<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2304-0106</journal-id>
<journal-title><![CDATA[Anales de la Academia de Ciencias de Cuba]]></journal-title>
<abbrev-journal-title><![CDATA[Anales de la ACC]]></abbrev-journal-title>
<issn>2304-0106</issn>
<publisher>
<publisher-name><![CDATA[Academia de Ciencias de Cuba]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2304-01062024000300020</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Nueva metodología de análisis estadístico en la investigación de problemas de salud]]></article-title>
<article-title xml:lang="en"><![CDATA[New statistical analysis methodology in health problems research]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Sagaró del Campo]]></surname>
<given-names><![CDATA[Nelsa María]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Matamoros]]></surname>
<given-names><![CDATA[Larisa Zamora]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Ciencias Médicas Facultad Medicina 1 ]]></institution>
<addr-line><![CDATA[ Santiago de Cuba]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Oriente Facultad de Ciencias Naturales y Exactas ]]></institution>
<addr-line><![CDATA[ Santiago de Cuba]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2024</year>
</pub-date>
<volume>14</volume>
<numero>3</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S2304-01062024000300020&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S2304-01062024000300020&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S2304-01062024000300020&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN  Introducción:  Las técnicas estadísticas tradicionales con que se estudia esta causalidad parten del supuesto de la linealidad, aun cuando se conoce de la complejidad de los procesos de salud enfermedad.  Objetivo:  Describir los fundamentos, diseño y validación de una metodología para la aplicación del análisis estadístico implicativo en las investigaciones médicas de causalidad y evaluar su efectividad en la solución de un problema de salud concreto.  Métodos:  El diseño de la metodología propuesta se basó en la articulación de procedimientos elaborados a partir de las limitaciones identificadas. La validación se llevó a cabo mediante 3 estudios. El primero para la validación de criterio mediante la comparación con la regresión logística binaria. El segundo para la validación de contenido permitió verificar la correspondencia de las reglas obtenidas con lo planteado en la literatura, además, se clasificaron la mayoría de dichas reglas, según el juicio de los expertos, como acertadas, y se emitió una opinión favorable sobre la metodología, por los usuarios potenciales de la misma. El tercer estudio fue un metaanálisis que resumió los indicadores obtenidos en los estudios que aplicaron la metodología, que también corroboró su buen desempeño.  Resultados:  Al evaluar la efectividad de la metodología se logró identificar los factores pronósticos de mortalidad por cáncer de mama en la provincia Santiago de Cuba.  Conclusiones:  La metodología constituye una nueva perspectiva de análisis de datos e interpretación de resultados, que contribuye a perfeccionar la investigación de causalidad en medicina, por tanto, se recomienda su empleo en estos estudios.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT  Introduction:  Traditional statistical techniques used to study causality are based on the assumption of linearity, even though the complexity of health-disease processes is known.  Objective:  To describe the foundations, design and validation of a methodology for the application of implicative statistical analysis in medical causality research and to evaluate its effectiveness in solving a specific health problem.  Methods:  The design of the proposed methodology was based on the articulation of procedures developed from previously identified limitations. Validation was carried out through 3 studies. The first one for criterion corroboration through comparison with binary logistic regression. The second one for content validation allowed verifying the correspondence of the rules obtained with what was proposed in the literature. In addition, most of these rules were classified, according to the experts criteria, as correct, and a favorable opinion was issued on the methodology by its potential users. The third study was a meta-analysis that summarized the indicators obtained in the studies that applied the methodology, which also corroborated its good performance.  Results:  By evaluating the effectiveness of the methodology, it was possible to identify the prognostic factors of mortality due to breast cancer in the province of Santiago de Cuba.  Conclusions:  The methodology constitutes a new perspective of data analysis and interpretation of results, which contributes to improving causality research in medicine, therefore, its use in these studies is recommended.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[metodología]]></kwd>
<kwd lng="es"><![CDATA[estadística]]></kwd>
<kwd lng="es"><![CDATA[análisis estadístico implicativo]]></kwd>
<kwd lng="es"><![CDATA[investigaciones médicas]]></kwd>
<kwd lng="es"><![CDATA[causalidad]]></kwd>
<kwd lng="es"><![CDATA[interpretación de resultados.]]></kwd>
<kwd lng="en"><![CDATA[methodology]]></kwd>
<kwd lng="en"><![CDATA[statistics]]></kwd>
<kwd lng="en"><![CDATA[implicative statistical analysis]]></kwd>
<kwd lng="en"><![CDATA[medical research]]></kwd>
<kwd lng="en"><![CDATA[causality]]></kwd>
<kwd lng="en"><![CDATA[interpretation of results.]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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