The brief measure of preoperative emotional stress screens preoperative maladaptive psychological features and predicts postoperative opioid use: an observational study.

BACKGROUND: The Brief Measure of Preoperative Emotional Stress (B-MEPS) is a suitable screening tool for Preoperative Emotional Stress (PES). However, personalized decision-making demands practical interpretation of the refined version of B-MEPS. Thus, we propose and validate cut-off points on the B-MEPS to classify PES. Also, we assessed if the cut-off points screened preoperative maladaptive psychological features and predicted postoperative opioid use. METHODS: This observational study comprises samples of two other primary studies, with 1009 and 233 individuals, respectively. The latent class analysis derived emotional stress subgroups using B-MEPS items. We compared membership with the B-MEPS score through the Youden index. Concurrent criterion validity of the cut-off points was performed with the severity of preoperative depressive symptoms, pain catastrophizing, central sensitization, and sleep quality. Predictive criterion validity was performed with opioid use after surgery. RESULTS: We chose a model with three classes labeled mild, moderate, and severe. The Youden index points -0.1663 and 0.7614 of the B-MEPS score classify individuals, in the severe class, with a sensitivity of 85.7% (80.1%-90.3%) and specificity of 93.5% (91.5-95.1%). The cut-off points of the B-MEPS score have satisfactory concurrent and predictive criterion validity. CONCLUSIONS: These findings showed that the preoperative emotional stress index on the B-MEPS offers suitable sensitivity and specificity for discriminating the severity of preoperative psychological stress. They provide a simple tool to identify patients prone to severe PES related to maladaptive psychological features, which might influence the perception of pain and analgesic opioid use in the postoperative period.

Mobile Application Increased Nutrition Knowledge Among Brazilian Physicians.

OBJECTIVE: To assess whether using a Dietary Approaches to Stop Hypertension (DASH) diet recommendation application increases primary care physicians' knowledge and dietary counseling skills. DESIGN: A randomized controlled trial. SETTING: Brazilian public primary care service. PARTICIPANTS: Two hundred and twenty-two physicians (intervention group: n = 111; control group: n = 111). INTERVENTION: Thirty days of using the Dieta Dash application. The application provides information about nutritional recommendations for hypertension management. MAIN OUTCOME MEASURES: Nutrition knowledge score. SECONDARY OUTCOMES: self-assessment of knowledge, self-confidence, assessment of eating habits, and barriers to dietary counseling. ANALYSIS: Linear mixed-effects models for repeated measures and generalized estimating equations for comparing changes between groups. RESULTS: A total of 66.2% of participants completed the follow-up. There was no significant difference between the groups regarding the mean knowledge score (P = 0.15). The prevalence of high knowledge increased by 12% (prevalence ratio [PR] = 1.12; 95% confidence interval [CI], 1.00-1.25) in the intervention group and showed an improvement in the self-confidence assessment (PR = 1.21; 95% CI, 1.02-1.44), and increased assessment of eating habits (PR = 1.26; 95% CI, 1.10-1.55). CONCLUSIONS AND IMPLICATIONS: The Dieta Dash application helped address dietary counseling, improving knowledge and self-confidence. However, innovative strategies are needed to minimize the primary care barriers.

Validation of the regret coping scale for healthcare professionals (RCS-HCP) in portuguese for Brazil

Introduction: assessing the ability to cope with regret can contribute to support strategies for health professionals. However, in Brazil only few instruments evaluate this ability in general. Objective: this study aimed was to adapt and validate the Regret Coping Scale for Healthcare Professionals (RCS-HCP) to Brazilian Portuguese . Methods: the instruments were translated, and the psychometric properties evaluated for validity and reliability. Three hundred and forty-one professionals participated, with an average age of 38.6 ± 9.2, and 87 participated in a retest survey 30 days later. Results: exploratory factor analysis showed adequacy of the structure (KMO = 0.786) composed of three factors. In the confirmation, the performance was close to acceptable. Reliability was good for the maladaptive strategies (α = 0.834) and adequate for the problem-focused initiatives (α = 0.717), but slightly too low for adaptive strategies (α = 0.595). Test- retest showed lower than expected values, with a Spearman- Brown coefficient of 0.703. Conclusion: the RCS-HCP scale showed satisfactory performance in relation to the properties evaluated.

Introdução: a avaliação da capacidade de lidar com o arrependimento pode contribuir para estratégias de apoio aos profissionais de saúde. No entanto, no Brasil existem poucos instrumentos que avaliam essa habilidade no contexto geral. Objetivo: o objetivo do estudo foi adaptar e validar a Regret Coping Scale for Healthcare Professionals (RCS-HCP) para profissionais de saúde brasileiros. Método: na validação, os instrumentos foram traduzidos e as propriedades psicométricas avaliadas quanto à validade e confiabilidade. Participaram 341 profissionais, com média de idade de 38,6 ± 9,2, e 87 participaram de uma pesquisa de reteste 30 dias depois. Resultados: a análise fatorial exploratória mostrou adequação da estrutura (KMO = 0,786) composta por três fatores. Na confirmação, o desempenho ficou próximo do aceitável. A confiabilidade foi boa para as estratégias mal adaptativas (α = 0,834) e adequada para as estratégias focadas no problema (α = 0,717), mas um pouco baixa demais para as estratégias adaptativas (α = 0,595). Teste-reteste apresentou valores abaixo do esperado, com coeficiente de Spearman-Brown de 0,703. Conclusão: a escala RCS-HCP apresentou desempenho satisfatório em relação às propriedades avaliadas.

Validation of the Brazilian version of the child pain catastrophizing scale and its relationship with a marker of central sensitization

Abstract Objectives The Pain Catastrophizing Scale-Child version (PCS-C) allows to identify children who are prone to catastrophic thinking. We aimed to adapt the Brazilian version of PCS-C (BPCS-C) to examine scale psychometric properties and factorial structure in children with and without chronic pain. Also, we assessed its correlation with salivary levels of Brain-Derived Neurotrophic factor (BDNF). Methods The Brazilian version of PCS-C was modified to adjust it for 7-12 years old children. To assess psychometric properties, 100 children (44 with chronic pain from a tertiary hospital and 56 healthy children from a public school) answered the BPCS-C, the visual analogue pain scale, and questions about pain interference in daily activities. We also collected a salivary sample to measure BDNF. Results We observed good internal consistency (Cronbach's value = 0.81). Parallel analysis retained 2 factors. Confirmatory factor analysis of our 2-factor model revealed consistent goodness-of-fit (IFI = 0.946) when compared to other models. There was no correlation between visual analogue pain scale and the total BPCS-C score; however, there was an association between pain catastrophizing and difficulty in doing physical activities in school (p= 0.01). BPCS-C total scores were not different between groups. We found a marginal association with BPCS-C (r= 0.27, p= 0.01) and salivary BDNF levels. Discussion BPCS-C is a valid instrument with consistent psychometric properties. The revised 2-dimension proposed can be used for this population. Children catastrophism is well correlated with physical limitation, but the absence of BPCS-C score differences between groups highlights the necessity of a better understanding about catastrophic thinking in children.

Validation of the Family Health Behavior Scale for the Brazilian population

Abstract Objective: To validate the Family Health Behavior Scale (FHBS) for Brazilian families. Methods: The sample included 272 children aged 5 to 12 years old. Caregivers and their healthy answered the FHBS and questions about physical activity. In addition, anthropometric measurements of the children's weight and height were performed, as well as the bioimpedance exam. The scale was translated and the following validities were assessed: content (qualitative analysis and content validity index), construct (factor analysis) and concurrent validity (difference between domains and the total score with the categories of BMI, fat percentage and physical activity). Reliability (Cronbach's alpha, ceiling-floor effect, two-half test, intraclass correlation and Bland - Altman) was also assessed. Results: FHBS instrument performed well with regard to the psychometric properties in the Brazilian population. The content validity index was 0.987. Fit indices of the factor analysis were considered satisfactory, according to Bartlett's sphericity test (χ 2 = 1927, df = 351; p < 0.001) and the Kaiser-Meyer-Olkin index (KMO = 0.789). Concurrent validity, the differences between the mean of the domains and the total score between the categories of BMI (p = 0.011), percentage of fat (0.004) and physical activity (p < 0.001) were all significant. The reliability results were Cronbach's alpha internal consistency = 0.83, adequate ceiling-floor effect, 0.8105 (0.09 SD) two-half test, 0.626 intraclass correlation (95% CI: 0.406 to 0.777) and Bland - Altman -0.840 (-22.76 to 21.07). Conclusion: The FHBS adapted for the Brazilian population showed evidence of adequate psychometric performance.

Derivation and validation of a national multicenter mortality risk stratification model - the ExCare model: a study protocol.

INTRODUCTION: Surgical care is essential for proper management of various diseases. However, it can result in unfavorable outcomes. In order to identify patients at higher risk of complications, several risk stratification models have been developed. Ideally, these tools should be simple, reproducible, accurate, and externally validated. Unfortunately, none of the best-known risk stratification instruments have been validated in Brazil. In this sense, the Ex-Care model was developed by retrospective data analysis of surgical patients in a major Brazilian university hospital. It consists of four independent predictors easily collected in the preoperative evaluation, showing high accuracy in predicting death within 30 days after surgery. OBJECTIVES: To update and validate a Brazilian national-based model of postoperative death probability within 30 days based on the Ex-Care model. Also, to develop an application for smartphones that allows preoperative risk stratification by Ex-Care model. METHODS: Ten participating centers will collect retrospective data from digital databases. Variables age, American Society of Anesthesiologists (ASA) physical status, surgical severity (major or non-major) and nature (elective or urgent) will be evaluated as predictors for in-hospital mortality within 30 postoperative days, considered the primary outcome. EXPECTED RESULTS: We believe that the Ex-Care model will present discriminative capacity similar to other classically used scores validated for surgical mortality prediction. Furthermore, the mobile application to be developed will provide a practical and easy-to-use tool to the professionals enrolled in perioperative care.

Validation of the Brazilian version of the child pain catastrophizing scale and its relationship with a marker of central sensitization.

OBJECTIVES: The Pain Catastrophizing Scale-Child version (PCS-C) allows to identify children who are prone to catastrophic thinking. We aimed to adapt the Brazilian version of PCS-C (BPCS-C) to examine scale psychometric properties and factorial structure in children with and without chronic pain. Also, we assessed its correlation with salivary levels of Brain-Derived Neurotrophic factor (BDNF). METHODS: The Brazilian version of PCS-C was modified to adjust it for 7-12 years old children. To assess psychometric properties, 100 children (44 with chronic pain from a tertiary hospital and 56 healthy children from a public school) answered the BPCS-C, the visual analogue pain scale, and questions about pain interference in daily activities. We also collected a salivary sample to measure BDNF. RESULTS: We observed good internal consistency (Cronbach's value = 0.81). Parallel analysis retained 2 factors. Confirmatory factor analysis of our 2-factor model revealed consistent goodness-of-fit (IFI = 0.946) when compared to other models. There was no correlation between visual analogue pain scale and the total BPCS-C score; however, there was an association between pain catastrophizing and difficulty in doing physical activities in school (p = 0.01). BPCS-C total scores were not different between groups. We found a marginal association with BPCS-C (r = 0.27, p = 0.01) and salivary BDNF levels. DISCUSSION: BPCS-C is a valid instrument with consistent psychometric properties. The revised 2-dimension proposed can be used for this population. Children catastrophism is well correlated with physical limitation, but the absence of BPCS-C score differences between groups highlights the necessity of a better understanding about catastrophic thinking in children.

Validation of the Family Health Behavior Scale for the Brazilian population.

OBJECTIVE: To validate the Family Health Behavior Scale (FHBS) for Brazilian families. METHODS: The sample included 272 children aged 5 to 12 years old. Caregivers and their healthy answered the FHBS and questions about physical activity. In addition, anthropometric measurements of the children's weight and height were performed, as well as the bioimpedance exam. The scale was translated and the following validities were assessed: content (qualitative analysis and content validity index), construct (factor analysis) and concurrent validity (difference between domains and the total score with the categories of BMI, fat percentage and physical activity). Reliability (Cronbach's alpha, ceiling-floor effect, two-half test, intraclass correlation and Bland - Altman) was also assessed. RESULTS: FHBS instrument performed well with regard to the psychometric properties in the Brazilian population. The content validity index was 0.987. Fit indices of the factor analysis were considered satisfactory, according to Bartlett's sphericity test (χ 2 = 1927, df = 351; p < 0.001) and the Kaiser-Meyer-Olkin index (KMO = 0.789). Concurrent validity, the differences between the mean of the domains and the total score between the categories of BMI (p = 0.011), percentage of fat (0.004) and physical activity (p < 0.001) were all significant. The reliability results were Cronbach's alpha internal consistency = 0.83, adequate ceiling-floor effect, 0.8105 (0.09 SD) two-half test, 0.626 intraclass correlation (95% CI: 0.406 to 0.777) and Bland - Altman -0.840 (-22.76 to 21.07). CONCLUSION: The FHBS adapted for the Brazilian population showed evidence of adequate psychometric performance.

PSS Health: como calcular tamanho de amostra para testes de comparação de médias de dois grupos / PSS Health: how to calculate sample sizes for mean comparison tests between two groups

Dando continuidade à série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa, esta edição apresenta um passo a passo de como realizar o cálculo e de quais informações são necessárias para comparar médias: de dois grupos dependentes ou independentes, de dois grupos independentes com duas medidas repetidas (deltas), e com duas ou mais medidas repetidas. Todos os exemplos também são ilustrados e disponibilizados em vídeos no canal da Unidade de Bioestatística.

Following the series of articles aiming to guide users in using the PSS Health tool for research planning, this issue presents a step-by-step guide on how to calculate and what information is needed to compare means between 2 dependent or independent groups, 2 independent groups with 2 repeated measures (deltas), and 2 independent groups with 2 or more repeated measures. All examples are accompanied by figures and available in video on the Biostatistics Unit's channel.

PSS Health: como calcular tamanho de amostra para testar relações de variáveis com um desfecho binário / PSS Health: how to calculate the sample size to test variables relationships with a binary outcome

Dando continuidade à série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa, esta edição apresenta um passo a passo de como realizar o cálculo para tamanho de amostra e de quais informações são necessárias para testar relações estatísticas entre variáveis e um desfecho binário: comparação de proporções entre grupos independentes (dois ou mais), comparação de duas proporções dependentes e regressão logística. Todos os exemplos também são ilustrados e disponibilizados em vídeos no canal da Unidade de Bioestatística.

Following the series of articles that aim to guide the user in using the PSS Health tool for planning research, this issue presents a step-by-step guide on how to perform the sample size calculation and what information is needed to test statistical relationships between variables and a binary outcome: comparison of proportions between independent groups (two or more), comparison of two dependent proportions, and logistic regression. All examples are also illustrated and available in videos on the Biostatistics Unit's channel.

Portuguese validation of the Regret Intensity Scale (RIS-10) for measuring the intensity of regret associated with the provision of attention in health.

OBJECTIVES: The aim of the study was to adapt and validate the Regret Intensity Scale-10 (RIS-10) for Brazilian health professionals. METHODS: The validation study took place in two phases, in which the first was the translation of the instruments and the second, the field validation using psychometric properties validity and reliability of the scale with 341 professionals (doctors, nurses and physiotherapists) linked to hospitals. Validity was assessed using content validities (six judges evaluation), criteria (correlation with the Life Satisfaction Scale - SWLS and Self-Reporting Questionnaire 20 -SRQ-20) and construct (exploratory analysis using the rotation method Promax, based on the slope graph and the Kaiser criterion and confirmatory using the structural equation model) after applying the questionnaire to professionals.Reliability was measured by Cronbach's α coefficient and retest test over a maximum period of 30 days. Reproducibility was calculated by intraclass correlation. RESULTS: A total of 341 professionals participated, with an average age of 38.6 ± 9.2 years. The content validity index (CVI) was 1.00, for all items of the scale in the proportion of agreement of the judges. Exploratory factor analysis showed a satisfactory correlation (Kaiser-Meyer-Olkin = 0.88), suggesting a two-factor model, which comprises the main components of the emotion of regret (Factor I - emoticons, Factor II - feelings), accounting for 64% of the total variation of the first factor. In the confirmation, the index standardized root mean squared residual = 0.063 was close to the acceptable and other values were below. The scale correlated positively with SRQ-20 (p < 0.001) and negatively with SLWS (p = 0.003). Reliability showed (Cronbach's α = 0.863) and test-retest reliability showed lower values than expected. The Bland-Altman graph showed a mean bias of -1.5 with lower and upper limits of 15.8 to 12.8 respectively. CONCLUSIONS: The RIS-10 adapted for the population performed adequately in the psychometric properties evaluated for the assessment of the intensity of regret related to the provision of health care.

Evaluation of Polymorphisms in Toll-Like Receptor Genes as Biomarkers of the Response to Treatment of Erythema Nodosum Leprosum.

Erythema nodosum leprosum (ENL) is an inflammatory complication caused by a dysregulated immune response to Mycobacterium leprae. Some Toll-like receptors (TLRs) have been identified as capable of recognizing antigens from M. leprae, triggering a wide antimicrobial and inflammatory response. Genetic polymorphisms in these receptors could influence in the appearance of ENL as well as in its treatment. Thus, the objective of this work was to evaluate the association of genetic variants of TLRs genes with the response to treatment of ENL with thalidomide and prednisone. A total of 162 ENL patients were recruited from different regions of Brazil and clinical information was collected from their medical records. Genomic DNA was isolated from blood and saliva samples and genetic variants in TLR1 (rs4833095), TLR2 (rs3804099), TLR4 (rs1927914), and TLR6 (rs5743810) genes were genotyped by TaqMan real-time PCR system. In order to evaluate the variants' association with the dose of the medications used during the treatment, we applied the Generalized Estimating Equations (GEE) analysis. In the present sample, 123 (75.9%) patients were men and 86 (53.1%) were in treatment for leprosy during the ENL episode. We found an association between polymorphisms in TLR1/rs4833095, TLR2/rs3804099, TLR4/rs1927914, and TLR6/rs5783810 with the dose variation of thalidomide in a time-dependent manner, i.e., the association with the genetic variant and the dose of the drug was different depending on the moment of the treatment evaluated. In addition, we identified that the association of polymorphisms in TLR1/rs4833095, TLR2/rs3804099, and TLR6/rs5783810 with the dose variation of prednisone also were time-dependent. Despite these associations, in all the interactions found, the influence of genetic variants on dose variation was not clinically relevant for therapeutic changes. The results obtained in this study show that TLRs polymorphism might play a role in the response to ENL treatment, however, in this context, they could not be considered as useful biomarkers in the clinical setting due small differences in medication doses. A larger sample size with patients with a more genetic profile is fundamental in order to estimate the association of genetic variants with the treatment of ENL and their clinical significance.

PSS Health: como calcular tamanho de amostra para estimar média, proporção e correlação / PSS Health: how to calculate a sample size to estimate means, proportions, and correlations

A ferramenta PSS Health (Power and Sample Size for Health Researchers) foi desenvolvida com o propósito de facilitar o cálculo do tamanho amostral e do poder de testes de hipóteses para diferentes objetivos de estudo, usando interface amigável e terminologia comum à área da saúde. Este é o primeiro de uma série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa. Neste artigo, se ensina como utilizar o PSS Health quando o objetivo principal do estudo é estimar uma média, estimar uma proporção (prevalência ou incidência) ou estimar uma correlação. São disponibilizados vídeos demonstrando o uso da ferramenta em cada um dos contextos citados. (AU)

The PSS Health (Power and Sample Size for Health Researchers) tool was developed with the purpose of facilitating the calculation of sample size and power of hypothesis tests for different study objectives, based on a user-friendly interface and common health care terminology. This is the first in a series of articles intending to guide the user in how to use the PSS Health tool for planning a research project. This article teaches how to use PSS Health when the main objective of the study is to estimate means, proportions (prevalence or incidence), or correlations. Videos showing how to use the tool in each of the mentioned contexts are available. (AU)

The Brief Measure of Emotional Preoperative Stress (B-MEPS) as a new predictive tool for postoperative pain: A prospective observational cohort study.

BACKGROUND: Preoperative patients' vulnerabilities such as physical, social, and psychological are implicated in postoperative pain variability. Nevertheless, it is a challenge to analyze a patient's psychological profile in the preoperative period in a practical and consistent way. Thus, we sought to identify if high preoperative emotional stress, evaluated by the Brief Measure of Emotional Preoperative Stress (B-MEPS) scale is associated with higher postoperative pain levels and poor rehabilitation in patients submitted to intermediate or major surgery. Moreover, the possible neurobiological or neurophysiological mechanisms implicated in high preoperative emotional stress, evaluated through preoperative quantitative sensory pain tests and serum biomarkers BDNF and S100B were investigated. METHODS: We conducted a prospective, observational, cohort study of ASA 2 and 3 adult patients undergoing major urologic, gynecologic, proctologic and orthopedic surgeries from March 2017 to March 2018. B-MEPS and Central Sensitivity Inventory were evaluated preoperatively, followed by a sequence of experimental pain tests and serum biomarkers collection. Postoperative evaluation carried out within the first 48 hours after surgery comprehended pain at rest and movement-evoked pain, and the consumption of morphine. Quality-of-Recovery was also evaluated in the 3rd postoperative day. RESULTS: 23 (15%) out of 150 patients included in the study presented high emotional preoperative stress. Variables significantly related to preoperative stress were: previous psychiatric diagnosis and Central Sensitization Inventory result. Mean movement-evoked pain in the first 12 to 48 hours was 95-105% higher than pain at rest. A mixed model for repeated measures showed a sustainable effect of B-MEPS as a movement-evoked pain predictor. Previous pain, cancer surgery, and preoperative pressure pain tolerance were also independent predictors of postoperative pain. Moderate to severe postoperative movement-evoked pain was predictive of poor rehabilitation in 48 hours after surgery. CONCLUSION: We confirmed that a brief screening method of preoperative emotional states could detect individuals prone to experience severe postoperative pain. Specific interventions considering the stress level may be planned in the future to improve perioperative outcomes.

Power and sample size for health researchers: uma ferramenta para cálculo de tamanho amostral e poder do teste voltado a pesquisadores da área da saúde / Power and sample size for health researchers: a tool for calculating sample size and statistical power designed for health researchers

Nas próximas edições da seção de Bioestatística da revistaClinical & Biomedical Researchuma nova série de artigos será publicada abordando um assunto de grande importância ao planejar uma pesquisa: o tamanho de amostra mínimo necessário para atingir os objetivos do estudo. Nessa série será apresentado como calcular o tamanho de uma amostra usando a ferramenta PSSHealth(Power and Sample Size for Health Researchers), construído em linguagem R por meio do pacote Shiny, para diferentes tipos e objetivos de estudo, direcionado à pesquisadores da área da saúde, utilizando termos e conceitos comumente utilizados nesta área. Além disso, o pacote fornece uma sugestão de texto com as informações consideradas no cálculo, e como devem ser descritas, com a finalidade de minimizar problemas de interpretação por parte dos pesquisadores. Neste primeiro artigo será apresentada essa ferramenta desenvolvida pela Unidade de Bioestatística do Grupo de Pesquisa e Pós-Graduação do Hospital de Clínicas de Porto Alegre, que permite calcular não apenas o tamanho de amostra, mas também o poder de um teste de hipóteses. (AU)

In the next issues ofClinical and Biomedical Research, the Biostatistics section will introduce a new series of articles addressing a very important subject for research planning: the minimum sample size to achieve the aim of a study. This series will show how to calculate sample size using PSS Health (Power and Sample Size for Health Researchers). This tool was built using R language through the Shiny package. It can be used for different types of study and is designed for health researchers by using terms and concepts commonly used in this area. PSS Health also suggests a text with information considered in the calculation to minimize problems of interpretation by the researchers. In this first article, a general overview of PSS Health will be presented. This tool, which was developed by the Research and Graduate Group Biostatistics Unit of the Hospital de Clínicas de Porto Alegre, is useful not only to calculate sample size but also to determine power of a hypothesis test. (AU)

Equívocos estatísticos: perguntas que você sempre quis fazer, mas nunca teve coragem / Statistical misconceptions: questions you've always wanted to ask, but never dared

Este artigo visa elucidar algumas dúvidas enfrentadas ou equívocos estatísticos cometidos por pesquisadores de diversas áreas. São explanados os temas: "tradução não é validação", "análise fatorial exploratória ou confirmatória", "nem todo estudo com dois grupos tem delineamento caso-controle", "teste ou ajuste de Bonferroni", "tamanho de amostra para teste de hipóteses e/ou para intervalo de confiança", e "testes ou dados paramétricos". A abordagem é realizada em uma linguagem acessível ao público leigo, utilizando exemplos e sugerindo referências para aprofundar o conhecimento.(AU)

This article aims to answer some questions and elucidate statistical misconceptions of researchers from different fields. The following topics are addressed: "translation is not validation", "exploratory or confirmatory factor analysis", "not every study with two groups is a case-control study", "Bonferroni test or adjustment", "sample size for testing hypotheses and/or for confidence intervals", and "parametric data or tests". The topics are explained in lay terms, using examples and suggesting references to advance knowledge.(AU)

Modelagem estatística: perguntas que você sempre quis fazer, mas nunca teve coragem / Statistical modeling: questions you have always wanted to ask but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas dos pesquisadores do Hospital de Clínicas de Porto Alegre sobre estatística, este quarto artigo se propõe a responder às principais dúvidas levantadas sobre modelagem estatística. São discutidas questões referentes à classificação de variáveis em independentes e dependentes, diferenças entre correlação, associação e regressão, os principais tipos de regressão e quais etapas são necessárias na construção de modelos. Os conceitos são abordados numa linguagem acessível ao público leigo e diversas referências são sugeridas para os curiosos em relação ao tema. (AU)

Continuing the series of articles "Questions you have always wanted to ask but never had the courage to," which aims to answer the most common questions of researchers at Hospital de Clínicas de Porto Alegre regarding statistics and to suggest references for a better understanding, this forth article addresses the topic of statistical modeling. Questions about classification of variables as dependent or independent, differences between correlation, association and regression, types of regression and steps for statistical modeling are discussed. The concepts are explained in plain language for lay readers and several references are suggested for those curious about the topic. (AU)

Bioestatística e epidemiologia: perguntas que você sempre quis fazer, mas nunca teve coragem / Biostatistics and epidemiology: questions you always wanted to ask but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas estatísticas levantadas por pesquisadores da área da saúde, este terceiro artigo aborda o contexto epidemiológico. Neste contexto, foram diferenciadas as principais medidas como prevalência, incidência, Odds Ratio (OR), Risco Relativo (RR), Razão de Prevalência (RP) e Hazard Ratio (HR), foi esclarecido o uso de análises por intenção de tratar e análise por protocolo, e também discutidos alguns dos termos comumente utilizados e pouco compreendidos como tipo de amostra, nível de evidência, relevância clínica e estatística, entre outros. (AU)

Continuing the series of articles "Questions you always wanted to ask but never had the courage to," which aims to answer key statistical questions raised by health researchers and suggest references for a better understanding, this third article addresses the epidemiological context. In this context, important measures such as prevalence, incidence, odds ratio (OR), relative risk (RR), prevalence ratio (PR) and hazard ratio (HR) were differentiated; the use of intention-to-treat analysis and per-protocol analysis was clarified; and some terms commonly used and poorly understood were discussed, such as type of sample, level of evidence, clinical and statistical relevance, among others. (AU)

Teste de hipóteses: perguntas que você sempre quis fazer, mas nunca teve coragem / Hypothesis testing: questions you have always wanted to ask, but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas dos pesquisadores do Hospital de Clínicas de Porto Alegre sobre estatística, este segundo artigo se propõe a responder às principais dúvidas levantadas sobre Teste de Hipóteses. São discutidas questões referentes à metodologia de um teste de hipóteses na concepção clássica de Inferência Estatística, bem como tamanho de efeito, tipos de erros, valor de p e poder. Os conceitos são abordados numa linguagem acessível ao público leigo e diversas referências são sugeridas para os curiosos em relação ao tema. (AU)

Continuing the series of articles "Questions you have always wanted to ask, but never had the courage to", which aims to answer the most common questions of researchers at Hospital de Clínicas de Porto Alegre regarding statistics and to suggest references for a better understanding, this second article addresses the topic of hypothesis testing. The hypothesis testing method is discussed from a classical conception of statistical inference, including effect size, type of errors, p-value and power. The concepts are explained in plain language for lay readers and several references are suggested for those curious about the topic. (AU)

Estatística descritiva: perguntas que você sempre quis fazer, mas nunca teve coragem / Descriptive statistics: questions you have always wanted to ask, but never had the courage to

A revista do HCPA (Clinical & Biomedical Research) está reabrindo a seção de Bioestatística com o intuito de apresentar artigos explicativos, conceituais ou tutoriais, de modo a elucidar os leitores sobre os mais diversos temas estatísticos. Neste contexto, este artigo será o primeiro de uma série que tem como objetivo responder algumas das questões mais levantadas por pesquisadores da área da saúde. Começando pela Estatística Descritiva, alguns conceitos são esclarecidos e diversas referências são indicadas para o estudo do tema e para análises em SPSS ou R-project. (AU)

The HCPA journal (Clinical & Biomedical Research) is reopening its Biostatistics section with the aim of presenting readers with explanatory, conceptual or tutorial articles on a wide range of statistical topics. In this context, this is the first in a series of articles seeking to answer some of the questions raised by health researchers. Starting with descriptive statistics, some concepts are introduced and several references are indicated for those interested in studying the topic and performing analyses in SPSS or R-project. (AU)