Words In Sentence Research Articles

The Effectiveness of Using an H5P Pathway to Enhance College Students' Academic Style in Writing

This study investigates the effectiveness of using an H5P pathway to enhance college students' academic style in writing. The study was conducted at XJTLU, a Sino-foreign university, where the language barriers of first-year students posed difficulties in their transition from informal language to the formal tone required in academic writing. Through a careful experimental design, participants were assigned to either an experimental or a control group, with the former engaging in a structured H5P pathway including five specific academic writing style rules based on learner needs analysis. The five rules are in aspects of word choice, sentence structure, transition, hedging and redundancy. The latter received lesson PPTs with the same content. This paper discusses the results of the study, which show that the application of the H5P pathway effectively assisted Year 1 students at XJTLU in narrowing the gap between the two writing styles. Preliminary analysis indicates a significant improvement in the experimental group's academic writing style specifically in aspects of using formal words and complex sentence structure. By comparison, other than word choice, there is no significant improvement in the control group. The findings of this study highlight the potential of H5P pathways as an effective tool for enhancing college students' academic writing style. Through interactive and tailored activities, students’ challenges at academic writing conventions could be addressed. This research provides implications for innovative pedagogical strategies that can promote students' academic development.

Canadian Practice and Recommendations on Functional MRI to Lateralize Language in Epilepsy.

Identifying a patient's dominant language hemisphere is an important evaluation performed prior to epilepsy surgery and is commonly assessed using functional magnetic resonance imaging (fMRI). However, the lack of standardization and resultant heterogeneity of fMRI paradigms used in clinical practice limits the ability of cross-center comparisons to be made regarding language laterality results. Through surveying Canadian Epilepsy Centres in combination with reviewing supporting literature, current fMRI language lateralization practices for the clinical evaluation of patients with epilepsy were assessed. To encourage standardization of this practice, we outlined a two-part paradigm series that demonstrates widespread acceptance, reliability and accessibility in lateralizing various aspects of language functioning in individuals with average or near-average IQ and normal literacy skills. The collected data confirm a lack of standardization in fMRI laterality assessments leading to clinical heterogeneity in stimulation and control tasks, paradigm design and timing, laterality index calculations, thresholding values and analysis software and technique. We suggest a Sentence Completion (SC) and Word Generation (WG) paradigm series as it was most commonly employed across Canada, demonstrated reliability in lateralizing both receptive and expressive language areas in supporting literature, and could be readily intelligible to an inclusive population. Through providing recommendations for a two-part paradigm series, we hope to contribute to the standardization of this practice across Canada to reduce clinical heterogeneity, encourage communicability between institutions, and enhance methodologies for the surgical treatment of epilepsy for the benefit of all individuals living with epilepsy in Canada.

Testing the Continuum/Spectrum Model in Russian-Speaking Children With and Without Developmental Language Disorder.

Previously, Lancaster and Camarata (2019) showed that the continuum/spectrum model of the developmental language disorder (DLD) best explained the high heterogeneity of symptoms in children with DLD. We hypothesize that the continuum/spectrum approach can include not only children with DLD but also typically developing (TD) children with different timelines and patterns of language acquisition. This model can explain individual language profiles and deficits in children. We assessed language abilities in a group of Russian-speaking children with DLD aged 4-7 years (n = 53) and their age- and gender-matched peers without speech and language diagnoses (n = 53, TD). We evaluated the children's performance at four language levels in production and comprehension domains, using 11 subtests of the standardized language assessment for Russian: Russian Child Language Assessment Battery (RuCLAB). Using the k-means cluster method and RuCLAB scores, we obtained two clusters of children and analyzed their language performance in individual subtests. The analysis revealed that the two clusters of children both included DLD and TD participants: Group 1, with higher test scores (TD = 45, DLD = 24 children), and Group 2, with lower scores (TD = 8, DLD = 29). Children from Group 1 mostly had lower scores at one of the language levels, whereas those from Group 2 struggled at several language levels. Furthermore, children with DLD from both groups tended to be more sensitive to linguistic features such as word length, noun case, and sentence reversibility compared to TD children. The presence of two mixed groups shows that children with diagnosed DLD could perform on par with TD children, whereas some younger TD children could perform similarly to children with DLD. Our findings support the continuum/spectrum model: Linguistic skills in preschool children are a continuum, varying from high to poor skills at all language levels in comprehension and production. To describe a child's language profile, the tasks assessing all language levels should be used. https://doi.org/10.23641/asha.25521400.

Exploring the impact of ChatGPT on art creation and collaboration: Benefits, challenges and ethical implications

This paper examines the chaos caused by introducing advanced language models, specifically ChatGPT, to art. Our focus is on the potential impact of ChatGPT on art creation and collaboration. We explore how it has been utilized to generate art and assist in creative writing and how it facilitates collaboration between artists. This exploration includes an investigation into the use of AI in creating art, music, and literature, emphasizing ChatGPT’s role in generating poetry and prose and its ability to provide valuable suggestions for sentence structure and word choice in creative writing. We conduct case studies and interviews with diverse artists and AI experts to understand the benefits and challenges of using ChatGPT in the creative process. Our findings reveal that artists find ChatGPT helpful in generating new ideas, overcoming creative blocks, and improving the quality of their work. It enables remote collaboration between artists by providing a real-time communication and idea-sharing platform. However, ethical concerns relating to authorship ownership and authenticity have emerged. Artists fear using ChatGPT may lead to losing their artistic identity and ownership of their work. While our data suggests that ChatGPT holds the potential to transform the art world, careful consideration must be given to the ethical implications of AI in art. We recommend future research to focus on developing guidelines for the responsible use of AI in art, safeguarding artists’ rights, and preserving artistic authenticity.

Modifying Language for a Higher Goal: Investigating Quantitative Features of Apple’s Launch Event Speech from 2016 to 2022

ABSTRACT In response to the COVID-19 pandemic, Apple Inc. switched its product launch from onsite events to pre-recorded online broadcasts. Yet this form has been carried on even though the pandemic has faded. It is unclear if this shift was accompanied by a move in language complexity and how the communication effect was influenced. This study analysed Apple’s product launch events from 2016 to 2022 using quantitative linguistics metrics such as lexical complexity, word token length, entropy, readability, and sentence length distribution. The analysis adopted the reach-effect-durability framework for interpreting the effects of strategic communication. The results showed that Apple’s online product launch events featured richer and longer words, increased text difficulty, and a decrease in the proportion of short sentences. Such changes happened in a balanced manner that can be interpreted in view of the driving and restraining forces resulting from the mode shift of the launch event. This study demonstrates the feasibility of assessing efforts and strategies used in a communication campaign through quantitative text analysis.

Underrated and Underestimated – Deprivation in Dementia. A Case Report

Introduction Deprivation is widely known in children and adolescents and means a lack of social, emotional, or sensory stimuli, due to disabilities such as deafness, but also social isolation and reduced parental care. It may cause developmental disorders such as impaired language, motoric and social development. Little is known of the impact of social deprivation in demented patients.Stimulus shielding, which is a widespread option for psychiatric symptoms of dementia such as agitation, vocalization and aggressive behavior may – if frequently used- have similar effects on demented patients.ObjectivesWe report the case of a 71-year-old patient with dementia caused by PSP (Progressive Supranuclear Palsy), who was in inpatient treatment due to continuous undirected vocalizations. She presented with inability to walk, dysarthria, aphasia, and hearing difficulties beside major mnestic impairment. In a prior hospitalization and in her residency, she was frequently isolated from other patients due to loud screaming and vocalizations in terms of stimulus shielding by suspected overstimulation. In order to that, for four months, she developed progressive difficulties to speak, hear, understand, as well as gait disorders. In addition, the vocalizations increased.Methods We rated the symptoms due to deprivation, triggered by lack of mobilization, social experiences, visual, tactile and acoustic stimuli following a vicious circle of anxiety, vocalizations and recurrent isolations. Therefore, a multimodal therapy assessment was implemented, including daily physical therapy, mobilization, basal stimulation, social reintegration and basal conversation training.Results After a few days of high intensity treatment, speech reappeared in form of one- word sentences and proceeded to the ability to have short conversations. Mobility increased, starting from severe gait disorder, including the use of a wheelchair and emerged to the ability of walking up to 50 metres. Additionally, the undirected vocalizations improved and were reduced. In addition, hearing ability improved during the four-week treatment.Conclusions This case highlights the impact of deprivation in demented patients. Especially it shows that these symptoms can be reversible under a high intensity multimodal and multi- professional treatment within a few weeks. Therefore, stimulus shielding, should be carefully evaluated in order to prevent deprivation – and thus deterioration of the symptoms – in demented patients.Disclosure of InterestNone Declared

Comparing Speech Production Errors of 3 to 5 Year Old Bengali Children with Cleft Lip and/or Palate in Two Contexts: Word Naming And Sentence Repetition

Research suggests various standardized assessment tools to collect and analyze the speech of the individual with cleft lip and/or palate (CLP). Despite the importance of developing an assessment framework for the growing CLP population, documentation on Bengali cleft speech is limited. This study aims to investigate the phonetic differences that happen in the speech sound production of 3 to 5-year-old Bengali-speaking CLP children in two different contexts: single word and sentence repetition. It also aims to evaluate the effects of these two speech assessment tools in those children’s phonological evaluation to identify the proper evaluation for CLP individuals. In total, 12 Bengali-speaking CLP children from 3 to 5 years old participated in each test. Thus, data has been collected from a sample of 24 with 79-word stimuli. Two types of speech materials were used: single-word naming and sentence repetition tasks. The samples were analyzed using narrow phonetic transcription for targeted speech items. The percentage of consonants correct (PCC), percentage of correct places (PCP), percentage of correct manners (PCM), as well as phonological simplification processes (PSP) were assessed from the samples. Results showed a range of word structures and place-manner features produced by CLP children in both tasks. Also, the PCC, PCP, PCM, and PSP results were considerably less accurate in the sentence repetition task, suggesting that the task may provide a more accurate assessment of the CLP population. Social Science Review, Vol. 40(2), December 2023 Page: 205-224

A medical report generation method integrating teacher–student model and encoder–decoder network

The automatic medical report generation task can reduce the burden of radiologists and improve the intelligence of auxiliary diagnosis, but still faces the following challenges: (1) The small lesions are easily overlooked, leading to loss of crucial information in the report and low accuracy; (2) The generated long text reports often suffer from jumbled word order and sentence order, resulting in poor fluency. Through simulation of the cognitive principle of professional physicians during their training and work, this paper put forward a medical report generation method integrating a teacher–student model with an encoder–decoder network. The core idea is to propose a cross-modal teacher (text)-student (image) model, adopting different supervision methods for different stages of report generation to improve the model’s learning performance. A semantic space alignment mechanism is designed to enhance the cross-modal feature matching ability by contrasting the encoding methods of different modalities through adversarial learning, gradually optimizing and capturing the critical information. A layer-supervised decoder based on the Transformer hierarchical structure is proposed with the teacher model guiding the student model to decode layer by layer to increase the fluency of report generation. Comparative experiments are conducted on IU-X-ray and MIMIC-CXR datasets with various other methods, and the results show that the proposed method can effectively improve the quality of generated reports.

Towards Efficient and Effective Text-to-Video Retrieval with Coarse-to-Fine Visual Representation Learning

In recent years, text-to-video retrieval methods based on CLIP have experienced rapid development. The primary direction of evolution is to exploit the much wider gamut of visual and textual cues to achieve alignment. Concretely, those methods with impressive performance often design a heavy fusion block for sentence (words)-video (frames) interaction, regardless of the prohibitive computation complexity. Nevertheless, these approaches are not optimal in terms of feature utilization and retrieval efficiency. To address this issue, we adopt multi-granularity visual feature learning, ensuring the model's comprehensiveness in capturing visual content features spanning from abstract to detailed levels during the training phase. To better leverage the multi-granularity features, we devise a two-stage retrieval architecture in the retrieval phase. This solution ingeniously balances the coarse and fine granularity of retrieval content. Moreover, it also strikes a harmonious equilibrium between retrieval effectiveness and efficiency. Specifically, in training phase, we design a parameter-free text-gated interaction block (TIB) for fine-grained video representation learning and embed an extra Pearson Constraint to optimize cross-modal representation learning. In retrieval phase, we use coarse-grained video representations for fast recall of top-k candidates, which are then reranked by fine-grained video representations. Extensive experiments on four benchmarks demonstrate the efficiency and effectiveness. Notably, our method achieves comparable performance with the current state-of-the-art methods while being nearly 50 times faster.

Development and Evaluation of Drug Management Information System in Mijen Community Health Center Demak

Background: Drug management information systems can serve as tools for decision-making. The effectiveness of such a system can be assessed through evaluation. One of the evaluation methods used is the PIECES method.Objectives: This research aims to evaluate and develop a drug management information system using the PIECES method.Methods: The research conducted was a qualitative descriptive study with inductive analysis. Sampling for this research was conducted purposive sampling. System development in this study utilized the prototype method, with interviews conducted for Management Information System (MIS) evaluation using the PIECES Framework. The design of the MIS system was created using Data Flow Diagrams and Entity Relationship Diagrams. The designed MIS system development was evaluated using the same method. Data processing in qualitative research consists of valid, clear, and accountable word descriptions, sentences, or narratives provided by the researchers, followed by data validation using triangulation techniques and Nvivo 12 Plus software.Results: Evaluation results using the PIECES Framework indicate that the implemented MIS system benefits and aids staff performance in daily drug dispensing. However, there are still manual tasks and lacking features such as distribution, drug expiration warnings, and minimum stock on the dashboard. The proposed design for MIS system development includes several features such as stock in, stock out, and distribution, complemented with drug expiration warnings, minimum stock alerts on the dashboard, and reports for each feature.Conclusion: Implementing the proposed MIS system design can assist and streamline work processes by providing comprehensive information, thus serving as a decision-making tool.

Word separation in continuous sign language using isolated signs and post-processing

Continuous Sign Language Recognition (CSLR) is a long challenging task in Computer Vision due to the difficulties in detecting the explicit boundaries between the words in a sign sentence. To deal with this challenge, we propose a two-stage model. In the first stage, the predictor model, which includes a combination of CNN, SVD, and LSTM, is trained with the isolated signs. In the second stage, we apply a post-processing algorithm to the Softmax outputs obtained from the first part of the model in order to separate the isolated signs in the continuous signs. While the proposed model is trained on the isolated sign classes with similar frame numbers, it is evaluated on the continuous sign videos with a different frame length per each isolated sign class. Due to the lack of a large dataset, including both the sign sequences and the corresponding isolated signs, two public datasets in Isolated Sign Language Recognition (ISLR), RKS-PERSIANSIGN and ASLLVD, are used for evaluation. Results of the continuous sign videos confirm the efficiency of the proposed model to deal with isolated sign boundaries detection. The intuition behind the proposed post-processing methodology is to improve the recognition accuracy by removing the untrained and repetitive signs using the sliding window approach during the inference phase. This marks the first instance of such a mechanism within this domain. So, we present our methodology as a baseline for research community to enrich the methodology as well as evaluating on the other real data.

The role of consciousness in Chinese nominal metaphor processing: a psychophysical approach

Abstract Conceptual metaphor theory (CMT) holds that most conceptual metaphors are processed unconsciously. However, whether multiple words can be integrated into a holistic metaphoric sentence without consciousness remains controversial in cognitive science and psychology. This study aims to investigate the role of consciousness in processing Chinese nominal metaphoric sentences ‘A是B’ (A is[like] B) with a psychophysical experimental paradigm referred to as breaking continuous flash suppression (b-CFS). We manipulated sentence types (metaphoric, literal and anomalous) and word forms (upright, inverted) in a two-staged experiment (CFS and non-CFS). No difference was found in the breakthrough times among all three types of sentences in the CFS stage, while literal sentences were detected more slowly than either metaphoric or anomalous sentences in the non-CFS stage. The results suggest that the integration of multiple words may not succeed without the participation of consciousness, let alone metaphoric processing. These findings may redefine ‘unconscious’ in CMT as ‘preconscious’ and support the indirect access view regarding how the metaphoric meaning is processed in the brain.

PENGGUNAAN GAYA BAHASA DALAM PUISI KARYA SISWA KELAS VIII SMP NEGERI 27 MALANG

Poetry is one of the standards for junior high school (SMP) students' literary abilities. In poetry, there is definitely a language style that functions to beautify the language in poetry. Likewise with poems written by class VIII A students at SMPN 27 Malang. Based on this, the aim of this research is to reveal the use of language styles in students' poetry, so that the types and forms of use of language styles are known and students' abilities in applying diction in poetry. The research used is qualitative. The data sources contained in this research are 34 poems written by students. From the results of the analysis, it was found that sixteen (16) types of language styles were obtained, with a total of 79. The language styles found include: the first is rhetorical reticence with the highest number of occurrences of around 22 data, then followed by the metaphor, hyperbole and personification language styles with 9 data, followed by the anaphora language style with 6 data. There are other language styles such as rhetorical questions and associations with 4 data each, followed by synecdoche pars pro toto and repetition with 3 data. Next there are the language styles of allegory, tautology, synecdoche totem pro parte which both amount to 2 data, then there are also the language styles of epic parable, simile, pleonasm, and alliteration which each have 1 data. The forms of language style units obtained from students' poetry are in the form of word units, sound units and sentence units. Finally, students' ability to apply denotative and connotative meaningful diction in poetry.

Parent implementation of a treatment for late talkers based on cross-situational statistical learning principles: Treatment fidelity and acceptability

Purpose Early intervention based on principles of cross-situational statistical learning (CSSL) for late-talking children has shown promise. This study explored whether parents could be trained to deliver this intervention protocol with fidelity and if they found the intervention to be acceptable. Method Mothers of four English-speaking children aged 18–30 months who scored <10th centile for expressive vocabulary were recruited to an 8-week group training program. Parents were taught principles of CSSL and asked to perform 16 home treatment sessions (30 minutes each) in total, providing auditory bombardment of target words in full sentences at high dose number and syntactic variability, using a range of physical exemplars. Home diaries and two videotaped sessions measured treatment fidelity. Pre- and post-treatment questionnaires measured acceptability. Result One parent discontinued the study after the second group training session. Three parents completed 15/16 group training sessions and reported completing 87% of home sessions. Two parents demonstrated implementing the intervention as per the target dose number by the first fidelity session (Weeks 2/3), and the third parent was very close to meeting target dose number by the second fidelity session (Weeks 7/8). Conclusion Parents can be trained to deliver an intervention based on cross-situational statistical learning principles.

Telerehabilitation with Verb Network Strengthening Treatment (VNeST) in two participants with mild-to-moderate and moderate-to-severe aphasia: A single-case experimental design study

ABSTRACT Background Verb Network Strengthening Treatment (VNeST) is a verb-centred aphasia treatment that targets the semantic relationships between a verb (e.g., dig) and related content words (e.g., gardener, hole), aiming to promote word retrieval and sentence production in aphasia. Previous research shows promising results of VNeST in several participants. Aims This study investigates the effects of VNeST through telerehabilitation on word retrieval and sentence production with treated and semantically related untreated verbs, as well as the possible generalisation to confrontation naming and connected speech. Further, functional communication, communicative participation, health-related quality of life and client satisfaction are explored. Methods and Procedures A single-case experimental design study with multiple baselines was conducted with two participants with stroke-induced mild-to-moderate Broca’s aphasia or moderate-to-severe Wernicke’s aphasia who received VNeST through telerehabilitation. Percentage of non-overlapping data, Baseline Corrected Tau and d-index effect size were used to measure improvement in word retrieval and sentence production elicited through video-clip stimuli. The study is registered with ClinicTrials.gov, number NCT05152979. Outcomes and Results The participant with Wernicke’s aphasia improved in word retrieval in sentences with trained and untrained verbs and showed some – albeit limited – generalisation to confrontation naming of nouns and verbs. The participant with Broca’s aphasia withdrew after half of the planned dosage, as he did not consider VNeST suitable for his needs. He did not improve in word retrieval or sentence production. Conclusions VNeST shows promise when it comes to improving word retrieval in trained and semantically related untrained stimuli in moderate-to-severe Wernicke’s aphasia. This study adds to the existing literature by showing potential improvement in VNeST through telerehabilitation.

Style-Enhanced Transformer for Image Captioning in Construction Scenes.

Image captioning is important for improving the intelligence of construction projects and assisting managers in mastering construction site activities. However, there are few image-captioning models for construction scenes at present, and the existing methods do not perform well in complex construction scenes. According to the characteristics of construction scenes, we label a text description dataset based on the MOCS dataset and propose a style-enhanced Transformer for image captioning in construction scenes, simply called SETCAP. Specifically, we extract the grid features using the Swin Transformer. Then, to enhance the style information, we not only use the grid features as the initial detail semantic features but also extract style information by style encoder. In addition, in the decoder, we integrate the style information into the text features. The interaction between the image semantic information and the text features is carried out to generate content-appropriate sentences word by word. Finally, we add the sentence style loss into the total loss function to make the style of generated sentences closer to the training set. The experimental results show that the proposed method achieves encouraging results on both the MSCOCO and the MOCS datasets. In particular, SETCAP outperforms state-of-the-art methods by 4.2% CIDEr scores on the MOCS dataset and 3.9% CIDEr scores on the MSCOCO dataset, respectively.

The Impact of ChatGPT on Language Evolution: A Linguistic Analysis

This research sought to identify changes in terms of word choice, sentence structure, and semantics introduced by ChatGPT and how the functionality of ChatGPT impacts the pragmatics of the English language: politeness, deixis, and discourse markers. This study used corpus analysis as part of the methodology involving Natural Language Processing (NLP) tools for part-of-speech tagging and sentiments, analyzing changes in wordings, syntaxes, and semantic elements generated by ChatGPT as an advanced language modal. A qualitative approach, including user surveys and comparative analysis, proved useful in clarifying the changing patterns of politeness, deixis, and discourse markers in AI-supported communication. Henceforth, ChatGPT generates neologism, unique cultural references, verbal contextual adaptations, and a wide range of technical terms. Moreover, the researchers found that user preferences for communication mediums vary, which showed a complex field of users and their expectations in the context of language generated by ChatGPT. Thus, it was observed that ChatGPT contributes significantly to developing the pragmatic aspects of language use in the modern era. Hence, the study proposes that the ChatGPT polishes the usage of politeness terms and improves its deixis along with formal discourse markers. This highlights the need for continuous improvement, especially in areas such as politeness, deixis management, and integration of discourse markers for the developers.

A standardised method for improving patient education material readability for orthopaedic trauma patients.

While the National Institutes of Health and American Medical Association recommend patient education materials (PEMs) should be written at the sixth-grade reading level or below, many patient education materials related to traumatic orthopaedic injuries do not meet these recommendations. The purpose of this study is to create a standardised method for enhancing the readability of trauma-related orthopaedic PEMs by reducing the use of≥three syllable words and reducing the use of sentences >15 words in length. We hypothesise that applying this standardized method will significantly improve the objective readability of orthopaedic trauma PEMs. A patient education website was queried for PEMs relevant to traumatic orthopaedic injuries. Orthopaedic trauma PEMs included (N=40) were unique, written in a prose format, and <3500 words. PEM statistics, including scores for seven independent readability formulae, were determined for each PEM before and after applying this standard method. All PEMs had significantly different readability scores when comparing original and edited PEMs (p<0.01). The mean Flesch Kincaid Grade Level of the original PEMs (10.0±1.0) was significantly higher than that of edited PEMs (5.8±1.1) (p<0.01). None of the original PEMs met recommendations of a sixth-grade reading level compared with 31 (77.5%) of edited PEMs. This standard method that reduces the use of≥three syllable words and <15 word sentences has been shown to significantly reduce the reading-grade level of PEMs for traumatic orthopaedic injuries. Improving the readability of PEMs may lead to enhanced health literacy and improved health outcomes.

A Critical Discourse Analysis of E-Paper 'KPU chief rebuffs allegations of bias during VP debate" in Jakarta Post

This research employs critical discourse analysis (CDA) to examine a news article titled "KPU Chief Rebuffs Allegations of Bias during VP Debate" from the Jakarta Post, focusing on the transition from print to online media or E-Paper. In this research, the two main methods used to collect data are documentation via the Jakarta Post e-paper news page and content review. This approach provides the advantage of exploring information in depth and comprehensively related to the phenomenon or event that is the focus of the research. Utilizing Teun A. van Dijk's CDA framework, the analysis encompasses macro, superstructure, and micro structures. The macro-structural analysis reveals the social and political context, identifying social groups and emphasizing narrative importance. The critical discourse superstructure analysis delves into linguistic patterns, representations of power, and strategic language use. Finally, the micro-structural analysis explores word choice, grammar, writing style, and sentence structure to understand how language constructs arguments and responds to accusations. Through these lenses, the study provides a comprehensive understanding of how the news shapes and reflects social and political dynamics, contributing valuable insights into media discourse surrounding political events in Indonesia.

한국형 과도한 남성성 척도 타당화

Objectives The purpose of this study was to validate the unmitigated agency scale into the Korean version.&#x0D; Methods The KUAS was constructed through adaptation and reverse translation of the unmitigated agency scale. The preliminary study examined the mean, standard deviation, and preference of sentence types and word types among 55 men aged 20-29. This study conducted exploratory factor analysis on 212 men aged 20 to 29. Confirmatory factor analysis was performed on 200 men aged 20 to 29, and discriminant validity, and criterion val-idity were confirmed. Reliability was confirmed through test-retest with 40 people.&#x0D; Results Through exploratory factor analysis, 8 items for 1 factor were confirmed and verified through confirmatory factor analysis. The overall internal consistency was .86, and the correlation coefficient for retest reliability was .83. Variant validity and criterion validity were found to be appropriate.&#x0D; Conclusions This study provided a reliable and valid scale to measure unmitigated agency, the negative aspect of masculinity in gender roles. It laid the foundation for viewing the multifaceted aspects of gender roles.