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Many traditional cancer treatments, such as chemotherapy and radiation, effectively destroy cancer cells but often lead to severe side effects that leave patients feeling even more sick.

Two University of Washington researchers are developing treatments that aim to simultaneously treat cancer and improve patients’ quality of life. Miqin Zhang, UW professor of materials science and engineering and of neurological surgery in the UW School of Medicine, develops tiny systems that deliver cancer treatment specifically to cancer cells. Dr. Avik Som, UW assistant professor of materials science and engineering and of radiology in the UW School of Medicine, uses interventional radiology to precisely deliver cancer treatment to the body.

Both Zhang and Som are studying a cancer treatment method called immunotherapy, where a patient’s own immune cells are trained to target and destroy cancer cells. The two researchers are now collaborating with the goal of getting their therapeutics into the clinic.

For World Cancer Day, UW News asked Zhang and Som to discuss their novel materials and how these materials can treat both the cancer and the patient.

Tell us about your research in this area. 

Miqin Zhang: One of our key research areas is developing biocompatible nanoplatforms for cancer diagnosis, treatment and therapy-response monitoring. For example, one of our recent advances is using tiny particles called nanoparticles to deliver immunotherapies or vaccines in preclinical animal models. The payloads from these nanoparticles activate immune cells to eradicate drug-resistant solid tumors and metastases.

In general, our nanoplatforms provide tumor specificity in two unique ways:

• The nanoparticles can carry diverse payloads — including chemotherapeutics and genetic materials — to address tumor heterogeneity
• We can use different methods to trigger our nanoparticles to release their payloads, such as changing the temperature or pH. Other methods include using enzymes or magnetic fields.

Our systems are designed for versatility and can work in tandem with various tumor-targeting and therapeutic agents.

Avik Som: I am a physician-scientist with clinical training in interventional radiology, with a specific focus in interventional oncology. In this field we often deliver therapy directly to single lesions using small needles and wires. This eliminates the need for invasive surgery in patients who are often too sick for surgery.

My research expertise has focused on developing novel drug delivery materials and techniques for interventional radiologists to use, including in the field of immunotherapy. Interventional radiologists have long succeeded at delivering therapy highly precisely within the body. Using the best of material science, my lab looks at changing what we’re delivering to heal our patients of both their cancer and the underlying ravages that the cancer has caused.

How can your materials both extend patients’ lives and improve their quality of life?

MZ: Our new nanoparticle materials promise more effective and less harmful treatments in a variety of ways. First, the nanoparticles target cancer cells specifically, which minimizes side effects and enables controlled drug release to maintain therapeutic levels without toxicity spikes.

Next, we design these nanoparticles using biocompatible materials, such as iron oxide and chitosan coatings, which reduce immune-response reactions and make the nanoparticles more compatible with long-term use.

Cancer’s complex and variable nature means that treatments that are effective for one patient might not work for another, which makes it difficult to create one-size-fits-all solutions. But our nanoparticles support personalized medicine because we can target specific mutated genes in individual patients. Furthermore, we can develop nanoparticles that are multifunctional. For example, a single nanoparticle can have capabilities that enable both monitoring as well as treatment.

AS: The concepts of extending patients’ lives and improving their quality of life have effectively been done in parallel for years. For example, the UW has extensive history and expertise in tissue engineering. But it usually isn’t combined with cancer care because the two goals often feel contradictory: Tissue engineering results from inducing cell growth, while historically cancer therapy has directly focused on killing cells. So the fields have diverged.

But we can design novel materials to do both: One material can use different release rates to stagger the anti-cancer versus tissue-engineering effects. For example, we can use interventional radiology to implant a material directly into a tumor. The material can have an initial burst of drug release that has an anti-cancer effect. And then, after killing the tumor, the residual material can release factors that recruit normal cells to fill in the gap where the cancer was.

Alternatively, as radiologists, we can see where cancer is and isn’t. It is therefore possible to selectively deliver anti-cancer agents to the cancer, while simultaneously delivering pro-tissue engineering agents to normal tissue.

Are any of these treatments currently available in the clinic?

MZ: The process of getting a treatment like this approved is complex and resource-intensive, because it requires extensive research, clinical trials and regulatory approvals. To reduce clinical trial costs, our nanoparticle platform is adaptable for multiple genetic therapies, which offers regulatory advantages and paves the way for FDA approval.

Right now, our nanoparticles are still at the basic research stage and have not yet entered clinical trials. They have, however, demonstrated their efficacy in various pre-clinical animal models. We are now prepared to engage with venture capitalists and major pharmaceutical companies to advance our nanoparticles into clinical trials.

AS: Our research is also still in the basic stage for the moment. We need to determine the best type of material and safest way to deliver it into patients through rigorous pre-clinical testing.

That being said, at the Fred Hutch Cancer Center and UW Medicine, we are leading an intratumoral therapy group that is ramping up clinical trials for patients using therapies that are in development around the country. In addition, we are working on bringing on more minimally invasive tissue engineering trials to the clinic soon.

What part of this collaboration is the most exciting to you?

AS: I was fortunate to meet Miqin during my interview at UW, and we struck up a vibrant conversation. Miqin has been a leader in the fields of biomaterials and drug delivery, and she is an ideal mentor to help me with my goal of bringing these advances to the clinic.

MZ: I have more than 15 years of experience in cancer research, and I strongly believe that interventional radiology is transforming cancer care by offering minimally invasive, precise treatment options that reduce side effects and improve patient outcomes. I am thrilled to collaborate with Avik so that we can apply our advanced materials and his innovative approaches to enhance interventional radiology for cancer treatment and tissue growth in a way that minimizes side effects and improves patients’ quality of life.

Zhang’s research is funded by the Kuni Foundation and the National Institutes of Health. Zhang is also a faculty researcher with the UW Institute for Nano-Engineered Systems and the Molecular Engineering and Sciences Institute. Som’s research has been funded by the Radiologic Society of North America and the National Institutes of Health.

For more information, contact Zhang at mzhang@uw.edu and Som at aviksom@uw.edu.

The vast majority of earthquakes strike inside the Ring of Fire, a string of volcanoes and tectonic activity that wraps around the coastlines of the Pacific Ocean. But when an earthquake hits, the areas that experience the strongest shaking aren’t always the places that suffer the greatest damage.

Take the massive Chi-Chi earthquake, which caused extensive damage in Taiwan in the fall of 1999 and killed more than 2,400 people. The distribution of damage followed an uneven pattern: Deaths caused by the earthquake were concentrated not in densely populated city centers, but in those cities’ suburbs and outer fringes. A similar pattern has occurred following earthquakes in China, Chile and Nepal.

More than two decades later, researchers at the University of Washington have identified a hidden factor behind what they call ‘suburban syndrome’ — migration. Workers from small, rural communities often move into the outer edges of cities, which offer greater economic opportunities but often have low-quality housing that is likely to suffer greater damage during an earthquake. The risk grows even more when migrants come from low-income or tribal villages.

The findings, published in December in the journal Natural Hazards and Earth System Sciences, suggest that emergency management organizations should pay greater attention to migration and housing quality when developing disaster mitigation and response plans.

UW News spoke with lead author Tzu-Hsin Karen Chen, an assistant professor of environmental & occupational health sciences and of urban planning, to discuss ‘suburban syndrome,’ how migration can amplify disparities in a disaster’s impact, and what U.S. officials can learn from a Taiwanese disaster.

Your work on this study builds on an existing model that assesses earthquake risk by considering migration patterns and the movement of vulnerable populations. What does the existing model miss, and why is it important to fill those gaps?  

Tzu-Hsin Karen Chen: This risk-assessment model has been used by many organizations internationally and in the United States. For example, FEMA uses a similar risk model to assess populations exposed to hazards, vulnerabilities and potential disaster impacts. They typically do a comprehensive risk assessment geographically within states and counties, identify areas with potential larger impacts, and then draft a preparedness plan.

In United States, temporary domestic migrants and undocumented immigrants don’t always officially register in government systems. One common reason is the fear of deportation or other legal repercussions. And so, when a government agency like FEMA allocates resources for disaster preparedness or recovery, relying on registered population data can lead to an underestimate of the support required in certain areas.

In Taiwan, our study case, many migrant workers moving from rural to urban areas don’t update their registered residence. They still have their registration back in their hometown, like in a tribal area. It just doesn’t make sense to re-register, because they might have multiple jobs within a single year in different places. To minimize expenses, some workers look for the lowest possible rent, and their rental housing might not be officially registered either. Those could be informal housing structures, like a metal floor added on top of a concrete building, which don’t comply with safety regulations. The informality of this process can help lower their cost of living, but can also leave them more vulnerable to disasters.

How did you get started in this research? 

TKC: I’ll share my personal story, but I also want to acknowledge my co-authors for their years of work in risk assessments. For me, it started back in 2010, when I volunteered in a tribal area of Taiwan teaching computer skills. This provided bigger lessons for me than anything I could’ve taught them. I learned how teenagers often move from their tribal areas downhill to nearby cities to take construction jobs during the off-crop seasons. Those jobs pay more than farm work, but they’re also very physically demanding and often lack worker protections like job security and health insurance. Seeing that put a seed in my mind. 

When I was a master’s student, a team from the National Earthquake Center and Academia Sinica in Taiwan was working on a risk assessment of the Chi-Chi earthquake using the exposure, vulnerability and hazard framework. They had already published a fundamental risk assessment, and reached out to me to develop an extended study by incorporating spatial statistics. That collaboration eventually evolved into the study in this paper. 

The COVID-19 pandemic also shaped this study. I came across news about how migrant workers were stuck in urban fringe areas of India. Because of the lockdown, they weren’t able to continue their work, and their crowded living conditions left them at even greater risk during the pandemic. I started to wonder: How can we shift from a pure statistical model to something more meaningful? How can we bring migration into the center of the discussion? 

The final push came from colleagues’ work at the UW. I’ve noticed initiatives for undocumented students and research efforts around environmental justice and health equity. For example, my co-author Diana Ceballos’s research on migrant worker’s health was particularly motivating. We read and wrote back and forth to refine the framing and discussion in this paper.  

How did you incorporate migration data into a larger earthquake-risk model, and what did you find?

TKC: At the time of the Chi-Chi earthquake in the late 1990s, we didn’t have any detailed migration data. Today, new research uses mobile phone signals to track people, but such data wasn’t available back then. So we adapted the radiation model — a model widely used to predict human migration — to estimate migration flow and used it as a new way to estimate migrants from low-income and tribal areas. This provided new variables to incorporate into the large risk model. 

Most of our findings are supportive of previous studies, where we can see, logically, if there’s stronger ground movement, there are likely to be more fatalities. That’s a very straightforward way of thinking of how disasters can happen. However, it’s not just a physical story. We also confirm that in areas where incomes are lower, there are more fatalities. Income is a known risk factor in the vulnerability theory. What’s unique in this study is that we tested whether an increase in migration flows leads to an increase in fatalities, and we found that to be true. 

Tell me about the migration model. What is it estimating? 

TKC: We applied the radiation model and adapted it to measure different migration populations. The fundamental idea of the radiation model comes from a simple model called the gravity model. In this context, gravity refers to the idea that larger populations have a stronger “pull” on people in nearby communities. The model assumes that, for a place, the number of people who want to migrate to nearby cities depends on the population size of those cities. Larger cities tend to attract more people.  

If the distance is too far, then it costs too much to travel, so the model will predict fewer migrants. But if the city is closer, or even far away but has a very large population, it becomes a more attractive destination, leading to greater migration flow.  

The radiation model builds on these principles and adds another layer. It considers competitors along the way. In other words, migration flow may also be influenced by other cities or opportunities that lie between the starting point and the destination. 

At first glance, it seems obvious that greater migration would lead to higher fatalities in a given area, just because there are more people present when disaster strikes. Is that the primary driver, or are there other factors at play?  

TKC: Logically, if there are more people, and the percentage of fatalities is equal, then there should be more people dying from a specific event. But we found it’s not just about population numbers. There are two additional factors: When migrant workers are from areas with lower incomes, or when they are from tribal areas, those factors significantly contribute to higher fatalities in the places they migrate to. 

Our hypothesis is that it’s about housing safety. Migrant workers tend to move to cities, and when cities are more expensive, affluent workers might be able to secure housing that offers better protection against disasters. However, workers from tribal or low-income areas tend to settle in urban fringe zones where affordable housing options might not meet safety standards, making them more vulnerable to earthquakes.

Why did you choose to study this earthquake from 1999 in particular?  

TKC: The research team that invited me to work on this project was interested in the Chi-Chi earthquake, partly because it was one of the most disastrous in Taiwan’s history. And even 20 years later, there’s still a conference focused on the Chi-Chi earthquake that brings domestic and international researchers to talk about it.

How widely applicable are your findings? Could they help us better understand hazards in other earthquake-prone areas of the world, like, say, the Pacific Northwest?  

TKC: It’s important to consider this risk assessment as a tool for preparedness for future hazards. When the next earthquake occurs, migrant communities will likely face elevated impacts if housing safety policies do not improve.

I believe the migration component is universally important, even outside Taiwan. There has always been a paradox, a structural dilemma of disaster governance: Because migrants are often invisible, they suffer from little support. But making them visible can sometimes lead to exclusion and discrimination. This model represents migrants in a geographic sense rather than identifying every person individually through government surveillance, which could address this challenge. By protecting anonymity while still accounting for migrant populations, the model might help ensure their needs are considered in housing safety and resource allocation.

Co-authors on this study include Diana Ceballos of the UW Department of Environmental & Occupational Health Sciences; Kuan-Hui Elaine Lin of National Taiwan Normal University, Thung-Hong Lin of Academia Sinica in Taiwan; and Gee-Yu Liu and Chin-Hsun Yeh of the National Center for Research on Earthquake Engineering in Taiwan.

For more information, contact Chen at kthchen@uw.edu.

In most doctors’ offices these days, you’ll find a pattern: Everybody’s Googling, all the time. Physicians search for clues to a diagnosis, or for reminders on the best treatment plans. Patients scour WebMD, tapping in their symptoms and doomscrolling a long list of possible problems.  

But those constant searches leave something to be desired. Doctors don’t have the time to sift through pages of results, and patients don’t have the knowledge to digest medical research. Everybody has trouble finding the most reliable information.  

Optimists believe artificial intelligence could help solve those problems, but the bots might not be ready for prime time. In a recent paper, Dr. Gary Franklin, a University of Washington research professor of environmental & occupational health sciences and of neurology in the UW School of Medicine, described a troubling experience with Google’s Gemini chatbot. When Franklin asked Gemini for information on the outcomes of a specific procedure – a decompressive brachial plexus surgery – the bot gave a detailed answer that cited two medical studies, neither of which existed.  

Franklin wrote that it’s “buyer beware when it comes to using AI Chatbots for the purposes of extracting accurate scientific information or evidence-based guidance.” He recommended that AI experts develop specialized chatbots that pull information only from verified sources.  

One expert working toward a solution is Lucy Lu Wang, a UW assistant professor in the Information School who focuses on making AI better at understanding and relaying scientific information. Wang has developed tools to extract important information from medical research papers, verify scientific claims, and make scientific images accessible to blind and low-vision readers. 

UW News sat down with Franklin and Wang to discuss how AI could enhance health care, what’s standing in the way, and whether there’s a downside to democratizing medical research.  

Each of you has studied the possibilities and perils of AI in health care, including the experiences of patients who ask chatbots for medical information. In a best-case scenario, how do you envision AI being used in health and medicine? 

Gary Franklin: Doctors use Google a lot, but they also rely on services like UpToDate, which provide really great summaries of medical information and research. Most doctors have zero time and just want to be able to read something very quickly that is well documented. So from a physician’s perspective trying to find truthful answers, trying to make my practice more efficient, trying to coordinate things better — if this technology could meaningfully contribute to any of those things, then it would be unbelievably great. 

I’m not sure how much doctors will use AI, but for many years, patients have been coming in with questions about what they found on the internet, like on WebMD. AI is just the next step of patients doing this, getting some guidance about what to do with the advice they’re getting. As an example, if a patient sees a surgeon who’s overly aggressive and says they need a big procedure, the patient could ask an AI tool what the broader literature might recommend. And I have concerns about that. 

Lucy Lu Wang: I’ll take this question from the clinician’s perspective, and then from the patient’s perspective.  

From the clinician’s perspective, I agree with what Gary said. Clinicians want to look up information very quickly because they’re so taxed and there’s limited time to treat patients. And you can imagine if the tools that we have, these chatbots, were actually very good at searching for information and very good at citing accurately, that they could become a better replacement for a type of tool like UpToDate, right? Because UpToDate is good, it’s human-curated, but it doesn’t always contain the most fine-grained information you might be looking for. 

These tools could also potentially help clinicians with patient communication, because there’s not always enough time to follow up or explain things in a way that patients can understand. It’s an add-on part of the job for clinicians, and that’s where I think language models and these tools, in an ideal world, could be really beneficial. 

Lastly, on the patient’s side, it would be really amazing to develop these tools that help with patient education and help increase the overall health literacy of the population, beyond what WebMD or Google does. These tools could engage patients with their own health and health care more than before.  

Zooming out from the individual to the systemic, do you see any ways AI could make health systems as a whole function more smoothly? 

GF: One thing I’m curious about is whether these tools can be used to help with coordination across the health care system and between physicians. It’s horrible. There was a book called “Crossing the Quality Chasm” that argued the main problem in American medicine is poor coordination across specialties, or between primary care and anybody else. It’s still horrible, because there’s no function in the medical field that actually does that. So that’s another question: Is there a role here for this kind of technology in coordinating health care? 

LLW: There’s been a lot of work on tools that can summarize a patient’s medical history in their clinical notes, and that could be one way to perform this kind of communication between specialties. There’s another component, too: If patients can directly interact with the system, we can construct a better timeline of the patient’s experiences and how that relates to their clinical medical care. 

We’ve done qualitative research with health care seekers that suggests there are lots of types of questions that people are less willing to ask their clinical provider, but much more willing to put into one of these models. So the models themselves are potentially addressing unmet needs that patients aren’t willing to directly share with their doctors. 

What’s standing in the way of these best-case scenarios?  

LLW: I think there are both technical challenges and socio-technical challenges. In terms of technical challenges, a lot of these models’ training doesn’t currently make them effective for tasks like scientific search and summarization.  

First, these current chatbots are mostly trained to be general-purpose tools, so they’re meant to be OK at everything, but not great at anything. And I think there will be more targeted development towards these more specific tasks, things like scientific search with citations that Gary mentioned before. The current training methods tend to produce models that are instruction-following, and have a very large positive response bias in their outputs. That can lead to things like generating answers with citations that support the answer, even if those citations don’t exist in the real world. These models are also trained to be overconfident in their responses. If the way the model communicates is positive and overconfident, then it’s going to lead to lots of problems in a domain like health care.  

And then, of course, there’s socio-technical problems, like, maybe these models should be developed with the specific goal of supporting scientific search. People are, in fact, working toward these things and have demonstrated good preliminary results. 

GF: So are the folks in your field pretty confident that that can be overcome in a fairly short time? 

LLW: I think the citation problem has already been overcome in research demonstration cases. If we, for example, hook up an LLM to PubMed search and allow it only to cite conclusions based on articles that are indexed in PubMed, then actually the models are very faithful to citations that are retrieved from that search engine. But if you use Gemini and ChatGPT, those are not always hooked up to those research databases.  

GF: The problem is that a person trying to search using those tools doesn’t know that. 

LLW: Right, that’s a problem. People tend to trust these things because, as an example, we now have AI-generated answers at the top of Google search, and people have historically trusted Google search to only index documents that people have written, maybe putting the ones that are more trustworthy at the top. But that AI-generated response can be full of misinformation. What’s happening is that some people are losing trust in traditional search as a consequence. It’s going to be hard to build back that trust, even if we improve the technology. 

We’re really at the beginning of this technology. It took a long time for us to develop meaningful resources on the internet — things like Wikipedia or PubMed. Right now, these chatbots are general-purpose tools, but there are already starting to be mixtures of models underneath. And in the future, they’re going to get better at routing people’s queries to the correct expert models, whether that’s to the model hooked up to PubMed or to trusted documents published by various associates related to health care. And I think that’s likely where we’re headed in the next couple of years.  

Trust and reliability issues aside, are there any potential downsides to deploying these tools widely? I can see a potential problem with people using chatbots to self-diagnose when it might be preferable to see a provider. 

LLW: You think of a resource like WebMD: Was that a net positive or net negative? Before its existence, patients really did have a hard time finding any information at all. And of course, there’s limited face time with clinicians where people actually get to ask those questions. So for every patient who wrongly self-diagnoses on WebMD, there are probably also hundreds of patients who found a quick answer to a question. I think that with these models, it’s going to be similar. They’re going to help address some of the gaps in clinical care where we don’t currently have enough resources.  

For more information or to reach the researchers, email Alden Woods at acwoods@uw.edu. 

When University of Washington President Ana Mari Cauce launched the Population Health Initiative in 2016, she spoke in soaring, ambitious terms. “We have an unprecedented opportunity to help people live longer, healthier, more productive lives – here and around the world,” she said. UW researchers have leapt at that opportunity, forging connections across the university, working side by side with community partners and breaking down traditional barriers to improving public health.  

In just eight years, the Initiative has funded 227 innovative, interdisciplinary projects. Many are focused right here in Western Washington, where projects have helped improve transportation accessibility in South Seattle, identified soil contaminants in community gardens in the Duwamish Valley, and improved how community leaders along the Okanogan River communicate the public health risks of wildfire smoke. Other projects have reached across the globe, targeting health disparities in Somalia, Peru, Brazil and more.  

“In this relatively short period of time, we’ve demonstrated the power that accrues when faculty and staff across the various areas of our campuses are working together and also exposing students to the cutting-edge work of tackling grand challenges,” Cauce said in her most recent campus address. 

And they’re just getting started. Many PHI-funded projects are still in their earliest stages, leveraging initial funding to show proof-of-concept for their ideas and setting the stage for future work. Fourteen projects so far have received much larger grants to empower researchers and community partners to expand successful projects and scale up for greater impact. 

With the Initiative now a third of the way into its 25-year vision, UW News checked in with three projects that recently received funding to scale their efforts. 

Spotting potential memory health issues in rural Washington

Diagnosing memory health issues in the best of circumstances is extraordinarily difficult. Patients typically make multiple visits to their doctor and take a rash of tests, many of which can produce flawed results — people who take the same test more than once, for example, will often score higher, potentially masking memory loss.  

It’s even harder in rural America, which has a severe shortage of neurologists. Patients seeking memory care might have to make a long, expensive trip to a major city, which leads many people to wait until a problem becomes apparent. By then, it’s often too late — modern treatments can slow the progress of memory loss, but there’s no way to regain what’s been lost. 

“So, how do you catch it early?” said Andrea Stocco, a UW associate professor of psychology. “We give people an app to have them check for themselves.”  

Stocco and Dr. Thomas Grabowski, director of the UW Alzheimer’s Disease Research Center, together with Hedderik van Rijn of the University of Groningen in the Netherlands, led the development of an online program that can measure a person’s memory and predict their risk of memory disorders. Like a flash-card app that helps students cram for a test, the program shows pictures and asks the user to recall what they saw a few minutes earlier. The app records how quickly and accurately the user responds to each question and makes the next one a little easier or more difficult.  

Researchers have long understood that a person’s ability to recall a specific memory tends to fade over time. This is called the “forgetting curve.” In previous work, Stocco and van Rijn found that they could measure individual differences in the slopes of such curves.  The app works by comparing a person’s responses to an internal model of forgetting and adjusting the slope of the model until it matches the responses. The resulting slope can be used to estimate the likelihood that their memory is fading faster than normal.  

By taking the test regularly, a person can track their memory’s decline over time. But preliminary tests, Stocco said, have shown that even a single use can spot a potential problem. 

“Just by looking at a single lesson, based on the result, there’s almost a perfect correspondence between the speed of forgetting and your probability of being diagnosed by a doctor,” Stocco said. “It can be as accurate as the best clinical tests but, instead of taking two or three hours, this can be done in eight minutes, and you don’t need a doctor.” 

A Tier 3 grant from the Population Health Initiative and a collaboration with the Central Washington Area Health Education Center will allow the researchers to share the app with up to 500 people in rural Chelan and Douglas counties. Participants can take the test on their own time, and the results will be shared with researchers. If a potential problem emerges, the researchers plan to invite participants to Seattle for an in-person evaluation.  

“It’s a solution that seems to solve these problems of early access and diagnostic bottlenecks,” Stocco said. “If this works, there’s no problem giving it to everybody in the state. We’re really interested in expanding and adding people from underrepresented populations and underrepresented areas, and the grant will allow us to do that.” 

Nancy Spurgeon of the Central Washington Area Health Education Center is also a collaborator on the project to test the prototype app, which is not yet available to the public. 

Revamping the Point-In-Time Count to better understand King County’s unhoused population 

For years, volunteers fanned across King County on a cold night each January, flashlights and clipboards in hand, searching for people sleeping outside. They’d also gather the shelter head counts for that night. Officially called the Point-In-Time Count, this effort attempted to tally the number of people who lacked stable housing. This endeavor was replicated in cities across the country, and the results were combined to create a national count that influences how the federal government allocates funding. 

There’s just one problem – the count is notoriously inaccurate. Volunteers can’t possibly find everybody. It captures only a single moment in time, and collects only limited data on people’s circumstances or personal needs. A person sleeping in their car might need different services than a person who sleeps in a tent, and the count didn’t fully capture that distinction. 

So, a team of UW researchers designed a better way to count. Their method, detailed in a paper published Sept. 4 in in the American Journal of Epidemiology, taps into people’s social networks to generate a more representative sample, which the researchers then ran through a series of calculations to estimate the total unhoused population.   

Called “respondent-driven sampling,” the method stations volunteers in common “hubs,” like libraries or community centers, and offers cash gift cards for in-person interviews and peer referrals. Volunteers collect detailed information on people’s circumstances and needs, giving each person three tickets to share with their unhoused peers. When those peers come in for an interview and show the ticket, the person who referred them receives another small reward. The new person gets a gift card and another three tickets. 

“This method gives people a more active voice in being counted. It’s a more humane way to count people, and it’s also voluntary,” said Zack Almquist, a UW associate professor of sociology and co-lead on the project. “The regular PIT (Point-In-Time) count just counted people. Now we can collect all sorts of information from people on their circumstances and their needs. Should policymakers want to, they could leverage that data to change service offerings.” 

The researchers received a Tier 2 grant to develop the system. They launched it in partnership with King County in 2022 and 2024, and were recently awarded a Tier 3 grant to test out the feasibility of running it quarterly.  

“Running the count quarterly allows us to estimate how many people move in and out of homelessness and whether there are seasonal changes, which are rarely measured,” Almquist said. “Also, people’s needs change depending on the time of year, and this method will help us better understand those rhythms.”  

Other cities and counties have expressed interest, the researchers said. The team has also begun to expand the effort, aiming to improve data across the broad spectrum of housing and homelessness services.  

“A very important byproduct of this work across schools and departments at UW is that we can create an ecosystem of people and projects,” said Amy Hagopian, a UW professor emeritus of health systems and population health and co-lead on the project. “We’ve spun off projects on sleep assessments, relationships with organizations that collect data on homelessness, and we’re mapping the sweeps of encampments in relationship to where people choose to be located. We have a whole network of homelessness-related research now. 

“These PHI grants gave us the fuel to ignite these projects.” 

Other collaborators are Paul Hebert of the UW Department of Health Systems and Population Health and of the VA Health Services Research and Development; Tyler McCormick of the UW Departments of Sociology and Statistics; Junhe Yang of the Center for Studies in Demography & Ecology and the eScience Institute; and Owen Kajfasz, Janelle Rothfolk and Cathea Carey of the King County Regional Homelessness Authority. 

Engaging community to mitigate flood risk in the Duwamish Valley 

More than a century ago, Seattle leaders set out to control and redirect the Duwamish River. They dredged the riverbed and dug out its twists and turns. Wetlands were filled in, the valley was paved over and a system of hydrology was severed. What had been a wild, winding river valley with regular flooding became an angular straightaway built for industry. But when UW postdoctoral scholar Maja Jeranko looks out at the Duwamish, she sees the river fighting back.  

“The water was always there,” Jeranko said, “and now it’s fighting to come back up.”  

The river returned with devastating effect in December 2022, when a king tide and heavy rainfall flooded the South Park neighborhood, submerging homes and shuttering local businesses. The underserved neighborhood faces a significant risk of future floods. 

To mitigate that risk, the City of Seattle has updated the neighborhood’s stormwater drainage system and launched a new flood-warning system. But the Duwamish River Community Coalition, a nonprofit focused on river pollution and environmental health, saw an opportunity for something greater. The DRCC asked a team of UW researchers to help develop flood adaptation plans that are community-based, culturally responsive and that enrich the local environment.  

“In the community, people don’t think there’s been enough engagement. There’s all this talk about flood mitigation, but all they see are sandbags,” Jeranko said. “So DRCC was like, ‘Look, we really need the people who live in the flood zone to understand the solutions.’ Because we have this long-lasting relationship with them, they see us as someone who’s able to provide a list of solutions, not favor one over the others, and do it in an informative way.” 

Boosted by a Tier 3 grant from the PHI, Jeranko and a team representing five UW departments, the Burke Museum and the DRCC are engaging with the community. This fall, the team will present the neighborhood with an expansive list of flood mitigation options and encourage city leaders to consider people’s preferences. Early work shows the community would favor nature-based solutions, Jeranko said. Floodable parks, for example, would provide ecological, recreational and public health benefits to the entire community, while storing flood water during storms.  

“It has been wonderful to collaborate with the UW team on this to make sure we are centering community voices in every single step of the planning for climate resilience,” said Paulina López, executive director of the DRCC. “Community leadership and representation is indispensable to bring climate justice to the Duwamish Valley.” 

Jeranko hopes their community-based model will be replicated by communities across the country facing similar risks from climate change and sea level rise. 

“Even though UW and a lot of other universities really support and invest in community-engaged work, a lot of times it’s fundamentally hard to make that research happen,” Jeranko said. “But the Population Health Initiative grant was about supporting all those things.” 

Other collaborators on the project are Nicole Errett, BJ Cummings, Katelin Teigen and Juliette Randazza of the Department of Environmental & Occupational Health Sciences; Celina Balderas Guzman of the Department of Landscape Architecture; Bethany Gordon of the Department of Civil & Environmental Engineering, Sameer Shah of the School of Environmental and Forest Sciences; Amir Sheikh of the Quaternary Research Center and the Burke Museum; and López and Robin Schwartz of the DRCC. 

For more information on any of the projects mentioned, or to learn more about the UW Population Health Initiative, visit the Initiative’s website or contact Alden Woods at acwoods@uw.edu.  

Twelve years after Washington and Colorado became the first states to legalize recreational marijuana, it’s safe to say that weed is here to stay. Nearly 30% of Washington adults report using cannabis in the last month, and a majority of Americans believe marijuana products are safe.  

When it comes to the safety of long-term marijuana use among the general population, the jury’s still out. But there are some groups for whom cannabis poses a serious health risk. Among the most vulnerable are young adults with psychosis, who tend to use cannabis at extremely high rates, and whose symptoms can be exacerbated by long-term marijuana use. A team of University of Washington researchers is focused on this particular group. 

To effectively treat these patients’ symptoms and improve long-term outcomes, it’s critical for providers to help young adults stop using marijuana as quickly as possible after their first psychotic episode. But that’s proven tricky. Current best practices aren’t always effective for young adults with psychosis, who tend to use cannabis for different reasons than their peers and who may feel different effects. 

That leaves mental health care providers with a difficult problem: How can they best discern why their patients use cannabis, and what’s the best way to help them stop?  

UW researchers Denise Walker and Ryan Petros, from the School of Social Work, and Maria Monroe-DeVita, an associate professor in department of psychiatry and behavioral sciences in the UW School of Medicine, studied motivations among this group and then developed a novel treatment method. A pilot study of 12 people showed the method to be effective, though final results have yet to be published. UW News sat down with the research team to discuss their intervention and why it’s so important to help young people in this group cut down their use. 

Cannabis use is increasing across the board, but the numbers are staggeringly high among young adults with psychosis – you cite statistics estimating that 60-80% have used cannabis at some point in their lifetime. What makes a person experiencing psychosis so much more likely to use cannabis?  

Denise Walker: Many people were probably using cannabis before the onset of their psychosis symptoms, because there is strong research evidence that cannabis increases the risk for developing psychosis-related disorders. For those who do develop a psychosis-related disorder like schizophrenia, continued cannabis use impedes the recovery process and makes outcomes worse. There is still a lot more to learn about the cause and effect of these relationships, but cannabis does seem to have a unique relationship with psychosis. 

Ryan Petros: In addition, there is some evidence to suggest that people with schizophrenia are more prone to feeling bored than people without schizophrenia. In general, a lot of people use cannabis because they like it, and they find the associated high to be fun. It may be that people with schizophrenia-spectrum disorders are more likely to use cannabis to have fun and feel good because they are more likely to feel bored and less likely to feel pleasure in everyday activities. But the fact of the matter is, we don’t really know. Another reason that people use cannabis, in general, is because it facilitates social interactions or provides a shared activity in social settings. Because people with schizophrenia-spectrum disorders have smaller social networks and fewer social engagements, it may be that they use cannabis to facilitate improved social interaction, but here again, we need more research to know with more certainty. 

At the heart of all this research is the different health risks of cannabis use for people with and without psychosis or other mental health challenges. What are those differences, and why is cannabis use among young adults with psychosis particularly concerning? 

RP: For people with a psychosis, cannabis use is associated with higher rates of dropping from treatment and decreased adherence to medication. It leads to increased symptoms of psychosis and higher rates of psychiatric rehospitalization. In the long –term, cannabis use increases the risk of poor psychosocial outcomes and diminished overall functioning. 

DW: Essentially, continued cannabis use makes it much harder for young adults with psychosis to take advantage of treatment, make strides in their recovery and, ultimately, get on with having the life they want. 

RP: Another major reason for concern is that not only is cannabis use on the rise, people also have progressively adopted more tolerant attitudes toward cannabis. Cannabis has recently overtaken alcohol as the drug most often used on a daily basis in the United States. While some people can use cannabis without a problem, it’s recommended that some others abstain from using at all.  Over time, however, people have come to believe that cannabis use has health benefits, and they are less likely to perceive risks of use. This may result in a particularly challenging set of circumstances for helping someone with psychosis to learn about the real risks that cannabis use has for their health and wellness and to make the choice to reduce or abstain from use. 

DW: I agree. Perceptions surrounding cannabis are often polarized – it is often viewed as either “good” or “bad,” when in reality, it’s somewhere in the middle. There can be benefits for some to use cannabis and real risks of harm for others. These mixed messages, or at least the lack of acknowledgement of harms, contribute to continued hardship for those experiencing psychosis and their families. 

What methods are currently recommended to help people reduce their cannabis use, and why might those not be as effective for young adults with psychosis?  

DW: The gold standard treatment includes a combination of motivational enhancement therapy (MET), cognitive behavioral therapy (CBT), and contingency management. Contingency management is often not available in the community, and studies show that MET plus CBT perform almost as well. Because it is normal for motivation to wax and wane for someone contemplating changing their cannabis use, MET addresses the issue of motivation early on. CBT teaches skills to avoid drug use, cope with social situations and negative moods, and solve problems without the use of cannabis. Family therapy is another option with strong support.  

The big problem is that we don’t know if these treatments are effective for young adults with psychosis.  MET is the most studied intervention in cannabis treatment, alone and in combination; however, it has not been tested with young adults with psychosis.  With a few optimizations, we believe that it could perform even better than with the general population, and we have begun to test it with young adults with psychosis. 

Your team has developed an intervention for young adults with psychosis that incorporates MET. Can you describe what that intervention looks like, and why it might be more effective for this population?  

DW: MET is a person-centered, nonjudgmental approach that facilitates an honest and candid discussion about cannabis use. The techniques are intended to draw out the individuals’ personal reasons for making a change and to grow their motivation to do so. Individualized feedback is created based on a client’s responses to an assessment of their cannabis use and related experiences and summarizes information about their cannabis use patterns, how their cannabis use compares with others, and their risk factors for developing a cannabis use disorder. It also provides an opportunity for clients to think about their personal goals and how their cannabis use promotes or detracts from their ability to attain those goals.  

When we asked young adults with psychosis what they wanted in a cannabis intervention, they were clear that they wanted an individualized and nonjudgmental approach. They also said they wanted accurate and science-based information about the relationship between cannabis and psychosis. MET ticks those boxes. With a few adaptations, it is an ideal format for providing objective information, while also inviting the young adult to talk it through and consider what the information means to them personally. 

Currently, providers are giving the message to patients that cannabis is harmful for those with psychosis, which is a great start.  But most providers don’t feel confident discussing why cannabis is harmful and what the research has found.  My sense is that patients often take that message and defend against it with their own personal experiences of what they like about cannabis. MET offers an invitation to receive and discuss objective evidence, consider their own experiences of how cannabis affects their symptoms and what they want for their future, and do so in a supportive environment that allows for looking at their use from a variety of perspectives.   

You ran a pilot program to understand how the new intervention works. What did you learn in that pilot study?  

DW: We adapted the MET intervention to include personalized feedback on the interaction between cannabis and psychosis and included some graphics and ideas about ways to reduce those risks in addition to abstinence. Twelve young adults experiencing psychosis who used cannabis regularly enrolled in the study and were offered the intervention. Most of the participants were not interested in changing their use of cannabis at the outset of the study, and by the end, several chose to reduce their cannabis use. 

Overall, the feedback was very positive. Participants overwhelmingly said they would recommend the intervention and would retain the psychosis specific pieces of the conversation. They appreciated the data that was included and the opportunity to discuss what it meant for them. They also said they enjoyed talking about how cannabis fits into their larger life and goals for the future. Overall, the feedback suggests this intervention has promise and should be studied in a larger trial. 

Maria Monroe-DeVita: My long-term goal would be to offer this new intervention either in addition to, or integrated within, the evidence-based package of services known to work best for individuals experiencing first episode psychosis. 

Denise Walker is a research professor in the UW School of Social Work, Ryan Petros is an associate professor in the UW School of Social Work, and Maria Monroe-DeVita is an associate professor of psychiatry and behavioral sciences in the UW School of Medicine.  

For more information or to reach the researchers, contact Alden Woods at acwoods@uw.edu.