Evaluación de la condición física en poblaciones de 6 a 14 años de México y Cuba

El presente estudio constituye un trabajo trascendente en el área del conocimiento de la condición física y representa el resultado de investigaciones realizadas en la República de Cuba y en los Estados Unidos Mexicanos como respuesta a la solicitud de ambos países. Fue diseñado estadísticamente, para representar datos oficiales y altamente confiables, con el objetivo de conocer el estado de la condición física de las dos naciones y valorar así, el efecto de los programas de Educación Física que se aplican. Se contó con el apoyo de las organizaciones deportivas y de cultura física al conformar los estudios, cuidadosamente tratados en el diseño de muestra, para ello se contó con un equipo de estadísticos especialistas que tuvieron a su cargo el procesamiento de la información. Los datos de este estudio se consideraron limitados para la publicación y una vez desclasificados se dan conocer. Se utilizaron iguales metodologías en su aplicación, lo que resulta una información valiosa para el perfeccionamiento de los planes y programas que en el campo de la Licenciatura en Cultura Física y se brinda una información que, en su comparación, llama a la reflexión de los especialistas de Educación Física, para continuar el perfeccionamiento de estas especialidades, en general.

O presente estudo constitui um trabalho transcendental na área do conhecimento da aptidão física e representa o resultado de uma pesquisa realizada na República de Cuba e nos Estados Unidos Mexicanos em resposta à solicitação de ambos os países. Foi projetado estatisticamente para representar dados oficiais e altamente confiáveis, com o objetivo de conhecer o estado da aptidão física em ambos os países e, assim, avaliar o efeito dos programas de Educação Física aplicados. As organizações esportivas e de cultura física foram apoiadas na elaboração dos estudos, cuidadosamente tratadas no desenho da amostra, com a ajuda de uma equipe de estatísticos especializados que foram responsáveis pelo processamento das informações. Os dados deste estudo foram considerados limitados para publicação e, uma vez desclassificados, são tornados públicos. Foram utilizadas as mesmas metodologias em sua aplicação, o que resulta em informações valiosas para o aprimoramento dos planos e programas no campo da cultura física e fornece informações que, em sua comparação, exigem a reflexão dos especialistas em educação física, a fim de continuar o aprimoramento dessas especialidades em geral.

The present study constitutes a transcendent work in the area of knowledge of physical condition and represents the result of research carried out in the Republic of Cuba and in the United Mexican States in response to the request of both countries. It was designed statistically, to represent official and highly reliable data, with the objective of knowing the state of the physical condition of the two nations and thus evaluating the effect of the Physical Education programs that are applied. It was had the support of sports and physical culture organizations when forming the studies, carefully treated in the sample design, for this it was had a team of specialist statisticians who were in charge of processing the information. The data from this study was considered limited for publication and will be released once declassified. The same methodologies were used in its application, which is valuable information for the improvement of plans and programs in the field of the Bachelor's Degree in Physical Culture and information is provided that, in comparison, calls for reflection by specialists. of Physical Education, to continue the improvement of these specialties, in general.

Las falacias de la p y significación estadística / The fallacies of P and statical significance

Resumen ANTECEDENTES: El valor de p es el método más empleado para estimar la significación estadística de cualquier hallazgo; sin embargo, en los últimos años se ha intensificado su debate al respecto, debido a la baja credibilidad y reproducibilidad de diversos estudios. OBJETIVO: Describir el estado actual del concepto del valor de p y la significación estadística (prueba de significación de la hipótesis nula [por sus siglas en inglés: Null Hypothesis Significance Testing: NHST]), especificar los problemas más importantes y puntualizar las soluciones propuestas para la mejor utilización de los conceptos. METODOLOGÍA: Se llevó a cabo la búsqueda bibliográfica en MEDLINE y Google Scholar, con los términos: "NHST", "Statistical significance; P value" en idioma inglés y español, de 2018-2019, limitándose a la selección de artículos publicados entre 2005 y 2019, mediante la revisión de tipo narrativo con búsqueda manual; sobre todo estudios de metodología. RESULTADOS: La búsqueda global reportó 1411 artículos: 875 de PubMed y 536 de Google Scholar. Se excluyeron 817 por duplicación, 155 sin acceso completo y 414 ensayos clínicos (sin metodología estadística); los 25 restantes fueron el motivo del análisis. CONCLUSIONES: El concepto del valor de p no es simple, tiene varias falacias y malas interpretaciones que deben considerarse para evitarlas en lo posible. Se recomienda no usar el término "estadísticamente significativo" o "significativo", sustituir el umbral de 0.05 por 0.005, informar valores de p precisos y con IC95%, riesgo relativo, razón de momios, tamaño del efecto o potencia y métodos bayesianos.

Abstract BACKGROUND: The P value is the most widely used method of estimating the statistical significance of any finding, however, in recent years the debate over the P value has been increasingly intensified due to the low credibility and reproducibility of many studies. OBJECTIVE: To describe the current state of the concept of the value of P and the statistical significance (Null Hypothesis Significance Testing (NHST), specify the most important problems and point out the solutions proposed in the literature for their best use. METHODOLOGY: Search in MEDLINE and Google Scholar, with the terms: "NHST", "Statistical significance; P value "in English and Spanish, carried out from 2018-2019, limited to articles published from 2005 to 2019, and a narrative-type review with manual search. Articles on methodology were preferably selected. RESULTS: The global search yielded 1411 articles, 875 from PubMed and 536 from Google Scholar. 817 were excluded by duplication, 155 without full access, 414 from clinical trials, without statistical methodology. The 25 selected articles were the reason for the analysis. CONCLUSIONS: The concept of the value of P is not simple, and it has several fallacies and misinterpretations that must be taken into account to avoid them as much as possible. Recommendations: Do not use "statistically significant" or "significant", replace the threshold of 0.05 with 0.005, report accurate P values with 95% CI, relative risk, odds ratio, effect size or power, and Bayesian methods.

Uso de pruebas estadísticas inferenciales en la Revista Cubana de Medicina Militar / Use of Inferential Statistical Tests in the Cuban Journal of Military Medicine

Introducción: desde hace años, existe un debate sobre el uso de las pruebas estadísticas inferenciales en los reportes de resultados de investigación, se destaca la crítica al empleo de las pruebas de significación estadística y sus limitaciones. Objetivos: determinar la frecuencia de empleo de las pruebas de significación estadística (PSE) e intervalos de confianza (IC) por tipos de estudio publicado, cómo se reflejan los resultados de estas, la influencia del tamaño de la muestra, así comosu vinculación con las conclusiones. Resultados: en el periodo 2010 - 2015 de 150 artículos originales, 98 por ciento fueron descriptivos o explicativos y de ellos, el 95 por ciento emplea las PSE, solas o con IC. Predomina el uso de las PSE solas (69 por ciento de los trabajos). En el 25 por ciento se explica la selección del nivel de significación utilizado y el 53 por ciento de los estudios reflejan las cifras exactas de las pruebas realizadas. Solo el 15 por ciento menciona la influencia del tamaño de la muestra en relación con los resultados de las pruebas estadísticas. En las conclusiones, el 86 por ciento de los artículos se refieren adecuadamente a los objetivos del estudio. Conclusiones: predomina el uso de las PSE e IC, fundamentalmente de las PSE, más de la mitad de los trabajos mencionan los resultados precisos de las pruebas, la mayoría no argumenta la relación de estos resultados con el tamaño de la muestra y los autores elaboran las conclusiones de acuerdo con los objetivos planteados en el estudio(AU)

Introduction: For years there has been a debate about the use of inferential statistical tests in the reports of research results, highlighting the criticism to the use of tests of statistical significance and its limitations. Objectives: To determine the frequency of use of statistical significance tests (SST) and confidence intervals (CI) by published study types, how the results are reported, and the influence of sample size, as well as their relationship with the conclusions. Results: In the period 2010-2015 of 150 original articles, 98 percent were descriptive or explanatory and of them, 95 percent used SST alone or with CI. The use of SST alone (69 percent of the articles) predominates. In 25 percent the significance level selection is explained and 53 percent of the studies reflect the exact figures of the tests performed. Only 15 percent mentions the influence of sample size on the results of statistical tests. In the conclusions, 86 percent of the articles refer adequately to the objectives of the study. Conclusions: SST and CI use predominate, mainly SST, more than half of the studies mention the precise results of the tests, most do not argue the relation of these results to the sample size and the authors elaborate the conclusions in accordance with the objectives set out in the study(AU)

A Review on the Use of Effect Size in Nursing Research

PURPOSE: The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. METHODS: For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. RESULTS: Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. CONCLUSION: It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

Role of Statistics in Multidisciplinary Research – With Reference to Psychological Research.

Statistics is the study of the collection, organization, analysis, interpretation and presentation of data. It deals with all aspects of data. It is usually noticed that some routine words are given technical meanings in statistical parlance (e.g. “mean,” “normal,” “significance,” “effect,” and “power”). It is essential to resist the temptation of conflating their technical meanings. A failure to do so may have a lot to do with the ready acceptance of the “effect size” and “power” arguments in recent years. As, statistics is used (i) to describe data in terms of the shape, central tendency, and dispersion of their simple frequency distribution, and (ii) to make decisions about the properties of the statistical populations on the basis of sample statistics. Statistical decisions are made with reference to a body of theoretical distributions: the distributions of various test statistics that are in turn derived from the appropriate sample statistics. In every case, the calculated test statistic is compared to the theoretical distribution, which is made up of an infinite number of tokens of the test statistic in question. Hence, the “in the long run” caution should be made explicit in every probabilistic statement based on inferential statistics (e.g. “the result is significant at the 0.05 level in the long run”).Despite the recent movement to discourage psychologists from conducting significance tests, significance tests can be defended by (i) clarifying some concepts, (ii) examining the role of statistics in empirical research, and (iii) showing that the sampling distribution of the test statistic is both the bridge between descriptive and inferential statistics and the probability foundation of significance tests. The present paper discusses the critical issues of statistics in psychological research.

Interpreting “statistical hypothesis testing” results in clinical research.

Difference between “Clinical Signifi cance and Statistical Signifi cance” should be kept in mind while interpreting “statistical hypothesis testing” results in clinical research. This fact is already known to many but again pointed out here as philosophy of “statistical hypothesis testing” is sometimes unnecessarily criticized mainly due to failure in considering such distinction. Randomized controlled trials are also wrongly criticized similarly. Some scientifi c method may not be applicable in some peculiar/particular situation does not mean that the method is useless. Also remember that “statistical hypothesis testing” is not for decision making and the fi eld of “decision analysis” is very much an integral part of science of statistics. It is not correct to say that “confi dence intervals have nothing to do with confi dence” unless one understands meaning of the word “confi dence” as used in context of confi dence interval. Interpretation of the results of every study should always consider all possible alternative explanations like chance, bias, and confounding. Statistical tests in inferential statistics are, in general, designed to answer the question “How likely is the difference found in random sample(s) is due to chance” and therefore limitation of relying only on statistical signifi cance in making clinical decisions should be avoided.

Designs for research of High Dilutons in animal models: an update / Designs for research of High Dilutons in animal models: an update

This article discusses the series of tests on animal experimental models carried out by our group to evaluate the effect of homeopathic preparations selected according to traditional criteria of pathogenetic similarity. Our overall experience indicates that it is not difficult to carry out experimental studies assaying homeopathic medicines in randomized placebo-controlled tests returning statistically analyzable results. The basic requirement for this purpose is to select validated experimental models. The simplest and most reliable ones are the ones arising from common daily clinical practice or those taken from classical pharmacological studies modified as to fit the goals of a homeopathic assay. By proceeding in this way it will be possible to build a sound body of evidence for the biological effects of high dilutions [1].

Designs for research of high dilutons in animal models: an update

This article discusses the series of tests on animal experimental models carried out by our group to evaluate the effect of homeopathic preparations selected according to traditional criteria of pathogenetic similarity. Our overall experience indicates that it is not difficult to carry out experimental studies assaying homeopathic medicines in randomized placebo-controlled tests returning statistically analyzable results. The basic requirement for this purpose is to select validated experimental models. The simplest and most reliable ones are the ones arising from common daily clinical practice or those taken from classical pharmacological studies modified as to fit the goals of a homeopathic assay. By proceeding in this way it will be possible to build a sound body of evidence for the biological effects of high dilutions

Este artigo discute a série de experimentos em modelos animais realizada por nosso grupo para avaliar o efeito de preparações homeopáticas escolhidas de acordo com o critério tradicional de similitude patogenêtica. Nossa experiência global indica que não é difícil realizar estudos experimentais com medicamentos homeopáticos em ensaios randomizados controlados com placebo que forneçam resultados analisáveis estatisticamente. O requisito básico para este propósito é escolher modelos experimentais validados. Os mais simples e mais confiáveis são aqueles derivados da prática clínica cotidiana assim como aqueles tomados de estudos farmacológicos clássicos modificados de modo a se corresponderem com os objetivos de um experimento homeopático. Procedendo desse modo, será possível construir um corpo sólido de evidência a favor dos efeitos biológicos das altas diluições.

Este artículo discute la serie de experimentos en modelos animales realizada por nuestro grupo, con el propósito de evaluar el efecto de preparados homeopáticos elegidos según el criterio tradicional de similitud patogenética. Nuestra experiencia global indica que no es difícil llevar a cabo estudios experimentales con medicamentos homeopáticos en ensayos randomizados controlados con placebo que resulten en datos pasibles de análisis estadística. El requisito fundamental para este fin es elegir modelos experimentales validados. Los más simples y confiables son aquellos derivados de la praxis clínica cotidiana así como los tomados de estudios farmacológicos clásicos, modificados para cumplir los objetivos de un experimento homeopático. Actuando de esta manera, será posible construir un corpus sólido de evidencia favorable a los efectos biológicos de las altas diluciones.

Diferencias estadísticamente significativas vs. relevancia clínica / Statistically significant differences vs. clinical relevance

En este artículo se hace una revisión de los peligros que conlleva el uso del término significación estadística y la importancia de analizar la magnitud de las diferencias que se encuentran al final de los estudios de investigación. Para ello, se hace una presentación del concepto de significación estadística, los errores tipo I y tipo II y del concepto de relevancia clínica. Asimismo, se discute el uso de otro tipo de medidas como son los intervalos de confianza. Finalmente se presentan, a manera de conclusión, dos ideas básicas: la primera tiene que ver con la importancia de identificar la prueba estadística que mejor se ajuste al estudio para rechazar o aceptar la hipótesis nula y la necesidad de establecer si la magnitud de las diferencias obtenidas tienen alguna importancia desde el punto de vista clínico.

This article reviews the potential hazards of using the term ‘statistical significance’ as well as the mportance of analyzing size effects of differences ound at the research reports articles. Thus, this rticle presents a review of concepts like statistical ignificance, type I and type II errors, and clinical elevance. Similarly, a discussion regarding other tatistical measures, such as confidence intervals, s presented. At last, two ideas are presented as ain conclusions of this analysis: the first délas ith the importance of identifying the best tatistical tests to either accept or reject the null ypothesis in a research study. The second idea ighlights the need of clarifying the clinical elevance of differences’ size effect.

Uma visão evidente da prática baseada em evidências na medicina perinatal: ausência de evidência não é evidência de ausência / An evident view of evidence-based pratice in perinatal medicine: absence of evidence is not evidence of absence

OBJETIVO: Proporcionar elementos valiosos e um pouco de humor nesta chamada era da "prática baseada em evidências" com o objetivo de ajudar os clínicos a fazer escolhas melhores no cuidado que eles provêem com base em evidências, e não simples ou exclusivamente com base em um ensaio clínico randomizado (ECR) ou meta-análise (o que pode não ser evidência). FONTE DOS DADOS: Livros e artigos com revisão por pares são citados e listados na bibliografia. Evidências de vida, aprendizado através de nossos próprios erros e muitos outros fatos evidentes que sustentam esta revisão não são citados. SÍNTESE DOS DADOS: 1) "Ausência de evidência não é evidência de ausência" e "falta de evidência de efeito não significa evidência de nenhum efeito". 2) Os ECR com resultado "negativo" e aqueles com resultado "positivo", mas sem os resultados importantes, muitas vezes não podem concluir o que concluem. 3) Os ensaios clínicos não-randomizados e os estudos práticos podem ser importantes. 4) A pesquisa em busca de provas é diferente da pesquisa em busca de aperfeiçoamento. 5) A escolha clínica deve avaliar os efeitos nos desfechos importantes para os pacientes e seus pais. 6) A quantificação de desfechos adversos, do número necessário para causar dano e do número necessário para tratamento não é assim tão simples. CONCLUSÕES: Desafios importantes inerentes à pesquisa em serviços de saúde devem ser correlacionados a possíveis aplicações clínicas usando ferramentas que permitam uma "visão mais clara da prática baseada em evidências" na medicina perinatal, lembrando que a ausência de evidência não é evidência de ausência.

OBJECTIVE: To provide valuable elements and some humor in this so-called era of "evidence-based practice" with the aim of helping clinicians make better choices in the care they deliver based on evidence, not simply or exclusively based on a randomized clinical trial (RCT) or meta-analysis (which may not be evidence). SOURCES: Books and peer-reviewed articles are quoted and listed in the bibliography. Evidence of life, learning from our own mistakes and many other evident facts that support this review are not quoted. SUMMARY OF THE FINDINGS: 1) "Absence of evidence is not evidence of absence" and "lack of evidence of effect does not mean evidence of no effect". 2) RCTs with "negative" results and those with "positive" results, but without outcomes that matter, often cannot conclude what they conclude. 3) Non-randomized clinical trials and practical trials may be important. 4) Research to prove is different than research to improve. 5) Clinical choice must assess effects on outcomes that matter to patients and their parents. 6) Quantifying adverse outcomes, number needed to damage and to treat is not that simple. CONCLUSIONS: Significant challenges inherent to health service research must be correlated to possible clinical applications using tools to have a more "evident view of evidence-based practice" in perinatal medicine, recalling that absence of evidence is not evidence of absence.

Notes on the Interpretation of the Results of Statistical Tests in the Journal of the Society / 日本東洋医学雑誌

Statistical tests are commonly reported in papers published in the journal. The interpretation of the statistical results, however, is not necessarily proper, which may invalidate the conclusions. This paper describes the issues regarding the interpretation of the results of statistical tests in the journal, and refers to the proper use of statistical test and estimation.