Lay, professional, and artificial intelligence perspectives on risky medical decisions and COVID-19: How does the number of lives matter in clinical trials framed as gains versus losses?

Outcomes of clinical trials need to be communicated effectively to make decisions that save lives. We investigated whether framing can bias these decisions and if risk preferences shift depending on the number of patients. Hypothetical information about two medicines used in clinical trials having a sure or a risky outcome was presented in either a gain frame (people would be saved) or a loss frame (people would die). The number of patients who signed up for the clinical trials was manipulated in both frames in all the experiments. Using an unnamed disease, lay participants (experiment 1) and would-be medical professionals (experiment 2) were asked to choose which medicine they would have administered. For COVID-19, lay participants were asked which medicine should medical professionals (experiment 3), artificially intelligent software (experiment 4), and they themselves (experiment 5) favour to be administered. Broadly consistent with prospect theory, people were more risk-seeking in the loss frames than the gain frames. However, risk-aversion in gain frames was sensitive to the number of lives with risk-neutrality at low magnitudes and risk-aversion at high magnitudes. In the loss frame, participants were mostly risk-seeking. This pattern was consistent across laypersons and medical professionals, further extended to preferences for choices that medical professionals and artificial intelligence programmes should make in the context of COVID-19. These results underscore how medical decisions can be impacted by the number of lives at stake while revealing inconsistent risk preferences for clinical trials during a real pandemic.

Twitter Mediated Sociopolitical Communication During the COVID-19 Pandemic Crisis in India

While Twitter has grown popular among political leaders as a means of computer-mediated mass media communication alternative, the COVID-19 pandemic required new strategies for socio-political communication to handle such a crisis. Using the case of India, which was one of the worst-hit countries and is also the world’s largest democracy, this research explicates how political leaders responded to the COVID-19 crisis on Twitter during the first wave as it was the first time such a crisis occurred. Theoretical frameworks of discursive leadership and situational crisis communication theory have been used to analyze interactions based on the usage patterns, the content of communication, the extent of usage in relation to the severity of the crisis, and the possible role of leaders’ position along with the status of their political party. The sample consisted of tweets posted by six prominent political leaders in India across the four consecutive lockdown periods from 25th March to 31st May 2020. A total of 4,158 tweets were scrapped and after filtering for retweets, the final dataset consisted of 2,809 original tweets. Exploratory data analysis, sentiment analysis, and content analysis were conducted. It was found that the tweets had an overall positive sentiment, an important crisis management strategy. Four main themes emerged: crisis management information, strengthening followers’ resilience and trust, reputation management, and leaders’ proactiveness. By focusing on such discursive aspects of crisis management, the study comprehensively highlights how political interactions on twitter integrated with politics and governance to handle COVID-19 in India. The study has implications for the fields of digital media interaction, political communication, public relations, and crisis leadership.