The quality of life of disease-free Brazilian breast cancer survivors

The objective of this study was to compare the quality of life of women who survived breast cancer and women who have not had the disease, and to identify associated factors. It is cross-sectional study in which the comparison group includes survivors of breast cancer aged between 40 and 69 years. One hundred and fifty-four women were included, 70 with breast cancer and 84 without the disease. The SF-36 was used to evaluate quality of life. The chi-square test and multivariate linear models were used to compare the groups. The estimated mean physical and mental components were significantly better for the group who survived the disease (51.10 and 52.25, respectively) compared to the group without cancer (47.26 and 47.93, respectively). The study indicates that survivors of breast cancer had a better quality of life compared to women without the disease.

The use of the quality model of Parasuraman, Zeithaml and Berry in health services

This is an article about the theoretical model for assessing quality in health services proposed by Parasuraman, Zheitaml and Berry, in order to measure the degree of satisfaction of users. This model is based on the analysis of expectations and perceptions of users of health services, by means of five dimensions: tangibility, reliability, responsiveness, assurance and empathy. From the difference between what is expected by the user and the service offered, gaps or shortcomings are derived that may be the main obstacle for users to perceive the provision of such services with quality. It was observed that the use of the psychometric scale called Service Quality (SERVQUAL) in some studies about satisfaction, obtained very favorable results in the institutions in which it was employed. The analysis revealed the need to improve the existing models of evaluation, as well as the importance of measuring user satisfaction in health institutions.

Instrumental and ethical aspects of experimental research with animal models

Experimental animal models offer possibilities of physiology knowledge, pathogenesis of disease and action of drugs that are directly related to quality nursing care. This integrative review describes the current state of the instrumental and ethical aspects of experimental research with animal models, including the main recommendations of ethics committees that focus on animal welfare and raises questions about the impact of their findings in nursing care. Data show that, in Brazil, the progress in ethics for the use of animals for scientific purposes was consolidated with Law No. 11.794/2008 establishing ethical procedures, attending health, genetic and experimental parameters. The application of ethics in handling of animals for scientific and educational purposes and obtaining consistent and quality data brings unquestionable contributions to the nurse, as they offer subsidies to relate pathophysiological mechanisms and the clinical aspect on the patient.

Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care

BACKGROUND: The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. However, most commonly used measures raise conceptual issues. OBJECTIVES: We sought to evaluate the usefulness of the computerized algorithm for identifying avoidable readmissions on the basis of minimum bias, criterion validity, and measurement precision. RESEARCH DESIGN AND SUBJECTS: A total of 131,809 hospitalizations of patients discharged alive from 49 hospitals were used to compare the predictive performance of risk adjustment methods. A subset of a random sample of 570 medical records of discharge/readmission pairs in 12 hospitals were reviewed to estimate the predictive value of the screening of potentially avoidable readmissions. MEASURES: Potentially avoidable readmissions, defined as readmissions related to a condition of the previous hospitalization and not expected as part of a program of care and occurring within 30 days after the previous discharge, were identified by a computerized algorithm. Unavoidable readmissions were considered as censored events. RESULTS: A total of 5.2% of hospitalizations were followed by a potentially avoidable readmission, 17% of them in a different hospital. The predictive value of the screen was 78%; 27% of screened readmissions were judged clearly avoidable. The correlation between the hospital rate of clearly avoidable readmission and all readmissions rate, potentially avoidable readmissions rate or the ratio of observed to expected readmissions were respectively 0.42, 0.56 and 0.66. Adjustment models using clinical information performed better. CONCLUSION: Adjusted rates of potentially avoidable readmissions are scientifically sound enough to warrant their inclusion in hospital quality surveillance.

Probabilistic maximal covering location-allocation models with constrained waiting time or queue length for congested systems

When dealing with the design of service networks, such as healthand EMS services, banking or distributed ticket selling services, thelocation of service centers has a strong influence on the congestion ateach of them, and consequently, on the quality of service. In this paper,several models are presented to consider service congestion. The firstmodel addresses the issue of the location of the least number of single--servercenters such that all the population is served within a standard distance,and nobody stands in line for a time longer than a given time--limit, or withmore than a predetermined number of other clients. We then formulateseveral maximal coverage models, with one or more servers per service center.A new heuristic is developed to solve the models and tested in a 30--nodesnetwork.

Couple and family treatments: study quality and level of evidence.

This paper examines the application of the guidelines for evidence-based treatments in family therapy developed by Sexton and collaborators to a set of treatment models. These guidelines classify the models using criteria that take into account the distinctive features of couple and family treatments. A two-step approach was taken: (1) The quality of each of the studies supporting the treatment models was assessed according to a list of ad hoc core criteria; (2) the level of evidence of each treatment model was determined using the guidelines. To reflect the stages of empirical validation present in the literature, nine models were selected: three models each with high, moderate, and low levels of empirical validation, determined by the number of randomized clinical trials (RCTs). The quality ratings highlighted the strengths and limitations of each of the studies that provided evidence backing the treatment models. The classification by level of evidence indicated that four of the models were level III, "evidence-based" treatments; one was a level II, "evidence-informed treatment with promising preliminary evidence-based results"; and four were level I, "evidence-informed" treatments. Using the guidelines helped identify treatments that are solid in terms of not only the number of RCTs but also the quality of the evidence supporting the efficacy of a given treatment. From a research perspective, this analysis highlighted areas to be addressed before some models can move up to a higher level of evidence. From a clinical perspective, the guidelines can help identify the models whose studies have produced clinically relevant results.

Service Quality Analysis in the Five Stars Resort Hotels of Cape Verde

The objective of this study was the identification of the attributes and dimensions of service quality affecting the service performance of the five stars resort hotels located in the Cape Verde Islands. The reason boosting the initiative to do this research was the paramount role of the resort hotels in the development of the travel and tourism sector in Cape Verde, and the impact that today this sector has had in the economy of that country. The research opens with a literature review on the service quality theory in the hotel industry, starting from the middle of the 1980s with the classic model of service quality and SERVQUAL instrument to the analysis of recent models of service quality measurement in the hotel industry, as it is an example the scale of items developed in 2003 in the Lodging Quality Index (LQI). Furthermore, the study elaborates an analysis on the importance of the travel and tourism activities in the Cape Verde Islands, and it evidences the enormous importance of those activities in the performance of the Cape Verdean hotel industry. In sequence the study analyzes in details the hotel industry of Cape Verde and it identifies the market size of the five stars resort hotels and their current operators in that market. Moreover, the research develops with an online questionnaire elaborated and sent through the platforms of travel websites and communities to the guests whom have experienced the service of the five stars resort hotels located in the Cape Verde Islands. The scope of the questionnaire was to assess the attributes and dimensions of service quality in the five stars resort hotels of Cape Verde. The results of the questionnaire were in sequence analyzed through descriptive and applied statistics, using Microsoft Excel and the Statistical Package for Social Science (SPSS). Content validity analysis, factor analysis, and reliability analysis of the factors were made to purify an initial scale of 47 items of service quality. An instrument with three dimensions covering twenty four attributes of service quality assessment in the five stars resort hotels of Cape Verde was finally created. The three dimensions found were: staff competence; food and entertainment; and physical facilities. This study on the service in the five stars resort hotels of Cape Verde ends with brief comments on the status of service quality according to the identified dimensions and their attributes. In the conclusion, the study summarizes the whole work and gives some directions for future research.

Habitat-quality effects on metapopulation dynamics in greater white-toothed shrews, Crocidura russula.

The effects of patch size and isolation on metapopulation dynamics have received wide empirical support and theoretical formalization. By contrast, the effects of patch quality seem largely underinvestigated, partly due to technical difficulties in properly assessing quality. Here we combine habitat-quality modeling with four years of demographic monitoring in a metapopulation of greater white-toothed shrews (Crocidura russula) to investigate the role of patch quality on metapopulation processes. Together, local patch quality and connectivity significantly enhanced local population sizes and occupancy rates (R2 = 14% and 19%, respectively). Accounting for the quality of patches connected to the focal one and acting as potential sources improved slightly the model explanatory power for local population sizes, pointing to significant source-sink dynamics. Local habitat quality, in interaction with connectivity, also increased colonization rate (R2 = 28%), suggesting the ability of immigrants to target high-quality patches. Overall, patterns were best explained when assuming a mean dispersal distance of 800 m, a realistic value for the species under study. Our results thus provide evidence that patch quality, in interaction with connectivity, may affect major demographic processes.

No consistent association between processes-of-care and health-related quality of life among patients with diabetes : a missing link?

PURPOSE: Health-related quality of life (HRQoL) is considered a representative outcome in the evaluation of chronic disease management initiatives emphasizing patient-centered care. We evaluated the association between receipt of processes-of-care (PoC) for diabetes and HRQoL. METHODS: This cross-sectional study used self-reported data from non-institutionalized adults with diabetes in a Swiss canton. Outcomes were the physical/mental composites of the short form health survey 12 (SF-12) physical composite score, mental composite score (PCS, MCS) and the Audit of Diabetes-Dependent Quality of Life (ADDQoL). Main exposure variables were receipt of six PoC for diabetes in the past 12 months, and the Patient Assessment of Chronic Illness Care (PACIC) score. We performed linear regressions to examine the association between PoC, PACIC and the three composites of HRQoL. RESULTS: Mean age of the 519 patients was 64.5 years (SD 11.3); 60% were male, 87% reported type 2 or undetermined diabetes and 48% had diabetes for over 10 years. Mean HRQoL scores were SF-12 PCS: 43.4 (SD 10.5), SF-12 MCS: 47.0 (SD 11.2) and ADDQoL: -1.6 (SD 1.6). In adjusted models including all six PoC simultaneously, receipt of influenza vaccine was associated with lower ADDQoL (β=-0.4, p≤0.01) and foot examination was negatively associated with SF-12 PCS (β=-1.8, p≤0.05). There was no association or trend towards a negative association when these PoC were reported as combined measures. PACIC score was associated only with the SF-12 MCS (β=1.6, p≤0.05). CONCLUSIONS: PoC for diabetes did not show a consistent association with HRQoL in a cross-sectional analysis. This may represent an effect lag time between time of process received and health-related quality of life. Further research is needed to study this complex phenomenon.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Do habitat suitability models reliably predict the recovery areas of threatened species?

1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.

Diabetic patients who report receiving processes of diabetic care do not express a better quality of life

Background: Chronic disease management initiatives emphasize patient-centered care, and quality of life (QoL) is increasingly considered a representative outcome in that context. In this study we evaluated the association between receipt of processes of diabetic care and QoL. Methods: This cross-sectional population-based study (2011) used self-reported data from non-institutionalized, adult diabetics, recruited from randomly selected community pharmacies in Vaud. Outcomes included the physical and mental composites of the SF-36 (PCS, MCS) and the disease-specific Audit of Diabetes-Dependent QoL (ADDQoL). Main exposure variables were receipt of six diabetes processes-of care in the past 12 months. We also evaluated whether the association between care received and QoL was congruent with the chronic care model, when assessed by the Patient Assessment of Chronic Illness Care (PACIC). We used linear regressions to examine the association between process measures and the three composites of health-related QoL. Analyses were adjusted for age, gender, socioeconomic status, living companion, BMI, alcohol, smoking, physical activity, co-morbidities and diabetes mellitus (DM) characteristics (type, insulin use, complications, duration). Results: Mean age of the 519 diabetic patients was 64.4 years (SD 11.3), 60% were male and 73% had a living companion; 87% reported type 2 DM, half of respondents required insulin treatment, 48% had at least one DM complication, and 48% had DM over 10 years. Crude overall mean QoL scores were PCS: 43.4 (SD 10.5), MCS: 47.0 (SD 11.2) and ADDQoL: -1.56 (SD 1.6). In bivariate analyses, patients who received the influenza vaccine versus those who did not, had lower ADDQoL and PCS scores; there were no other indicator differences. In adjusted models including all processes, receipt of influenza vaccine was associated with lower ADDQoL (β= - 0.41, p=.01); there were no other associations between process indicators and QoL composites. There was no process association even when these were reported as combined measures of processes of care. PACIC score was associated only with the MCS (β= 1.57, p=.004). Conclusions: Process indicators for diabetes care did not show an association with QoL. This may represent an effect lag time between time of process received and quality of life; or that treatment may be related with inconvenience and patient worry. Further research is needed to explore these unexpected findings.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Development of Performance Properties of Ternary Mixtures and Concrete Pavement Mixture Design and Analysis (MDA): Effect of Paste Quality on Fresh and Hardened Properties of Ternary Mixtures, TPF-5(117), 2012

The purpose of this study was to investigate the effect of cement paste quality on the concrete performance, particularly fresh properties, by changing the water-to-cementitious materials ratio (w/cm), type and dosage of supplementary cementitious materials (SCM), and airvoid system in binary and ternary mixtures. In this experimental program, a total matrix of 54 mixtures with w/cm of 0.40 and 0.45; target air content of 2%, 4%, and 8%; a fixed cementitious content of 600 pounds per cubic yard (pcy), and the incorporation of three types of SCMs at different dosages was prepared. The fine aggregate-to- total aggregate ratio was fixed at 0.42. Workability, rheology, air-void system, setting time, strength, Wenner Probe surface resistivity, and shrinkage were determined. The effects of paste variables on workability are more marked at the higher w/cm. The compressive strength is strongly influenced by the paste quality, dominated by w/cm and air content. Surface resistivity is improved by inclusion of Class F fly ash and slag cement, especially at later ages. Ternary mixtures performed in accordance with their ingredients. The data collected will be used to develop models that will be part of an innovative mix proportioning procedure.

Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models

Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.