Incentivos governamentais para promoção da segurança e saúde no trabalho: em busca de alternativas e possibilidades

Introdução: A regulamentação e a fiscalização têm sido os principais instrumentos do Estado para promover a melhoria da segurança e da saúde no trabalho (SST). Neste estudo, argumenta-se que a combinação desses instrumentos com o uso de incentivos governamentais pode ser mais eficaz para promover essa melhoria. A questão que direcionou este estudo foi: "Quais incentivos governamentais, se implementados, seriam os mais promissores para influenciar a alta administração das organizações na melhoria da SST?". Metodologia: Na busca de respostas para essa questão foram entrevistados membros da alta administração de cinco companhias que operam 11 terminais marítimos para granéis líquidos no país. Utilizou-se um questionário contendo 43 questões que permitiu coletar informações sobre seis tipos de incentivos: flexibilização das alíquotas de contribuição do seguro acidente do trabalho (SAT), flexibilização da ocorrência das fiscalizações programadas dos ambientes e condições de trabalho, reconhecimento público em SST, publicidade negativa em SST, publicidade de dados comparativos do desempenho da SST entre organizações do mesmo segmento e estabelecimento de requisitos de SST nas licitações públicas. Resultados e conclusão: Os incentivos estudados têm potencial para exercer influência nas decisões dos entrevistados, com exceção do incentivo na forma de estabelecimento de requisitos de SST nas licitações públicas, pois essas companhias não possuem relações comerciais com o governo. Os incentivos na forma de flexibilização das alíquotas do SAT e na forma de flexibilização da ocorrência das fiscalizações programadas foram apontados como os mais promissores para promover a melhoria da SST

Assessing influence in survival data with a cure fraction and covariates

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

The characteristics of depressive symptoms in medical students during medical education and training: a cross-sectional study

Background: Medical education and training can contribute to the development of depressive symptoms that might lead to possible academic and professional consequences. We aimed to investigate the characteristics of depressive symptoms among 481 medical students (79.8% of the total who matriculated). Methods: The Beck Depression Inventory (BDI) and cluster analyses were used in order to better describe the characteristics of depressive symptoms. Medical education and training in Brazil is divided into basic (1(st) and 2(nd) years), intermediate (3(rd) and 4(th) years), and internship (5(th) and 6(th) years) periods. The study organized each item from the BDI into the following three clusters: affective, cognitive, and somatic. Statistical analyses were performed using analysis of variance (ANOVA) with post-hoc Tukey corrected for multiple comparisons. Results: There were 184 (38.2%) students with depressive symptoms (BDI > 9). The internship period resulted in the highest BDI scores in comparison to both the basic (p < .001) and intermediate (p < .001) periods. Affective, cognitive, and somatic clusters were significantly higher in the internship period. An exploratory analysis of possible risk factors showed that females (p = .020) not having a parent who practiced medicine (p = .016), and the internship period (p = .001) were factors for the development of depressive symptoms. Conclusion: There is a high prevalence towards depressive symptoms among medical students, particularly females, in the internship level, mainly involving the somatic and affective clusters, and not having a parent who practiced medicine. The active assessment of these students in evaluating their depressive symptoms is important in order to prevent the development of co-morbidities and suicide risk.

COOP/WONCA Charts as a Screen for Mental Disorders in Primary Care

PURPOSE most people with mental disorders receive treatment in primary care. The charts developed by the Dartmouth Primary Care Cooperative Research Network (COOP) and the World Organization of National Colleges, Academies, and Academic Associations of General Practitioners/Family Physicians (WONCA) have not yet been evaluated as a screen for these disorders, using a structured psychiatric interview by an expert or considering diagnoses other than depression. We evaluated the validity and feasibility of the COOP/WONCA Charts as a mental disorders screen by comparing them both with other questionnaires previously validated and with the assessment of a mental health specialist using a structured diagnostic interview. METHODS We trained community health workers and nurse assistants working in a collaborative mental health care model to administer the COOP/WONCA Charts, the 20-item Self-Reporting Questionnaire (SRQ-20), and the World Health Organization Five Well-Being Index (WHO-5) to 120 primary care patients. A psychiatrist blinded to the patients' results on these questionnaires administered the SCID, or Structured Clinical Interview for the DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition). RESULTS The area under the receiver operating characteristic curve was at least 0.80 for single items, a 3-item combination, and the total score of the COOP/WONCA Charts, as well as for the SRQ-20 and the WHO-5, for screening both for all mental disorders and for depressive disorders. The accuracy, sensitivity, specificity, and positive and negative predictive values of these measures ranged between 0.77 and 0.92. Community health workers and nurse assistants rated the understandability, ease of use, and clinical relevance of all 3 questionnaires as satisfactory. CONCLUSIONS One-time assessment of patients with the COOP/WONCA Charts is a valid and feasible option for screening for mental disorders by primary care teams.

Psychometric properties of the DASS-Depression scale among a Brazilian population with chronic pain

Background: Depression is a common contributor to suffering and disability in people with chronic pain. However, the assessment of depression in this population has been hampered by the presence of a number of somatic symptoms that are shared between chronic pain, treatment side-effects and traditional concepts of depression. As a result, the use of depression measures that do not contain somatic items has been encouraged. Objective: This study examined the psychometric properties of the Depression sub-scale of the Depression Anxiety and Stress Scales (DASS) in a Brazilian chronic pain patient population. Method: Data on a number of measures were collected from 348 participants attending pain facilities. Results: Principal components and exploratory factor analyses indicated the presence of only one factor. Item analyses indicated adequate item-scale correlations. The Cronbach alpha was .96, which suggests an excellent internal consistency. Conclusion: The DASS-Depression scale has adequate psychometric properties and its further use with Brazilian chronic pain populations can now be supported. (c) 2008 Elsevier Inc. All rights reserved.

Sexuality and quality of life of breast cancer patients post mastectomy

Aim: To evaluate the sexual functioning of breast cancer patients post mastectomy and its association with their quality of life, the personal characteristics of women and their partners, breast reconstruction, cancer staging and adjuvant therapies. Methods: A cross-sectional study was carried out in a University hospital located in the SouthEast of Brazil. A total of 100 women were included in the study. The parameters evaluated were sexual functioning, which was assessed based on the Sexual Quotient Female Version (SQ-F), quality of life (QoL), evaluated by the Medical Outcomes Study 36-item Short Form (SF-36), cancer staging, breast reconstruction, adjuvant therapies and the personal characteristics of patients (age, years of study and years of marriage) and their partners (age, years of study). Results: The majority (40.48%) of women had an unfavorable to regular SQ-F score. A significant positive correlation (p < 0.05) was found between the SQ-F score and years of education (p = 0.03), and the following SF-36 domains: functional capacity (p = 0.03), vitality (p = 0.06), emotional limitations (p = 0.00) and mental health (p = 0.03). A significant negative correlation was found between SQ-F score and the age of the partners (p = 0.03). SQ-F mean value was significantly higher (p = 0.04) among women who underwent breast reconstruction. Conclusions: Women with low educational level, who have older partners, and who did not have a breast reconstruction should receive special attention with respect to their sexuality, and the effects of mastectomy on the sexuality of patients should be assessed. Oncology nurses are best qualified to recognize issues related to sexuality and quality of life, and can offer specific and meaningful support for breast cancer patients. (C) 2010 Elsevier Ltd. All rights reserved.

Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi`s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is nonconforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure. (C) 2009 Elsevier B. V. All rights reserved.

Effects of the preventive and corrective adjustments in economical designs for online process control for attributes with misclassification errors

The procedure for online process control by attributes consists of inspecting a single item at every m produced items. It is decided on the basis of the inspection result whether the process is in-control (the conforming fraction is stable) or out-of-control (the conforming fraction is decreased, for example). Most articles about online process control have cited the stoppage of the production process for an adjustment when the inspected item is non-conforming (then the production is restarted in-control, here denominated as corrective adjustment). Moreover, the articles related to this subject do not present semi-economical designs (which may yield high quantities of non-conforming items), as they do not include a policy of preventive adjustments (in such case no item is inspected), which can be more economical, mainly if the inspected item can be misclassified. In this article, the possibility of preventive or corrective adjustments in the process is decided at every m produced item. If a preventive adjustment is decided upon, then no item is inspected. On the contrary, the m-th item is inspected; if it conforms, the production goes on, otherwise, an adjustment takes place and the process restarts in-control. This approach is economically feasible for some practical situations and the parameters of the proposed procedure are determined minimizing an average cost function subject to some statistical restrictions (for example, to assure a minimal levelfixed in advanceof conforming items in the production process). Numerical examples illustrate the proposal.

Economic design of an X chart for short-run production

The aim of this paper is to present an economical design of an X chart for a short-run production. The process mean starts equal to mu(0) (in-control, State I) and in a random time it shifts to mu(1) > mu(0) (out-of-control, State II). The monitoring procedure consists of inspecting a single item at every m produced ones. If the measurement of the quality characteristic does not meet the control limits, the process is stopped, adjusted, and additional (r - 1) items are inspected retrospectively. The probabilistic model was developed considering only shifts in the process mean. A direct search technique is applied to find the optimum parameters which minimizes the expected cost function. Numerical examples illustrate the proposed procedure. (C) 2009 Elsevier B.V. All rights reserved.

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved