Text Comments Research Articles

‘More group work would be nice’: exploring peer interaction and belonging in the first-year experiences of culturally and linguistically diverse migrant and refugee students

ABSTRACT A critical factor influencing culturally and linguistically diverse migrant and refugee (CALDMR) students’ educational outcomes is how they experience belonging through peer and educator interactions. To better understand their first-year experiences of belonging, this study analysed 788 responses in the National Student Experience Survey 2020–2022 from first-year CALDMR students studying at a large Australian university. Mixed methods were used with quantitative analysis of closed-ended survey items and qualitative text and thematic analysis of comments relating to peer interaction and sense of belonging. CALDMR students reported lower frequencies of interactions with peers than domestic students with English as first language, yet they highly valued these interactions and believed that educators had a key role in facilitating them. Therefore, this study offers new insights and recommendations on enhancing CALDMR students’ sense of belonging through educator and peer interactions.

Tekstmarkering, kommentarar og metaspråk

How do students in the second year of upper secondary school (vg2) comment on each other’s texts, which text aspects are emphasized and what meta-language do they use in such comments? The article presents a study of first drafts of academic articles in two vg2 classes, where students provide each other with feedback in the form of markings and comments. The texts are part of a text exchange project between two different classes from different parts of the country, where students provide anonymous feedback to the students in the other class. In addition to a classification of the comments with regard to text aspect and the functions of the comments, the specific meta-language the students use is examined more closely. The analysis shows that the students have a good balance between form and content and between micro and macro level in their text comments. At the same time, both praising and directive comments are largely general, which can make them less suitable as a basis for revision. All in all, it seems that the students have stronger and more explicit competence in the overall content and text organization aspects of the texts than is the case for form aspects and language systemic aspects. It is also related to the overall organization of the texts that they to the greatest extent display the use of an expanded meta-language.

Solihull Approach training in undergraduate midwifery education: a pilot study

Background/Aims To date, Solihull training for midwives in Northern Ireland has been facilitated as continuing professional development; however, incorporating Solihull Approach Antenatal Foundation Training in undergraduate midwifery education has been recommended. The aim of this pilot study was to evaluate the provision of this training for undergraduate midwifery students. Methods This mixed-method evaluation study used pre- and post-test questionnaires with a purposive sample of 24 final year midwifery students. The data were analysed using descriptive statistics with thematic analysis of free text comments. Results Four themes emerged: perceived benefits in clinical practice; increased knowledge and confidence; increased recognition of the public health role of the midwife; and integration and timing of the training. Conclusions The innovative initiative was positively evaluated and considered an enhancement to current education provision. However, the initiative would have been welcomed earlier in the education programme. Implications for practice Solihull Approach training will be provided at undergraduate level and introduced earlier in the programme, with the subsequent potential to incrementally build on this foundation and include further tiers of training. The impact of students' application of the Solihull Approach in clinical practice warrants further investigation.

Text Comment Classification and Sentiment Analysis Model Based on LSTM

This study addresses the challenge of sentiment analysis and text classification in user-generated comments, an essential task for understanding public opinion in the digital age. With the widespread adoption of social media, the sheer volume of text data has increased exponentially, thereby necessitating advanced analytical tools. The study integrates Long Short-Term Memory (LSTM) networks with attention mechanisms to develop a model adept at both classifying and analyzing the sentiment of textual comments. The research methodology commences with data cleaning, tokenization, and feature extraction, subsequently followed by the implementation of a bidirectional LSTM architecture augmented with an attention mechanism. The model underwent rigorous training and testing on a comprehensive dataset, yielding high accuracy rates in sentiment analysis and text classification. The results underscore the model’s proficiency in capturing sentiment nuances and underscore its potential for deployment in e-commerce and content recommendation systems, emphasizing the practical implications of this research for enhancing decision-making processes in businesses and among policymakers.

Mental health matters: Evaluating the preparedness of sport psychologists to incorporate within their role.

Mental health has become increasingly important for the applied sport psychologist, a factor which may include screening, promoting literacy, individual support, and educational programs. However, despite of this importance, few checks have been made on the perceived preparedness of sport psychologists to undertake this work and whether differences may exist between those recently qualified compared to experienced practitioners. Underpinned by the theoretical domains framework, 62 Health and Care Professions Council registered practitioner sport and exercise psychologists (30 females: age: M=46.13years and SD=10.44years and 32 males: age: M=43.25years and SD=10.47years) completed an online survey to assess whether they felt equipped to address the mental health dimension of their work. The survey comprised three sections: Demographic and background information, a series of statements (n=31) adapted from the determinants of implementation behavior questionnaire, and three questions with space for free text comments, inviting participants to explain their level of preparedness to incorporate and deliver mental health interventions. A 6×12 analyses of variance yielded significant differences between domain ratings but not across levels of experience or interactions. Data from free text comments were analyzed thematically and categorized into the following three themes: (a) complementing the performance role, (b) awareness of professional boundaries, and (c) importance of further continued professional development. Combined, although practitioners emphasized importance, preparedness ratings ranged from neutral to somewhat agree, calling for further specific sport psychology-based mental health training.

Female Ordination and the Buddha’s Dispensation with a Critical Analysis of <em>Brahmacariya</em> Practice

When the Buddha permitted women to join the monastic community, he predicted that the Buddha’s dispensation (Buddhasāsana) would last only a thousand years due to their ordination. Many scholars dispute this claim. Bhikkhu Anālayo, for example, argues against the Cullavaggapāḷi’s prediction of decline, suggesting it has not materialized, and he explores the impact of the Bhikkhuṇī Order on the dispensation’s longevity. This article investigates how female ordination affects the dispensation and critically analyzes the practice of brahmacariya (celibacy). It utilizes both primary and secondary sources for a thorough critique of existing scholarly views and a detailed examination of brahmacariya within canonical and commentarial texts. The analysis suggests that while female ordination might not cause the complete disappearance of the Buddhasāsana, it could influence the dynamics between monks and nuns, potentially leading to a decline in brahmacariya and spiritual progress within monastic life. Thus, the article supports Bhikkhu Anālayo’s view that the issue lies more with the practice of brahmacariya and spiritual advancement rather than the overall longevity of the dispensation.

Usability and feasibility of an online intervention for older adults to support changes to routines and the home ('Light, activity and sleep in my daily life')

BackgroundIndoor lighting, exposure to outdoor daylight, physical activity and sleep interact to influence functioning, mood and cicadian rhythm. Older adults (≥ 65 years), who often spend more time at home, are less physically active and experience more sleep problems, could benefit from strategies to support behavioural change and self-managed modifications in the home. The study’s primary objective was to assess the usability and feasibility of the ‘Light, activity and sleep in my daily life’ intervention, delivered as a web-based course.MethodsThis 9-week intervention was delivered in a municipality in Sweden (55.70° N). Participants were eight healthy women (age 71–84), community-living in one-person households. We recruited through municipal staff and posters at senior citizen meeting points. Both qualitative and quantitative data were collected before and after the intervention. The outcome measures were intervention usability (ease of use, usefulness) and study feasibility (e.g., recruitment procedure, online engagement). Measures also included changes to routines and self-managed home adjustments to determine whether the participants applied what they had learnt.ResultsAll participants completed the intervention. Time logged in varied between 25 min and 3 h (M = 1 h 50 min) per week. Seven participants’ system usability scores were between 90 and 100 (‘Excellent’) out of 100. When interviewed, participants reported overall high satisfaction with what they had learnt. Six participants were particularly satisfied with the modules targeting light. Seven participants made changes to their lighting or darkness conditions, such as replaced bulbs with either 3-step dimming or higher colour temperature LEDs (samples were included in the intervention test kit). One suggestion to improve the online delivery was to enable participants to add text comments to the weekly evaluation form.ConclusionsThe web-based intervention was feasible to deliver but time for recruitment should be extended and advertisement in the local newspaper should be considered. Participants’ computer proficiency and access to the internet at home will be critical in a future study with a larger sample. Only minor changes to the online content of the intervention are needed based on participants’ feedback. The intervention will be possible to evaluate in a future pilot study.

Recognizing Implicitly Toxic Content Based on Multiple Attention Mechanisms

ABSTRACTToxic content on social media has posed a significant threat to user experience and societal stability. In contrast to explicitly toxic content, implicitly toxic content, lacking overt toxic words, is challenging to identify through single‐text features. Therefore, this study proposes a multi‐feature fusion algorithm to recognize implicit toxic content. Firstly, we collect various features for each post, including text content, likes, comments, user information and other features. Subsequently, employing a multi‐head attention mechanism, we extract and fuse these features. Then, utilizing ensemble learning algorithms, we identify implicitly toxic content based on the fused features. Finally, we analyze the decision‐making process of the model using an interpretable algorithm and derive the most critical features and factors for identifying implicitly toxic content. The experimental results show that the proposed algorithm outperforms algorithms such as BERT, TextCNN, and XGBoost, demonstrating the advantage of multiple features over a single text feature in recognizing implicitly toxic content. In addition, this study provides insights into the decision‐making process of the model and provides more effective toxic content management strategies for social media platforms.

"I Had No Idea This Happened": Electronic Feedback on Clinical Reasoning for Hospitalists.

Feedback on the diagnostic process has been proposed as a method of improving clinical reasoning and reducing diagnostic errors. Barriers to the delivery and receipt of feedback include time constraints and negative reactions. Given the shift toward asynchronous, digital communication, it is possible that electronic feedback ("e-feedback") could overcome these barriers. We developed an e-feedback system for hospitalists around episodes of care escalation (transfers to ICU and rapid responses). The intervention was evaluated by measuring hospitalists' satisfaction with e-feedback and commitment to change. A qualitative survey study conducted at one academic medical center from February to June 2023. Hospitalists - physicians and advanced practice providers. Two hospitalists, one internal medicine resident, and a nurse reviewed escalations of care on the hospitalist service each week using the Revised Safer Dx framework. Confidential feedback was emailed to the hospitalists involved in the patient's care. Hospitalists were asked to rate and explain their satisfaction with the e-feedback and whether they might modify their clinical practice based on the e-feedback. The open-ended text comments from the hospitalists were analyzed using a thematic analysis framework. Forty-nine out of fifty-eight hospitalists agreed to participate. One hundred five out of one hundred twenty-four (85%) e-feedback surveys that were sent were returned by the hospitalists. Hospitalists were highly satisfied with 67% (n = 70) of the e-feedback reports, moderately satisfied with 23% (n = 24), and not satisfied with 10% (n = 11). Six themes were identified based on analysis of the comments. Themes related to satisfaction with the intervention included appreciation for learning about patient outcomes, general appreciation of feedback on clinical care, and importance of detailed and specific feedback. Themes related to changing clinical practice included reflection on clinical decision-making, value of new insights, and anticipated future behavior change. E-feedback was well received by hospitalists. Their perspectives offer useful insights for enhancing electronic feedback interventions.

Patient Experience in Older Adults Ambulatory Care services in a large Irish teaching hospital

Abstract Background Ambulatory care pathways aim to reduce hospital overcrowding, provide multidisciplinary, speciality outpatient care, in a timely and cost-effective manner to older people with complex care needs. The delivery of care is centred on the needs of the patient; obtaining and implementing personalized feedback is essential to upholding the highest standards of care. Methods All Patients attending ambulatory care services, at a large teaching hospital in 2023–2024 were offered a 30-question survey covering demographics, hospital access, facility usage, and care delivery, with yes/no responses, 5-point Likert scale and free text comments. Results This cohort represents 3.5% of overall service users (n=642). Of the group in question, 55% were between 65 and 85, and 10% were over 85, a quarter were under 65. A quarter of people were seen within a month, a further 38% within four months of referral. 63% of respondents travelled by car, 31% took public transportation, 5% walked, and 1% rode a bike. 68% of older adults commuted by car (12% by taxi). Taxi use was due to inability to conveniently access onsite parking. Over three quarters were accompanied to their appointment. A delay was reported by 24% of respondents, two thirds cited a parking issue on campus, with almost 20% identifying a traffic issue. 4% found the distance from the car park to the department challenging. The majority of concerns related to campus traffic and delays getting parking onsite. When asked to rate communication, the environment, and multidisciplinary care delivery, 99%-100% responded positively. Conclusion Care delivery was positively represented in this sample. This patient feedback highlights the need for accessible parking in hospital infrastructure planning. Vulnerable older adults requiring supportive care should be protected from the cost implications of hospital attendance, costly taxi use is indicated in this group. There is a need for national action on this.

A Comparative Analysis of the Water Odes by Sururi and Fuzuli, and the Commentary on Sururi’s Water Ode

In our classical literature, all the poems of Fuzuli in the genres of ghazal, qasida, and masnavi have influenced subsequent poets in terms of their literary value. The Water Ode, due to the excellence in its subject matter and its treatment, has been imitated by poets who came after Fuzuli. Sururi, by composing his own Water Ode, proclaimed his presence in this field. However, Sururi's Water Ode is not as successful as that of Fuzuli. Renowned as a commentator on masnavi and known for his annotations on Sheikh Saadi Shirazi's works "Bostan" and "Gulistan," Sururi is one of the significant figures who shed light on his era. This article first provides information on text commentary and the theories proposed in this context. A comparison of the Water Odes by Fuzuli and Sururi will be made, and the commentary on Sururi’s Water Ode will be examined. Keywords: Sururi, life, art, works, Fuzuli’s Water Ode, Sururi’s Water Ode, text commentary.

Using Patient Experience Surveys to Identify Potential Diagnostic Safety Breakdowns: A Mixed Methods Study.

One in 20 outpatients in the United States experiences a diagnostic error each year, but there are no validated methods for collecting feedback from patients on diagnostic safety. We examined patient experience surveys to determine whether patients' free text comments indicated diagnostic breakdowns. Our objective was to evaluate associations between patient-perceived diagnostic breakdowns reported in free text comments and patients' responses to structured survey questions. We conducted an exploratory mixed methods study using data from patient experience surveys collected from adult ambulatory care patients March 2020 to June 2020 in a large U.S. health system. Data analysis included content analysis of qualitative data and statistical analysis of quantitative data. In 2525 surveys with negative comments, 619 patients (24.5%) identified diagnostic breakdowns, including issues with accuracy (n = 282, 46%), timeliness (n = 243, 39%), or communication (n = 290, 47%); some patients (n = 181) reported breakdowns in multiple categories. Patients who gave a low average score (50 or less on a 100-point scale) on provider questions were almost seven times more likely to perceive a diagnostic breakdown than patients who scored their provider higher. Similarly, patients who gave a low average score on practice-related questions were twice as likely to perceive a diagnostic breakdown. Patient feedback in routinely collected patient experience surveys is a valuable and actionable information source on diagnostic breakdowns in the ambulatory setting. The more easily monitored structured survey data provide a screening method to identify encounters that may have included a patient-perceived diagnostic breakdown and therefore require further examination.

Midwifery student engagement with digital interactive books: A cross sectional survey

AimTo explore the benefit and engagement of undergraduate students’ use of H5P interactive books for student learning. DesignAn evaluation study of technology enabled learning for first year undergraduate Bachelor of Midwifery students in Australia. MethodsStudents were invited to complete an online evaluation survey of their use and engagement with H5P interactive books. The survey included the long form User Engagement Scale which has four subscales of focused attention, aesthetic appeal, reward factor and perceived usability scored on a 5-point Likert scale. Content analysis was used to analyse the text comments given to five open text questions. ResultsThere were 21 students who completed the survey. There was a high overall User Engagement Scale score of 73.1 % with aesthetic appeal and reward factor being the highest scoring subscales. The content analysis showed students found the interactive books engaging and easy to navigate. Areas for improvement identified were not including a large amount of content and providing downloadable content. ConclusionsThis study demonstrates the valuable and engaging use of H5P Interactive Books for undergraduate students in higher education. Students who used H5P Interactive Books identified their ease of use, organised layout and engaging format.

Discursive Patinas: Anchoring Discussions in Data Visualizations.

This paper presents discursive patinas, a technique to visualize discussions onto data visualizations, inspired by how people leave traces in the physical world. While data visualizations are widely discussed in online communities and social media, comments tend to be displayed separately from the visualization and we lack ways to relate these discussions back to the content of the visualization, e.g., to situate comments, explain visual patterns, or question assumptions. In our visualization annotation interface, users can designate areas within the visualization. Discursive patinas are made of overlaid visual marks (anchors), attached to textual comments with category labels, likes, and replies. By coloring and styling the anchors, a meta visualization emerges, showing what and where people comment and annotate the visualization. These patinas show regions of heavy discussions, recent commenting activity, and the distribution of questions, suggestions, or personal stories. We ran workshops with 90 students, domain experts, and visualization researchers to study how people use anchors to discuss visualizations and how patinas influence people's understanding of the discussion. Our results show that discursive patinas improve the ability to navigate discussions and guide people to comments that help understand, contextualize, or scrutinize the visualization. We discuss the potential of anchors and patinas to support discursive engagements, including critical readings of visualizations, design feedback, and feminist approaches to data visualization.

Evolution of radiology staff perspectives during artificial intelligence (AI) implementation for expedited lung cancer triage

Evolution of radiology staff perspectives during artificial intelligence (AI) implementation for expedited lung cancer triage

Evaluating ChatGPT as a patient resource for frequently asked questions about lung cancer surgery—a pilot study

ObjectiveChat-based artificial intelligence programs like ChatGPT are reimagining how patients seek information. This study aims to evaluate the quality and accuracy of ChatGPT-generated answers to common patient questions about lung cancer surgery. MethodsA 30-question survey of patient questions about lung cancer surgery was posed to ChatGPT in July 2023. The ChatGPT-generated responses were presented to 9 thoracic surgeons at 4 academic institutions who rated the quality of the answer on a 5-point Likert scale. They also evaluated if the response contained any inaccuracies and were prompted to submit free text comments. Responses were analyzed in aggregate. ResultsFor ChatGPT-generated answers, the average quality ranged from 3.1 to 4.2 of 5.0, indicating they were generally “good” or “very good.” No answer received a unanimous 1-star (poor quality) or 5-star (excellent quality) score. Minor inaccuracies were found by at least 1 surgeon in 100% of the answers, and major inaccuracies were found in 36.6%. Regarding ChatGPT, 66.7% of surgeons thought it was an accurate source of information for patients. However, only 55.6% thought they were comparable with answers given by experienced thoracic surgeons, and only 44.4% would recommend it to their patients. Common criticisms of ChatGPT-generated answers included lengthiness, lack of specificity regarding surgical care, and lack of references. ConclusionsChat-based artificial intelligence programs have potential to become a useful information tool for patients with lung cancer surgery. However, the quality and accuracy of ChatGPT-generated answers need improvement before thoracic surgeons would consider this method as a primary education source for patients.

Exploring the Impact of Emojis on Paralanguage in Social Media Communication among University Students

This research investigated the evolving role of emojis in shaping paralanguage within social media communication, with a particular focus on how these visual symbols enhance linguistic and emotional expression. The study examined the nuanced ways in which emojis contribute to the overall tone, context, and meaning in written discourse, while also considering cultural and contextual variations in emoji usage among individuals from diverse linguistic backgrounds. Conducted with a sample of 55 Year-3 Bachelor of Education students at a university in Fiji, where English is a second language, the research employed a mixed methods approach to analyze data on the usage and perception of emojis in social media communication. This paper argues that emojis play a crucial role in conveying emotions, fostering engagement, and adding personality to messages, thereby augmenting textual communication with emotional nuance and clarity, leading to more empathetic and meaningful online interactions. The findings indicate that emojis are widely used across various communication channels, including text messages, comments, and direct messages, reflecting their versatility and widespread adoption. Respondents overwhelmingly perceive emojis as positive tools that enhance the effectiveness of digital communication by conveying emotions, fostering engagement, and adding personality to messages. The study also highlights the significant role emojis play in nonverbal communication, particularly in expressing emotions that may be difficult to articulate through text alone. By providing emotional nuance, clarity, and depth, emojis contribute to more empathetic and meaningful interactions in online spaces. Overall, this research provides valuable insights into the dynamic interplay between emojis and paralanguage in contemporary digital communication, signifying the importance of these symbols in enriching text-based exchanges and fostering more engaging and emotionally resonant social media interactions.

Attitude towards artificial intelligence among medical students in Kerala

Objectives: Surveys conducted on a global scale have revealed a significant level of importance in artificial intelligence (AI) among medical pupils’. There have been no inquiries overseen in Kerala to explore the opinions of medical students regarding the consumption of AI in health care or their level of understanding of AI. We seek to evaluate the depths of Kerala’s medical learners concerning AI, both in the field of health care and its potential integration into the medical program. Methods: A digital scrutiny apparatus was created through a thorough examination of existing text and collaboration with doyens in the field. The inquiry was tested with a trio of medical learners and improved based on their valuable input. We distributed a digital probe to all medical pupils in Kerala, which amounted to around 20,000 students. The survey was available for responses from April 1st, 2024 to June 1st, 2024. The students’ responses were carefully analysed, both in terms of categories and the content of their free text comments. The analysis was conducted using open coding techniques to ensure a thorough qualitative analysis. Results: In total, 1000 students provided comprehensive answers to all the questions. A significant proportion of students (82.0%) fell within the age range of 20-29 years, pursuing medicine as their undergraduate degree (85%). Many students showed a keen interest in AI, with a significant majority (79.9%) expressing their curiosity. A large percentage (83.1%) asserted to have a basic realizing of AI, but when it came to the fundamental computational principles of AI, only a minority (39.8%) agreed that they grasped them. Similarly, more than half of the students (51.6%) acknowledged their lack of knowledge regarding the limitations of AI. Most students (81.1%) had not obtained any instruction in AI. A significant portion of students (57.3%) expressed their support for incorporating AI into medical training, while a majority (76.2%) expressed a desire for increased emphasis on teaching AI in medicine. A significant portion (61.3%) of medical students expressed a lack of worry about the potential effect of AI on their job safety as doctors. According to the survey, the majority of students believe that radiology, pathology, and medical administration are the specialties that will be most affected by AI. On the other hand, psychiatry, palliative care, and obstetrics and gynaecology are considered to be the least likely to be stuck by AI. Through qualitative study of the free text notes, it was discovered that AI is viewed as a valuable tool rather than a replacement for doctors. This finding emerged as a common theme. Conclusion: It seems that medical students in Kerala have shown a keen interest in AI. However, their knowledge about AI is limited and they feel they lack a deep understanding of its fundamental computational principles and limitations. It seems that AI is currently lacking in the medical curriculum in Kerala and India, and a majority of surveyed students expressed their support for its implementation. These findings align with previous surveys conducted on a global scale.

Facilitators and barriers to implementing successful exclusion among children with shiga toxin-producing Escherichia coli: a qualitative analysis of public health case management records

BackgroundShiga toxin-producing Escherichia coli (STEC) infections are a significant public health concern as they can cause serious illness and outbreaks. In England, STEC incidence is highest among children and guidance recommends that children under six diagnosed with STEC are excluded from childcare until two consecutive stool cultures are negative. We aimed to describe the barriers and facilitators to implementing exclusion and the impact of exclusion policies on young children and their families.MethodsIndividual level data was obtained from a wider study focusing on shedding duration among STEC cases aged < 6 years between March 2018 – March 2022. Data was extracted from England’s public health case management system. The case management system includes notes on telephone conversations, email correspondence and meeting minutes relating to the case. Collected data consisted of free text in three forms: (1) quotes from parents, either direct or indirect, (2) direct quotes from the case record by health protection practitioners or environmental health officers, and (3) summaries by the data collector after reviewing the entire case record. We analysed free text comments linked to 136 cases using thematic analysis with a framework approach.ResultsThe median age of included cases was 3 years (IQR 1.5-5), with males accounting for 49%. Nine key themes were identified. Five themes focused on barriers to managing exclusion, including (i) financial losses, (ii) challenges with communication, engagement and collaboration, (iii) issues with sampling, processing, and results, (iv) adverse impact on children and their families and (v) conflicting exclusion advice. Four themes related to facilitators to exclusion, including (i) good communication with parents and childcare settings, (ii) support with childcare, (iii) improvements to sampling, testing, and reporting of results, and (iv) provision of supervised control measures.ConclusionsQualitative analysis of public health case records can provide evidence-based insights around complex health protection issues to inform public health guidelines. Our analysis highlights the importance of considering wider social and economic consequences of exclusion when developing policies and practices for the management of STEC in children.

Joint coordinate attention mechanism and instance normalization for COVID online comments text classification.

The majority of extant methodologies for text classification prioritize the extraction of feature representations from texts with high degrees of distinction, a process that may result in computational inefficiencies. To address this limitation, the current study proposes a novel approach by directly leveraging label information to construct text representations. This integration aims to optimize the use of label data alongside textual content. The methodology initiated with separate pre-processing of texts and labels, followed by encoding through a projection layer. This research then utilized a conventional self-attention model enhanced by instance normalization (IN) and Gaussian Error Linear Unit (GELU) functions to assess emotional valences in review texts. An advanced self-attention mechanism was further developed to enable the efficient integration of text and label information. In the final stage, an adaptive label encoder was employed to extract relevant label information from the combined text-label data efficiently. Empirical evaluations demonstrate that the proposed model achieves a significant improvement in classification performance, outperforming existing methodologies. This enhancement is quantitatively evidenced by its superior micro-F1 score, indicating the efficacy of integrating label information into text classification processes. This suggests that the model not only addresses computational inefficiencies but also enhances the accuracy of text classification.