Frequent Topics Research Articles

535 Translational science vs. translational research in CTSA pilot projects: characteristics and perceptions

OBJECTIVES/GOALS: NCATS requires that CTSA-funded pilot projects focus on translational science (TS) and evaluate the translational process. However, a consistent understanding of TS remains elusive. This gap is being addressed by a consortium of 12 CTSA hubs aimed at identifying distinctive features of TS and translational research (TR) proposals. METHODS/STUDY POPULATION: CTSA External Review Exchange Consortium (CEREC) is a reciprocal review collaboration among CTSA hubs. Reviewers were CEREC members from hubs that submitted CTSA applications (PAR-21-293); read the Notice of Funding Opportunity (NOFO) Clinical and Translations Science Pilot Module; and discussed TS with their hubs “a fair amount” or “quite a bit” and then they independently categorized proposals. Proposals were labeled TS or TR if reviewers reached a consensus on category assignment; without consensus, proposals were labeled unclassified. In addition to category assignment, reviewers commented about their classifications. R was used to evaluate the comments and create word clouds with phrases/themes that distinguished between the categories of proposals. RESULTS/ANTICIPATED RESULTS: Twelve CEREC participating hubs submitted 26 proposals, which were funded prior to the new NCATS TS requirements. Eight reviewers from distinct CEREC hubs evaluated and classified each proposal as TS or TR. Consensus (at least 87% agreement) was reached for 12 proposals, 6 TS and 6 TR. Reviewers provided comments describing the rationale for their classifications for 70% of the proposals. Qualitative analysis of the reviewers’ comments and rationale by classification (TS, TR, or unclassified) revealed common themes within and differences between groups and shed light on what defines TS and TR. The most frequent themes that distinguished TS from TR were generalizability across multiple diseases and a focus on increasing research efficiency. DISCUSSION/SIGNIFICANCE: NIH is focused on research that meets the new definition of TS. Investigators seeking to address this funding priority should explicitly state the relevance of their research to multiple diseases and to the acceleration of future research. Programs seeking to attract TS projects should instruct applicants to include this information.

Медный лик древней Америки: репрезентация мезоамериканских цивилизаций в американском pulp-журнале Weird tales в межвоенный период

In the Interwar period different form of Ancient civilization had been one the most frequent theme in American popular culture. Lost Indian civilization wasn’t exception, but this is-sue is still poorly investigate in the popular culture’s field. The article examines, based on John Cavelti's theory of for-mular fiction and John Saler’s “imaginary worlds”, the repre-sentation of pre-Columbian civilizations in one of the most significant American pulp magazines, Weird tales, and the ways in which their heritage is appropriated by American popular culture. We come to conclusion that representation of pre-Colombian indian civilization was within the general nar-rative of the ancient (like Egypt and Babylon), but had differ-ence in tropes. This concerned attention to the phenomenon of sacrifices. Also, the authors were anxious about issues of race, since the racist view of Latin Americans was a constitu-tive stereotype for many Americans. To prevent this problem from interfering with the appropriation of the Indian ancient heritage as uniquely American, the writers excluded the in-termediary in the person of a modern resident of Mexico. Mexico was represented as a poor, unstable country, just an epigone of its magnificent ancestors.

Insights from the Twittersphere: a cross-sectional study of public perceptions, usage patterns, and geographical differences of tweets discussing cocaine.

Cocaine abuse represents a major public health concern. The social perception of cocaine has been changing over the decades, a phenomenon closely tied to its patterns of use and abuse. Twitter is a valuable tool to understand the status of drug use and abuse globally. However, no specific studies discussing cocaine have been conducted on this platform. 111,508 English and Spanish tweets containing "cocaine" from 2018 to 2022 were analyzed. 550 were manually studied, and the largest subset underwent automated classification. Then, tweets related to cocaine were analyzed to examine their content, types of Twitter users, usage patterns, health effects, and personal experiences. Geolocation data was also considered to understand regional differences. A total of 71,844 classifiable tweets were obtained. Among these, 15.95% of users discussed the harm of cocaine consumption to health. Media outlets had the highest number of tweets (35.11%) and the most frequent theme was social/political denunciation (67.88%). Regarding the experience related to consumption, there are more tweets with a negative sentiment. The 9.03% of tweets explicitly mention frequent use of the drug. The continent with the highest number of tweets was America (55.44% of the total). The findings underscore the significance of cocaine as a current social and political issue, with a predominant focus on political and social denunciation in the majority of tweets. Notably, the study reveals a concentration of tweets from the United States and South American countries, reflecting the high prevalence of cocaine-related disorders and overdose cases in these regions. Alarmingly, the study highlights the trivialization of cocaine consumption on Twitter, accompanied by a misleading promotion of its health benefits, emphasizing the urgent need for targeted interventions and antidrug content on social media platforms. Finally, the unexpected advocacy for cocaine by healthcare professionals raises concerns about potential drug abuse within this demographic, warranting further investigation.

Robotic surgery across Latin America: a bibliometric analysis of research trends from 2009 to 2022.

The rise of robotic surgery throughout the world, particularly in Latin America, justifies an objective evaluation of research in this field. This study aimed to use bibliometric techniques to identify the research trends and patterns of robotic surgery in Latin America. The research strategy used the terms "Robotic," "Surgery," and the name of all the Latin American countries, in all fields and collections of Web of Science database. Only original articles published between 2009 and 2022 were included. The software Rayyan, Bibliometric in the R Studio, and VOSViewer were used to develop the analyses. After screening, 96 articles were included from 60 different journals. There was a 22.51% annual increase in the scientific production of robotic surgery in the period studied. The more frequent topics by specialty were: Urology (35.4%), General Surgery (34.4%), and Obstetrics and Gynecology (12%). International cooperation was observed in 65.62% of the studies. The Latin American institution with the highest production of manuscripts was the Pontificia Universidad Católica de Chile. Mexico, Chile, and Brazil were, in descending order, the nations with the highest number of corresponding authors and total citations. When considering the total number of articles, Brazil ranked ahead of Chile. Scientific production regarding robotic surgery in Latin America has experienced accelerated growth since its beginning, supported by the high degree of collaboration with leading countries in the field.

Research trends of computational thinking in mathematics learning: A bibliometric analysis from 2009 to 2023

This study presents a comprehensive overview of computational thinking (CT) research trends in mathematics learning from 2009 to 2023. To reach this aim, a bibliometric approach was used in this study to analyze the publication distribution pattern on CT focused on the following categories: research development, the most productive journals and countries, highly cited references, topic network, and thematic evolution map. A total of 276 articles retrieved from the Scopus database were analyzed and visualized through the Bibliometrix analysis package from R and VOSviewer software. The finding shows that since 2009, CT has been the subject of mathematics learning research, which has grown significantly since 2013. Regarding total publication in CT, Education and Information Technologies contributes as the most productive journal, and the United States places first among all countries. The article ‘computational thinking’ appears as the most widely referenced source. Moreover, the frequent topics network with CT are the integration of CT with programming, STEM, and coding. This result is analyzed further by the thematic evolution map showing CT research in STEM education, including mathematics, exhibits promising prospects for future development.

A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis

Artificial intelligence (AI) tools (in particular Large Language Models) have the potential to reduce the time needed to perform thematic analysis. To better understand their potential in the transportation field, we compare human-based to AI-based outcomes. Our findings indicate that AI tools, such as ChatGPT, could synthetize and summarize major topics present in our dataset regardless of previous user exposure to the subject or not. Nonetheless, caution is required as results might miss the nuance of less frequent themes. These tools could be used to accelerate the process under the supervision of researchers and practitioners given responder consent and the following of ethical practices.

The mixed-method approach to identify perceived reasons for increased procrastination among students during the first pandemic lockdown in Poland

The beginning of the COVID-19 pandemic brought about a sudden and significant change in the conditions of various academic activities. In the present study, we wanted to investigate the influence of the first pandemic lockdown on procrastination tendencies among Polish students. To achieve this goal we employed a mixed-method, embedded longitudinal study. In the quantitative part of the research, the same group of university students completed the procrastination questionnaire twice: a year before, and two months after the introduction of the first pandemic lockdown. The qualitative part included the open-ended questions about the perceived reasons for an observed change in a tendency to postpone tasks after the pandemic outbreak. Our analyses showed a significant increase in academic procrastination after the lockdown introduction. In particular, students reported a decrease in the study interest and lower working discipline. As the causes of higher procrastination during the lockdown period, students most frequently pointed out the reduced monitoring of work progress by supervisors and lower negative consequences of delaying tasks. The second most frequent theme in provided answers included difficulty in restraining from alternative activities and problems with focusing on tasks or ignoring distractions. Embedding qualitative and quantitative data gave a consistent picture of students' situation in the first lockdown and provided potential explanation for the exacerbation of procrastinatory behaviors after the pandemic outbreak.

Organizational learning capability: A bibliometric and content analysis based on Scopus data (1978–2023)

BACKGROUND: Organizational learning capability research has been gaining more attention. OBJECTIVE: Specifically, this paper examines annual trend publication, active journals, authors, institutions, nations, keywords, citation pattern and top cited articles over the past 45 years. It decides the frequent organizational learning capability topics and highlights future research directions. METHODS: A bibliometric was performed on 149 papers published between 1978–2023 from the Scopus database. A content analysis was also performed. RESULTS: Publication trends have exhibited growth over time. Learning Organization and Industrial Marketing Management are two key journals that publish organizational learning capability. Publications are contributed by Chiva, R. and Alerge, J. Universidad Jaume I and Universitat de València are the two main institutions that exert the influence over the publication. Spain has been contributing more publications. Citations pattern analysis revealed 158.78 citations per year and 7145 citations for 149 papers. Sixthly, publications use keywords such as “organizational learning”, “innovation”. Both highly cited articles accumulated 442 citations. CONCLUSIONS: The findings are useful for policy-makers seeking reference and evidence to guide them in designing organizational learning capability policies, implementing management actions and programs.

Analysis of Public Sentiment on COVID-19 Mitigation Measures in Social Media in the United States Using Machine Learning

Public sentiment can impact the implementation of public policies and even cause policy failure if public support is not received. Therefore, knowledge of public sentiment concerning new and emerging policies is critical for policymakers. During the coronavirus disease 2019 (COVID-19) pandemic, several precautionary measures have been suggested in an attempt to delay or mitigate the spread of the virus. This study presents a framework that applies natural language processing (NLP) techniques, such as sentiment and bigram analyses, to characterize the public sentiment on three prominent mitigation measures (mask wearing, social distancing, and quarantine) as shared by Twitter users in the United States. As part of the framework, we apply a bigram graph-based approach to visualize the most frequent topics in Twitter discussions during the COVID-19 pandemic. The objective is to provide insights into the most commonly discussed topics among Twitter users with similar demographic characteristics (e.g., age and gender). The sentiment and bigram analyses identified the most frequently discussed topics expressing both positive and negative sentiments among different age and gender groups. Discussions containing positive sentiment prevailed and revolved around the benefits of the measures and trust in the government, while the topics of negative sentiment involved conspiracy theories, skepticism, and distrust of government mandates. It is also notable that the discussions among people 19–29 and over 40 years old focus on government officials and political parties, benefits or inefficiency of mitigation measures, and conspiracy theories more often than other demographic groups. Our proposed approaches and results offer a novel and potentially valuable contribution to public policymakers.

Systematic online academic resource (SOAR) review: Pediatric respiratory infectious disease.

Free open access medical education (FOAM) resources have become increasingly popular in graduate medical education. Despite their accessibility, the assessment of FOAM resources' quality is challenging due to their decentralized nature and the diverse qualifications of their authors and distribution platforms. In this first pediatric systematic online academic resource (SOAR) review, we utilized a systematic methodology to aggregate and assess the quality of FOAM resources on pediatric respiratory infectious disease topics. We searched 177 keywords using FOAMSearch, the top 50 FOAM websites on the Social Media Index, and seven additional pediatric emergency medicine-focused blogs. Following a basic initial screen, resources then underwent full-text quality assessment utilizing the revised Medical Education Translational Resources: Impact and Quality (rMETRIQ) tool. The search yielded 44,897 resources. After 44,456 were excluded, 441 underwent quality assessment. A total of 36/441 posts (8% of posts) reached the high-quality threshold score (rMETRIQ ≥ 16). The most frequent topics overall were pneumonia and bronchiolitis. A total of 67/441 posts (15% of posts) were found to have a rMETRIQ score of less than or equal to 7, which may indicate poor quality. We systematically identified, described, and performed quality assessment on FOAM resources pertaining to the topic of pediatric respiratory infectious disease. We found that there is a paucity of high-quality posts on this topic. Despite this, the curated list of high-quality resources can help guide trainees and educators toward relevant educational information and suggest unmet needs for future FOAM resources.

The Type 1 & 2 systemic lupus erythematosus model: Perspectives of people living with systemic lupus erythematosus.

In the new Type 1 & 2 model for systemic lupus erythematosus (SLE), Type 1 SLE represents classic inflammatory manifestations, such as arthritis, while Type 2 SLE encompasses symptoms such as pain and fatigue where the relationship to inflammation is less clear. The objective of this study was to interview individuals living with SLE to determine the content and face validity of the Type 1 & 2 SLE model. We conducted a qualitative study using semi-structured interviews with a purposeful sample of participants who met classification criteria for SLE. Participants were asked to describe their experiences with Type 1 & 2 SLE symptoms and treatments, and they indicated if and how their personal experiences aligned with the Type 1 & 2 SLE model. All interviews were audio-recorded and transcribed; applied thematic analysis identified the most frequent and salient themes. We interviewed 42 participants with SLE. Type 2 SLE symptoms, such as pain and fatigue, were very common, with almost all participants experiencing some Type 2 symptoms at some point during their disease course. Participants described Type 1 SLE symptoms as being acute flares and life-threatening and Type 2 SLE symptoms as "everyday lupus" that affected their daily lives and were a dominant part of their SLE disease experience. Most participants stated they want their rheumatologists to discuss Type 2 symptoms during clinical appointments in order to address their full symptom experience. We demonstrated content and face validity of the Type 1 & 2 SLE model with people living with SLE. Participants in our study largely understood the model and felt it accurately reflected their experience living with SLE. Type 2 SLE symptoms are very common in individuals with SLE and impact patients' quality of life. Using the model to address Type 2 SLE symptoms allows the rheumatologist to incorporate the patient's perspective and provide patient-centered care.

Comparing GPT-4 and Human Researchers in Health Care Data Analysis: Qualitative Description Study.

Large language models including GPT-4 (OpenAI) have opened new avenues in health care and qualitative research. Traditional qualitative methods are time-consuming and require expertise to capture nuance. Although large language models have demonstrated enhanced contextual understanding and inferencing compared with traditional natural language processing, their performance in qualitative analysis versus that of humans remains unexplored. We evaluated the effectiveness of GPT-4 versus human researchers in qualitative analysis of interviews with patients with adult-acquired buried penis (AABP). Qualitative data were obtained from semistructured interviews with 20 patients with AABP. Human analysis involved a structured 3-stage process-initial observations, line-by-line coding, and consensus discussions to refine themes. In contrast, artificial intelligence (AI) analysis with GPT-4 underwent two phases: (1) a naïve phase, where GPT-4 outputs were independently evaluated by a blinded reviewer to identify themes and subthemes and (2) a comparison phase, where AI-generated themes were compared with human-identified themes to assess agreement. We used a general qualitative description approach. The study population (N=20) comprised predominantly White (17/20, 85%), married (12/20, 60%), heterosexual (19/20, 95%) men, with a mean age of 58.8 years and BMI of 41.1 kg/m2. Human qualitative analysis identified "urinary issues" in 95% (19/20) and GPT-4 in 75% (15/20) of interviews, with the subtheme "spray or stream" noted in 60% (12/20) and 35% (7/20), respectively. "Sexual issues" were prominent (19/20, 95% humans vs 16/20, 80% GPT-4), although humans identified a wider range of subthemes, including "pain with sex or masturbation" (7/20, 35%) and "difficulty with sex or masturbation" (4/20, 20%). Both analyses similarly highlighted "mental health issues" (11/20, 55%, both), although humans coded "depression" more frequently (10/20, 50% humans vs 4/20, 20% GPT-4). Humans frequently cited "issues using public restrooms" (12/20, 60%) as impacting social life, whereas GPT-4 emphasized "struggles with romantic relationships" (9/20, 45%). "Hygiene issues" were consistently recognized (14/20, 70% humans vs 13/20, 65% GPT-4). Humans uniquely identified "contributing factors" as a theme in all interviews. There was moderate agreement between human and GPT-4 coding (κ=0.401). Reliability assessments of GPT-4's analyses showed consistent coding for themes including "body image struggles," "chronic pain" (10/10, 100%), and "depression" (9/10, 90%). Other themes like "motivation for surgery" and "weight challenges" were reliably coded (8/10, 80%), while less frequent themes were variably identified across multiple iterations. Large language models including GPT-4 can effectively identify key themes in analyzing qualitative health care data, showing moderate agreement with human analysis. While human analysis provided a richer diversity of subthemes, the consistency of AI suggests its use as a complementary tool in qualitative research. With AI rapidly advancing, future studies should iterate analyses and circumvent token limitations by segmenting data, furthering the breadth and depth of large language model-driven qualitative analyses.

What Do My (Online) Friends Think? A Topic Modeling Approach to Identifying Patterns of Response to Self-Injurious Behaviors on Reddit

Objective Approximately 17% of adolescents and young adults will engage in non-suicidal self-injury (NSSI) at least once in their lifetime, leading the World Health Organization to identify self-injury as one of the top five public health concerns for adolescents. Despite the widespread prevalence of this behavior, NSSI continues to be heavily stigmatized in both medical and community settings, deterring many engaged in NSSI from seeking informal support from friends and family as well as formal psychological or psychiatric treatment. In contrast to the low rates of in-person help-seeking for NSSI, online support groups are highly utilized by those engaged in NSSI. Thus, an empirical study of responses to frequent, voluntary disclosure of NSSI on social media is needed to better understand how these communities meet the needs of those who self-injure. Method The current project used latent Dirichlet allocation to identify frequent and favored themes in response to self-injury content in the largest self-injury group on Reddit (over 100,000 members). Reddit, the 9th most visited website in the world, is a chat-based social media platform that has 430+ million active users and billions of site visits, with current estimates suggesting that ∼63% of the U.S. population are Reddit users. Results Identified themes included: (1) recovery encouragement; (2) provision of social and instrumental support; and (3) daily realities of living with NSSI. Responses that encouraged recovery received more upvotes on Reddit than any other type of comment. Conclusion These results can inform evidence-based, person-centered, dimensional treatments for NSSI. HIGHLIGHTS Responses to NSSI that encourage recovery resonated most with members of the group. Group members provided many social and instrumental NSSI supports to each other. Results provide insight into the real-time needs of those engaged in NSSI.

Understanding Patients' Negative Experiences with Telehealth: A Content Analysis of Survey Data.

Understanding differences in how demographic groups experience telehealth may be relevant in addressing potential disparities in telehealth usage. We seek to identify and examine themes most pertinent to patients' negative telehealth experiences by age and race in order to inform interventions to improve patients' future telehealth experiences. We performed a content analysis of Press Ganey patient experience surveys from adult patients at 17 primary care sites of a large, public healthcare system with visits from April 30, 2020 to August 27, 2021. We used sentiment analysis to identify negative comments. We coded for content themes and analyzed their frequency, stratifying by age and race. We analyzed 745 negative comments. Most frequent themes differed by demographic categories, but overall, the most commonly applied codes were "Contacting the Clinic" (n = 97), "Connectivity" (n = 84), and "Webside Manner" (n = 79). The top three codes accounted for >40% of the negative codes in each race category and >35% of the negative codes in each age category. While there were common negative experiences among groups, patients of different demographics highlighted different aspects of their telehealth experiences for potential improvement.

GRAY HAIR AND PINK SLIPS: AN ANALYSIS OF TWITTER RESPONSES TO GENDERED AGEISM

Abstract Popular, long-time Canadian broadcaster, Lisa LaFlamme, was fired in August 2022, with some observers suggesting that CTV National News did not renew her contract because she had “let her hair go gray” during the pandemic. Over the next several months, an international public outcry ensued on Twitter. Our study involved an analysis of over 400 of these tweets. Analyses revealed that over two-thirds of tweets indicated support for LaFlamme’s position, with nearly all the remaining tweets indicating neutral rather than negative positions. Frequent themes in the supportive tweets included assessments of her firing as undeserved and the actions of the news corporation as unjust. Calls to boycott the corporation also appeared. Other themes found in supportive tweets included ageism and sexism; however, references to sexism were somewhat more frequent than those to ageism. A theme appearing not only in supportive but also in neutral or oppositional tweets centered on beauty standards, with supportive tweets more likely to critique these standards’ sexist and ageist underpinnings. Our study extends the literature on gendered ageism by attending to collective responses to it. In contrast, prior studies have focused on individual-level experiences of and responses to gendered ageism. Our study also contributes to the hashtag activism literature, which has given little attention to efforts to dismantle age inequality.

The Hashtag #CharlasEducativas as a Teacher Affinity Space on Twitter

Twitter has positioned itself as one of the social networks most used by teachers, generating teacher affinity spaces for them to share and collaborate. This study analyses the hashtag #CharlasEducativas, to explore whether it represents a teaching affinity space on this social network. It is a hashtag linked to an educational project created in Spain and related to all educational stages in a cross-cutting manner. Using a mixed methods research, 6073 tweets with the hashtag #CharlasEducativas, published between January 2020 and July 2022, were analysed, including a total of 761 Twitter profiles. Using the software MAXQDA, a category system was developed to classify the most frequent topics in the interactions and to study the tone of the discourse. The social network analysis software Graphext was used for in depth analysis of the profiles with the highest participation. It was confirmed that the characteristics of affinity spaces (collaboration, horizontal nature, creation of community, existence of hierarchy and source of informal learning) were met. The interactions linked to this hashtag are positive, friendly and with a close and relaxed tone, which favours the generation of a group feeling, facilitating informal learning. In addition, the space has a strong hierarchy with leadership roles that allows the information to flow and be fed continuously.

Online Integrative Community Therapy in Latin America: Health Promotion in Times of COVID-19.

This study described integrative community therapy (ICT) in the online modality as a health promotion resource in the context of COVID-19 in Latin America, characterizing the ICT circles, the ICT training centers, and the community therapists involved in this practice. It is a descriptive, observational, and cross-sectional study with a quantitative approach. Data were collected from November 2020 to July 2021 through an online questionnaire created on the Google Forms platform. The study's first stage involved the participation of ICT training centers, while the second involved community therapists. Forty-three centers participated in the first stage; 86.1% offered online ICT in the period evaluated, and 74.4% trained professionals to implement this modality. In the second stage, 66 community therapists responded to the questionnaire. Of these, 49 (74.2%) resided in Brazil, 84.8% were female, and 72.7% performed the work voluntarily, with an average of 6.1 hours per week dedicated to online circles. Community-based circles were the most cited, followed by those linked to the public sector, with an average of 20.7 participants/circle in the period. The most frequent themes were stress and negative emotions, problems with work/unemployment, and family conflicts. Strengthening self-care, participation in ICT circles, and personal empowerment stood out among the coping strategies. In conclusion, online ICT proved to be an innovative resource for health promotion during the pandemic through the articulation and engagement of community therapists and different institutions, expanding solidary social networks, and showing itself as a sustainable practice in the Latin American scenario.

Research collaboration between global North and global South assessed in terms of published output: a case study of Australia and Vietnam

Background: Vietnam and Australia have a long-standing history of collaboration in various fields, notably education, science, and technology. However, the results of this partnership remain indeterminate. Objectives: The aim of this study was to examine the current state of research coop-eration between Australia and Vietnam with reference to the following aspects: (1) increase in the number of research publications over time; (2) proportion of open access (OA) publications in total publications; (3) collaboration involving countries other than Australia and Vietnam; (4) funding sources; (5) top institutions; (6) subject areas; and (7) research topics. Methods: Scopus data set was analysed to identify those papers with two or more authors, with at least one author from Australia and at least one from Vietnam. Results: Most (nearly 84%) of research papers arising out of such collaborative research were published between 2014 and 2022 (7020 of the total of 8460 documents), and almost half (49.6%) of those are OA. Besides Australia and Vietnam, the authors of those papers were from other countries as well nor were the agencies that funded the research reported in those papers limited to Australia or Vietnam. Among the countries involved in terms of co-authorship or funding, the United States was the most influential. The institutional collaborations formed three distinct clusters, each with a varying number of members and a different university at the core (Australian in two clusters and Vietnamese in the third). Medicine was the most frequent field of collaborative research, and the most frequent topics were Vietnam, coronavirus disease 2019, and climate change. Conclusions: The findings offer useful insights to policymakers as well as to senior management of academic institutes in Vietnam and Australia. The study also extends our understanding of collaborative research between the Global North and the Global South.

Qualitative analysis of mental health conversational agents messages about autism spectrum disorder: a call for action.

Conversational agents (CA's) have shown promise in increasing accessibility to mental health resources. This study aimed to identify common themes of messages sent to a mental health CA (Wysa) related to ASD by general users and users that identify as having ASD. This study utilized retrospective data. Two thematic analyses were conducted, one focusing on user messages including the keywords (e.g., ASD, autism, Asperger), and the second one with messages from users who self-identified as having ASD. For the sample of general users, the most frequent themes were "others having ASD," "ASD diagnosis," and "seeking help." For the users that self-identified as having ASD (n = 277), the most frequent themes were "ASD diagnosis or symptoms," "negative reaction from others," and "positive comments." There were 3,725 emotion words mentioned by users who self-identified as having ASD. The majority had negative valence (80.3%), and few were positive (14.8%) or ambivalent (4.9%). Users shared their experiences and emotions surrounding ASD with a mental health CA. Users asked about the ASD diagnosis, sought help, and reported negative reactions from others. CA's have the potential to become a source of support for those interested in ASD and/or identify as having ASD.

Ze sztuki wysokiej pod strzechy. Temat „Czuwający Emmanuel” w XIX-wiecznym ukraińskim malarstwie ikonowym

“The Unsleeping Eye” is one of the frequent themes of Ukrainian domestic icons in the 19th century. The little Jesus is resting on the cross lying on the ground, and next to him there are the instruments of the Passion. His closed eyes indicate sleep (death?) after the crucifixion, and the arma passionis emphasize the Passion contents. A late medieval Byzantine theme with deep and complex symbolism, called in Greek άναπεσών (Anapeson) constitutes the origin of this representation. The main idea of this picture grows from the parallel of the lion – Christ, described in the fourth‑century Greek Physiologist. The article shows how the theme, which arose within Byzantine intellectual circles, in gradually changing its form, content and purpose, settled down in the art of the common people.