Spanish Texts Research Articles

Exploring the Effect of Plain Terminology on Processing and Comprehension of Administrative Texts in Spanish: A Self‐Paced Reading Experiment

ABSTRACTClear communication between government administrations and citizens is a challenge in democratic societies. Public administration texts often contain technical legal terms, essential to convey specialized knowledge with precision but often impenetrable to non‐experts. The plain language movement provides guidelines for simplifying legal‐administrative texts, recommending avoiding, explaining, or replacing technical terms with more transparent synonyms. This study assesses the effect of plain terminology on the processing and comprehension of administrative texts in Spanish. We conducted a self‐paced reading experiment in which participants (N = 117) read texts with legal‐administrative terms and their plain synonyms and answered comprehension questions. Results showed that plain terms significantly improved comprehension but did not reduce reading times. Mixed linear regression analysis revealed that other term properties—length, frequency, and comprehensibility—also influenced reading speed and comprehension. These findings suggest that these factors should be considered when proposing clear alternatives to legal terminology.

Detecting and Reducing Gender Bias in Spanish Texts Generated with ChatGPT and Mistral Chatbots: The Lovelace Project

Current Artificial Intelligence (AI) systems can effortlessly and instantaneously generate text, images, songs, and videos. This capability will lead us to a future where a significant portion of available information will be partially or wholly generated by AI. In this context, it is crucial to ensure that AI-generated texts and images do not perpetuate or exacerbate existing gender biases. We examined the behavior of two common AI chatbots, ChatGPT and Mistral, when generating text in Spanish, both in terms of language inclusiveness and perpetuation of traditional male/female roles. Our analysis revealed that both tools demonstrated relatively low gender bias in terms of reinforcing traditional gender roles but exhibited higher gender bias concerning language inclusiveness, at least in the Spanish language. Additionally, although ChatGPT showed lower overall gender bias than Mistral, Mistral provided users with more control to modify its behavior through prompt modifiers. As a final conclusion, while both AIs exhibit some degree of gender bias in their responses, this bias is significantly lower than the gender bias present in their human-authored source materials.

Limited Availability and Readability of Spanish Language Patient Educational Material: A Review of the Nation's Top Children's Hospitals.

Cleft lip with or without cleft palate (CL/P) is a common congenital facial pathology that occurs at higher incidences in Hispanic communities. The authors analyzed the availability and readability of Spanish-written patient education materials (PEMs) on CL/P from top-ranking U.S. children's hospitals to determine the presence of health literacy barriers. Availability of PEM was evaluated by 2 methods: (1) Google search and (2) evaluation of the official hospital websites. For each institution, a Google search was conducted using the phrase, "labio leporino y/o paladar hendido (translation: CL/P) + (hospital name)." In addition, each hospital website was assessed for Spanish PEM availability. Spanish PEMs were then categorized by whether they had been generated by an automated translation function or if they were independently written Spanish text. English PEM readability was assessed using the Simple Measure of Gobbledygook (SMOG). Spanish PEM readability was assessed using spanish orthgraphic length (Spanish Orthographic Length), the SMOG converted for the Spanish language. Unpaired 2-tailed t tests were used to compare readability. Of a total of 85 pediatric hospitals, 28 (37.3%) had Spanish PEM. Five (6.7%) hospitals created their own Spanish-language document. The average spanish orthgraphic length reading level was 9.49 compared with an average SMOG of 11.38 (P < 0.001). Institutions that did not provide Spanish PEM in any format had a significantly higher SMOG for English PEM of 12.13 compared with 11.38 of those that had SMOG with English PEM (P = 0.04). Health literacy barriers not only exist for Spanish PEM but also for English PEM, indicating an opportunity to improve communication.

Exploring Large Language Models to generate Easy to Read content

Ensuring text accessibility and understandability are essential goals, particularly for individuals with cognitive impairments and intellectual disabilities, who encounter problems accessing information across various mediums such as web pages, newspapers, online administrative tasks, or health documents. Initiatives like Easy to Read and Plain Language guidelines aim to simplify complex texts; however, standardizing these guidelines remains challenging and often involves manual processes. This work presents an exploratory investigation into leveraging Artificial Intelligence (AI) and Natural Language Processing (NLP) approaches to simplify Spanish texts into Easy to Read formats, with a focus on utilizing Large Language Models (LLMs) for creating accessible texts, especially in generating Easy to Read content. The study contributes a parallel corpus of Spanish adapted for Easy To Read format, which serves as a valuable resource for training and testing text simplification systems. Additionally, several text simplification experiments using LLMs and the collected corpus are conducted, involving fine-tuning and testing a Llama2 model to generate Easy to Read content. A qualitative evaluation, guided by an expert in text adaptation for Easy to Read content, is carried out to assess the automatically simplified texts. This research contributes to advancing text accessibility for individuals with cognitive impairments, highlighting promising strategies for leveraging LLMs while responsibly managing energy usage.

Readability Level of Spanish Language Online Health Information: A Systematic Review.

Introduction: Because there is limited online health information in Spanish and it is critical to raise health literacy among Spanish-speaking people, it is essential to assess the readability level of Spanish material. Method: This systematic review included all articles published up to January 3, 2024, and used the CINAHL, MEDLINE, and PubMed databases. The objective was to include the body of knowledge on published articles on the readability levels of Spanish-language, web-based health information intended for lay audiences. Results: There were 27 articles in the final review. Within these articles, 11 tools were used in the Spanish language text. Of the tools, INFLESZ was the most frequently used and the FRY formula, Flesch-Szigriszt Index, and Flesch Formula Index were least used. Most materials (85.2%) reported readability levels of online Spanish information above the 8th grade reading level. Conclusions: The findings show the lack of internet-based Spanish language health information and materials at a recommended (e.g., 5th to 8th grade) reading level. More research is needed to determine which readability tests are more accurate for calculating the readability of Spanish web health information.

Transformer-based approach for symptom recognition and multilingual linking.

This paper presents a transformer-based approach for symptom Named Entity Recognition (NER) in Spanish clinical texts and multilingual entity linking on the SympTEMIST dataset. For Spanish NER, we fine tune a RoBERTa-based token-level classifier with Bidirectional Long Short-Term Memory and conditional random field layers on an augmented train set, achieving an F1 score of 0.73. Entity linking is performed via a hybrid approach with dictionaries, generating candidates from a knowledge base containing Unified Medical Language System aliases using the cross-lingual SapBERT and reranking the top candidates using GPT-3.5. The entity linking approach shows consistent results for multiple languages of 0.73 accuracy on the SympTEMIST multilingual dataset and also achieves an accuracy of 0.6123 on the Spanish entity linking task surpassing the current top score for this subtask. Database URL: https://github.com/svassileva/symptemist-multilingual-linking.

Dynamic Interaction Between Text Characteristics, Order and Time of Assessment on Bilingual Student Reading Efficiency in Spanish and in English

In this study, we examine the dynamic interaction between (a) text characteristics such as genre, number of multisyllabic words, order of texts, and time of assessment (i.e., beginning, middle, or end of the school year), and (b) student fluency described here as text reading efficiency (TRE; Kim et al., 2021) in Spanish and in English. TRE is operationalized as words read correct per minute (WCPM). Participants were 817 s grade Spanish native speakers attending different types of bilingual programs. To examine the interaction of text characteristics and TRE, we first equated texts and then ran a series of mixed effects models. We also examined text characteristics descriptively. Findings indicated that, in general, text characteristics, order of texts, and different timepoints had a significant effect on students’ TRE. Although a clear pattern of differences between texts within and across languages did not emerge, regardless of language, students read fewer words in texts in the beginning of the year than in the middle and at the end of the year. Spanish texts included more multisyllabic words than did English texts, which could explain, in part, lower WCPM in Spanish than in English. Impact Statement Words read correct per minute (WCPM) is considered a reliable indicator of students’ reading fluency and comprehension in the early grades in Spanish and in English. Given potential differences in text characteristics and in the time of assessment (i.e., beginning, middle, or end of the school year), equating texts and examining their differences in Spanish and in English can lead to more accurate and effective identification and support for a student population that is increasingly more culturally and linguistically diverse.

«Oda quiere dezir ffin e acabaminto de las cosas». El origen y la evolución de la expresión «quiere decir» en español

The objective of the paper is to analyze the origin and the evolution of the explanatory value of the construction &lt;querer ‘want’ + infinitive&gt;, documented in Castilian texts from the Middle Ages. Through a relatively large corpus of Latin texts (5th–12th centuries) and Spanish texts (13th–15th centuries), the Author explores the main linguistic and discursive reasons that determined its use in the Spanish language.

Enhancing online cataract surgery patient education materials through artificial intelligence

ObjectiveTo assess the feasibility of using artificial intelligence (AI) to improve readability of online cataract surgery patient education materials (PEMs) in English and Spanish. ParticipantsWebsites with information dedicated to educating patients about cataract surgery. DesignComparative cross-sectional study. MethodsThe first 50 patient-oriented websites containing PEMs related to cataract surgery were identified through online search. Website authorship was categorized as an institution, private practice, or medical organization. Websites were assessed qualitatively for information accuracy, the presence of narrative video content, and multilingual availability. Readability of PEMs was assessed using five validated reading formulas. A natural language processing platform was used to simplify PEMs in English and Spanish. Converted PEMs were reassessed for readability and accuracy. ResultsA total of 32 institution, 7 private practice, and 11 medical organization sites were included. The overall average original reading grade level was 11.68 ± 1.59. After conversion, overall reading grade level improved to 7.94 ± 0.82 (p < 0.01). The first 10 results had better readability (10.40 ± 1.59) and reading ease (57.51 ± 9.24) compared to the subsequent 40 results (11.99 ± 1.43; p = 0.01; 47.64 ± 8.59; p < 0.01). Converted simplified Spanish text had an average reading ease score of 61.17 ± 5.39 (8–9th grade level). Native Spanish text reading ease improved from 57.41 ± 5.24 to 71.78 ± 5.24 (p < 0.01) following conversion (7th-grade level). ConclusionAI conversion can enhance the readability of online PEMs on cataract surgery, while maintaining accuracy and content integrity, thereby improving accessibility and comprehensibility for a wider audience.

Cross-cultural adaptation of the writer-reader relationship in non-translated and translated English health information websites on HIV and TB diagnostic testing

The ideal multilingual health information website is relatable to all readers. Natives and immigrants should have a culturally adapted website in their language hosted by their place of residence that imparts the facts and incites a call to action to improve health, and ultimately reduces disease in the diverse community. The writer’s word choices and attitude as conveyed through the text influence the reader’s decision-making process. This paper will examine the differences between the non-translated and translated English versions of multilingual health information websites on HIV and TB diagnostic testing. These samples pertain to a large interdisciplinary study whose purpose is to determine whether the multilingual health communication websites are appropriately written regarding health literacy, and whether each cultural population, in terms of language adaptation, would receive the health information as intended. The study questions whether there exist differences between the translated and non-translated texts in English, Spanish and Catalan; this paper focuses on the two English sub-corpora. A comparable corpus of seventy-three multilingual health information websites underwent a quantitative and a qualitative analysis. The methodology is based on adaptations of Clerehan et al.’s (2005) Evaluative Linguistic Framework to assess the writer-reader relationship. The findings show statistically significant differences between the two English subcorpora as regards the writers’ and translators’ approach; the non-translated English sub-corpus contained more relational and engagement markers, whereas the translated English sub-corpus had more persuasion markers. These results should serve researchers and professionals in the translation and language sciences as well as the public health field for, respectively, future studies and techniques to improve the composition of multilingual health information texts in culturally diverse countries.

Harmony in diversity: exploring cross-linguistic, cross-cultural and multimodal dimensions of temporality within tourism discourse

Abstract This study explores temporal aspects in tourism discourse across modes, languages and cultures, focusing on translated texts in German, Italian, French, English, and Spanish. Tourism communication, a persuasive force promoting destinations, constructs authentic experiences for potential tourists. Beyond promotion, it reflects a societal practice shaping tourist identities and destination cultures. The translation of tourism texts involves considerations of cultural values and multimodal representations, seeking to transfer the unique selling proposition effectively. Existing research has analyzed trigger words, interlingual strategies, and cultural representations, but a gap exists in understanding the translation of temporal aspects. This paper investigates the multimodal representation, promotion, and transfer of temporality in tourism texts, contributing to contrastive and multimodal research in tourism communication. Key questions addressed include how elements from different modes contribute to the unique selling proposition, how the advertising message is conveyed in a multimodal coherent way, and which temporal aspects are translated and adapted in the target language. The present paper sheds light on the intricate interplay of language and image in conveying the temporal dimension of tourist experiences across diverse linguistic and cultural contexts.

Patterns of interaction between experiential and interpersonal meanings in student texts in Spanish: grounds for system-based applications in an academic writing context

Abstract This paper presents a systemic functional analysis of process types in academic texts in Spanish from the Appraisal Theory perspective in order to establish connections and observe the interaction of the experiential and interpersonal metafunctions and the systems of Transitivity and Attitude. Our purpose is to explore how student writers use process types to construe their specific disciplinary experience, how they inscribe attitudinal meanings in their texts, and how the Transitivity and Attitude systems interact in student choices in academic writing. We used student texts from the CLAE corpus (Ignatieva, Natalia &amp; M. Cecilia Colombi (eds.). 2014. CLAE: El lenguaje académico en México y los Estados Unidos, un análisis sistémico funcional. Mexico: UNAM). The texts belong to two disciplines (literature and history) and to three text types, or genres, labeled in the university setting as essays, reviews, and question-answers. The methodology included a quantitative and qualitative analysis of 1) process type realizations, 2) expressions of Attitude, classified according to type (Affect, Judgment, Appreciation) and 3) interaction between the process types and Attitude types. This was followed by a comparative analysis between the disciplines and genres, detecting both the similarities and the differences. In addition, some patterns that combine process types and Attitude expressions were found. Such patterns could represent an important tool in the teaching of academic writing in Spanish.

The balance of Spanish and English child-directed text in bilingual picture books

The balance of Spanish and English child-directed text in bilingual picture books

Reframing social media discourse: Converting hate speech to non-hate speech

In this paper, we investigate the issue of hate speech by presenting a novel task of translating hate speech into non-hate speech text while preserving its meaning. As a case study, we use Spanish texts. We provide a dataset and several baselines as a starting point for further research in the task. We evaluated our baseline results using multiple metrics, including BLEU scores. We used a cross-validation approach and an average of the metrics per fold for evaluation. We achieved a 0.236 sentenceBLEU score on four folds. This study aims to contribute to developing more effective methods for reducing the spread of hate speech in online communities.

How effective are mobile apps in managing people with type 2 diabetes mellitus? A systematic literature review protocol.

The rise of new technologies in the field of health is yielding promising results. In certain chronic conditions such as type 2 diabetes mellitus, which ranks among the top five causes of global mortality, it could be useful in supporting patient management. A systematic review will be conducted on scientific publications from the last 5 years (January 2019 to October 2023) to describe the effect of mobile app usage on glycated hemoglobin for the management of adult patients with type 2 diabetes mellitus who participated in randomized controlled clinical trials. The search will be carried out in the databases of MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCOhost), CENTRAL, WoS, Scopus, Epistemonikos, and LILACS. The search strategy will be constructed using both controlled and natural language. Additionally, the Cochrane filter will be applied to identify randomized controlled trials. The review will include scientific articles reporting studies that present results from randomized controlled trials, with texts in Spanish, English, or French, utilizing mobile applications for the management of adult individuals (over 18 years) with type 2 diabetes mellitus, and whose outcomes report the effects on glycated hemoglobin. The Cochrane Risk of Bias Tool will be used to assess the quality of the studies, and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology will be implemented to evaluate the certainty of the evidence. The analysis will be conducted by observing the value of the glycated hemoglobin levels of the participants. Given that this data is a quantitative and continuous value, it facilitates the identification of the effects of the mobile applications used for the management of type 2 diabetes mellitus (T2DM) in adults. Furthermore, if sufficient data are available, a meta-analysis will be conducted using IBM-SPSS. The effect of the intervention will be estimated by the mean difference. All point estimates will be accompanied by 95% confidence intervals. A random effects model will be used. The heterogeneity of the results will be assessed using Cochrane's Q and I2 statistics. Considering that the quality of content and functionality of certain applications in the healthcare field is highly variable, it is necessary to evaluate the scientific evidence reported on the effect of the use of this type of technology in people with T2DM.

Automatic Spell-Checking System for Spanish Based on the Ar2p Neural Network Model

Currently, approaches to correcting misspelled words have problems when the words are complex or massive. This is even more serious in the case of Spanish, where there are very few studies in this regard. So, proposing new approaches to word recognition and correction remains a research topic of interest. In particular, an interesting approach is to computationally simulate the brain process for recognizing misspelled words and their automatic correction. Thus, this article presents an automatic recognition and correction system of misspelled words in Spanish texts, for the detection of misspelled words, and their automatic amendments, based on the systematic theory of pattern recognition of the mind (PRTM). The main innovation of the research is the use of the PRTM theory in this context. Particularly, a corrective system of misspelled words in Spanish based on this theory, called Ar2p-Text, was designed and built. Ar2p-Text carries out a recursive process of analysis of words by a disaggregation/integration mechanism, using specialized hierarchical recognition modules that define formal strategies to determine if a word is well or poorly written. A comparative evaluation shows that the precision and coverage of our Ar2p-Text model are competitive with other spell-checkers. In the experiments, the system achieves better performance than the three other systems. In general, Ar2p-Text obtains an F-measure of 83%, above the 73% achieved by the other spell-checkers. Our hierarchical approach reuses a lot of information, allowing for the improvement of the text analysis processes in both quality and efficiency. Preliminary results show that the above will allow for future developments of technologies for the correction of words inspired by this hierarchical approach.

Sign-to-Text Translation from Panamanian Sign Language to Spanish in Continuous Capture Mode with Deep Neural Networks

Convolutional neural networks (CNN) have provided great advances for the task of sign language recognition (SLR). However, recurrent neural networks (RNN) in the form of long–short-term memory (LSTM) have become a means for providing solutions to problems involving sequential data. This research proposes the development of a sign language translation system that converts Panamanian Sign Language (PSL) signs into text in Spanish using an LSTM model that, among many things, makes it possible to work with non-static signs (as sequential data). The deep learning model presented focuses on action detection, in this case, the execution of the signs. This involves processing in a precise manner the frames in which a sign language gesture is made. The proposal is a holistic solution that considers, in addition to the seeking of the hands of the speaker, the face and pose determinants. These were added due to the fact that when communicating through sign languages, other visual characteristics matter beyond hand gestures. For the training of this system, a data set of 330 videos (of 30 frames each) for five possible classes (different signs considered) was created. The model was tested having an accuracy of 98.8%, making this a valuable base system for effective communication between PSL users and Spanish speakers. In conclusion, this work provides an improvement of the state of the art for PSL–Spanish translation by using the possibilities of translatable signs via deep learning.

Function of the Clitic se in the Spanish of the 14th century (on the material of Juan Manuel’s “Count Lucanor”)

Despite the existence of numerous studies dedicated to the analysis of the clitic se in the Spanish language, there is currently a lack of systematic research on the element se found in Old Spanish texts. This article provides a description of the functions of the clitic in a 14th-century text based on a previously developed classification.

Clinical Applications of "In-Hospital" 3D Printing in Hip Surgery: A Systematic Narrative Review.

Introduction: Interest in 3D printing for orthopedic surgery has been increasing since its progressive adoption in most of the hospitals around the world. The aim of the study is to describe all the current applications of 3D printing in patients undergoing hip surgery of any type at the present time. Materials and Methods: We conducted a systematic narrative review of publications indexed in MedLine through the search engine PubMed, with the following parameters: 3D printing AND (orthopedics OR traumatology) NOT tissue engineering NOT scaffold NOT in vitro and deadline 31 July 2023. After reading the abstracts of the articles, papers were selected according to the following criteria: full text in English or Spanish and content related to hip surgery. Those publications involving experimental studies (in vitro or with anatomical specimens) or 3D printing outside of hospital facilities as well as 3D-printed commercial implants were excluded. Results are presented as a reference guide classified by disease, including the used software and the steps required for the development of the idea. Results: We found a total of 27 indications for in-house 3D printing for hip surgery, which are described in the article. Conclusions: There are many surgical applications of 3D printing in hip surgery, most of them based on CT images. Most of the publications lack evidence, and further randomized studies should be encouraged to assess the advantages of these indications.

Guide for the application of the data augmentation approach on sets of texts in Spanish for sentiment and emotion analysis.

Over the last ten years, social media has become a crucial data source for businesses and researchers, providing a space where people can express their opinions and emotions. To analyze this data and classify emotions and their polarity in texts, natural language processing (NLP) techniques such as emotion analysis (EA) and sentiment analysis (SA) are employed. However, the effectiveness of these tasks using machine learning (ML) and deep learning (DL) methods depends on large labeled datasets, which are scarce in languages like Spanish. To address this challenge, researchers use data augmentation (DA) techniques to artificially expand small datasets. This study aims to investigate whether DA techniques can improve classification results using ML and DL algorithms for sentiment and emotion analysis of Spanish texts. Various text manipulation techniques were applied, including transformations, paraphrasing (back-translation), and text generation using generative adversarial networks, to small datasets such as song lyrics, social media comments, headlines from national newspapers in Chile, and survey responses from higher education students. The findings show that the Convolutional Neural Network (CNN) classifier achieved the most significant improvement, with an 18% increase using the Generative Adversarial Networks for Sentiment Text (SentiGan) on the Aggressiveness (Seriousness) dataset. Additionally, the same classifier model showed an 11% improvement using the Easy Data Augmentation (EDA) on the Gender-Based Violence dataset. The performance of the Bidirectional Encoder Representations from Transformers (BETO) also improved by 10% on the back-translation augmented version of the October 18 dataset, and by 4% on the EDA augmented version of the Teaching survey dataset. These results suggest that data augmentation techniques enhance performance by transforming text and adapting it to the specific characteristics of the dataset. Through experimentation with various augmentation techniques, this research provides valuable insights into the analysis of subjectivity in Spanish texts and offers guidance for selecting algorithms and techniques based on dataset features.