From broken arms to brain injuries: The alarming toll of SF’s e-bike boom 2%

By Garrett Leahy18%

8/7/2026, 6:00:00 AM

BS Summary: This article contains 31 faulty reasoning types, including Availability Heuristic, Negativity Bias, and Post Hoc (False Cause), with Anecdotal as the most egregious example at 16.5% saturation with 261 hits. Analysis detected 2,442 faulty-reasoning hits from 1,586 analyzed words, generating a BS Score of 6.7% and a BS Rank of 2% (29,233 of 29,795 articles). This article is better (less manipulative) than 98.10% of the article peer group.

The first time Sabrina Yeung rode an e-bike, she broke her arm. 
The 33-year-old tech worker was leaving Hayes Valley the evening of June 19 to meet her boyfriend at Haight pizza spot Jules  a little too far to walk, but too close for an Uber. 
She had some time, so it seemed like the perfect chance to try a Lyft e-bike. 
But when she began pedaling, she was unprepared for the jolt of power from the motor. 
After a few feet, she fell, using her left arm to catch herself and the heavy bike. 
The next morning, she felt a sharp pain whenever she twisted it. 
“That’s when I realized, ‘Oh, it’s probably more serious than just a simple strain,’” she said. 
Such stories are becoming more frequent. 
At SF General, the city’s only trauma center, injuries from e-bikes, scooters, and other stand-up devices are the second-most-common source of trauma, after falls among older adults, according to ER chief Dr. 
Christopher Colwell. 
Five years ago, he could go a day or two without an e-bike or scooter patient. 
Now he sees at least two or three a day  sometimes far more. 
“We don’t go a day without seeing it,” he said. 
‘People don’t seem to be wearing helmets’ 
On July 4, a patient landed in Colwell’s ER after falling off a scooter while traveling about 30 mph downhill without a helmet and “basically face-planted,” he said. 
He said she needed plastic surgery for “very significant cosmetic” damage and suffered a concussion but no lasting brain damage  the most debilitating possible outcome of a head injury. 
SF General sees riders with catastrophic head injuries “a couple of times” a month, Colwell said, often from being hit by a car but also from high-speed falls on e-bikes and scooters. 
This isn’t just a San Francisco problem. 
E-bike and scooter injuries are rising across California and the country  the Consumer Product Safety Commission counted nearly 250,000 ER visits involving e-bikes and e-scooters nationwide between 2017 and 2022  and cities from New York to Sacramento are racing to write rules for vehicles that got popular faster than regulators could keep up. 
In San Francisco, the injuries are climbing just as Lyft prepares to add hundreds more e-bikes under a five-year expansion announced last week. 
Lyft currently operates 2,333 e-bikes and 1,380 pedal bikes citywide, according to the Metropolitan Transportation Commission. 
ER doctors say the number of patients treated for e-bike and scooter falls has roughly doubled in five years as the devices have become more widely adopted. 
Arm and wrist fractures are common, as are head and face injuries, the worst of which can cause brain damage. 
Kaiser’s Dr. 
Corrine McLeary said her ER caseload has grown from one or two patients a week to five or 10 a day. 
She frequently sees injured food-delivery drivers  four or five in the past month  and estimates that roughly half her patients weren’t wearing helmets at the time of the crash. 
“We have a lot of people who use these e-bikes and scooters who underestimate their vulnerability,” McLeary said. 
“Rentals, especially scooters  those people don’t seem to be wearing helmets.” 
People with serious brain injuries from e-bike and scooter crashes often end up in the office of Dr. 
Blake Taylor, a Marin-based UCSF neurosurgeon who has called for more education and enforcement to prevent such injuries. 
He sees one e-bike or scooter patient a week, usually with a traumatic brain injury from a fall or collision with a car. 
A common TBI complication is bleeding within the brain or between the brain and skull  and roughly 10% require surgery, depending on the bleed’s location and size, Taylor said. 
Even a minor TBI can cause cognition and mood changes, concentration trouble, persistent headaches, dizziness, or balance problems. 
“Those symptoms can go on for weeks to months after minor traumatic brain injury,” Taylor said. 
“With a severe one, you may never recover.” 
The San Francisco Municipal Transportation Agency last week presented data showing that the number of injuries involving “powered stand-up devices”  electric scooters, skateboards, unicycles  increased from 36 in 2018 (the year Bird scooters arrived in SF) to 315 in 2025. 
Whether e-bike crashes increased in SF is harder to determine, since bikes and e-bikes are lumped together in city data, though total bike collisions dropped from 599 to 463 over the same period. 
But a UC San Diego study found that e-bike injuries are rising exponentially around the state, particularly in suburban areas, and that helmet use is lower among riders of e-bikes than riders of conventional ones. 
Nationally, e-bike and e-scooter injuries have soared. 
Doctors acknowledge that their observations are anecdotal, since departments don’t track the data systematically, and usually know from intake notes whether a patient was riding an e-bike or e-scooter. 
City crash data, collected by police and the Public Health Department, is often a significant undercount: 29% of ambulance-transported, hospitalized Zuckerberg SF General patients who were involved in transportation crashes went unreported in police records, per a methodology study conducted by the Department of Public Health in 2019, the most recent available. 
Among cyclists, the figure was 39%. 
Spiking ridership 
The rise in injuries has tracked a boom in ridership in San Francisco. 
Lime’s ridership more than doubled between 2024 and 2025. 
Spin’s ridership grew 30% over the same period, and Lyft bike trips rose 34%. 
While the data don’t distinguish between Lyft’s pedal-only and e-bikes, 63% of Lyft’s fleet in San Francisco are e-bikes. 
Complicating the picture: the blurred lines between e-bikes and their more powerful, infamous cousins, e-motos  pedalless, far faster, and often mislabeled as e-bikes. 
Under California law, e-bikes are capped at 750 watts and 20 or 28 mph, depending on class; anything faster is legally a motor vehicle, requiring registration and a license. 
A murkier middle ground exists among bikes with functioning pedals whose peak power far outruns a typical e-bike’s top speed. 
Goat Power Bikes’ Motor Goat V3, for instance, ships capped at the government-mandated 20 mph but can easily be unlocked to hit 50 mph. 
A 2025 report commissioned by the state Legislature recommended cracking down on illegal e-motos rather than legal e-bikes  but most of the e-bike bills moving through Sacramento this year don’t follow that recommendation, drawing pushback from bike advocates who argue that lawmakers are targeting the wrong vehicles. 
Colwell said patients often end up in the hospital after riding drunk, and about half were riding rental vehicles. 
Roughly 30% were wearing helmets when injured, he said. 
As part of his Street Safety Initiative launched in December, Mayor Daniel Lurie committed to forming an E-Mobility Working Group to tackle e-bike and stand-up device safety concerns through education, enforcement, and regulation. 
The group is still being assembled, and it’s unclear from its website whether it has formally convened. 
“It is more and more an accepted way to get around town,” Colwell said. 
“The problem is, it still remains, in my opinion, underregulated.” 
‘These vehicles are here to stay’ 
Regulation is moving. 
SB 1167 (Blakespear, D-Encinitas) would bar e-bikes and mopeds exceeding 750 watts, throttle speeds above 20 mph, or pedal-assist above 28 mph from being sold as e-bikes; it would also require labels and point-of-sale disclosures on higher-powered devices and prohibit unregistered devices exceeding 20 mph on public roads. 
It would require police crash reports to record a vehicle’s classification label, or note that none existed  helping close the data gap that obscures how much of the increase in injuries involves legal e-bikes versus faster, unregulated devices. 
San Francisco isn’t alone in scrambling to catch up. 
New York City Council leadership unveiled a package of 17 bills this week aimed at tightening oversight of e-bikes, scooters, and other micromobility vehicles, following a string of high-profile crashes; a hearing is expected in late September. 
New York has already imposed a citywide 15 mph cap and a statewide crash-reporting requirement, while New Jersey is rolling out its own registration and licensing rules. 
Lyft CEO David Risher said in a July 29 interview with The Standard that the bikeshare app and stickers on the bikes encourage helmet use, but the company can’t force riders to comply. 
He pointed to other safety features, like reflective paint and a device that prevents sitting on the fender above the rear wheel. 
The Lyft bikeshare website  which still bears the retired “Bay Wheels” name  says riders are “encouraged” to wear a helmet. 
Lyft has also committed to sharing “hundreds” of free helmets through the SFMTA and the Bicycle Coalition which riders can keep, but are still finalizing timing and locations, the company said in an email. 
“You can lead a horse to water; you can’t make it drink,” Risher said. 
“We can design a bike that’s safe, encourage people to ride safely  but people also have to be responsible. 
Our job is to make it as easy as possible for people to do the right thing.” 
McLeary is more interested in offering advice than patient horror stories: ride sober, stay under 20 mph, and wear a helmet. 
She says San Francisco needs to build more bike lanes to protect cyclists and scooter riders, who occupy an “awkward space”  too fast for the sidewalk, too slow for car traffic. 
“These vehicles are here to stay,” she said. 
“But for now, people need to take commonsense precautions.” 
Article reasoning-pattern comparisonThis article: 4.7%Garrett Leahy: 1.0%The San Francisco Standard: 2.3%Confirmation Bias4.7%This article: 0.0%Garrett Leahy: 0.3%The San Francisco Standard: 0.9%Anchoring Bias0.0%This article: 11.5%Garrett Leahy: 3.0%The San Francisco Standard: 2.8%Availability Heuristic11.5%This article: 0.0%Garrett Leahy: 0.2%The San Francisco Standard: 0.9%Representativeness Heuristic0.0%This article: 0.0%Garrett Leahy: 0.3%The San Francisco Standard: 0.7%Hindsight Bias0.0%This article: 4.2%Garrett Leahy: 0.6%The San Francisco Standard: 1.2%Overconfidence Bias4.2%This article: 3.2%Garrett Leahy: 5.4%The San Francisco Standard: 5.2%Framing Effect3.2%This article: 0.0%Garrett Leahy: 0.5%The San Francisco Standard: 0.4%Loss Aversion0.0%This article: 3.1%Garrett Leahy: 0.2%The San Francisco Standard: 0.5%Status Quo Bias3.1%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.3%Sunk Cost Effect0.0%This article: 6.1%Garrett Leahy: 0.5%The San Francisco Standard: 2.2%Optimism Bias6.1%This article: 3.0%Garrett Leahy: 0.4%The San Francisco Standard: 1.1%Pessimism Bias3.0%This article: 10.8%Garrett Leahy: 3.3%The San Francisco Standard: 5.6%Negativity Bias10.8%This article: 3.3%Garrett Leahy: 0.2%The San Francisco Standard: 1.7%Self-Serving Bias3.3%This article: 3.6%Garrett Leahy: 0.3%The San Francisco Standard: 0.8%Fundamental Attribution Error3.6%This article: 4.1%Garrett Leahy: 0.3%The San Francisco Standard: 0.2%Actor-Observer Bias4.1%This article: 0.0%Garrett Leahy: 0.7%The San Francisco Standard: 0.7%In-Group Bias0.0%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.2%Out-Group Homogeneity Bias0.0%This article: 0.0%Garrett Leahy: 2.9%The San Francisco Standard: 3.2%Halo Effect0.0%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.2%Horn Effect0.0%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.0%Dunning-Kruger Effect0.0%This article: 1.1%Garrett Leahy: 0.4%The San Francisco Standard: 1.0%Recency Bias1.1%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.2%Primacy Effect0.0%This article: 0.0%Garrett Leahy: 0.2%The San Francisco Standard: 0.1%Blind-Spot Bias0.0%This article: 0.0%Garrett Leahy: 0.4%The San Francisco Standard: 0.4%Ad Hominem0.0%This article: 0.0%Garrett Leahy: 0.2%The San Francisco Standard: 0.2%Straw Man0.0%This article: 5.5%Garrett Leahy: 2.0%The San Francisco Standard: 2.3%Appeal to Authority5.5%This article: 5.0%Garrett Leahy: 0.0%The San Francisco Standard: 1.1%False Dilemma5.0%This article: 0.0%Garrett Leahy: 0.1%The San Francisco Standard: 0.7%Slippery Slope0.0%This article: 2.5%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%Circular Reasoning2.5%This article: 6.8%Garrett Leahy: 1.4%The San Francisco Standard: 3.9%Hasty Generalization6.8%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.2%Red Herring0.0%This article: 5.4%Garrett Leahy: 0.0%The San Francisco Standard: 0.4%Bandwagon5.4%This article: 2.8%Garrett Leahy: 2.8%The San Francisco Standard: 3.5%Appeal to Emotion2.8%This article: 0.0%Garrett Leahy: 0.2%The San Francisco Standard: 0.4%Begging the Question0.0%This article: 9.0%Garrett Leahy: 0.9%The San Francisco Standard: 1.7%Post Hoc (False Cause)9.0%This article: 3.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%Tu Quoque3.0%This article: 3.5%Garrett Leahy: 0.3%The San Francisco Standard: 0.3%Burden of Proof3.5%This article: 2.1%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%Appeal to Nature2.1%This article: 1.3%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%Composition/Division1.3%This article: 16.5%Garrett Leahy: 0.6%The San Francisco Standard: 2.6%Anecdotal16.5%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%No True Scotsman0.0%This article: 7.9%Garrett Leahy: 0.4%The San Francisco Standard: 1.1%Ambiguity (Equivocation)7.9%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.0%Gambler’s Fallacy0.0%This article: 5.2%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%Middle Ground5.2%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.0%Personal Incredulity0.0%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%Special Pleading0.0%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.1%Genetic Fallacy0.0%This article: 2.1%Garrett Leahy: 0.4%The San Francisco Standard: 0.9%Unattributed Quote2.1%This article: 0.8%Garrett Leahy: 0.2%The San Francisco Standard: 0.7%Quote-first Misdirection0.8%This article: 5.8%Garrett Leahy: 0.6%The San Francisco Standard: 4.4%Biased Writer Voice5.8%This article: 1.9%Garrett Leahy: 0.6%The San Francisco Standard: 1.0%Indoctrination1.9%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.2%Politically Left Leaning Bias0.0%This article: 0.0%Garrett Leahy: 0.0%The San Francisco Standard: 0.2%Politically Right Leaning Bias0.0%This article: 8.5%Garrett Leahy: 0.6%The San Francisco Standard: 1.9%Attempt to Sell a Product or S…8.5%

1586 words analyzed.

Speakers

12speakers47%attributed speech837writer words
Selected voice

Lyft

100%flagged-word coverage
34 attributed words4.5% of attributed speech69% writer coverage
0%50.0%100.0%Attempt to Sell a Product +100.0 ptsWriter: 0.0%Lyft: 100.0%100.0%Biased Writer Voice-11.0 ptsWriter: 11.0%Lyft: 0.0%0.0%Unattributed Quote-4.1 ptsWriter: 4.1%Lyft: 0.0%0.0%

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.