BACKGROUND: Suicide is a leading cause of death worldwide. Journalistic reporting guidelines were created to curb the impact of unsafe reporting; however, how suicide is framed in news reports may differ by important characteristics such as the circumstances and the decedent\'s gender.
OBJECTIVE: This study aimed to examine the degree to which news media reports of suicides are framed using stigmatized or glorified language and differences in such framing by gender and circumstance of suicide.
METHODS: We analyzed 200 news articles regarding suicides and applied the validated Stigma of Suicide Scale to identify stigmatized and glorified language. We assessed linguistic similarity with 2 widely used metrics, cosine similarity and mutual information scores, using a machine learning-based large language model.
RESULTS: News reports of male suicides were framed more similarly to stigmatizing (P<.001) and glorifying (P=.005) language than reports of female suicides. Considering the circumstances of suicide, mutual information scores indicated that differences in the use of stigmatizing or glorifying language by gender were most pronounced for articles attributing legal (0.155), relationship (0.268), or mental health problems (0.251) as the cause.
CONCLUSIONS: Linguistic differences, by gender, in stigmatizing or glorifying language when reporting suicide may exacerbate suicide disparities.

Science journalists, traditionally, play a key role in delivering science information to a wider audience. However, changes in the media ecosystem and the science-media relationship are posing challenges to reliable news production. Additionally, recent developments such as ChatGPT and Artificial Intelligence (AI) more generally, may have further consequences for the work of (science) journalists. Through a mixed-methodology, the quality of news reporting was studied within the context of AI. A content analysis of media output about AI (news articles published within the time frame 1 September 2022-28 February 2023) explored the adherence to quality indicators, while interviews shed light on journalism practices regarding quality reporting on and with AI. Perspectives from understudied areas in four European countries (Belgium, Italy, Portugal, and Spain) were included and compared. The findings show that AI received continuous media attention in the four countries. Furthermore, despite four different media landscapes, the reporting in the news articles adhered to the same quality criteria such as applying rigour, including sources of information, accessibility, and relevance. Thematic analysis of the interview findings revealed that impact of AI and ChatGPT on the journalism profession is still in its infancy. Expected benefits of AI related to helping with repetitive tasks (e.g. translations), and positively influencing journalistic principles of accessibility, engagement, and impact, while concerns showed fear for lower adherence to principles of rigour, integrity and transparency of sources of information. More generally, the interviewees expressed concerns about the state of science journalism, including a lack of funding influencing the quality of reporting. Journalists who were employed as staff as well as those who worked as freelancers put efforts in ensuring quality output, for example, via editorial oversight, discussions, or memberships of associations. Further research into the science-media relationship is recommended.

Science journalism is a critical way for the public to learn about and benefit from scientific findings. Such journalism shapes the public\'s view of the current state of science and legitimizes experts. Journalists can only cite and quote a limited number of sources, who they may discover in their research, including recommendations by other scientists. Biases in either process may influence who is identified and ultimately included as a source. To examine potential biases in science journalism, we analyzed 22,001 non-research articles published by Nature and compared these with Nature-published research articles with respect to predicted gender and name origin. We extracted cited authors\' names and those of quoted speakers. While citations and quotations within a piece do not reflect the entire information-gathering process, they can provide insight into the demographics of visible sources. We then predicted gender and name origin of the cited authors and speakers. We compared articles with a comparator set made up of first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period. In our analysis, we found a skew toward quoting men in Nature science journalism. However, quotation is trending toward equal representation at a faster rate than authorship rates in academic publishing. Gender disparity in Nature quotes was dependent on the article type. We found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin in both in extracted quotes and journal citations but dampened in citations.

Researchers and practitioners increasingly believe that journalism must improve its relationship with audiences to increase the likelihood that people will consume and support news. In this paper, we argue that this assumption overlooks the importance of structural- and individual-level factors in shaping news audience behavior. Drawing on Giddens\' theory of structuration, we suggest that, when it comes to the amount of time that people devote to news, consumers\' choices are guided more by life circumstances than by news preferences. To illustrate this point, we draw on a combination of interview and audience analytics data collected when so many people\'s life circumstances changed: the start of the COVID-19 pandemic. We find that people consumed more news during the early months of the pandemic than normal because (1) they had more time on their hands due to things like shelter-in-place orders, layoffs, and shifts to working from home and (2) they were more interested in understanding the coronavirus\' spread and risks as well as the preventative measures being pursued. We conclude that journalists should embrace \"journalistic humility,\" thereby acknowledging and accepting that they have much less control over the reception of their work than they would like to believe.

This study explores how fact-checkers understand information disorder in Ibero-America, in particular the COVID-19 disinformation. We conducted a quantitative content analysis of the LatamChequea Coronavirus alliance database and in-depth interviews with journalists from the network. Evidence found that one of the most prevalent disinformation topics was the government\'s restrictive measures, threatening to jeopardize the effectiveness of public health campaigns. This, added to disinformation that eroded the trust in the institutions and the press, and the opacity of governments constituted a political crisis in Ibero-America. Under this scenario, fact-checkers created relevant journalistic collaborations and strategies to fight disinformation in the region.

BACKGROUND: Given the complementary roles of health professionals and journalists in communicating health risks to patients and the public, there have been calls for physicians to work with journalists to improve the quality of health information received by the public. Understanding the preferences of medical and journalism students for the way in which health risks are communicated and their understanding of words used to describe risk is an important first step to inform interdisciplinary learning.
METHODS: Medical and journalism students (n = 203) completed an online survey where they were given qualitative descriptors of risk such as \'a chance\', \'probably\' and \'unlikely\', and asked to assign a number that represents what the word means to them. Different formats of communicating risk (percentages, natural frequency and visual aids) were provided and students were asked to select and explain their preference. A thematic analysis of reasons was conducted. Numeracy and perceived mathematics ability were measured.
RESULTS: Numbers assigned to the descriptor \'A chance\' had the highest variability for medical students. Numbers assigned to the descriptor \'Probably\' had the highest variability for journalism students. Using visual aids was the most popular format for risk communication for both courses (56% of medical students and 40% of journalism students). Using percentages was twice as popular with journalism students compared to medical students (36% vs. 18%). Perceived mathematics ability was lower in students with a preference for natural frequencies and in journalism students, however performance on an objective numeracy scale was similar for all three formats (percentages, natural frequency and visual aids). Reasons for choosing a preferred format included good communication, eliciting a response, or learning style.
CONCLUSIONS: Education on health risk communication for medical and journalism students should emphasize the need for qualitative descriptors of risk to be combined with the best available number. Students are already considering their role as future communicators of health risks and open to tailoring the mode of presentation to their audience. Further research is required on the design and evaluation of interdisciplinary workshops in health risk communication for medical and journalism students to maximise the opportunities for future inter-professional working.

Science journalists are uniquely positioned to increase the societal impact of open research outputs by contextualizing and communicating findings in ways that highlight their relevance and implications for non-specialist audiences. Yet, it is unclear to what degree journalists use open research outputs, such as open access publications or preprints, in their reporting; what factors motivate or constrain this use; and how the recent surge in openly available research seen during the COVID-19 pandemic has affected this. This article examines these questions through a review of relevant literature published from 2018 onwards-particularly literature relating to the COVID-19 pandemic-as well as seminal articles outside the search dates. We find that research that explicitly examines journalists\' engagement with open access publications or preprints is scarce, with existing literature mostly addressing the topic tangentially or as a secondary concern, rather than a primary focus. Still, the limited body of evidence points to several factors that may hamper journalists\' use of these outputs and thus warrant further exploration. These include an overreliance on traditional criteria for evaluating scientific quality; concerns about the trustworthiness of open research outputs; and challenges using and verifying the findings. We also find that, while the COVID-19 pandemic encouraged journalists to explore open research outputs such as preprints, the extent to which these explorations will become established journalistic practices remains unclear. Furthermore, we note that current research is overwhelmingly authored and focused on the Global North, and the United States specifically. We conclude with recommendations for future research that attend to issues of equity and diversity, and more explicitly examine the intersections of open access and science journalism.

This article analyzes the media coverage of the COVID-19 vaccine by major media outlets in five Latin American countries: Argentina, Colombia, Chile, Mexico, and Peru. For this purpose, the XLM-roBERTa model was applied and the sentiments of all tweets published between January 2020 and June 2023 (n = 24,243) by the five outlets with the greatest online reach in each country were analyzed. The results show that the sentiment in the overall media and in each nation studied was mostly negative, and only at the beginning of the pandemic was there some positivity. In recent months, negative sentiment has increased twelvefold over positive sentiment, and has also garnered many more interactions than positive sentiment. The differences by platform and country are minimal, but there are markedly negative media, some more inclined to neutrality, and only one where positive sentiment predominates. This paper questions the role of journalism in Latin America during a health crisis as serious as that of the coronavirus, in which, instead of the expected neutrality, or even a certain message of hope, the media seem to have been dragged along by the negativity promoted by certain discourses far removed from scientific evidence.

To investigate how people assess whether politically consistent news is real or fake, two studies (N = 1,008; N = 1,397) with adult American participants conducted in 2020 and 2022 utilized a within-subjects experimental design to investigate perceptions of news accuracy. When a mock Facebook post with either fake (Study 1) or real (Study 2) news content was attributed to an alternative (vs. a mainstream) news outlet, it was, on average, perceived to be less accurate. Those with beliefs reflecting News Media Literacy demonstrated greater sensitivity to the outlet\'s status. This relationship was itself contingent on the strength of the participant\'s partisan identity. Strong partisans high in News Media Literacy defended the accuracy of politically consistent content, even while recognizing that an outlet was unfamiliar. These results highlight the fundamental importance of looking at the interaction between user-traits and features of social media news posts when examining learning from political news on social media.

BACKGROUND: With emergence of chatbots to help authors with scientific writings, editors should have tools to identify artificial intelligence-generated texts. GPTZero is among the first websites that has sought media attention claiming to differentiate machine-generated from human-written texts.
METHODS: Using 20 text pieces generated by ChatGPT in response to arbitrary questions on various topics in medicine and 30 pieces chosen from previously published medical articles, the performance of GPTZero was assessed.
RESULTS: GPTZero had a sensitivity of 0.65 (95% confidence interval, 0.41-0.85); specificity, 0.90 (0.73-0.98); accuracy, 0.80 (0.66-0.90); and positive and negative likelihood ratios, 6.5 (2.1-19.9) and 0.4 (0.2-0.7), respectively.
CONCLUSIONS: GPTZero has a low false-positive (classifying a human-written text as machine-generated) and a high false-negative rate (classifying a machine-generated text as human-written).