Procrastinación académica y estrés académico en estudiantes de secundaria de una institución educativa privada del distrito Ventanilla - Callao, 2021

El propósito principal de esta investigación fue determinar la relación entre la procrastinación académica y el estrés académico en estudiantes de secundaria de una Institución Educativa Privada del distrito de Ventanilla – Callao, 2021. La muestra estuvo compuesta por 262 estudiantes del nivel secundario de ambos sexos, seleccionados mediante un muestreo no probabilístico intencional, el tipo de estudio fue descriptivo comparativo, con un diseño no experimental de corte transversal y con un enfoque cuantitativo. Los resultados evidenciaron una correlación positiva y estadísticamente significativa entre la procrastinación académica y el estrés académico, además de un tamaño de efecto grande (Rho=.538; p =.00; r²=.29). Por otro lado, no se hallaron diferencias estadísticamente significativas para la procrastinación académica, según sexo (p>.05) y grado escolar (p>.05). Asimismo, no se hallaron diferencias estadísticamente significativas para el estrés académico según grado escolar (p>.05), pero si hubo diferencias estadísticamente significativas según sexo (p<.05), donde las mujeres presentaron mayores niveles de estrés. En relación a los niveles encontrados, la procrastinación académica tuvo una prevalencia del 73.3% en el nivel muy alto. En cuanto al estrés académico, las prevalencias también se posicionaron en el nivel muy alto, donde las mujeres alcanzaron un 48.8% y los hombres un 32.8%

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press