Month: March 2024

Abstract

Natural disasters like earthquakes, and global crises like pandemics have historically captured the public’s imagination and prompted people to seek explanations. However, in times of limited information, these explanations can take the form of conspiracy theories, particularly regarding the origins or causes of such events. With the advent of social media conspiracy theories can spread quickly and easily, leaving little room for critical thinking. The focus of this study is the analysis of the so-called High-Frequency Active Auroral Research Program (HAARP) conspiracy, which explains earthquakes through the employment of secret weather control weapons. This study aims to answer the research question of how the discourse on the HAARP conspiracy theory changes over time, and what are the potential catalysts for heightened attention to this conspiracy theory. This study uses the Twitter API to collect tweet frequencies about this conspiracy from January 2022 through March 2023. The empirical data include over one million tweets on HAARP. The sentiment analysis of the HAARP conspiracy theory is applied to the tweets before, during, and after the 6th of February 2023 earthquake in Syria and Turkey. In addition, this study investigates possible triggers of the development of the HAARP tweet frequency. This study finds that the frequency of HAARP discussion increases following a high-impact earthquake. There is also a positive correlation between average tweet sentiment and the number of tweets, which could indicate that the discussion of HAARP reinforces people’s beliefs. This study makes a significant contribution to the field of social psychology and communication by providing insights into the dynamics of belief reinforcement within online communities amidst heightened attention to conspiracy theories triggered by significant events. This knowledge has broader implications for understanding the impact of social media on public perception during crises.

Abstract

Natural disasters like earthquakes, and global crises like pandemics have historically captured the public’s imagination and prompted people to seek explanations. However, in times of limited information, these explanations can take the form of conspiracy theories, particularly regarding the origins or causes of such events. With the advent of social media conspiracy theories can spread quickly and easily, leaving little room for critical thinking. The focus of this study is the analysis of the so-called High-Frequency Active Auroral Research Program (HAARP) conspiracy, which explains earthquakes through the employment of secret weather control weapons. This study aims to answer the research question of how the discourse on the HAARP conspiracy theory changes over time, and what are the potential catalysts for heightened attention to this conspiracy theory. This study uses the Twitter API to collect tweet frequencies about this conspiracy from January 2022 through March 2023. The empirical data include over one million tweets on HAARP. The sentiment analysis of the HAARP conspiracy theory is applied to the tweets before, during, and after the 6th of February 2023 earthquake in Syria and Turkey. In addition, this study investigates possible triggers of the development of the HAARP tweet frequency. This study finds that the frequency of HAARP discussion increases following a high-impact earthquake. There is also a positive correlation between average tweet sentiment and the number of tweets, which could indicate that the discussion of HAARP reinforces people’s beliefs. This study makes a significant contribution to the field of social psychology and communication by providing insights into the dynamics of belief reinforcement within online communities amidst heightened attention to conspiracy theories triggered by significant events. This knowledge has broader implications for understanding the impact of social media on public perception during crises.

Abstract

Background

Given the grave ethical tension and dilemmas posed continuously which are aggravated in the intensive care unit context and its related caregiving provision, combined with their impact on critical care nurses’ job satisfaction and work-related risks, exploring and analyzing these tensions and conflicts is crucial. This study was conducted to examine the relationship between perceived ethical work climate and problems among critical care nurses in addition to exploring their perspectives on the ethical work climates while caring for patients with infectious diseases.

Design and method

A mixed-method research design was used to conduct this study among 635 participants, comprising 170 from Egypt, 144 from Jordan, 161 from Saudi Arabia, and 160 from the United Arab Emirates. Online or paper-based survey forms were distributed to all eligible critical care nurses who agreed to take part in the study. The survey contained both quantitative and qualitative data that were analyzed separately and integrated during the discussion. The study was reported following the STROBE guidelines.

Findings

The overall ethical work climate was fairly good and was significantly associated with ICU nurses’ personal and professional characteristics. The findings also identified three main themes: (1) an ethical sense of failure, (2) environmental condemnation, and (3) an instant action plan for resolving ethical conflicts.

Conclusions

ICU nurses perceived that ICU ethical climate was fairly good. The results indicated that ICU nurses generally had a relatively fair perception of the ethical work climate, with implications for addressing ethical issues and conflicts in various settings.

Impact

Mentorship and/or close supervision concerning ethical resilience, consultation, and decision-making is crucial in the ICU milieu. Metacognitive strategies to reinforce problem-solving and decision-making ICU nurses’ skills could help them overcome the different ethical challenges. Adequate resources, teamwork, and organizational support are promising tactics to improve ICU nurses’ ethical skills.

Trial registration

Not applicable.

Abstract

The Artificial Intelligence (AI) natural language model ChatGPT (Chat Generative Pre-trained Transformer), often referred to as ChatGPT-4, has a wide range of possible uses in the fields of research, business, academia, health, and similar fields. This language model can accomplish a number of academic jobs that were previously completed by people, taking a significant amount of time and effort. The purpose of the article is to investigate ChatGPT’s potential opportunities and challenges in academia. To attain this objective, a review of relevant literature and online resources (news, articles, etc.) was carried out. The noticing-collecting-thinking approach was adopted to explore and categorize all observed concerns. The outcome of this study reveals that research, education, personal skill development, and social aspects constitute the four broad perspectives that articulate the opportunities and constraints of ChatGPT in academia. For instance, from the education perspective, ChatGPT can help students have a personalized learning experience. On the other hand, it might provide false information as well as lack the ability to generate responses on its own because those responses depend on training datasets, which may contain errors. Similarly, from the point of view of the personal skill development, this model may impair a person’s capacity for critical thought and content production; while providing reading and writing practice sessions and relevant content, it can improve a person’s language proficiency.

Abstract

The Artificial Intelligence (AI) natural language model ChatGPT (Chat Generative Pre-trained Transformer), often referred to as ChatGPT-4, has a wide range of possible uses in the fields of research, business, academia, health, and similar fields. This language model can accomplish a number of academic jobs that were previously completed by people, taking a significant amount of time and effort. The purpose of the article is to investigate ChatGPT’s potential opportunities and challenges in academia. To attain this objective, a review of relevant literature and online resources (news, articles, etc.) was carried out. The noticing-collecting-thinking approach was adopted to explore and categorize all observed concerns. The outcome of this study reveals that research, education, personal skill development, and social aspects constitute the four broad perspectives that articulate the opportunities and constraints of ChatGPT in academia. For instance, from the education perspective, ChatGPT can help students have a personalized learning experience. On the other hand, it might provide false information as well as lack the ability to generate responses on its own because those responses depend on training datasets, which may contain errors. Similarly, from the point of view of the personal skill development, this model may impair a person’s capacity for critical thought and content production; while providing reading and writing practice sessions and relevant content, it can improve a person’s language proficiency.