Differential item functioning in the beck Depression Inventory

INTRODUCTION:There are several studies showing the presence of Differential Item Functioning (DIF) in some items of the Beck Depression Inventory (BDI), when comparing men and women. The presence of a large number of items with DIF in BDI is a severe threat to the validity of measurement of the intensity of depressive symptoms obtained by Item Response Theory (IRT) and to the conclusions based on the scores derived from the items with or without DIF.\ud OBJECTIVE:The objectives of this study were to identify these items from the BDI, adjust the IRT model for embarrassing items (model 2), which accommodates items with the presence of DIF, and compare these results with the fit of the traditional two-parameter logistic IRT model (model 1).\ud METHODS: The results obtained with the both models were compared.\ud RESULTS: Items with DIF were: sadness, feeling of failure, dissatisfaction, guilty, punishment, crying, fatigability and loss of libido. The results of the adjustment of the two models are similar in discrimination, gravity (except for items with DIF), and in the calculation of scores for individuals. Nevertheless, model 2 is beneficial because it shows the differences in gravity of depressive symptoms for groups evaluated, thus providing more information to the researcher on the study population.\ud CONCLUSION:This model, which has a broader scope in terms of target population, may be a good alternative to the identification and follow-up of individuals with potential depression

Elaboration and validation of a measure to evaluate the knowledge of primary care physicians in Brazil about nutritional recommendation for hypertension control

Introdução: Médicos da Atenção Primária à Saúde têm papel primordial no aconselhamento nutricional para reduzir a morbidade e a mortalidade relacionadas à hipertensão. A literatura é escassa em instrumentos validados para o Brasil que avaliam o conhecimento com base em evidências desses profissionais. Objetivo: Elaborar uma medida para avaliar o nível de conhecimento de médicos de atenção primária do Brasil sobre recomendação nutricional para o controle de hipertensão arterial. Método: Utilizou-se de um instrumento validado para a língua inglesa como base para elaboração da medida, a qual foi testada de acordo com os fundamentos da Teoria de Resposta ao Item. A dimensionalidade do questionário foi realizada na matriz de correlação policórica. Para estimar os parâmetros dos itens, foi utilizado o modelo logístico de dois parâmetros (discriminação e dificuldade). Resultados: A maioria dos itens foi considerada fácil, e o poder discriminativo variou entre valores altos, moderados e baixos. A ausência de itens difíceis contribuiu para a imprecisão da medida entre aqueles com níveis superiores de conhecimento. Conclusão: Os resultados mostram uma medida que mensura com melhor precisão médicos com baixo nível de conhecimento, sendo uma ferramenta útil para identificar profissionais que precisam melhorar seu conhecimento nutricional.Background Primary health care physicians play a leading role in nutritional counseling to reduce hypertension related to morbidity and mortality. The literature is scarce on instruments validated for Brazil that evaluate the evidence based on knowledge of these professionals. Objective To elaborate a measure to evaluate the level of knowledge about nutritional recommendation for the control of hypertension for primary care physicians in Brazil. Method A validated instrument for the English language was used as the basis for the questionnaire elaboration, which was tested according to the fundamentals of the Item Response Theory. The dimensionality of the questionnaire was performed on the polychoric correlation matrix. For the estimation of the parameters of the items, the two Parameters Logistic Model (discrimination and difficulty) was used. Results Most of the items were considered easy, the discriminative power varied between high, moderate and low values. The absence of difficult items contributed to the imprecision of the measure among those with higher levels of knowledge. Conclusion The results show a measure that accurately measures physicians with a low level of knowledge, being a useful tool to identify professionals who need to improve their nutritional knowledge

Association between mistreatment of women during childbirth and symptoms suggestive of postpartum depression

Background: Postpartum depression is a common condition in the pregnancy and postpartum cycle. The development of this condition is multifactorial and can be influenced by previous traumas. This study sought to verify whether there is an association between having been exposed to mistreatment during childbirth and presenting symptoms suggestive of postpartum depression. Methods: This is a cross-sectional study, with the inclusion of 287 women without complications in childbirth, randomly selected from two maternity hospitals of Porto Alegre, southern Brazil, in 2016. Four weeks after delivery, the postpartum women answered a face-to-face interview about socioeconomic aspects, obstetric history, health history, and childbirth experience (practices and interventions applied) and completed the Edinburgh Postnatal Depression Scale (EPDS). From the perception of women regarding the practices performed in the context of childbirth care, a composite variable was created, using item response theory, to measure the level of mistreatment during childbirth. The items that made up this variable were: absence of a companion during delivery, feeling insecure and not welcome, lack of privacy, lack of skin-to-skin contact after delivery, not having understood the information shared with them, and not having felt comfortable to ask questions and make decisions about their care. To define symptoms suggestive of postpartum depression, reflecting on increased probability of this condition, the EPDS score was set at ≥ 8. Poisson Regression with robust variance estimation was used for modeling. Results: Women who experienced mistreatment during childbirth had a higher prevalence of symptoms suggestive of postpartum depression (PR 1.55 95% CI 1.07–2.25), as well as those with a history of mental health problems (PR 1.69 95% CI 1.16–2.47), while higher socioeconomic status (A and B) had an inverse association (PR 0.53 95% CI 0.33–0.83). Conclusions: Symptoms suggestive of postpartum depression seem to be more prevalent in women who have suffered mistreatment during childbirth, of low socioeconomic status, and with a history of mental health problems. Thus, qualifying care for women during pregnancy, childbirth and postpartum and reducing social inequalities are challenges to be faced in order to eliminate mistreatment during childbirth and reduce the occurrence of postpartum depression

BDNF and serum S100B levels according the spectrum of structural pathology in chronic pain patients

Central sensitivity syndrome (CSS) consists of adaptive pathophysiological changes associated with neuroplasticity in some chronic pain disorders. It could be grouped in two main conceptual conditions: one includes those chronic pain patients without overt structural pathology such as fibromyalgia, and the other subgroup includes conditions with recognizable structural abnormalities, both somatic (osteoarthritis) and visceral (endometriosis). In order to understand the role of neuromodulators in CCS we aim to determine whether brain-derived neurotrophic factor (BDNF) and S100B are associated to specific chronic pain disorders. Serum BDNF and S100B were measured in chronic pain women with different diagnosis: 88 with osteoarthritis, 36 with endometriosis, 117 with fibromyalgia, 33 with chronic tension type headache and in 41 healthy controls. ANCOVA analysis followed by heteroscedasticity-consistent covariance matrix was performed to evaluate BDNF and S100B levels, adjusted for depression severity, pain levels and use of analgesics according different pathologies. Serum BDNF concentrations were higher and not different in patients with fibromyalgia and headache, the CSS group without structural pathology. In contrast, the concentrations of S100B were higher in patients with osteoarthritis and endometriosis, in comparison to controls, fibromyalgia and tensional headache patients. This study supports the hypothesis that BDNF and S100B neuromodulators present different serum levels according to the background disease associated to the chronic pain. These have the potential to be studied as markers of active disease or treatment evolution

Bioestatística e Epidemiologia: Perguntas que você sempre quis fazer, mas nunca teve coragem

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.Palavras-chave: Delineamentos; nível de evidência; medidas de associação; ensaios clínicos; análise por intenção de tratar; análise por protocolo; amostra aleatória; amostra por conveniência; randomização em bloco

PSS Health : como calcular tamanho de amostra para estimar média, proporção e correlação

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

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

The impact of the incorporation of a feasible postoperative mortality model at the Post-Anaesthestic Care Unit (PACU) on postoperative clinical deterioration : a pragmatic trial with 5,353 patients

Background: Practical use of risk predictive tools and the assessment of their impact on outcome reduction is still a challenge. This pragmatic study of quality improvement (QI) describes the preoperative adoption of a customised postoperative death probability model (SAMPE model) and the evaluation of the impact of a Postoperative Anaesthetic Care Unit (PACU) pathway on the clinical deterioration of high-risk surgical patients. Methods: A prospective cohort of 2,533 surgical patients compared with 2,820 historical controls after the adoption of a quality improvement (QI) intervention. We carried out quick postoperative high-risk pathways at PACU when the probability of postoperative death exceeded 5%. As outcome measures, we used the number of rapid response team (RRT) calls within 7 and 30 postoperative days, in-hospital mortality, and non-planned Intensive Care Unit (ICU) admission. Results: Not only did the QI succeed in the implementation of a customised risk stratification model, but it also diminished the postoperative deterioration evaluated by RRT calls on very high-risk patients within 30 postoperative days (from 23% before to 14% after the intervention, p = 0.05). We achieved no survival benefits or reduction of non-planned ICU. The small group of high-risk patients (13% of the total) accounted for the highest proportion of RRT calls and postoperative death. Conclusion: Employing a risk predictive tool to guide immediate postoperative care may influence postoperative deterioration. It encouraged the design of pragmatic trials focused on feasible, low-technology, and long-term interventions that can be adapted to diverse health systems, especially those that demand more accurate decision making and ask for full engagement in the control of postoperative morbi-mortality

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.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