Interactive Online Research Articles

Empirical insights into the interaction effects of groups at high risk of depression on online social platforms with NLP-based sentiment analysis

With the proliferation of digital technology and the increasing prevalence of social media, some users at high risk of depression have opted to seek solace, acceptance, and assistance in online communities. However, the extant research is deficient in terms of the segmentation of groups, particularly subcultural groups. By analyzing the “Super Hashtags” and “Tree Hole” groups on Sina Weibo from January to March 2023 using a crawler and the ERNIE 3.0-Base model for sentiment analysis, the study uncovers distinct sentiment profiles and interaction patterns, revealing significant correlations between interaction metrics and sentiment levels. The findings indicate that while there are no significant differences in sentiment levels between the two communities, the “Tree Hole” community exhibits greater sentiment variability. Moreover, the study identifies that interaction behaviors are closely linked to sentiment states, emphasizing the importance of understanding the complex dynamics between online interactions and mental well-being. These insights contribute to the development of more effective support mechanisms within online platforms for individuals at risk of depression.

Model predictive complex system control from observational and interventional data

Complex systems, characterized by intricate interactions among numerous entities, give rise to emergent behaviors whose data-driven modeling and control are of utmost significance, especially when there is abundant observational data but the intervention cost is high. Traditional methods rely on precise dynamical models or require extensive intervention data, often falling short in real-world applications. To bridge this gap, we consider a specific setting of the complex systems control problem: how to control complex systems through a few online interactions on some intervenable nodes when abundant observational data from natural evolution is available. We introduce a two-stage model predictive complex system control framework, comprising an offline pre-training phase that leverages rich observational data to capture spontaneous evolutionary dynamics and an online fine-tuning phase that uses a variant of model predictive control to implement intervention actions. To address the high-dimensional nature of the state-action space in complex systems, we propose a novel approach employing action-extended graph neural networks to model the Markov decision process of complex systems and design a hierarchical action space for learning intervention actions. This approach performs well in three complex system control environments: Boids, Kuramoto, and Susceptible-Infectious-Susceptible (SIS) metapopulation. It offers accelerated convergence, robust generalization, and reduced intervention costs compared to the baseline algorithm. This work provides valuable insights into controlling complex systems with high-dimensional state-action spaces and limited intervention data, presenting promising applications for real-world challenges.

The development of a model for monitoring the quality of online psychological and educational services by using automated analysis of user reviews

Introduction. Digitalization of education and healthcare is an inevitable response to the demands of society. However, it is associated with the emergence of many risks, and the need for regulation and evaluation of new online practices is becoming increasingly important. Questions about the quality of online services are becoming more and more significant, as well as the search for new methods to monitor large amounts of publicly available data about online interactions with helping professionals. The purpose of this study is to develop a model for monitoring psychological and educational online services through automated analysis of user reviews and feedback. Materials and methods. The sample for the study consisted of a variety of reviews about online psychological and educational services. A total of 24,351 reviews of psychologists' work and 6,812 reviews of tutors' work were uploaded. These reviews were ranked in order to identify levels of user satisfaction. We used the following methods to collect and analyze the data: 1) Automated data parsing to extract relevant feedback using the GraphQL API; 2) The TF-IDF (term frequency-inverse document frequency) method to identify the most important linguistic markers in the reviews; 3) The LDA (latent Dirichlet allocation) method for thematic modeling of the reviews. The results of the study. An empirical study of online reviews of psychological and educational services in accordance with this model revealed their thematic structure in four main areas: assessment of interaction (19.8%), assessment of results (26%), organization of professional interaction (20.4%), and assessment of professional skills relevant to clients (29.1%).The main characteristics that users perceive in psychological online services are: the importance of comfortable communication (21.9%), inclusiveness (13.9%), and specialist experience (5.9%). Additionally, the ability to structure a request is also significant (19.8%). The result of evaluating the psychologist's work can be seen in user reviews. Some of the most common responses include: understanding the problem (18.5%), seeing the issue from a different perspective (6.7%), and feeling better (11.3%). Assessments of the quality of online education services include accessibility and clarity of presentation (29.5%), as well as confidence and flexibility in communication (6.1%). Additionally, finding a common language with students is also important (6.2%). Conclusion. The analysis of user feedback on educational and psychological online services can help to understand the directions for the development of work by helping specialists, create a system for monitoring non-specialized assistance, describe criteria for the training and retraining of specialists, and create educational programs for developing digital competence among psychologists and educators.

Exploring the effects of multiple online interaction on emotions of L2 learners in synchronous online classes

The decline in both the quantity and quality of interaction has emerged as a notable challenge in online learning. However, the definition of interaction quality remains unclear. This study clarifies it as a decrease in the breadth of interaction, which refers to interaction that can only cover a smaller number of learners. To address this, a synchronous interaction modality, termed Multiple Online Interaction (MOI), based on Zoom's interactive tools, was introduced. In a quasi-experiment involving 58 Chinese L2 learners (with 30 beginner and 28 intermediate students), emotions were assessed using the Brief Mood Introspection Scale (BMIS) while real-time emotional dynamics were revealed through the analysis of 5129 facial expression images during a 35-min synchronous class. MOI participants reported higher levels of Lively and Happy but also experienced more Nervous and less Calm. These emotional dynamics, tracked through expression recognition technology, demonstrate that MOI's impact is primarily observed during the first Grammar & Practice section of the teaching. The empirical findings of this study provide practical insights for educators aiming to conduct effective online teaching in the future.

Exploring how video conferencing impacts students' cognitive, emotional, and behavioral engagement

Video conferencing has become an essential tool in the realm of education, offering educators a plethora of features to enhance student learning. This study delved into the comparative impact of video conferencing and Learning Management Systems (LMS) on student engagement in online education. The primary objective was to discern the most effective mode of communication for fostering student engagement in online learning, examining cognitive, emotional, and behavioral dimensions of engagement. The researchers used a quasi-experimental design with a historical cohort control group to compare the effectiveness of Zoom and Moodle (LMS) on student engagement. The study involved English education students from a private university in Indonesia, with 20 students in each group. Data collection included recording online interactions, conducting semi-structured interviews, and administering a Likert-style survey. Data analysis involved content analysis, thematic analysis, and the Mann-Whitney U test. The findings underscored the advantages of utilizing Zoom, particularly in nurturing interpersonal relationships among students. Notably, the platform enhanced intimacy and interactivity within the learning environment, bolstering students' intrinsic motivation. Moreover, indicators such as creativity and idea exchange pointed towards heightened cognitive engagement facilitated by Zoom. Additionally, Zoom emerged as a practical tool for fostering social interaction and stimulating higher-order thinking during discussions. Consequently, these results provide compelling evidence supporting the integration of Zoom to enrich learning experiences and promote deeper engagement among students, both practically and theoretically.

[Translated article] Bibliometric Study of the Advances Made in Clinical Dermatological Research in Spain from 2015 through 2021: Update of the MaIND Project and Interactive Online Map

IntroductionA clinical dermatological research was conducted in Spain from 2005 through 2014 as part of the MaIND project with the provinces or centers with the highest number of published articles. However, a low level of evidence in scientific production was confirmed as the overall result. The aim of this study is to update the Spanish clinical dermatological research in bibliometric terms from 2015 through 2021 with comparisons between both periods of time. Material and methodsWe conducted a bibliometric study to replicate the methodology used in the article to be updated. We included articles whose corresponding authors’ affiliation was a Spanish dermatological center, which met the criteria for clinical research in dermatology, including a level of evidence ≤4. ResultsA total of 1,674 out of the 10,199 articles met the inclusion criteria. An interactive map representing quantitative and qualitative indicators calculated for the 2005-2021 is presented here. In the study period, we found an increasing trend both in the number of published articles (P<.002) and in the mean number of citation-years per article (P<.01). A total of 22 of the articles had a level of evidence >4, with a positive trend towards more articles having a higher level of evidence (P<.03). ACTAS DERMOSIFILOGRÁFICAS still maintains its position as the journal with the highest number of articles received (18%, a total of 302 articles). ConclusionsThe results of this study show that, in Spain, the scientific production of dermatology represents an upward trend in quantity, impact, and level of evidence.

Evaluating the feasibility and effectiveness of an LGBTQ+ cultural humility training for community mental health providers

BackgroundLGBTQIA+ patients face significant physical and mental health disparities, and providers often lack the training and knowledge to meet their needs. PurposeThe purpose of this quality improvement project was to evaluate the feasibility and effectiveness of an LGBTQIA+ cultural humility training program. MethodsUsing a pre-posttest design, 20 community mental health center employees completed surveys on knowledge, attitudes, and skills related to working with LGBTQIA+ patients before and after completion of an interactive online training module. ResultsResults showed statistically significant improvement in clinical preparedness. DiscussionFurther research is needed to determine the impact of improved provider knowledge and skills on patient outcomes.

737. ETHNIC, GENDER AND TUMOR-SPECIFIC ASSESSMENT OF BODY COMPOSITION IS CRITICAL FOR CLINICAL RELEVANCE IN PATIENTS UNDERGOING THERAPY FOR ESOPHAGEAL

Abstract Background Growing evidence has supported a role for body composition in predicting survival in patients undergoing esophagectomy. A contemporary meta-analysis of published data (n=44 studies) conducted for this study confirmed an association between reduced muscle mass at diagnosis and worse overall survival (HR 1.72, 95%CI 1.49-1.97). Variation in methods of assessing and defining parameters of body composition remain however an important barrier to the wider adoption in routine clinical practice. This is particularly pertinent in esophageal cancer due to known sex, biological and geographical difference in tumor subtypes. This study seeks to define baseline variation in body composition parameters and to report their association with 90-day and overall survival in a large international cohort of patients undergoing esophagectomy for cancer. Methods Patients who underwent esophagectomy in fourteen high-volume centers between January 2007 to December 2019 were eligible for inclusion. Survival data were included up until June 2022. Skeletal muscle, visceral and subcutaneous adipose tissues within CT images, acquired at the time of diagnosis, were analyzed in accordance with a standardized protocol. Results 1716 patients were recruited to this study from three global regions: North America (n=386;22.5%), Europe (n=940;54.8%) and Asia (n=390;22.7%). Patients were predominantly male (79.5%) and adenocarcinoma was the most common histological subtype (66.6%). Wide variation of skeletal muscle (17.1-83.5cm2), visceral adiposity (0.2-170.1cm2) and subcutaneous adiposity (0.2-216.8cm2) was observed at presentation. Characteristics significantly associated with levels of muscle and adiposity were global region, sex, age, and histological subtype (P&amp;lt;0.001) (Figure 1). Compared to adenocarcinoma, squamous cell carcinoma was associated with significantly lower levels of muscle and adiposity, a finding that was independent of global region, sex, and age using a multivariable linear regression model (p&amp;lt;.0001). Median follow-up was 71.3 (95%CI 69.1-73.5) months with a median overall survival of 60.9 (95%CI 53.0-68.9) months. Reduced skeletal muscle and an excess of total adiposity at the time of diagnosis was associated with worse 90-day mortality and long-term survival. An interactive online survival prediction tool was developed to provide personalized survival estimates based on relevant predictors including skeletal muscle, total adiposity at diagnosis and other tumor and patient specific variables. Conclusions This is the first and largest study to adopt standardized methods to define international variation in parameters of body composition in esophageal cancer patients. Findings corroborate the potential role of body composition as a method of prognostication in esophageal cancer and presents a on-line tool for convenient integration into clinical practice.

The impact of online interaction and information technology accessibility on academic engagement among international undergraduate students in Chinese universities: The mediating effect of learning interest

Academic engagement was recognized as a crucial predictor to measure the effectiveness of online teaching of international students. Therefore, this study established a mediating model to explore the mechanism underlying of interaction and information technology accessibility on academic engagement of international students, as well as the impact of learning interest on these mechanisms with the context of online teaching. Using a stratified random sampling method, 1895 international students from 32 Chinese universities were selected. These international students had completed the academic engagement scale, interaction scale, information technology accessibility scale, and learning interest scale. The study variables were analyzed in sequence for reliability and validity, common method biases test, correlation analysis, structural equation model testing, and bias-corrected percentile Bootstrap testing. The results revealed that online interaction positively affected the academic engagement of international students in Chinese universities (β= 0.35, p < 0.001), and learning interest played a partial mediating role between online interaction and academic engagement (indirect effect = 0.10, 95 % Boot CI = [0.06, 0.13], p < 0.001). Information technology accessibility did not have a direct impact on academic engagement (β= 0.06, p > 0.05); but learning interest played a complete mediating role between information technology accessibility and academic engagement (indirect effect = 0.09, 95 % Boot CI = [0.05, 0.11], p < 0.001). The results of Bootstrap showed that the mediating effects within the model were significant. The findings of this study explored the potential mechanism underlying the online academic engagement of international students in Chinese universities, and provided empirical evidence for universities and educators to implement differentiated learning support, assist international students in adapting to online learning styles, and stimulate the endogenous motivation of students' learning.

High-resolution three-dimensional atlas of congenital heart defects based on micro-CT images of human postmortem wax-infiltrated heart specimens

IntroductionPostmortem heart specimens are essential for education and research on the anatomy, morphology, and pathology of congenital heart defects. However, such specimens are rarely obtained these days, and the specimens stored in formalin are inexorably deteriorating. This study aimed to develop methods to archive three-dimensional data of rare human heart specimens and to publish the data. MethodsAll wax-infiltrated human postmortem heart specimens stored in the Cardiac Registry, Boston Children's Hospital were scanned using microfocus computed tomography (X-Tek HMXST225, Nikon Metrology, Inc.), and reproduced using a three-dimensional printer (Form 3B, Formlabs Inc.). The digital models were published as an interactive three-dimensional online atlas. The resolution of the three-dimensional data was evaluated. ResultsThe primary diagnoses in the 88 specimens included in the study include normal cardiac anatomy (11 cases), transposition of the great arteries {S,D,D} (11 cases), ventricular septal defect (10 cases), double-outlet right ventricle (9 cases), hypoplastic left heart syndrome (9 cases), and common atrioventricular canal (7 cases). Twenty-five cases (28%) underwent previous surgical or percutaneous interventions to the heart, including Mustard procedure (1 case), Senning procedure (2 cases, one was performed on a postmortem heart specimen). The median voxel size of the three-dimensional data was 40.5 um (IQR, 32.8–64.2). All intracardiac structures were precisely reproduced as digital and physical three-dimensional models. ConclusionsThe methods and resultant models were considered useful for archiving and furthering the utilization of these invaluable specimens. The atlas is available at https://www.sketchfab.com/heartmodels/collections.

Not our kind of crowd! How partisan bias distorts perceptions of political bots on Twitter (now X).

Social bots, employed to manipulate public opinion, pose a novel threat to digital societies. Existing bot research has emphasized technological aspects while neglecting psychological factors shaping human-bot interactions. This research addresses this gap within the context of the US-American electorate. Two datasets provide evidence that partisanship distorts (a) online users' representation of bots, (b) their ability to identify them, and (c) their intentions to interact with them. Study 1 explores global bot perceptions on through survey data from N = 452 Twitter (now X) users. Results suggest that users tend to attribute bot-related dangers to political adversaries, rather than recognizing bots as a shared threat to political discourse. Study 2 (N = 619) evaluates the consequences of such misrepresentations for the quality of online interactions. In an online experiment, participants were asked to differentiate between human and bot profiles. Results indicate that partisan leanings explained systematic judgement errors. The same data suggest that participants aim to avoid interacting with bots. However, biased judgements may undermine this motivation in praxis. In sum, the presented findings underscore the importance of interdisciplinary strategies that consider technological and human factors to address the threats posed by bots in a rapidly evolving digital landscape.

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.

Offline connections, online votes: The role of offline ties in an online public election

Building democratic communities and fostering inclusive participation is challenging, especially in participatory organisations where governance and sustained contributions are critical. This study explores the dynamics of election participation within the peer-production project Wikipedia, a prime example of an online collaboration model of democratic organisation where democratically elected administrators wield special rights. While previous research on online governance has predominantly focused on online interactions, this study shifts the spotlight to the influence of offline interactions occurring at various gatherings and meetings. Using fixed effects models and large-scale observational data spanning 20 years of offline and online actions, this study finds significant effects of offline meeting participation on users’ voting behaviour. It makes use of novel data sources to emphasise the significance of offline relationships in shaping online (democratic) processes and shows that traditional findings of political science and election research regarding social capital and social networks hold within an online context.

Emotional Digital Labor Among Young People Within the Context of Lumpencybertariat

Türkiye ranks among the countries with the highest rates of social media usage. Especially among the young population, the prevalence of social media usage reaches the highest rates. This article focuses on the formation of hate within the cultural production processes on social media among young population. The monopolization of social media platforms fosters an economic logic where hateful interactions gain exchange value within algorithmic distribution systems. The online activities of social media users are at risk of being drawn into a “discursive spiral of hate”. Algorithms direct social media activities towards emotional escalation and transform online interactions into the “emotional digital labor”. Thus, the digital cultural production is tended to be dominated by the “lumpencybertariat”. This lumpenization process poses a direct risk to young social media users. This article aims to outline the conceptual framework of the position of lumpencybertariat as the producer of emotional digital labor in the digital capitalism. The possibility of “emotional sustainability” as a potential tool to counter the risk of lumpenization in digital cultural production is discussed.

Project SIGNAL: A Dashboard for Supporting Community Confidence in Making Data-Driven Decisions.

Data dashboards have emerged as critical tools for surveillance and informing resource allocation. Despite their utility and popularity during COVID-19, there is a growing need to understand what tools and training are tailored to nonprofit community-based organizations that may partner with public health officials. In June 2021, the Rhode Island Department of Health and Brown University partnered to create Project SIGNAL (Spatiotemporal Insights to Guide Nuanced Actions Locally), which utilizes spatiotemporal analytics to identify Rhode Island's largest disparities in COVID-19-related outcomes (eg, testing, diagnosis, vaccinations) at the neighborhood level. Results were hosted in an interactive online dashboard (signal-ri.org) designed using principles of the CDC Clear Communication Index. The target audience included a network of 15 geographic areas called Health Equity Zones, funded by the health department to provide critical grassroots public health programs to address social, health, and economic outcomes in their communities. To disseminate the dashboard, a 6-hour virtual workshop series was created to train leaders to use the dashboard and increase their confidence in understanding common public health data terminology and concepts and better prepare attendees for rapid decision making during future public health emergencies. The Project SIGNAL dashboard was launched in August 2022 and has been accessed over 7500 times. A total of 84 community leaders were trained to use this dashboard, increasing their confidence in applying common public health metrics to make decisions about their COVID-19-related activities. While several studies have outlined best practices for data dashboards, this is among the first to examine incorporating these practices into a spatiotemporal decision tool designed specifically for community organizations. Project SIGNAL demonstrates that by incorporating design best practices and pairing data dashboards with hands-on training, we can empower community leaders to utilize advanced spatiotemporal methods to identify health disparities and take localized action.

The virtual disengagement hypothesis: A neurophysiological framework for reduced empathy on social media.

Social media is a hotbed of interpersonal conflict and aggression. Platforms such as Twitter and Instagram are used by more than 62% of the global population, facilitating billions of user interactions every day. However, many of these exchanges involve hostile, insensitive, and antisocial behaviors. This raises the question: is empathy blunted on social media? Substantial evidence demonstrates that humans tend to behave more rudely in virtual settings, but considering the scarcity of physiological data collected under these circumstances, it remains unclear how the neural systems guiding social cognition and empathy may function differently in online interactions. We propose the "Virtual Disengagement Hypothesis," a conceptual framework to explain the prevalence of hostility online. It posits that interactions occurring on social media omit social cues that facilitate the assessment of a social partner's affective state, such as facial expressions and vocal tone, and thus fail to sufficiently recruit brain circuitry involved in empathy, such as the anterior cingulate cortex, insula, and prefrontal cortex. Additionally, interactions on social media occur asynchronously and in a "replayed" context, which may further limit recruitment of empathy systems. As a result of this diminished sensitivity to others' states, users may be predisposed to inconsiderate or outright antisocial behaviors. Given the massive and growing base of users on these platforms, we urge researchers to expand efforts that focus on neuroimaging in virtual settings with a particular emphasis on developing social media-relevant behavioral designs.

A visual digital twin framework based on residual-based fourier neural operator online simulation method

ABSTRACT To enjoy a wonderful cooking experience in a smart kitchen, users and designers need a visual interaction platform. This paper proposes a DT framework incorporating data processing, flow field online simulation, equipment monitoring, interaction and visualization. Specifically, the DT online simulation and visualization of the kitchen fume flow field serve as the foundation for appliance design and control. Additionally, users can gain deeper insight into the state and change trends of the kitchen. To address the online simulation of the flow field, a RFNO online simulation method is proposed. In addition, this paper proposes an Echarts-based 2D and UE5-based 3D flow field visualization method to enable dynamic visualization and interaction of the flow field. The proposed DT framework was successfully verified in the case of the smart kitchen, demonstrating its efficiency and effectiveness.

A data science pipeline applied to Australia's 2022 COVID-19 Omicron waves

The field of software engineering is advancing at astonishing speed, with packages now available to support many stages of data science pipelines. These packages can support infectious disease modelling to be more robust, efficient and transparent, which has been particularly important during the COVID-19 pandemic. We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic. We aimed to identify the key processes relevant to COVID-19 transmission dynamics and thereby develop a model that could quantify relevant epidemiological parameters.The pipeline's advantages include markedly increased speed, an expressive application programming interface, the transparency of open-source development, easy access to a broad range of calibration and optimisation tools and consideration of the full workflow from input manipulation through to algorithmic generation of the publication materials. Extending the base model to include mobility effects slightly improved model fit to data, with this approach selected as the model configuration for further epidemiological inference. Under our assumption of widespread immunity against severe outcomes from recent vaccination, incorporating an additional effect of the main vaccination programs rolled out during 2022 on transmission did not further improve model fit. Our simulations suggested that one in every two to six COVID-19 episodes were detected, subsequently emerging Omicron subvariants escaped 30–60% of recently acquired natural immunity and that natural immunity lasted only one to eight months on average. We documented our analyses algorithmically and present our methods in conjunction with interactive online code notebooks and plots.We demonstrate the feasibility of integrating a flexible domain-specific syntax library with state-of-the-art packages in high performance computing, calibration, optimisation and visualisation to create an end-to-end pipeline for infectious disease modelling. We used the resulting platform to demonstrate key epidemiological characteristics of the transition from the emergency to the endemic phase of the COVID-19 pandemic.

Care Experience, Mental Health and Social Media: Implications for Practice from Conversations with Professionals and Care Leavers

There is increasing need to strike a balance between minimizing online risks and encouraging independence and freedom of interaction amongst the young adult population, particularly those with preexisting vulnerabilities. This paper presents the findings from a study exploring how professionals working with care leavers understand social media and perceive their role in recognizing and responding to the online needs of this group. Qualitative data was collected during focus groups, arts-based workshops, and interviews with 17 professionals. Thirteen young adults with experience of leaving the care system in Scotland also provided insights into the impact of social media on their mental health and personal relationships. These multiple voices highlight that professionals could improve their understanding of social media platforms by moving away from risk management and harm minimization to adopt more individualized ways of enhancing online relationships. These views are reiterated by care leavers who perceive social media interactions as both a source of support and a cause of anxiety during complex transitions. Drawing upon the health and social work literature suggests that professionals should work in partnership with care leavers to establish training that acknowledges lived experiences and prioritizes resilience and social capital in the development of positive online interactions.

Teacher practices regarding teaching presence in Vietnamese tertiary online distance education programmes

This study explored how teachers adapt their agentic teaching practices in the context of online distance education programmes in Vietnam. A single-institution case study design was used to collect data through online individual semistructured interviews that were conducted via Zoom with five teachers from a variety of disciplines who had been teaching in online distance education programmes at the Centre for E-Learning at a Vietnamese higher education institution. Data analysis highlighted the role of teachers’ agentic teaching presence in the pedagogy used in online distance education programmes. Specifically, the teachers exhibited acceptance of an approach to organising their practice that involved adherence to course outlines that had previously been designed and approved without questioning and modifications. However, the results further revealed the agentic direct instruction strategies used by teachers in terms of the varied delivery of course content, student feedback and assessments, which exhibited a stronger emphasis on facilitating online classroom discourse and interactions via various channels with the goal of enhancing students’ learning support, experience, and engagement. The findings of this research thereby affirm the pivotal role played by teaching presence in the setting investigated in this research in particular as well as in the context of online distance education in general. The study highlights the need for further interconnections to be established to link multiple aspects of social, cognitive and teaching presence to the practices that teachers use to enhance students’ engagement and learning experience. The study also has pedagogical implications with regard to teaching in online distance education programmes that pertain not only to teachers’ classroom practices but also to their professional development.