The study was carried out with the objective of comparing and analyzing psychosocial factors such as stress, depression and anxiety in undergraduate university students from Loreto, Ancash, Moquegua and Puno during confinement by Covid-19, Peru. The study was based on a non-experimental, quantitative-descriptive, cross-sectional and correlational design with non-probability and intentional sampling, an online survey was applied to a sample of 665 undergraduate students using validated instruments such as the List of Indicators of Vulnerability to stress, the Zung Depression Scale, and the Hamilton Anxiety Scale. The study reports vulnerability to stress in 50.8%, 46.3%, 36.4% and 37.5% in Loreto, Ancash, Moquegua and Puno. The prevalence of depression was 100.0%, 97.6%, 96.9% and 95.2% between mild, moderate and severe; likewise, 100.0% presented anxiety symptoms. It was concluded that a situation of obligatory social confinement is directly related to the presence of stress, depression and anxiety, particularly in undergraduate university students, affecting a greater proportion of women; of these between 19 and 22 years, and with a higher incidence in regions with a greater number of confirmed cases; where insomnia, worry and irritability are the most significant symptoms.
The study was carried out in the sanitary landfill of Puno, from December 2017 to January 2018 and aimed to determine the relationship between working conditions and the risk factors faced by waste pickers from the Cancharani sanitary landfill, Puno-Peru. The methodology applied corresponds to the transversal correlational design, with a census-type study sample. The statistical tests applied were the Spearman correlation test and the Mann Whitney U test. The results indicate that there is no correlation (r = 0.102; α = 0.01), between working conditions and the risk factors that workers face. With regard to gender, it was found that women admit the inadequate working conditions in which they work (U = 60.00), considering that they are the same who manipulate solid waste from dangerous places such as pharmacies and others without optimal protection. On the other hand, men are the ones who perceive more the risk factors they face (U = 50.00) and are the ones who handle the waste coming from the homes. According to the age ranges, it was obtained that those aged 18 to 29 identify and perceive the inadequate working conditions in which they work (RP = 96.50). Likewise, it is those of this age range who identify the risk factors to which they are subject (PR = 91.00). We can conclude that the work situations and the risk factors are not significantly related.
is limited by a wide range of socioeconomic and cultural factors. The study aimed to develop a multivariate model to identify the socioeconomic and cultural factors that influence labor insertion of graduates of the National University of Moquegua, 2019. The type of research according to its purpose was basic and the non-experimental cross-sectional design, with a stratified random sample with proportional allocation with a significance level of 5% and a sampling error of 7%. The data collection technique was the survey and two validated and reliable instruments were applied. The population consisted of 537 graduates, with a sample of 121 graduates from six Professional Schools. The results of the application of logistic regression models indicate that the employment status (Wald ¼ 21.179 and p-value ¼ 0.000), basic electricity services (Wald ¼ 4.567 and p-value ¼ 0.033), the preference for movies (Wald ¼ 6,136 and p-value ¼ 0.013), and the communications media: TV and radio (Wald ¼ 4.962 and p-value ¼ 0.026) significantly influence the labor insertion of graduates of UNAM. It is concluded that both the working condition, electricity services, the preference for movies and communication media like TV and radio significantly influence the labor insertion of graduates of the National University of Moquegua.
In this paper, a discourse-based method that merges syntactic and semantic models for developing an automated system for reading comprehension assessment is proposed. For evaluating semantic content, we use the classical models from the literature: Vector Space Modelling and Latent Semantic Analysis. For evaluating the coherence of a text, we used an entity grid representation of the texts, which extracts syntactic patterns from the texts and relies on the assumption that coherent texts will have similar underlying syntactic patterns. The contribution of this work is twofold: firstly, we develop a new methodology for free-text responses in which we assess student‘s texts by semantic content and coherence. Secondly, we develop an automated system for assessing a student's reading comprehension for Spanish language using features that can be computed automatically. Experiments show that we can get accuracies of 90% when assessing text content, and of 55% - 60% when assessing text coherence.
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