support the proposed factor structures of the SDS or its subscales. After modifications, the indices indicated that the modified model of each subscale had satisfactory fit. ^ Conclusion. This study provided psychometric evidence that the modified Arabic SDS translated and culturally adapted instrument, is valid and conceptually consistent with the content of the original English SDS in measuring stigma perception among families of mentally ill relatives in Jordan. ^

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The purpose of this investigation was to develop a reliable scale to measure the social environment of hospital nursing units according to the degree of humanistic and dehumanistic behaviors as perceived by nursing staff in hospitals. The study was based on a conceptual model proposed by Jan Howard, a sociologist. After reviewing the literature relevant to personalization of care, analyzing interviews with patients in various settings, and studying biological, psychological, and sociological frames of reference, Howard proposed the following necessary conditions for humanized health care. They were the dimensions of Irreplaceability, Holistic Selves, Freedom of Action, Status Equality, Shared Decision Making and Responsibility, Empathy, and Positive Affect.^ It was proposed that a scale composed of behaviors which reflected Howard's dimensions be developed within the framework of the social environment of nursing care units in hospitals. Nursing units were chosen because hospitals are traditionally organized around nursing care units and because patients spend the majority of their time in hospitals interacting with various levels of nursing personnel.^ Approximately 180 behaviors describing both patient and nursing staff behaviors which occur on nursing units were developed. Behaviors which were believed to be humanistic as well as dehumanistic were included. The items were classified under the dimensions of Howard's model by a purposively selected sample of 42 nurses representing a broad range of education, experience, and clinical areas. Those items with a high degree of agreement, at least 50%, were placed in the questionnaire. The questionnaire consisted of 169 items including six items from the Marlowe Crowne Social Desirability Scale (Short Form).^ The questionnaire, the Social Environment Scale, was distributed to the entire 7 to 3 shift nursing staff (603) of four hospitals including a public county specialty hospital, a public county general and acute hospital, a large university affiliated hospital with all services, and a small general community hospital. Staff were asked to report on a Likert type scale how often the listed behaviors occurred on their units. Three hundred and sixteen respondents (52% of the population) participated in the study.^ An item analysis was done in which each item was examined in relationship to its correlation to its own dimension total and to the totals of the other dimensions. As a result of this analysis, three dimensions, Positive Affect, Irreplaceability, and Freedom of Action were deleted from the scale. The final scale consisted of 70 items with 26 in Shared Decision Making and Responsibility, 25 in Holistic Selves, 12 in Status Equality, and seven in Empathy. The alpha coefficient was over .800 for all scales except Empathy which was .597.^ An analysis of variance by hospital was performed on the means of each dimension of the scale. There was a statistically significant difference between hospitals with a trend for the public hospitals to score lower on the scale than the university or community hospitals. That the scale scores should be lower in crowded, understaffed public hospitals was not unexpected and reflected that the scale had some discriminating ability. These differences were still observed after adjusting for the effect of Social Desirability.^ In summary, there is preliminary evidence based on this exploratory investigation that a reliable scale based on at least four dimensions from Howard's model could be developed to measure the concept of humanistic health care in hospital settings. ^