Sophie Bjork-James, Vanderbilt University; Anna-Grace Lilly, University of Toledo, and Isabelle Perry Newman, University of Virginia

Abortion bans are intended to reduce elective abortions, but they are also affecting the way physicians practice medicine.

That is the key finding from our recently published article in the journal Social Science & Medicine.

Medical providers practicing in states that implemented abortion bans in the wake of the 2022 Dobbs v. Jackson Women’s Health Supreme Court decision are forced to balance the needs of their pregnant patients against the risk that the providers could be prosecuted for treating these patients. This dilemma has serious and far-reaching consequences.

We interviewed 22 medical providers working in reproductive health care across Tennessee in the six months following the implementation of the state’s total abortion ban in 2022.

Providers spoke with our team about the need to protect themselves from criminal liability and told us that they were increasingly hesitant to provide care that their patients needed.

Why it matters

A 2024 ProPublica investigation found that at least two women have died in Georgia as a result of being denied medical care stemming from the implementation of these abortion bans. Nearly all of our interviewees spoke about their fear that these kinds of deaths would happen.

Providers told us that patients often believe that these bans include exceptions when the health of the pregnant person is at risk, but that is not always true in practice.

The Tennessee abortion ban allows for an “exception for situations where the abortion is necessary to prevent the death of a pregnant woman or prevent serious risk of substantial and irreversible impairment of major bodily function.”

The problem is that such cases are rarely clear-cut. And the stakes for health care providers are very high. In certain states, including Tennessee, if they are found to have provided an abortion in a case where the mother’s life or health was not imminently at risk, they can face felony charges, which could include multiple years in prison.

In interviews, providers described many cases where terminating a pregnancy is medically necessary for the pregnant person. Take cases of preterm premature membrane rupture, a condition where a pregnant person’s water breaks before 37 weeks of pregnancy. Serious complications can follow a premature membrane rupture, particularly in cases that do not result in the beginning of labor.

The standard treatment for this condition is to induce labor in an effort to prevent such potential medical complications. However, if it is early on in a pregnancy and the fetus would likely not survive outside the womb, this treatment is now discouraged, as the law does not sufficiently clarify what interventions are allowed to protect the pregnant person.

In many cases, the physical harm the pregnant person is experiencing correlates with the level of legal protection a medical provider receives.

Although doctors are trained to follow best practices around health care treatment, fear of malpractice accusations leads to the widely documented practice of defensive medicine, cases where providers either over-administer testing or avoid risks in an effort to prevent malpractice lawsuits.

Abortion bans make this dynamic far worse because they often involve the threat of criminal prosecution, which is not covered by malpractice insurance. This exposes providers to a new form of risk, one that is shaping how providers interact with patients and provide care.

Our team calls this new form of defensive medicine “hesitant medicine.” Providers are forced to prioritize their own criminal legal protection over the well-being of their patients, so they hesitate to provide treatment that patients need. Hesitancy is exacerbated by bans that are ambiguous about when a provider can intervene during a pregnancy complication.

What’s next

It will take years before researchers have data showing the full picture of how abortion bans are affecting women’s reproductive health. However, our interviews show that these bans are already shaping how providers are treating pregnant people.

A majority of our interviewees had considered moving to a state without an abortion ban to practice medicine with far less stress around the threat of criminal prosecution, a trend that is already occurring. Over time, this exodus of providers could exacerbate the problem of health care deserts in the United States.

To mitigate some of this harm, more effort is needed from medical associations, employers and legislatures to clarify or revise the Tennessee “Human Life Protection Act” in a way that better protects women’s health.

Sophie Bjork-James, Assistant Professor of Anthropology, Vanderbilt University; Anna-Grace Lilly, Medical Student, University of Toledo, and Isabelle Perry Newman, Medical Student, University of Virginia

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Haoran Chu, University of Florida and Sixiao Liu, University of Central Florida

Stories define people – they shape our relationships, cultures and societies. Unlike other skills replaced by technology, storytelling has remained uniquely human, setting people apart from machines. But now, even storytelling is being challenged. Artificial intelligence, powered by vast datasets, can generate stories that sometimes rival, or even surpass, those written by humans.

Creative professionals have been among the first to feel the threat of AI. Last year, Hollywood screenwriters protested, demanding – and winning – protections against AI replacing their jobs. As university professors, we’ve seen student work that seems suspiciously AI-generated, which can be frustrating.

Beyond the threat to livelihoods, AI’s ability to craft compelling, humanlike stories also poses a societal risk: the spread of misinformation. Fake news, which once required significant effort, can now be produced with ease. This is especially concerning because decades of research have shown that people are often more influenced by stories than by explicit arguments and entreaties.

We set out to study how well AI-written stories stack up against those by human storytellers. We found that AI storytelling is impressive, but professional writers needn’t worry – at least not yet.

The power of stories

How do stories influence people? Their power often lies in transportation – the feeling of being transported to and fully immersed in an imagined world. You’ve likely experienced this while losing yourself in the wizarding world of Harry Potter or 19th-century English society in “Pride and Prejudice.” This kind of immersion lets you experience new places and understand others’ perspectives, often influencing how you view your own life afterward.

When you’re transported by a story, you not only learn by observing, but your skepticism is also suspended. You’re so engrossed in the storyline that you let your guard down, allowing the story to influence you without triggering skepticism in it or the feeling of being manipulated.

Given the power of stories, can AI tell a good one? This question matters not only to those in creative industries but to everyone. A good story can change lives, as evidenced by mythical and nationalist narratives that have influenced wars and peace.

Studying whether AI can tell compelling stories also helps researchers like us understand what makes narratives effective. Unlike human writers, AI provides a controlled way to experiment with storytelling techniques.

Head-to-head results

In our experiments, we explored whether AI could tell compelling stories. We used descriptions from published studies to prompt ChatGPT to generate three narratives, then asked over 2,000 participants to read and rate their engagement with these stories. We labeled half as AI-written and half as human-written.

Our results were mixed. In three experiments, participants found human-written stories to be generally more “transporting” than AI-generated ones, regardless of how the source was labeled. However, they were not more likely to raise questions about AI-generated stories. In multiple cases, they even challenged them less than human-written ones. The one clear finding was that labeling a story as AI-written made it less appealing to participants and led to more skepticism, no matter the actual author.

Why is this the case? Linguistic analysis of the stories showed that AI-generated stories tended to have longer paragraphs and sentences, while human writers showed more stylistic diversity. AI writes coherently, with strong links between sentences and ideas, but human writers vary more, creating a richer experience. This also points to the possibility that prompting AI models to write in more diverse tones and styles may improve their storytelling.

These findings provide an early look at AI’s potential for storytelling. We also looked at research in storytelling, psychology and philosophy to understand what makes a good story.

We believe four things make stories engaging: good writing, believability, creativity and lived experience. AI is great at writing fluently and making stories believable. But creativity and real-life experiences are where AI falls short. Creativity means coming up with new ideas, while AI is designed to predict the most likely outcome. And although AI can sound human, it lacks the real-life experiences that often make stories truly compelling.

Closing in?

It’s too early to come to a definitive conclusion about whether AI can eventually be used for high-quality storytelling. AI is good at writing fluently and coherently, and its creativity may rival that of average writers. However, AI’s strength lies in predictability. Its algorithms are designed to generate the most likely outcome based on data, which can make its stories appealing in a familiar way. This is similar to the concept of beauty in averageness, the documented preference people have for composite images that represent the average face of a population. This predictability, though limiting true creativity, can still resonate with audiences.

For now, screenwriters and novelists aren’t at risk of losing their jobs. AI can tell stories, but they aren’t quite on par with the best human storytellers. Still, as AI continues to evolve, we may see more compelling stories generated by machines, which could pose serious challenges, especially when they’re used to spread misinformation.

Haoran Chu, Assistant Professor of Communications, University of Florida and Sixiao Liu, Assistant Professor of Population Health Sciences, University of Central Florida

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Shao Lin, University at Albany, State University of New York; Arshad Arjunan Nair, University at Albany, State University of New York; Fangqun Yu, University at Albany, State University of New York, and Quan Qi, University at Albany, State University of New York

Long-term high ultrafine particle concentrations in New York state neighborhoods are linked to higher numbers of deaths. That is the key finding of our new research, published in the Journal of Hazardous Materials.

Our study shows that high levels of ultrafine particles in the atmosphere over long periods of time are significantly associated with increased non-accidental deaths, particularly from cardiovascular and respiratory diseases.

Ultrafine particles are aerosols less than 0.1 micrometers, or 100 nanometers, in diameter — about one-thousandth the width of a human hair. Due to their tiny size, they can be easily inhaled into the distal branches of lungs, quickly absorbed into the bloodstream and even pass through organ barriers.

We also found that certain underserved populations, including Hispanics, non-Hispanic Black people, children under 5, older adults and non-New York City residents, are more susceptible to the adverse effects of ultrafine particles. The disparities our study uncovered underscore the necessity for public health agencies to focus on and protect high-risk populations.

We quantified the long-term health impacts of exposure to these pollutants by combining mortality data from vital records in New York state and using a model that tracks how particles move and change through the air.

Why it matters

Air pollution is now ranked the second-leading risk factor for death, accounting for about 8.1 million deaths globally and about 600,000 deaths in the United States in 2021.

Most air pollution standards and regulations have been focused on larger particulate matter, such as PM2.5 – which includes organic compounds and metal particulates – and PM10, a category that includes dust, pollen and mold.

In comparison, ultrafine particles are typically much greater in number and have a much larger surface area-to-volume ratio, allowing them to carry substantial amounts of hazardous metals and organic compounds. Furthermore, because of their smaller size, ultrafine particles can follow the air flow and get deep into the lungs when inhaled. These unique characteristics make ultrafine particles particularly dangerous, leading to a range of adverse health problems.

Despite this understanding, ultrafine particles remain largely unregulated, while larger particulates are regulated under the National Ambient Air Quality Standards.

Due to their unique characteristics, ultrafine particles require additional, tailored attention.

Ultrafine particles stem from both natural sources and human activity – primarily from combustion processes such as motor vehicles, power plants, wood burning and wildfires. A large share of ultrafine particles is created by chemical reactions in the atmosphere involving acidic gases from fossil fuel burning and ammonia from farming and residential wastes.

As cities continue to expand and urban populations grow, people’s exposure to these harmful particles is likely to increase. Both PM2.5 and ultrafine particles come from similar sources and can also form through chemical reactions in the atmosphere, but their trends diverge.

PM2.5 mass has been declining in many places, including New York, thanks to air quality regulations. However, recent research suggests that ultrafine particle numbers are not going down and have been increasing since 2017.

What still isn’t known

There are currently no large-scale monitoring sites in the U.S. dedicated to tracking ultrafine particles in the environment. This limits the ability of researchers like us to comprehend the extent of ultrafine particle exposure and its impact on public health.

What’s more, the exact biological mechanisms through which ultrafine particles cause harm are not yet fully understood. Increasing research evidence suggests that ultrafine particles can affect heart function, causing hardening of arteries, lung inflammation and systemic inflammation.

There have been few prior studies looking at death rates related to ultrafine particle exposure by demographics and seasonality. By understanding which groups are most vulnerable to ultrafine particle exposure, interventions can be more effectively tailored to lower the risks and protect those who are disproportionately affected. Our study, which is funded by the New York State Energy Research and Development Authority, helps fill in these critical knowledge gaps.

The Research Brief is a short take on interesting academic work.

Shao Lin, Professor of Public Health, University at Albany, State University of New York; Arshad Arjunan Nair, Research Scientist in Atmospheric Sciences, University at Albany, State University of New York; Fangqun Yu, Senior Researcher in Atmospheric Sciences, University at Albany, State University of New York, and Quan Qi, PhD candidate in Economics, University at Albany, State University of New York

This article is republished from The Conversation under a Creative Commons license. Read the original article.