Application of biostatistical methods in health sciences research: scope review of classical and contemporary scientific and methodological literature. - Villavicencio Cedeño, Lissette Beatriz; Azúa Menéndez, Marieta del Jesús; Chilán Santana, Caleb Isaac; Batista Garcet, Yoiler (Spanish Journal of Medical Education, 2026)
Introduction: Despite the importance of biostatistics in health sciences research, numerous shortcomings persist in the biomedical literature. Objective: To analyze the application of biostatistical methods in health sciences research through a comprehensive, systematic review of recent scientific literature, with an emphasis on inferential foundations, application problems, and contemporary methodological alternatives. Methods: A comprehensive, systematic review was conducted, guided by PRISMA-ScR. The search was primarily performed in Scopus and Web of Science, with supplementary searches in PubMed, ERIC, CINAHL, and Google Scholar. Search terms related to biostatistics, statistical methods, medical research, epidemiology, public health, and clinical research were used. 245 records were identified; after removing duplicates and applying eligibility criteria, 32 studies were included. The information was organized into three categories: theoretical foundations of statistical inference, problems and limitations in the application of biostatistical methods, and contemporary methodological approaches. Results: The reviewed studies showed a predominance of the frequentist approach, especially regarding the use of hypothesis tests and the p-value. Recurring errors were identified in the interpretation of statistical significance, inappropriate use of tests, poor reporting of assumptions, inadequate handling of multiple comparisons, limited consideration of confounding variables, and insufficient integration of clinically relevant data. Emerging proposals were also observed, focusing on the use of confidence intervals, effect sizes, multivariate models, Bayesian analyses, metascience, open science practices, and improvements in statistical reporting. Conclusions: Biostatistics remains a crucial element for the quality of health sciences research; however, its practical application presents significant gaps. Overcoming these limitations requires strengthening statistical training, promoting a more critical inferential interpretation, abandoning the exclusive dependence on the p-value, integrating measures of magnitude and precision, improving the transparency of reporting, and fostering complementary analytical approaches oriented towards the reproducibility of evidence.