ABSTRACT
This study aimed to explore how metaphors were used to interpret the pandemic and to address its challenges in primary and secondary schools in Reggio Emilia, Italy. A questionnaire was administered to educators and teachers to understand how languages, images, and metaphors were used by themselves and their students to talk about the pandemic and their experiences of living with it. The goal of the questionnaire was to guide critical reflection and encourage more informed language choices. While the existing literature points out the alleged overuse of war metaphors and military frames in public discourse, our findings show that war metaphors are relatively frequent, with other metaphorical frames widely used by teachers and educators to foster resilient attitudes in students. Moreover, in their professional contexts, teachers and educators mostly use metaphorical frames involving resilient attitudes. Our interpretation of the results supports the hypothesis that the purposeful use and deliberate production of metaphors support the choice of metaphors with positive, constructive implications. Finally, some implications of these findings on the theory of metaphor and the methodology of the research are discussed.
ABSTRACT
Large language models have abilities in creating high-volume human-like texts and can be used to generate persuasive misinformation. However, the risks remain under-explored. To address the gap, this work first examined characteristics of AI-generated misinformation (AI-misinfo) compared with human creations, and then evaluated the applicability of existing solutions. We compiled human-created COVID-19 misinformation and ed it into narrative prompts for a language model to output AI-misinfo. We found significant linguistic differences within human-AI pairs, and patterns of AI-misinfo in enhancing details, communicating uncertainties, drawing conclusions, and simulating personal tones. While existing models remained capable of classifying AI-misinfo, a significant performance drop compared to human-misinfo was observed. Results suggested that existing information assessment guidelines had questionable applicability, as AI-misinfo tended to meet criteria in evidence credibility, source transparency, and limitation acknowledgment. We discuss implications for practitioners, researchers, and journalists, as AI can create new challenges to the societal problem of misinformation. © 2023 Owner/Author.
ABSTRACT
In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-checking module, which is supported by novel natural language inference methods with a self-attention network, outperforms state-of-the-art approaches. It is also able to give automated veracity assessment and ranked supporting evidence with the stance towards the claim to be checked. In addition, PANACEA adapts the bi-directional graph convolutional networks model, which is able to detect rumours based on comment networks of related tweets, instead of relying on the knowledge base. This rumour detection module assists by warning the users in the early stages when a knowledge base may not be available. © 2023 Association for Computational Linguistics.
ABSTRACT
Faced with linguicism, racism, and xenophobia aggravated by COVID-19 and political tensions in recent years, multilingual international students, especially those of Asian descent, are in urgent need of engaging in healing practices for meaningful identity expression, restoration, and peace. Translingualism is a justice-oriented literacy practice that disrupts the boundaries of named languages and allows communicators to draw upon all resources in their linguistic repertoires. Storytelling, as a powerful research method and a pedagogical tool, offers a unique opportunity to encourage multilingual students' translingual meaning making for healing. This qualitative case study examined how multimodal translingual storytelling functioned as a form of restoration and peace for a first-semester Chinese student pursuing her graduate degree in English at a private university in the United States. The findings indicate that when offered opportunities to reflect on her cultural and linguistic identities, the participant was likely to detach deficit self-perceptions as an "English language learner" and embrace her differences as a strength, which benefited her first-semester language and academic experiences. This study calls for pedagogical strategies and curriculum design that open up humanizing spaces for culturally and racially minoritized multilingual students by acknowledging, valuing, and inviting their whole linguistic repertories through multimodal, translingual storytelling.
ABSTRACT
Virtual online teaching was adopted at the Iraqi educational institutions: schools and universities when COVID-19 break out. It was the only alternative to revival the education sector after locking down schools and universities by the condition of the quarantine. The scenario of locking down schools and universities after the spread of COVID-19 pandemic pushed stakeholders and decision makers to switch the educational process to the online mode (Thi1 &Minh, 2021). This sudden shift arose many issues and challenges which was faced by both teachers as well as learners, soon questions about the validity and authenticity of the educational process and outcomes were raised. The current study seeks to uncover hidden issues and challenges which English language teachers at Diyala University encounter at this critical period 2019-2022. A semi-structured interview was utilized as the instrument of this small scale qualitative and descriptive study. The qualitative raw data obtained from the interview transcripts were thematically coded and analyzed. The finding were interpreted in two directions: first: failure of the new online teaching process in obtaining the desired educational outcomes outlined by the ministries of education and higher education due to several reasons: uncontrolled examination session which led to student cheating and resulted in unauthentic grading marks. In addition to internet connection issues which is added to the teachers burden and affect negatively EFL teaching process. Secondly: it was proven that online teaching can be beneficial in the sense that it can save time and effort if new strategies of assessment were adopted, intensive training courses for teachers as well as students were applied, in addition to providing good internet service for both student and teacher. © 2023 Otjivanda Presse.Essen. All rights reserved.
ABSTRACT
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the process of classifying reviews many researchers have adopted machine learning approaches. Keeping in view, the rising demand for educational applications, especially during COVID-19, this research aims to automate Android application education reviews' classification and sentiment analysis using natural language processing and machine learning techniques. A baseline corpus comprising 13,000 records has been built by collecting reviews of more than 20 educational applications. The reviews were then manually labelled with respect to sentiment and issue types mentioned in each review. User reviews are classified into eight categories and various machine learning algorithms are applied to classify users' sentiments and issues of applications. The results demonstrate that our proposed framework achieved an accuracy of 97% for sentiment identification and an accuracy of 94% in classifying the most significant issues. Moreover, the interpretability of the model is verified by using the explainable artificial intelligence technique of local interpretable model-agnostic explanations. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
Rapid and continuous changes in digital technologies have changed both classroom practices and teacher profiles in education. It can be argued that a new context of teaching may lead some teachers to develop a different teacher identity in order to meet the needs of the era. Within this perspective, this case study attempts to explore the impacts of Information and Communication Technologies (ICT) revolution in education on teachers' professional identity through the lens of three English instructors from three different contexts in Turkey. The study particularly focuses on reflections of teachers during the pandemic. As a theoretical framework, the study adopts Wenger's (1997) social theory of learning and, within this framework, it discusses these teachers' professional identities in relation to their ICT usage. In particular, three modes of belonging, Engagement, Imagination and Alignment, are underlined. A qualitative approach is employed based on the written history documents of the participants and semi-structured interviews as data collection tools. The findings are gathered with a deductive thematic analysis, and they illustrate that teachers have some external and internal difficulties regarding their ICT usage, and they form a new shape of professional identity mainly through collaboration, community expertise and contributing new ideas in their school contexts. Although the use of new digital technologies mostly enables them to adopt a positive and modern teacher identity in their teaching contexts, it also leads some of them to sometimes question their teacher identity due to their limited ICT knowledge and competence. Thus, the study suggests some implications both for language teachers to invest in their digital identities, and for school administrations to create a friendly atmosphere where the community of expertise can be shared freely among teachers.
ABSTRACT
The acquisition of emotion words is critical to children's socio-emotional development. Previous studies report that children acquire emotion words gradually during ages 3-5 and beyond. The majority of this work, however, has used demanding tasks for young children (e.g., asking children to label emotion-related facial configurations) and has predominantly relied on facial configurations. Here we designed a child-friendly, word-comprehension task incorporating both facial configurations and body language. In two preregistered online experiments, we asked two to four-year-olds (N = 96) to connect emotion words-happy, sad, angry, and scared-to either facial configurations (Experiment 1) or combined facial and body cues (Experiment 2). We found relatively early competence in understanding emotion words, especially those of the same-valence. All age groups, including 2-year-olds, successfully linked emotion words to corresponding facial configurations (Experiment 1). Experiment 2 replicated this pattern and further showed that children performed equally well (though not substantially better) when given additional body cues. Parental reports of children's exposure to and use of masks during the COVID-19 pandemic did not correlate with children's performance in either experiment. Even before children can produce emotion words in an adult-like manner, they possess at least a partial understanding of those words and can map them to emotion cues within valence domains. © 2023 University of California Press. All rights reserved.
ABSTRACT
The COVID-19 pandemic has caused substantial damage to global health. Even though three years have passed, the world continues to struggle with the virus. Concerns are growing about the impact of COVID-19 on the mental health of infected individuals, who are more likely to experience depression, which can have long-lasting consequences for both the affected individuals and the world. Detection and intervention at an early stage can reduce the risk of depression in COVID-19 patients. In this paper, we investigated the relationship between COVID-19 infection and depression through social media analysis. Firstly, we managed a dataset of COVID-19 patients that contains information about their social media activity both before and after infection. Secondly, We conducted an extensive analysis of this dataset to investigate the characteristic of COVID-19 patients with a higher risk of depression. Thirdly, we proposed a deep neural network for early prediction of depression risk. This model considers daily mood swings as a psychiatric signal and incorporates textual and emotional characteristics via knowledge distillation. Experimental results demonstrate that our proposed framework outperforms baselines in detecting depression risk, with an AUROC of 0.9317 and an AUPRC of 0.8116. Our model has the potential to enable public health organizations to initiate prompt intervention with high-risk patients. © 2023 ACM.
ABSTRACT
Background: In the field of antibody engineering, an essential task is to design a novel antibody whose paratopes bind to a specific antigen with correct epitopes. Understanding antibody structure and its paratope can facilitate a mechanistic understanding of its function. Therefore, antibody structure prediction from its sequence alone has always been a highly valuable problem for de novo antibody design. AlphaFold2 (AF2), a breakthrough in the field of structural biology, provides a solution to this protein structure prediction problem by learning a deep learning model. However, the computational efficiency and undesirable prediction accuracy on antibody, especially on the complementarity-determining regions limit its applications in de novo antibody design. Method(s): To learn informative representation of antibodies, we trained a deep antibody language model (ALM) on curated sequences from observed antibody space database via a well-designed transformer model. We also developed a novel model named xTrimoABFold++ to predict antibody structure from antibody sequence only based on the pretrained ALM as well as efficient evoformers and structural modules. The model was trained end-to-end on the antibody structures in PDB by minimizing the ensemble loss of domain-specific focal loss on CDR and the frame aligned point loss. Result(s): xTrimoABFold++ outperforms AF2 and OmegaFold, HelixFold-Single with 30+% improvement on RMSD. Also, it is 151 times faster than AF2 and predicts antibody structure in atomic accuracy within 20 seconds. In recently released antibodies, for example, cemiplimab of PD1 (PDB: 7WVM) and cross-neutralizing antibody 6D6 of SARS-CoV-2 (PDB: 7EAN), the RMSD of xTrimoABFold++ are 0.344 and 0.389 respectively. Conclusion(s): To the best of our knowledge, xTrimoABFold++ achieved the state-of-the-art in antibody structure prediction. Its improvement on both accuracy and efficiency makes it a valuable tool for de novo antibody design, and could make further improvement in immuno-theory.
ABSTRACT
The creation of beautiful literature and art is one of humanity's most essential endeavours. The importance of literature as a component of the language-teaching curriculum has fluctuated over the last century with the popularity of various language-teaching pedagogies. Notwithstanding, it has recently seen a resurrection of appreciation for its effective utility in language acquisition. Covid-19 lockdown combined with the further progress of computer-assisted language learning has led to a gradual shift in the provision of literature-based language education to an online setting. Under this trend, Sandra Stadler-Heer and Amos Paran's edited chapter book Taking Literature and Language Learning Online: New Perspectives on Teaching, Research and Technology concentrates on a particular component of this transfer process, namely the interaction between literature and language learning. This book review provides an overview of this volume.
ABSTRACT
Amaç: COVID-19 sebebi ile ilan edilen pandemi süreciyle birlikte ülkemizde dil ve konuşma terapisi alanında tele-terapi hizmetinin kullanımında artış gözlenmiştir. Bu araştırma kapsamında vakaların bu süreç içerisinde aldıkları tele-terapi hizmetlerindeki memnuniyet düzeylerinin incelenmesi amaçlanmıştır. Çalışmada, dil ve konuşma terapisi alanında tele-terapi hizmeti alan bireylerin, terapiye yönelik memnuniyet düzeylerinin aldıkları tele-terapi seansı sayısına ve bozukluk türlerine göre incelenmesi hedeflenmiştir. Yöntem: Bu çalışma 0-64 yaş aralıǧında, 42 katılımcıdan (24E, 18K) alınan veriler doǧrultusunda oluşturulmuştur. Araştırmacılar tarafından hazırlanan "Dil ve Konuşma Bozukluklarında Tele-Terapi Danışan Memnuniyet Anketi" katılımcılara çevrimiçi platformlar aracılıǧı ile ulaştırılmıştır. Hazırlanan anket, 26 soru ve altı alt boyuttan oluşmaktadır. Bu alt boyutlar;"Terapistin Yetkinliǧi", "Íletişim Yeterliliǧi", "Erişilebilirlik ve Ödemeler", "Tele-terapiye Yönelik Donanım", "Genel Tele-terapi Memnuniyeti" ve "Anket Toplam Puan" olarak düzenlenip, analizleri gerçekleştirilmiştir. Elde edilen veriler, normal daǧılıma uygun olmadıǧı (Shapiro Wilk test;p <. 05) için verilerin istatistiksel analizi Mann Whitney U ve Kruskal Wallis testleri kullanılarak gerçekleştirilmiştir. Sonuçlar %95 güven aralıǧında, anlamlılık ise p < .05 düzeyinde deǧerlendirilmiştir. Bulgular: Analizler sonucunda bozukluk türü, alınan tele-terapi seansı sayısı deǧişkenlerine göre "Íletişim yeterliliǧi" alt boyutu dışında diǧer alt boyutlar ve toplam skorda anlamlı farklılık bulunmamıştır. "Íletişim yeterliliǧi" alt boyutunda akıcılık bozuklukları-konuşma sesi bozuklukları (Mann Whitney U test;p = ,044 < ,05) ile akıcılık bozuklukları-ses bozuklukları (Mann Whitney U test;p = ,019 < ,05) olan katılımcılar arasında istatistiksel anlamlılık ortaya çıkmıştır. Sonuç: Çalışmamıza katılan bireylerin bozukluk türü, terapistin yetkinliǧi ve alınan tele-terapi seansı sayısı deǧişkenlerine göre tele-terapi memnuniyetleri arasında anlamlı bir farklılık bulunmamaktadır. Yalnızca akıcılık bozuklukları -konuşma sesi bozuklukları ile ses bozuklukları olan katılımcıların "Íletişim yeterliliǧi" alt boyutunda anlamlı derecede daha yüksek puanlar verdikleri sonucuna ulaşılmıştır. Elde edilen sonucun iki grup arasındaki katılımcı sayılarından kaynaklandıǧı düşünülmektedir. Bu çalışma kapsamında ülkemizde tele-terapinin memnuniyetine yönelik bilgilerin ilk verilerine ulaşılmıştır. Bu çalışmanın katılımcı sayısının arttırılarak tekrar edilebileceǧi düşünülmektedir.Alternate :Purpose: Due to the COVID-19 outbreak, the usage of tele-therapy services has been increased in Turkey. There also seems to be an increase in the use of tele-therapy in speech and language pathology services. Therefore, the satisfaction levels of the clients in tele-therapy appears to be an important subject to examine. The aim of this study was to investigate the satisfaction levels in individuals who receive tele-therapy services for speech and language therapy. The data has been examined based on tele-therapy sessions the participants received and, the type of disorder they had. Method: This study is based on data from 42 participants (24 men, 18 women). The "Tele-therapy Client Satisfaction Questionnaire in Speech and Language Disorders" was prepared by the researchers and delivered to the participants through online platforms. The questionnaire consists of 26 questions and six sub-dimensions. These sub-dimensions "Therapist's Competence", "Communication Adequacy", "Accessibility and Payments", "Equipment for Tele-therapy", "Generalized Tele-therapy Satisfaction", and " Questionnaire Total Point" were analyzed. Since the data did not show normal distribution (Shapiro Wilk test;p < .05), the statistical analysis was carried out u ing non-parametric Mann Whitney U and Kruskal Wallis tests. The results were evaluated at a 95% confidence interval, and significance was evaluated at p < .05 level. Results: The results revealed no significant difference between the sub-dimensions and total score, except for the "Communication competence" sub-dimension, based on the variables of the type of disorder and the number of tele-therapy sessions received. In the "Communication Adequacy" sub-dimension, a statistical significance was found among the participants with fluency disorders-speech sound disorders (Mann Whitney U test;p = .044 < .05) and fluency disorders-voice disorders (Mann Whitney U test;p = .019 < .05). Conclusion: According to the variables in our study;type of disorder, the competence of the therapist, and the number of tele-therapy sessions received, there is no significant difference between the satisfaction of the tele-therapy in speech and language services. It was concluded that the participants with fluency disorders, speech sound disorders, and voice disorders gave significantly higher scores on "Communication Adequacy". It is thought that the result obtained is due to the number of participants between the two groups. Within the scope of this study, the first data on the satisfaction of tele-therapy in Turkey was reached. It is thought that this study can be repeated by increasing the number of participants. Future studies may also examine the satisfaction levels of participants with speech and language disorders separately.
ABSTRACT
Due to the outbreak of COVID 19, an online bilingual curriculum was conducted via "Google Meet." The learning material was developed and implemented by using a smartphone application, STEMUP, based on augmented reality (AR) and automatic speech recognition (ASR) technologies. This study investigated the oral performance and perceptions of learning with STEMUP of ninety non-English major students from several colleges at a technical university in Taiwan. Data were collected from pre- and post-tests and a questionnaire survey. Results indicated that students significantly improved their oral performance and recorded their positive perceptions. Students' oral performance significantly depended on their English proficiency. Their perceptions were not significant related to their English proficiency, gender, or college. Instant feedback and evaluation provided by ASR technology and online "Google" text-to-speech service both embedded in STEMUP helped students notice, modify and improve their listening and speaking skills. They were satisfied with the bilingual curriculum, which helped them increase understanding about content knowledge by the teacher's explanation in Chinese, and improve English listening and speaking skills by learning with STEMUP. This study is a good start in creating an interactive and communicative learning environment where translanguaging is effectively integrated with innovative technologies.
ABSTRACT
Our charity's mission is dedicated to beating blood cancer by funding research and supporting those affected. Since 1960, we have invested over 500 million in blood cancer research, transforming treatments and saving lives. Since 2015 there has been a Support Services team within the charity. This service was established to provide information that the blood cancer community can trust, in a language they can understand. By connecting and listening to our community they deepen our understanding and help shape our work. Research suggests that blood cancer patients are more likely than any other patients to leave their diagnosis appointment feeling they do not fully understand their condition. Our service can often consolidate the information given by clinicians. Patients also need advice and support on how to adapt to day-to- day life after their diagnosis. There are challenges that are unique to blood cancer, such as living with cancer as a chronic condition, being on 'watch and wait' or fluctuating remissions and relapses. In 2023 the Support Services team have a 7 day presence on our phone line, email and social media platform where people can communicate with one of our trained blood cancer support officers, or one of three Registered Nurses, all who can provide information about blood cancer diagnosis and help with emotional and practical support. We also run an online community forum where people affected by blood cancer can connect, share experiences and provide peer support. The highly experienced haematology nurses provide a clinical aspect to the support of the Blood Cancer Community that enhances the established patient centred support given historically by the charity. The nurses advanced knowledge and experience of haematological cancers, treatments, side effects, holistic care and NHS process can further guide the community. This is in addition to the invaluable information from their treatment teams. In 2023 the Support Services team are now reaching thousands of the blood cancer community. We understand that in the past 3 years the COVID-19 pandemic and the work of our charity around this will have influenced the significant increase in contacts but equally the robust and trusted services provided through this charity has contributed too.
ABSTRACT
The coronavirus outbreak has resulted in unprecedented measures, forcing authorities to make decisions related to establishing lockdowns in areas most affected by the pandemic. Social Media have supported people during this difficult time. On November 9, 2020, when the first vaccine with an efficacy rate over 90% was announced, social media reacted and people around the world began to express their feelings about this vaccination. This paper aims to analyze the dynamics of opinion on COVID-19 vaccination, in which the civil society is highly manifested in the vaccination process. We compared classical machine learning algorithms to select the best performing classifier. 4,392 tweets were collected and analyzed. The proposed approach can help governments create and evaluate appropriate communication tools to provide clear and relevant information to the general public, increasing public confidence in vaccination campaigns. © 2022 Copyright for this paper by its authors.
ABSTRACT
Background and Objectives: The decline in GDP caused by the global economic recession of 2008 and that caused by the COVID-19 pandemic has resulted in the poor economy of countries around the globe with increased rates of unemployment and adverse job conditions. This systematic review aims to identify the impact of a Financial crisis on Psychological well-being, Life satisfaction, Health Satisfaction, and Financial Incapability. Methodology: The literature included in the review was searched from Feb 1, 2023, to March 26, 2023, by using the PUBMED database as the search engine. Studies discussing the impact of the financial or economic crisis on psychological well-being, Health, Life satisfaction, and Financial Incapabilities published in the English Language were included in this review whereas systematic reviews and metanalysis, case reports, articles published in languages other than English and articles with limited access were excluded. Result(s): Of the 26 articles found eligible for the study, there were 22 Quantitative studies, 2 qualitative studies, and 2 Mixed Method Studies. Most of the articles included in this study discussed the Global Economic crisis caused by COVID-19 and the Global Financial Crisis of 2008. Almost 80% of the studies included in this review discussed psychological well-being and the prevalence of psychological disorders including Depression, Anxiety, Stress, Fear, Loneliness, Burnout, and Suicide whereas the rest of the articles discussed mortality regarding mental disorders. Conclusion(s): Financial crisis or economic recession results in an increased prevalence of common mental disorders affecting psychological well-being by increasing rates of unemployment and adverse job conditions. Policymakers with competitive financial behavior and knowledge are essential elements for psychological well-being and life satisfaction.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.
ABSTRACT
On social media, misinformation can spread quickly, posing serious problems. Understanding the content and sensitive nature of fake news and misinformation is critical to prevent the damage caused by them. To this end, the characteristics of information must first be discerned. In this paper, we propose a transformer-based hybrid ensemble model to detect misinformation on the Internet. First, false and true news on Covid-19 were analyzed, and various text classification tasks were performed to understand their content. The results were utilized in the proposed hybrid ensemble learning model. Our analysis revealed promising results, establishing the capability of the proposed system to detect misinformation on social media. The final model exhibited an excellent F1 score (0.98) and accuracy (0.97). The AUC (Area Under The Curve) score was also high at 0.98, and the ROC (Receiver Operating Characteristics) curve revealed that the true-positive rate of the data was close to one in this model. Thus, the proposed hybrid model was demonstrated to be successful in recognizing false information online. © 2022 IEEE.
ABSTRACT
How teachers creatively adopted and adapted to the effects of the COVID-19 outbreak is at the heart of the findings presented in this chapter. With the support of the Avenue-LearnIT2teach project, English Second Language (ESL) teachers in Canada enabled the rapid response of many Language Instruction for Newcomers to Canada (LINC) programs to site closures, resulting in an unprecedented uptake of online learning (OL) in a matter of weeks. The project rapidly changed course to support LINC teachers to adopt blended learning (BL) courseware and adapt teaching practices to the new OL reality. This chapter discusses the impact of the project's efforts to meet the surge in demand in teacher training and learner courseware for these online immigrant settlement and language learning programs. The project's rapid response to onsite LINC program closures during the COVID-19 crisis is reviewed. As a result of the disruptions to in-person program delivery, the focus of the project has shifted from blended learning (BL) to online learning (OL) by adapting its formal and informal professional development (PD) offerings. Findings with respect to the surge in demand for teacher training, course development, and mentoring are presented. Feedback from teachers on the "front lines" further illustrates teachers' OL uptake. The chapter also addresses the impact of formal and informal PD provided by a committed team of mentors as well as the importance of teacher presence in online program delivery. Implications and recommendations with respect to rapid responses in situations of crises conclude the chapter. © Springer Nature Switzerland AG 2021. All rights reserved.
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This article explores the future of language teaching in the light of recent developments. It is set against the background of the COVID-19 pandemic, which accelerated technology-related changes within the field. The article outlines factors that have contributed to a shift in the role of language teachers, followed by a depiction of the transformation observed at three distinct points in time during the pandemic. Trends in the changes are drawn from the data with the help of direct quotes, categories of responses, and vignettes representing aggregated language teacher voices. Finally, based on the uncovered trends, we outline reasons for being optimistic about the future of our profession, and provide recommendations for language teachers and language educators to take charge of developments to co-create possible futures for our roles in the profession. © 2023, equinox publishing.
ABSTRACT
Aims: The COVID-19 pandemic presented new difficulties for integrated healthcare worldwide. Our study aims to highlight developing needs for cooperation while describing structures and practices of consultation liaison (CL) services established during pandemic across Europe. Method(s): The cross-sectional survey used an ONLINE self-developed 25-item questionnaire in four language versions (English, French, Italian, German). Dissemination was via national professional societies cooperating in EAPM, and heads of CL services from June to October 2021 Results: 259 hospital CL services took part in the study (28.0% response rate). 222 (85.7%) of these services reported providing COVID-19-related mental health care (COVIDpsyCare). Among them, 192 services (86.5%) reported the development of specialized COVID-psyCare co-operation arrangements. 135 services (50.8%) provided specific COVID-psyCare for patients, 85 (38.2%) for relatives, and 171 (77.0%) for staff, with 56.3%, 14.6%, and 23.7% of time resources invested for these groups, respectively. Interventions for hospital staff, commonly related to the liaison function of CL services, were rated as being the most helpful. Regarding newly emerging demands, 129 (58.1%) CL services stated a need for communication and support among themselves concerning COVID-psyCare, and 142 (64.0%) suggested certain adjustments or enhancements that they thought were crucial for the future. Conclusion(s): Specific structure to provide COVID mental health care for patients, their relatives, or staff were implemented in over 80% of the participating CL services. Resources were primarily allocated for patient care, and staff assistance was mostly achieved through the implementation of specialized interventions. COVID psyCare's development calls for further intra- and interinstitutional cooperation.Copyright © 2023