10 resultados para Vietnam limitations and exceptions
em DigitalCommons@The Texas Medical Center
Resumo:
Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS) are life- threatening disorders that can result from many severe conditions and diseases. Since the American European Consensus Conference established the internationally accepted definition of ALI and ARDS, the epidemiology of pediatric ALI/ARDS has been described in some developed countries. In the developing world, however, there are very few data available regarding the burden, etiologies, management, outcome, and factors associated with outcomes of ALI/ARDS in children. ^ Therefore, we conducted this observational, clinical study to estimate the prevalence and case mortality rate of ALI/ARDS among a cohort of patients admitted to the pediatric intensive care unit (PICU) of the National Hospital of Pediatrics in Hanoi, the largest children's hospital in Vietnam. Etiologies and predisposing factors, and management strategies for pediatric ALI/ARDS were described. In addition, we determined the prevalence of HIV infection among children with ALI/ARDS in Vietnam. We also identified the causes of mortality and predictors of mortality and prolonged mechanical ventilation of children with ALI/ARDS. ^ A total of 1,051 patients consecutively admitted to the pediatric intensive care unit from January 2011 to January 2012 were screened daily for development of ALI/ARDS using the American-European Consensus Conference Guidelines. All identified patients with ALI/ARDS were followed until hospital discharge or death in the hospital. Patients' demographic and clinical data were collected. Multivariable logistic regression models were developed to identify independent predictors of mortality and other adverse outcome of ALI/ARDS. ^ Prevalence of ALI and ARDS was 9.6% (95% confidence interval, 7.8% to 11.4%) and 8.8% (95% confidence interval, 7.0% to 10.5%) of total PICU admissions, respectively. Infectious pneumonia and sepsis were the most common causes of ALI/ARDS accounting for 60.4% and 26.7% of cases, respectively. Prevalence of HIV infection among children with ALI/ARDS was 3.0%. The case fatality rate of ALI/ARDS was 63.4% (95% confidence interval, 53.8% to 72.9%). Multiple organ failure and refractory hypoxemia were the main causes of death. Independent predictors of mortality and prolonged mechanical ventilation were male gender, duration of intensive care stay prior to ALI/ARDS diagnosis, level of oxygenation defect measured by PaO2/FiO2 ratio at ALI/ARDS diagnosis, presence of non-pulmonary organ dysfunction at day one and day three after ALI/ARDS diagnosis, and presence of hospital acquired infection. ^ The results of this study demonstrated that ALI/ARDS was a common and severe condition in children in Vietnam. The level of both pulmonary and non-pulmonary organ damage influenced survival of patients with ALI/ARDS. Strategies for preventing ALI/ARDS and for clinical management of the disease are necessary to reduce the associated risks.^
Resumo:
Currently more than half of Electronic Health Record (EHR) projects fail. Most of these failures are not due to flawed technology, but rather due to the lack of systematic considerations of human issues. Among the barriers for EHR adoption, function mismatching among users, activities, and systems is a major area that has not been systematically addressed from a human-centered perspective. A theoretical framework called Functional Framework was developed for identifying and reducing functional discrepancies among users, activities, and systems. The Functional Framework is composed of three models – the User Model, the Designer Model, and the Activity Model. The User Model was developed by conducting a survey (N = 32) that identified the functions needed and desired from the user’s perspective. The Designer Model was developed by conducting a systemic review of an Electronic Dental Record (EDR) and its functions. The Activity Model was developed using an ethnographic method called shadowing where EDR users (5 dentists, 5 dental assistants, 5 administrative personnel) were followed quietly and observed for their activities. These three models were combined to form a unified model. From the unified model the work domain ontology was developed by asking users to rate the functions (a total of 190 functions) in the unified model along the dimensions of frequency and criticality in a survey. The functional discrepancies, as indicated by the regions of the Venn diagrams formed by the three models, were consistent with the survey results, especially with user satisfaction. The survey for the Functional Framework indicated the preference of one system over the other (R=0.895). The results of this project showed that the Functional Framework provides a systematic method for identifying, evaluating, and reducing functional discrepancies among users, systems, and activities. Limitations and generalizability of the Functional Framework were discussed.
Resumo:
Teen pregnancy is a continuing problem, bringing with it a host of associated health and social risks. Alternative school students are especially at risk, but are historically under-represented in research. This is especially problematic in that instruments are needed to guide effective intervention development, but psychometrics for these instruments cannot be assumed when used in new populations. Decisional balance from the transtheoretical model offers a framework for understanding condom decision making, but has not been tested with alternative school students. Using responses from 640 subjects from Safer Choices 2 (a school-based HIV/STD/pregnancy prevention program implemented in 10 urban, southwestern alternative schools), a decisional balance scale for condom use was examined. A two-factor, mildly correlated model fit the data well. Tests of invariance examined scale functioning within gender and racial/ethnic groups. The underlying structure varied slightly based on subgroup, but on a practical level the impact on the use of scales was minimal. The structure and loadings were invariant across experimental condition. The pro scale was associated with a lower probability of having engaged in unprotected sexual behavior for sexually active subjects, and this association remained significant while controlling for demographic variables. The con scale did not show a significant association with engagement in unprotected sexual behaviors. Limitations and directions for future research were also discussed.^
Resumo:
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.^
Resumo:
Obesity, among both children and adults, is a growing public health epidemic. One area of interest relates to how and why obesity is developing at such a rapid pace among children. Despite a broad consensus about how controlling feeding practices relate to child food consumption and obesity prevalence, much less is known about how non-controlling feeding practices, including modeling, relate to child food consumption. This study investigates how different forms of parent modeling (no modeling, simple modeling, and enthusiastic modeling) and parent adiposity relate to child food consumption, food preferences, and behaviors towards foods. Participants in this experimental study were 65 children (25 boys and 40 girls) aged 3-9 and their parents. Each parent was trained on how to perform their assigned modeling behavior towards a food identified as neutral (not liked, nor disliked) by their child during a pre-session food-rating task. Parents performed their assigned modeling behavior when cued during a ten-minute observation period with their child. Child food consumption (pieces eaten, grams eaten, and calories consumed) was measured and food behaviors (positive comments toward food and food requests) were recorded by event-based coding. After the session, parents self-reported on their height and weight, and children completed a post-session food-rating task. Results indicate that parent modeling (both simple and enthusiastic forms) did not significantly relate to child food consumption, food preferences, or food requests. However, enthusiastic modeling significantly increased the number of positive food comments made by children. Children's food consumption in response to parent modeling did not differ based on parent obesity status. The practical implications of this study are discussed, along with its strengths and limitations, and directions for future research.^
Resumo:
Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^
Resumo:
The discrete-time Markov chain is commonly used in describing changes of health states for chronic diseases in a longitudinal study. Statistical inferences on comparing treatment effects or on finding determinants of disease progression usually require estimation of transition probabilities. In many situations when the outcome data have some missing observations or the variable of interest (called a latent variable) can not be measured directly, the estimation of transition probabilities becomes more complicated. In the latter case, a surrogate variable that is easier to access and can gauge the characteristics of the latent one is usually used for data analysis. ^ This dissertation research proposes methods to analyze longitudinal data (1) that have categorical outcome with missing observations or (2) that use complete or incomplete surrogate observations to analyze the categorical latent outcome. For (1), different missing mechanisms were considered for empirical studies using methods that include EM algorithm, Monte Carlo EM and a procedure that is not a data augmentation method. For (2), the hidden Markov model with the forward-backward procedure was applied for parameter estimation. This method was also extended to cover the computation of standard errors. The proposed methods were demonstrated by the Schizophrenia example. The relevance of public health, the strength and limitations, and possible future research were also discussed. ^
Resumo:
Objective. This study investigates the life and health goals of older adults with diabetes, and explores the factors that influence their diabetes self-management. Methods: Qualitative in-depth interviews were conducted with 24 older adults with diabetes and other morbid conditions and/or their caregivers, when appropriate. ^ Results. Participants’ provided a consistent set of responses when describing life and health goals. Participants described goals for longevity, better physical functioning, spending time with family, or maintaining independence. Diabetes discordant conditions, but not diabetes, were seen as barriers to life goals for participants with functional impairments. Functionally independent participants described additional health goals that related to diabetes self-management as diabetes was seen often a barrier to life goals. Caregivers, co-morbid conditions, denial and retirement were among the factors that influenced initiation of diabetes self-management. ^ Conclusion. Participants endorsed health goals and diabetes self-management practices that they believed would help them accomplish their life goals. Functional capabilities and social support were key factors in the relationship between diabetes self-management and their broader goals. ^ Practice implications. When planning diabetes treatments, clinicians, patients and caregivers should discuss the relationship between diabetes self-management and health and life goals as well as the affects of functional limitations and caregiver support.^
Resumo:
Background. Consistent adherence to antiretroviral treatment is necessary for a treatment success. Improving and maintaining adherence rate >95% are challenging for health care professionals. This pilot randomized controlled study aimed to evaluate the impact of the interactive intervention on adherence to GPO-VIR, to describe the feasibility of the interactive intervention in Thailand, and to illustrate the adherence self-efficacy concept among HIV treatment-naïve patients in Thailand who were starting antiretroviral treatment. ^ Methods. The study took place at three HIV clinics located in Phayao, Thailand. Twenty-three patients were randomly assigned into the experimental (n=11) and the control groups (n=12). Each participant in the experimental group and a significant person to the patient received 5 educational sessions with a nurse at the clinics and at their homes. They also received 3 follow-up evaluations during the 6-month period of the study. The participants in the control group received the standard of care provided by HIV clinical personnel plus three follow-up evaluations at the clinic. ^ Results. Seventeen patients (7 in the experimental and 10 in the control group) completed the study. The 4-day recall on the Thai ACTG Adherence Scale demonstrated adherence rate >95% for most participants from both groups. After the first measurement, no experimental group patients reporting missing ART, while one control group participant continuously skipped ART. Participants from both groups had significantly increased CD4 cell counts after the study (F(1, 15) = 29.30, p = .000), but no differences were found between two groups (F(1, 15) = .001, p = .98). Examination of the intervention showed limitations and possibilities to implement it in Thailand. Qualitative data demonstrated self-efficacy expectations, resignation and acceptance as related concepts to improve adherence outcomes. ^ Conclusions. This interactive intervention, after appropriate modifications, is feasible to apply for Thai HIV-treatment naïve patients. Because of limitations the study could not demonstrate whether the interactive intervention improved adherence to ART among HIV-treatment naïve in Thailand. A longitudinal study in a larger sample would be required to test the impact of the intervention. ^ Keyword: antiretroviral treatment, adherence, treatment-naïve, Thailand, randomized controlled study ^
Resumo:
Standardization is a common method for adjusting confounding factors when comparing two or more exposure category to assess excess risk. Arbitrary choice of standard population in standardization introduces selection bias due to healthy worker effect. Small sample in specific groups also poses problems in estimating relative risk and the statistical significance is problematic. As an alternative, statistical models were proposed to overcome such limitations and find adjusted rates. In this dissertation, a multiplicative model is considered to address the issues related to standardized index namely: Standardized Mortality Ratio (SMR) and Comparative Mortality Factor (CMF). The model provides an alternative to conventional standardized technique. Maximum likelihood estimates of parameters of the model are used to construct an index similar to the SMR for estimating relative risk of exposure groups under comparison. Parametric Bootstrap resampling method is used to evaluate the goodness of fit of the model, behavior of estimated parameters and variability in relative risk on generated sample. The model provides an alternative to both direct and indirect standardization method. ^