More WA drug users are smoking rather than injecting, UW study finds 27%

By Ayeda Masood0%

4/24/2026, 7:15:17 PM

BS Summary: This article contains 26 faulty reasoning types, including Post Hoc (False Cause), Optimism Bias, and Unattributed Quote, with Appeal to Authority as the most egregious example at 30.3% saturation with 223 hits. Analysis detected 1,560 faulty-reasoning hits from 737 analyzed words, generating a BS Score of 38.4% and a BS Rank of 27% (16,016 of 21,887 articles). This article is better (less manipulative) than 73.20% of the article peer group.

More illegal drug users in Washington state are smoking drugs rather than injecting them. 
Results from the latest Syringe Services Program (SSP) Health Survey reveal that, since 2021, there has been a 49 percentage point decrease in respondents injecting drugs. 
In 2025, 90% of respondents reported smoking drugs the week prior, while only 44% had used a syringe. 
The survey is conducted every two years by the Addictions, Drug & Alcohol Institute at the University of Washington, and asks SSP participants throughout Washington state about their health needs, drug use patterns, and interest in treatment services. 
Nearly 1,700 SSP participants across 24 counties participated in the survey in 2025. 
SSPs are public health programs that provide resources to drug users so they can use safely, with the ultimate goal of saving lives and mitigating harm. 
There are about 40 of these programs in Washington state. 
Resources the program provides include education on overdose prevention, naloxone, HIV and hepatitis C testing, treatment and housing referrals, and supplies to promote safe drug use, according to the Washington State Department of Health. 
RELATED: Crime and drugs are Seattle voters' top concerns, new survey finds 
The Addictions, Drug & Alcohol Institute uses the results from the survey to assess and help improve programs for people who use drugs. 
For instance, as a result of the 2023 SSP survey, Washington funded health engagement hubs, where people can get physical care, harm reduction, mental health care, and substance use disorder treatment. 
Alison Newman, a lead author on the report, attributes the increase in smoking to a change in the drug supply with fentanyl becoming more popular than heroin. 
“Heroin… tended to have more black tar, which needed to be injected rather than smoked in order for people to use it,” Newman explained. 
“Fentanyl is more potent, people were able to get a similar effect from smoking it.” 
RELATED: Fentanyl fuels a persistent ‘hot spot’ at Seattle’s 12th and Jackson. 
What will it take to fix it? 
The survey also found that users were less likely to inject drugs at SSPs that provided smoking supplies. 
“At sites with smoking supplies, 94% of people smoked, and at sites without smoking supplies, 78% of people smoke,” Newman said. 
“However, when you flip it and look at past week injections, twice as many people are injecting at sites without smoking supplies.” 
RELATED: In new assessment, Trump team ranks fentanyl as a top threat to U.S. 
Because fentanyl is widespread, providing smoking supplies helps users smoke safely, Newman explained. 
While providing smoking supplies does not increase a user’s desire to smoke, it could cause them to inject less. 
“We know that especially safe injection supplies help reduce the risk of HIV and hepatitis C,” Newman said, “and we think safer smoking supplies helps bring people in the door to engage in all these other really important services." 
Other significant findings from the survey include: 
Methamphetamine remained the most frequently used drug (90%), followed by fentanyl (58%), cannabis (50%), alcohol (26%), crack or cocaine (26%), and heroin (9%). 
The majority of people surveyed wanted to stop using opioids or stimulants. 
Over half of the respondents were unhoused and around a quarter were in temporary or unstable housing. 
Newman says the percentage of drug users who were unhoused was higher in 2025 than past years. 
SSPs have adapted to meet the needs of the growing unhoused population amongst people who seek help from these programs. 
For example, Newman said they have started providing hygiene services, shower programs, and are helping connect people with food assistance.. 
SSPs are effective in improving public health in communities and connecting drug users with treatment, according to the state DOH. 
SSP participants are more than five times more likely to enter substance use treatment, and about three times more likely to report decreasing or stopping injecting drugs, the DOH reports. 
More than half of participants in the survey said they’re interested in more services from SSPs, including drug testing, as well as physical and mental health care. 
However, the DOH says SSPs still face "political challenges and stigma.” 
“I know that sometimes smoking supplies are seen as controversial, but we know they're really helping to engage a group of people that can otherwise be really hard to reach,” Newman said. 
“We really want to help support their health, and provide support and referrals.” 
Article reasoning-pattern comparisonThis article: 10.3%Ayeda Masood: 2.2%KUOW: 2.6%Confirmation Bias10.3%This article: 5.2%Ayeda Masood: 0.5%KUOW: 1.3%Anchoring Bias5.2%This article: 5.2%Ayeda Masood: 3.4%KUOW: 3.4%Availability Heuristic5.2%This article: 6.8%Ayeda Masood: 2.4%KUOW: 1.2%Representativeness Heuristic6.8%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.7%Hindsight Bias0.0%This article: 6.6%Ayeda Masood: 1.1%KUOW: 1.4%Overconfidence Bias6.6%This article: 5.6%Ayeda Masood: 3.0%KUOW: 7.4%Framing Effect5.6%This article: 0.0%Ayeda Masood: 0.0%KUOW: 1.0%Loss Aversion0.0%This article: 2.7%Ayeda Masood: 0.6%KUOW: 1.0%Status Quo Bias2.7%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.2%Sunk Cost Effect0.0%This article: 15.9%Ayeda Masood: 6.1%KUOW: 3.8%Optimism Bias15.9%This article: 0.0%Ayeda Masood: 1.8%KUOW: 1.8%Pessimism Bias0.0%This article: 4.2%Ayeda Masood: 2.6%KUOW: 8.0%Negativity Bias4.2%This article: 7.5%Ayeda Masood: 2.0%KUOW: 2.0%Self-Serving Bias7.5%This article: 0.0%Ayeda Masood: 0.1%KUOW: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Ayeda Masood: 0.1%KUOW: 0.2%Actor-Observer Bias0.0%This article: 4.3%Ayeda Masood: 1.7%KUOW: 2.0%In-Group Bias4.3%This article: 0.0%Ayeda Masood: 0.2%KUOW: 0.5%Out-Group Homogeneity Bias0.0%This article: 11.5%Ayeda Masood: 2.5%KUOW: 2.7%Halo Effect11.5%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.2%Horn Effect0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.0%Dunning-Kruger Effect0.0%This article: 5.2%Ayeda Masood: 0.6%KUOW: 1.1%Recency Bias5.2%This article: 1.6%Ayeda Masood: 0.3%KUOW: 0.4%Primacy Effect1.6%This article: 0.0%Ayeda Masood: 0.2%KUOW: 0.0%Blind-Spot Bias0.0%This article: 0.0%Ayeda Masood: 0.1%KUOW: 0.5%Ad Hominem0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.3%Straw Man0.0%This article: 30.3%Ayeda Masood: 5.2%KUOW: 4.3%Appeal to Authority30.3%This article: 3.0%Ayeda Masood: 1.8%KUOW: 1.4%False Dilemma3.0%This article: 2.6%Ayeda Masood: 0.3%KUOW: 0.9%Slippery Slope2.6%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.1%Circular Reasoning0.0%This article: 8.8%Ayeda Masood: 6.0%KUOW: 4.1%Hasty Generalization8.8%This article: 0.0%Ayeda Masood: 0.3%KUOW: 0.3%Red Herring0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.8%Bandwagon0.0%This article: 9.6%Ayeda Masood: 4.1%KUOW: 6.1%Appeal to Emotion9.6%This article: 0.0%Ayeda Masood: 0.2%KUOW: 0.8%Begging the Question0.0%This article: 23.9%Ayeda Masood: 4.5%KUOW: 2.2%Post Hoc (False Cause)23.9%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.1%Tu Quoque0.0%This article: 0.0%Ayeda Masood: 0.4%KUOW: 0.3%Burden of Proof0.0%This article: 1.8%Ayeda Masood: 0.6%KUOW: 0.2%Appeal to Nature1.8%This article: 1.8%Ayeda Masood: 0.4%KUOW: 0.2%Composition/Division1.8%This article: 0.0%Ayeda Masood: 2.3%KUOW: 3.3%Anecdotal0.0%This article: 0.0%Ayeda Masood: 0.3%KUOW: 0.1%No True Scotsman0.0%This article: 9.4%Ayeda Masood: 1.4%KUOW: 1.4%Ambiguity (Equivocation)9.4%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.1%Middle Ground0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.1%Personal Incredulity0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.2%Special Pleading0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.2%Genetic Fallacy0.0%This article: 14.9%Ayeda Masood: 2.3%KUOW: 1.0%Unattributed Quote14.9%This article: 0.0%Ayeda Masood: 0.2%KUOW: 0.8%Quote-first Misdirection0.0%This article: 7.9%Ayeda Masood: 0.8%KUOW: 3.2%Biased Writer Voice7.9%This article: 5.3%Ayeda Masood: 1.4%KUOW: 1.5%Indoctrination5.3%This article: 0.0%Ayeda Masood: 0.5%KUOW: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Ayeda Masood: 0.0%KUOW: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%Ayeda Masood: 2.3%KUOW: 1.3%Attempt to Sell a Product or S…0.0%

737 words analyzed.

Speakers

1speaker33%attributed speech494writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 38 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 26 words • 100.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageAlison Newman • 27 words • 0.0% coverageAlison Newman • 24 words • 100.0% coverageAlison Newman • 15 words • 100.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageAlison Newman • 21 words • 0.0% coverageAlison Newman • 22 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageAlison Newman • 13 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageAlison Newman • 39 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageAlison Newman • 17 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageAlison Newman • 20 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageAlison Newman • 32 words • 100.0% coverageAlison Newman • 13 words • 100.0% coverage
Selected voice

Alison Newman

100%flagged-word coverage
243 attributed words100% of attributed speech85% writer coverage
0%25.0%50.0%Unattributed Quote+45.3 ptsWriter: 0.0%Alison Newman: 45.3%45.3%Biased Writer Voice+7.9 ptsWriter: 5.3%Alison Newman: 13.2%13.2%Indoctrination+0.1 ptsWriter: 5.3%Alison Newman: 5.3%5.3%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.