RPFT study - Registered Pulmonary Function Technologist Updated: 2023

Chatbots are increasingly becoming a part of health care around the world, but do they encourage bias? That's what University of Colorado School of Medicine researchers are asking as they dig into patients' experiences with the artificial intelligence (AI) programs that simulate conversation.

"Sometimes overlooked is what a chatbot looks like – its avatar," the researchers write in a new paper published in Annals of Internal Medicine. "Current chatbot avatars vary from faceless health system logos to cartoon characters or human-like caricatures. Chatbots could one day be digitized versions of a patient's physician, with that physician's likeness and voice. Far from an innocuous design decision, chatbot avatars raise novel ethical questions about nudging and bias."

The paper, titled "More than just a pretty face? Nudging and bias in chatbots", challenges researchers and health care professionals to closely examine chatbots through a health equity lens and investigate whether the technology truly improves patient outcomes.

In 2021, the Greenwall Foundation granted CU Division of General Internal Medicine Associate Professor Matthew DeCamp, MD, PhD, and his team of researchers in the CU School of Medicine funds to investigate ethical questions surrounding chatbots. The research team also included Internal medicine professor Annie Moore, MD, MBA, the Joyce and Dick Brown Endowed Professor in Compassion in the Patient Experience, incoming medical student Marlee Akerson, and UCHealth Experience and Innovation Manager Matt Andazola.

If chatbots are patients' so-called 'first touch' with the health care system, we really need to understand how they experience them and what the effects could be on trust and compassion."

Annie Moore, Professor, School of Medicine, University of Colorado

So far, the team has surveyed more than 300 people and interviewed 30 others about their interactions with health care-related chatbots. For Akerson, who led the survey efforts, it's been her first experience with bioethics research.

"I am thrilled that I had the chance to work at the Center for Bioethics and Humanities, and even more thrilled that I can continue this while a medical student here at CU," she says.

The face of health care

The researchers observed that chatbots were becoming especially common around the COVID-19 pandemic.

"Many health systems created chatbots as symptom-checkers," DeCamp explains. "You can go online and type in symptoms such as cough and fever and it would tell you what to do. As a result, we became interested in the ethics around the broader use of this technology."

Oftentimes, DeCamp says, chatbot avatars are thought of as a marketing tool, but their appearance can have a much deeper meaning.

"One of the things we noticed early on was this question of how people perceive the race or ethnicity of the chatbot and what effect that might have on their experience," he says. "It could be that you share more with the chatbot if you perceive the chatbot to be the same race as you."

For DeCamp and the team of researchers, it prompted many ethical questions, like how health care systems should be designing chatbots and whether a design decision could unintentionally manipulate patients.

There does seem to be evidence that people may share more information with chatbots than they do with humans, and that's where the ethics tension comes in: We can manipulate avatars to make the chatbot more effective, but should we? Does it cross a line around overly influencing a person's health decisions?" DeCamp says.

A chatbot's avatar might also reinforce social stereotypes. Chatbots that exhibit feminine features, for example, may reinforce biases on women's roles in health care.

On the other hand, an avatar may also increase trust among some patient groups, especially those that have been historically underserved and underrepresented in health care, if those patients are able to choose the avatar they interact with.

"That's more demonstrative of respect," DeCamp explains. "And that's good because it creates more trust and more engagement. That person now feels like the health system cared more about them."

Marketing or nudging?

While there's little evidence currently, there is a hypothesis emerging that a chatbot's perceived race or ethnicity can impact patient disclosure, experience, and willingness to follow health care recommendations.

"This is not surprising," the CU researchers write in the Annals paper. "Decades of research highlight how patient-physician concordance according to gender, race, or ethnicity in traditional, face-to-face care supports health care quality, patient trust, and satisfaction. Patient-chatbot concordance may be next."

That's enough reason to scrutinize the avatars as "nudges," they say. Nudges are typically defined as low-cost changes in a design that influence behavior without limiting choice. Just as a cafeteria putting fruit near the entrance might "nudge" patrons to pick up a healthier option first, a chatbot could have a similar effect.

"A patient's choice can't actually be restricted," DeCamp emphasizes. "And the information presented must be accurate. It wouldn't be a nudge if you presented misleading information."

In that way, the avatar can make a difference in the health care setting, even if the nudges aren't harmful.

DeCamp and his team urge the medical community to use chatbots to promote health equity and recognize the implications they may have so that the artificial intelligence tools can best serve patients.

"Addressing biases in chatbots will do more than help their performance," the researchers write. "If and when chatbots become a first touch for many patients' health care, intentional design can promote greater trust in clinicians and health systems broadly."

The growing and widespread use of algorithms to make health care decisions for patients could be adding to racial bias against minorities, a new study has found.

Algorithms are the mathematical rules that tell a health care provider’s computer program how to solve problems affecting a patient’s access to medical treatment, quality of care and health outcomes. Doctors increasingly rely on their analysis of a patient’s medical and insurance history to recommend appropriate treatment. 

According to a study that seven public health researchers published Friday in JAMA Health Forum, 18 commonly used algorithms flag ethnicity and race in haphazard ways that may reinforce unequal treatment of dark-skinned patients due to a lack of oversight and knowledge of their functions.

The researchers posed 11 questions about the algorithms to the representatives of 42 clinical professional societies, universities, government agencies, health insurance payers and health technology organizations.

“Findings suggest that standardized and rigorous approaches for algorithm development and implementation are needed to mitigate racial and ethnic biases from algorithms and reduce health inequities,” the researchers wrote in the study.

Survey respondents recommended “guidance and standardization from government and others” to purge any bias and prevent the use of race as a “proxy for clinical variables,” the study stated.

“Only 20% of health outcomes are determined by the provision of health care services, and an individual’s ZIP code has more influence on their health than their own genetic code,” an anonymous clinician wrote in the survey, noting that racial data favors patients from better neighborhoods.

Some health care professionals echoed the study’s conclusions, noting that algorithms often pull data from older medical tests that treat skin color as a biological difference.

“Many tests in medicine are based on race, from renal function to lung strength,” said Dr. Panagis Galiatsatos, a faculty health equity leader at the Johns Hopkins School of Medicine. “Right now, we are attempting to change pulse oximeter readings, which are known to cause false reports in dark-skinned individuals, often missing key hypoxemia that would impact medical management.”

Another problem could be the algorithms themselves, said Katy Talento, a former top health adviser at the White House Domestic Policy Council under former President Donald Trump.

She now serves as executive director of the Alliance of Health Care Sharing Ministries, a Washington-based association of Christians who work to “rehumanize” medicine by sharing medical costs.

“The study rightly points out that race is a bad proxy for what matters: health history, genetics and social determinants of health such as income,” Ms. Talento said in an email. “Our broken system requires clinicians to use bots, checklists and rapid-fire office visits driven by insurance payment models instead of doctor-patient relationships.”

According to diversity experts, it’s easy to see how mathematical calculations might cause minorities to receive inferior medical treatment.

“Algorithms are scientific tools to analyze data, but the variables are input by humans who of course can have biases toward racial and ethnic groups,” said Tyrone Howard, a Black education professor at the University of California, Los Angeles who specializes in racial equity.

Some conservatives cautioned against reading too much into the algorithms. The potential for bias does not prove racist calculations are to blame for unequal health outcomes, they said.

© Jaap Arriens (NurPhoto via Getty Images) OpenAI and ChatGPT logos are seen on electronic device screens in this photo illustration in May 2023 in Warsaw, Poland.

When a patient asks about the risk of dying after swallowing a toothpick, two answers are given. The first points out that between two or six hours after ingestion, it is likely that it has already passed to the intestines, explaining that many people swallow toothpicks without anything happening them. But it also advises the patient to go to the emergency room if they are experiencing a “stomach ache.” The second answer is in a similar vein. It replies that, although it’s normal to worry, serious harm is unlikely to occur after swallowing a toothpick as it’s small and made of wood, which is not toxic or poisonous. However, if the patient has “abdominal pain, difficulty swallowing or vomiting,” they should see a doctor. “It’s understandable that you may be feeling paranoid, but try not to worry too much. It is highly unlikely that the toothpick will cause you any serious harm,” it adds.

The two answers say basically the same thing, but the way they do so is slightly different. The first one is more aseptic and concise; while the second is more empathetic and detailed. The first was written by a doctor, and the second was from ChatGPT, the artificial intelligence (AI) generative tool that has revolutionized the planet. This experiment — part of a study published in the journal Jama Internal Medicine — was aimed at exploring the role AI assistants could play in medicine. It compared how real doctors and the chatbot responded to patient questions in an internet forum. The conclusions — based on an analysis from an external panel of health professionals who did not know who had answered what — found that ChatGPT’s responses were more emphathetic and high quality than the real doctor’s in 79% of cases.

The explosion of new AI tools has opened debate about their potential use in the field of health. ChatGPT, for example, is seeking to become a resource for health workers by helping them avoid bureaucratic tasks and develop medical procedures. On the street, it is already planning to replace the imprecise and often foolish Dr Google. Experts who spoke to EL PAÍS say that the technology has great potential, but that it is still in its infancy. Regulation on how it is applied in real medical practice still needs to be fine-tuned to address any ethical doubts, they say. The experts also point out that it is fallible, and can make mistakes. For this reason, everything that comes out of the chatbot will require the final review of a health professional.

Paradoxically, the machine —not the human — is the most empathetic voice in the Jama Internal Medicine study. At least, in the written response. Josep Munuera, head of the Diagnostic Imaging Service at Hospital Sant Pau in Barcelona, Spain, and an expert in digital technologies applied to health, warns that the concept of empathy is broader than what the study can analyze. Written communication is not the same as face-to-face communication, nor is raising a question on an online forum the same as doing so during a medical consultation. “When we talk about empathy, we are talking about many issues. At the moment, it is difficult to replace non-verbal language, which is very important when a doctor has to talk to a patient or their family,” he pointed out. But Munuera does admit these generative tools have great potential when it comes to simplifying medical jargon. “In written communication, technical medical language can be complex and we may have difficulty translating it into understandable language. Probably, these algorithms find the equivalence between the technical word and another and adapt it to the receiver.”

Joan Gibert, a bioinformatician and leading figure in the development of AI models at the Hospital del Mar in Barcelona, points out another variable when it comes to comparing the empathy of the doctor and the chatbox. “In the study, two concepts that enter into the equation are mixed: ChatGPT itself, which can be useful in certain scenarios and that has the ability to concatenate words that deliver us the feeling that it is more empathetic, and burnout among doctors, the emotional exhaustion when it comes to caring for patients that leaves clinicians unable to be more empathetic,” he explained.

The danger of "hallucinations"

Nevertheless, as is the case with the famous Dr Google, it’s important to be careful with ChatGPT’s responses, regardless of how sensitive or kind they may seem. Experts highlight that the chatbot is not a doctor and can deliver incorrect answers. Unlike other algorithms, ChatGPT is generative. In other words, it creates information according to the databases that it has been trained on, but it can still invent some responses. “You always have to keep in mind that it is not an independent entity and cannot serve as a diagnostic tool without supervision,” Gibert insisted.

These chatboxes can suffer from what experts call “hallucinations,” explained Gibert. “Depending on the situation, it could tell you something that is not true. The chatbot puts words together in a coherent way and because it has a lot of information, it can be valuable. But it has to be reviewed since, if not, it can fuel fake news,” he said. Munuera also highlighted the importance of “knowing the database that has trained the algorithm because if the databases are poor, the response will also be poor.”

Outside of the doctor’s office, the potential uses of ChatGPT in health are limited, since the information they provide can lead to errors. Jose Ibeas, a nephrologist at the Parc Taulí Hospital in Sabadel, Spain, and secretary of the Big Data and Artificial Intelligence Group of the Spanish Society of Nephrology, pointed out that it is “useful for the first layers of information because it synthesizes information and help, but when you enter a more specific area, in more complex pathologies, its usefulness is minimal or it’s wrong.”

“It is not an algorithm that helps resolve doubts,” added Munuera. “You have to understand that when you ask it to deliver you a differential diagnosis, it may invent a disease.” Similiarly, the AI system can tell a patient that nothing is wrong, when something is. This can lead to missed opportunities to see a doctor, because the patient follows the advice of the chatbot and does not speak to a real professional.

Where experts see more room for possibilies for AI is as a support tool for health professionals. For example, it could help doctors answer patient messages, albeit under supervision. The Jama Internal Medicine study suggests that it would help “improve workflow” and patient outcomes: “If more patients’ questions are answered quickly, with empathy, and to a high standard, it might reduce unnecessary clinical visits, freeing up resources for those who need them,” the researchers said. “Moreover, messaging is a critical resource for fostering patient equity, where individuals who have mobility limitations, work irregular hours, or fear medical bills, are potentially more likely to turn to messaging.”

The scientific community is also studying the use of these tools for other repetitive tasks, such as filling out forms and reports. “Based on the premise that everything will always, always, always need to be reviewed by the doctor,” AI could help medical professionals complete repetitive but important bureaucratic tasks, said Gibert. This, in turn, would allow doctors to spend more time on other issues, such as patient care. An article published in The Lancet, for example, suggests that AI technology could help streamline discharge summaries. Researchers say automating this process could east the work burden of doctors and even Improve the quality of reports, but they are aware of the difficulties involved with training algorithms, which requires large amounts of data, and the risk of “depersonalization of care,” which could lead to resistance to the technology.

Ibeas insists that, for any medical use, these tools must be “checked” and the division of responsibilities must be well established. “The systems will never decide. It must be the doctor who has the final sign-off,” he argued.

Ethical issues

Gibert also pointed out some ethical considerations that must be taken into account when including these tools in clinical practice: “You need this type of technology to be under a legal umbrella, for there to be integrated solutions within the hospital structure and to ensure that patient data is not used to retrain the model. And if someone wants to do the latter, they should do it within a project, with anonymized data, following all the controls and regulations. Sensitive patient information cannot be shared recklessly.”

The bioinformatician also argued that AI solutions, such as ChatGPT or models that help with diagnosis, introduce “biases” that can affect how doctors relate to patients. For example, these tools could condition a doctor’s decision, one way or another. “The fact that the professional has the result of an AI model changes the very professional. Their way of relating [to patients] may be very good, but it can introduce problems, especially in professionals who have less experience. That is why the process has to be done in parallel: until the professional gives the diagnosis, they cannot see what the AI says.”

A group of researchers from Stanford University also examined how AI tools can help to further humanize health care in an article in Jama Internal Medicine. “The practice of medicine is much more than just processing information and associating words with concepts; it is ascribing meaning to those concepts while connecting with patients as a trusted partner to build healthier lives,” they concluded. “We can hope that emerging AI systems may help tame laborious tasks that overwhelm modern medicine and empower physicians to return our focus to treating human patients.”

As we wait to see how this incipient technology grows and what repercussions it has for the public, Munuera argued: “You have to understand that [ChatGPT] is not a medical tool and there is no health professional who can confirm the veracity of the answer [the chatbot gives]. You have to be prudent and understand what the limits are.” In summary, Ibeas said: “The system is good, robust, positive and it is the future, but like any tool, you have to know how to use it so that it does not become a weapon.”

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© Lane Turner/Globe Staff Boston Children’s Hospital already makes broad use of older types of artificial intelligence, such as to read radiology and pathology scans.

Artificial intelligence is already in wide use in health care: medical workers use it to record patient interactions and add notes to medical records; some hospitals use it to read radiology images, or to predict how long a patient may need to be in intensive care.

Boston Children’s Hospital recently posted an opening for an AI prompt engineer, to help integrate large language technology into the hospital’s operations.

Like other hospitals, Boston Children’s already makes broad use of older types of artificial intelligence, such as to read radiology and pathology scans and to make predictions about patients’ length of stay in the ICU and emergency departments.

John Brownstein, the hospital’s chief innovation officer, said the new role will build on that foundation. In the short term, the hospital hopes to implement such tools on the administrative and financial sides and is soliciting feedback from staff on where AI tools might help people. Brownstein envisions using the technology to manage licensing requirements for providers, or to cull resumes of job candidates. On the research side, such technology can be used to read and summarize scientific literature.

“From my perspective, it will be as fundamental a tool as a search engine and mobile phone, and we have to prepare people for that world,” Brownstein said. “It’s going to be hard in the future to be effective at your job without taking advantage of these technologies.”

However, he said, medical professionals are being thoughtful and deliberate about bringing the tools to patient care. There are concerns about patient privacy, consent, and bias. He said the technology also has a tendency to “hallucinate,” or say things that are not true.

Given those concerns, experts are considering guardrails for large language models. But one day, the technology could be used to navigate a person’s electronic medical record, summarize a medical history, and even potentially generate clinical and discharge notes. Writing e-mails, which clinicians have to do on a daily basis, may become more efficient with the use of AI.

“The holy grail is using these tools to optimize and provide the best possible clinical support to our patients,” Brownstein said. “But it’s also the place we have to take the most time because we have to be the most thoughtful.”

Elsewhere, Microsoft and electronic medical record software maker Epic are working to integrate large language model technology into electronic medical records. For example, UC San Diego Health, UW Health in Madison, Wisconsin, and Stanford Health Care have begun using it to draft messages to patients.

Dr. Sahil Mehta, a physician in Boston specializing in vascular and interventional radiology, uses ChatGPT with the administrative functions of his job. He just used it to help write an appeal of an insurance denial.

“While it needed some minor editing, this type of document easily could take 20-30 minutes to write, yet ChatGPT wrote it in a few seconds and required just minor changes,” Mehta said. “As this technology evolves, and is better integrated into workflows, it has the ability to significantly Improve physician morale, documentation, and patient care because we will spend more time with patients, less with paperwork.”

According to a survey of 500 health care professionals conducted in April by digital health platform Tebra, more than 10 percent were using AI. Another 50 percent expressed an interest in using the technology in the future.

Perhaps the most immediate implementation of the technology has been in medical school education. Mehta, who founded MedSchoolCoach, an educational technology company focused on pre-med and medical students, said students can use the technology as a brainstorming tool for medical school essays. MedSchoolCoach is also creating study aids using large language model technology that has been trained on medical textbooks and other expert-written texts.

Meanwhile, patients have already begun turning to AI. The Tebra survey, which also asked 1,000 Americans about the use of the technology, found that more than 5 percent of those surveyed had used ChatGPT to help diagnose a problem and had followed its advice. Additionally, a quarter of those surveyed would not visit a health care provider who refused to embrace AI technology.

Early evidence shows ChatGPT can accurately answer some medical questions. A accurate study by physicians at Massachusetts General Hospital and Taipei Medical University Shuang Ho Hospital, in Taiwan showed that the free version of the technology successfully answered common questions about colonoscopy prep. Most trained physicians couldn’t tell which responses were from the bot and which were taken from hospital websites.

Whether the technology can accurately answer more complicated questions is unclear, and will be the focus of future research, said Dr. Braden Kuo, a neurogastroenterologist and director of the Center for Neurointestinal Health at MGH, who worked on the study. Some research has already shown the chatbot is more empathetic than physicians when answering medical questions.

For his part, Kohane said he will be disappointed if hospitals don’t figure out how to use the technology to Improve care, a vision that includes alleviating administrative burdens and allowing physicians to spend more time with patients.

While the larger existential risks are worth considering, he said, the more immediate concern is making sure health systems use AI to Improve patient care and not simply to boost margins.

With the wrong goals, the technology could be problematic, squeezing ever more patient visits with every provider. Patients might be confronted with an empathetic robot when reaching out with questions or concerns, further fracturing the relationship patients have with their physicians.

The fact that the technology has been found to makes things up means it is concerning for use in patient clinical data.

“We need a public discussion about what we are going to do with this technology,” Kohane said. “It can be used to Improve not just the doctor experience but the patient one, and reestablish the relationship that has been incredibly frayed over the last couple of decades. The technology is giving us the opportunity.”

Patients with heart disease could benefit from less extensive interventions thanks to cutting-edge technology that creates 3D computer models of blood flow through the heart's arteries, according to research presented at the British Cardiovascular Society in Manchester.

When the research team trialled the VIRTUHeart^TM technology with doctors treating heart attack patients, they found that using it would have changed the treatment of more than 20 per cent of patients. In many cases, it would have led to fewer patients undergoing an invasive procedure such as having a stent fitted.

By giving doctors a clearer picture of a patient's arteries, the research funded by the British Heart Foundation (BHF) showed that VIRTUHeart^TM could help more heart patients to get the right treatment for them, free up doctors' time and better meet demand on heart care services.

The researchers are currently investigating the impact this technology could have if it was used widely in the NHS, including the effect it might have on waiting lists. They hope that it could be in use in as little as three years.

Dr Hazel Arfah Haley, Interventional Cardiologist at Sheffield Teaching Hospitals NHS Foundation Trust, led the study. She said:

"By giving doctors a better understanding of what is happening inside their patient's blood vessels, we've shown that this technology has the potential to help Improve how we assess and treat heart disease, ensuring patients have the treatment that best meets their needs.

"Our team are also investigating whether VIRTUHeart^TM could Improve treatment for people with another common heart condition called angina, helping to make sure that even more patients get the treatment they need first time around."

There are up to 250,000 coronary angiograms performed in the UK every year - a test which allows doctors to look inside a patient's coronary arteries (which supply the heart muscle with blood) and check for blockages. This is one of the first tests that patients admitted to hospital with a heart attack will undergo and helps doctors plan treatment to restore blood supply to the heart muscle.

But angiograms can be hard to interpret when an artery is only partly blocked, and this can make it challenging for treatment decisions to be made, particularly when doctors are managing patients with complex heart disease.

The innovative technology, developed by researchers at the University of Sheffield, re-creates another invasive but underused test called a Fractional Flow Reserve (FFR) in which doctors insert a special wire into arteries to calculate how well blood is flowing. FFR is underused for several reasons including time pressure, availability, complex anatomy, and operator's familiarity.

Using only the images from a patient's angiogram, VIRTUHeart^TM works as a "virtual FFR" and creates computer models of their blood vessels, allowing doctors to calculate blood flow and find out more about the extent of blockages.

There are around 100,000 hospital admissions each year due to heart attacks, mostly caused by the coronary arteries becoming narrowed and blocked by a build-up of fatty plaques.

Technologies like VIRTUHeart^TM show real promise to Improve treatment as well as reducing unnecessary interventions, expense and complications and freeing up clinicians' time to treat other patients."

Professor Sir Nilesh Samani, Medical Director, British Heart Foundation

The study involved 208 patients who were admitted to hospital with an NSTEMI – a type of heart attack where the affected coronary artery isn't completely blocked. All of the patients had their coronary arteries reconstructed using VIRTUHeart^TM.

After the patients had been treated, the researchers revealed the virtual blood vessel models to their doctors. They found that using the technology would have changed how doctors treated 46 patients (22 per cent). Of these, 21 patients who had an invasive procedure such as a stent would have instead been treated with medication only if the technology had been used to plan their treatment.

Overall, using VIRTUHeart^TM to plan treatment would have led to 42 fewer stents being fitted – a decrease of 18 per cent.

The VIRTUHeart^TM system was developed by the Mathematical Modelling in Medicine research group in the department of Infection, Immunity and Cardiovascular Disease at the University of Sheffield, in partnership with the Insigneo Institute and Sheffield Teaching Hospitals NHS Foundation Trust.

CAMBRIDGE, MASS. (WHDH) - A new Massachusetts Institute of Technology study on sleep is finding that as you’re nodding off you could be at your most creative.

Research from MIT and Harvard Medical School found that the sweet spot is when you’re between sleeping and waking.

Researchers at MIT found that sleep and creativity are connected and that people are inventive as they drift off but the tricky part is timing.

The study also found that people can be guided to dream about a given subject and that those targeted dreams can make them more creative in the waking hours.

The researchers are also working to find out what information about dreams in the later stage of the sleeping process will yield with regards to creativity.

(Copyright (c) 2022 Sunbeam Television. All Rights Reserved. This material may not be published, broadcast, rewritten, or redistributed.)

Estimated read time: 4-5 minutes

Editor's note: This is part of a series looking at the rise of artificial intelligence technology tools such as ChatGPT, the opportunities and risks they pose and what impacts they could have on various aspects of our daily lives.

SALT LAKE CITY — ChatGPT is not always great at providing accurate answers, but there's at least one realm in which it far surpasses social media: common cancer myths.

Dr. Skyler Johnson worked on a study with the Huntsman Cancer Institute days after the artificial intelligence chatbot was made available to see whether ChatGPT has accurate answers for common myths and misconceptions about cancer.

Johnson said the questions they fact-checked through the chatbot were commonly asked questions from a list created by the National Cancer Institute. ChatGPT's answers were pretty accurate, and 97% of the answers matched the answers from the National Cancer Institute.

On social media, about one-third of all articles or sources contain misinformation, according to Johnson.

He said sometimes patients' decisions, like refusing a prescribed or tested treatment in favor of something they read online or heard about from a friend, can lead to poor health outcomes. In a 2018 study, Johnson found patients who make the decision to go with unproven treatments have worse chances for survival; there is almost a sixfold increase in the risk for death.

For a while, it has been clear that social media is a source for much of this misinformation about cancer treatment, Johnson said, adding that "the vast majority of those contain the potential to hurt cancer patients."

He said the amount of misinformation is scary, and it is not uncommon to see patients make decisions to go with an alternative treatment and then come back later with cancer that has spread further.

"That's always disheartening, and I lose a lot of sleep over those situations," Johnson said.

Consequently, it's clear why Johnson was also interested in studying ChatGTP's accuracy. And after seeing the results of this most accurate study, he and other researchers noted answers the chatbot came up with, while accurate, were more vague than the answers provided by the National Cancer Institute.

That had them concerned about whether patients could interpret the answers as being less definitive than they are. Because of this, Johnson said they would not recommend using ChatGPT as a resource.

He also said it's likely ChatGPT would not be as accurate when asked about less-common cancer myths.

"I do think that we have to continually monitor this new information environment that includes these AI chatbots … because there's a potential risk that it starts producing misinformation at some point," Johnson said.

He said things could change, too. The study was completed when ChatGPT was only a few days old, and there have since been multiple updates.

"I have concerns, where things are evolving so quickly in this space, that although it looks accurate right now, it may not be accurate in the future," Johnson said.

He said cancer patients look for alternative treatments because they want to have control, have autonomy over their medical care, actively participate in their care, and because of fear of side effects from treatment.

"There's no guarantees in cancer care, and some people want certainty. … They will often choose false certainties in the face of known uncertainties," Johnson said.

He said doctors can work to Improve trust to help with this, spending more time with patients and communicating better. He said if doctors establish common goals with their patients, often to cure the cancer and reduce pain, then they can build trust.

Johnson splits his time between research and caring for patients directly. He said research allows for population-based changes, but as a physician he makes positive changes for individuals.

He encouraged patients to talk with their physicians about their questions and go to well-established websites for information, like the website for the Huntsman Cancer Institute or the National Cancer Institute.

"I think, a lot of times, patients have some fear that they might be judged by their physician or that their questions might be stupid, but that's rarely the case. Most physicians are very interested to know what patients are thinking about, and they want to help patients make the best decisions possible," he said.

Johnson said he is optimistic that AI could provide a way for cancer communication experts, doctors and organizations to help answer patients' questions accurately.

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