{
  "slug": "phone-while-cycling-injury",
  "question": "What are the odds of crashing while cycling distracted by a phone?",
  "category": "transport",
  "no_reliable_estimate": true,
  "perceived": {
    "description": "Most regular cyclists who have ever fumbled a phone in traffic recognise the feeling immediately: one hand off the bars, eyes off the road, balance drifting toward whichever side the device is on. The intuition is that phone use while cycling sharply raises the odds of a crash — and qualitatively, the cycling-distraction literature agrees. The problem is that no US data source converts that qualitative agreement into a defensible probability. NHTSA's Fatality Analysis Reporting System codes distracted *drivers* who hit cyclists; it does not code the cyclist's own phone use at the moment of crash. The CDC's emergency department surveillance (NEISS-AIP) explicitly notes that its narrative records \"do not provide detailed or consistent information about… injury circumstances\". The Dutch and broader European literature has the best behavioural and prevalence data, but converting it to a US adult lifetime probability requires assumptions about exposure, infrastructure, and cycling frequency that the underlying studies do not support.\n",
    "rough_estimate": "no defensible US denominator — qualitative direction (increased risk) is well supported, but the per-cyclist lifetime probability is not estimable",
    "kind": "intuition"
  },
  "sources": [
    {
      "url": "https://pubmed.ncbi.nlm.nih.gov/20069479/",
      "title": "Mobile phone use while cycling: incidence and effects on behaviour and safety",
      "publisher": "Ergonomics (Taylor & Francis), via PubMed",
      "source_type": "peer_reviewed",
      "statistic": "In Groningen, NL, 2.2% of observed cyclists were talking on a phone and 0.6% were texting or dialling; only 0.5% of accident-involved cyclists reported phone use at the time of the crash",
      "excerpt": "\"In Groningen 2.2% of cyclists were observed talking on their phone and 0.6% were text messaging or entering a phone number. In study 2, accident-involved cyclists responded to a questionnaire. Only 0.5% stated that they were using their phone at the time of the accident… Telephoning coincided with reduced speed, reduced peripheral vision performance and increased risk and mental effort ratings. Text messaging had the largest negative impact on cycling performance. Higher mental workload and lower speed may account for the relatively low number of people calling involved in accidents.\"\n",
      "source_date": "2010-01-01",
      "source_accessed": "2026-05-24",
      "archive_url": "http://web.archive.org/web/20260525095915/https://pubmed.ncbi.nlm.nih.gov/20069479/",
      "calculation_notes": "de Waard et al. 2010 is the foundational observational study on cyclist mobile phone prevalence in the Netherlands. It is cited here for two reasons: (1) it establishes that the behavioural effect of phone use on cycling performance is real and measurable (peripheral vision narrows, speed drops, perceived risk rises), and (2) the 0.5% self-report among crash-involved cyclists is not a crash-risk rate — it is a snapshot of what crashed cyclists recall doing, on a non-representative sample, in the Netherlands. Even if taken at face value, it cannot be converted to a US per-crash or per-cyclist-year probability because the denominator (total cycling-phone-use exposure-hours) is not measured. No conversion to native or normalized US-adult lifetime probability is performed.\n"
    },
    {
      "url": "https://pubmed.ncbi.nlm.nih.gov/22385735/",
      "title": "The use and risk of portable electronic devices while cycling among different age groups",
      "publisher": "Journal of Safety Research (Elsevier), via PubMed",
      "source_type": "peer_reviewed",
      "statistic": "Self-reported crash odds were ~1.6× higher for Dutch teen cyclists and ~1.8× higher for young adult cyclists who used portable electronic devices on every trip vs cyclists who never used them; no significant effect detected for middle-aged or older cyclists",
      "excerpt": "\"The odds of being involved in a bicycle crash are higher for teen cyclists (factor 1.6) and young adult cyclists (factor 1.8) who use electronic devices on every trip compared to cyclists who never use these devices. For middle-aged and older adult cyclists, the use of portable electronic devices was not a significant predictor of bicycle crashes, but frequency of cycling in demanding traffic situations was.\"\n",
      "source_date": "2012-02-01",
      "source_accessed": "2026-05-24",
      "archive_url": "http://web.archive.org/web/20250204053157/https://pubmed.ncbi.nlm.nih.gov/22385735/",
      "calculation_notes": "Goldenbeld et al. 2012 is the strongest peer-reviewed estimate of crash-risk elevation from cyclist device use. The reported odds ratios (1.6 and 1.8) are self-reported, age-stratified, and Dutch — they describe relative risk between \"every trip\" and \"never\" device users in the same age cohort, not absolute probability per trip or per year. The effect disappears in older cohorts, suggesting either behavioural compensation or selection. Multiplying any baseline US cyclist crash probability by ~1.7 would be inappropriate because (a) the underlying US baseline for distraction-attributable crashes does not exist, (b) Dutch cyclists ride on protected infrastructure that US cyclists do not, and (c) \"every trip\" device use is a behavioural extreme, not the modal phone-using cyclist. The OR is cited as qualitative direction evidence (distraction increases crashes for younger cyclists) without a quantitative US transfer.\n"
    },
    {
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC4785823/",
      "title": "Distracted biking: an observational study",
      "publisher": "Journal of Trauma Nursing (Wolters Kluwer), via PubMed Central",
      "source_type": "peer_reviewed",
      "statistic": "Of 1,974 cyclists observed at 4 Boston intersections in summer 2016, 31.2% were distracted; 17.7% by auditory devices (headphones/earbuds) and 13.5% by visual/tactile devices (phone or object in hand)",
      "excerpt": "\"Of the 1,974 bicyclists observed, 615 (31.2%) were distracted. Auditory distractions, predominantly headphones or earbuds, accounted for 17.7%, and visual/tactile distractions, predominantly a phone or other object in the hand, accounted for 13.5%. Reduced attention can place bicyclists and other road users at greater risk of sustaining an injury.\"\n",
      "source_date": "2016-03-01",
      "source_accessed": "2026-05-24",
      "archive_url": "http://web.archive.org/web/20260209141333/https://pmc.ncbi.nlm.nih.gov/articles/PMC4785823/",
      "calculation_notes": "Wolfe et al. 2016 (observations summer 2015, published 2016) is the best-available US observational prevalence study for cyclist distraction. It establishes that distraction is common (≈1 in 3 observed cyclists at Boston intersections) but does not link observed distraction to crash outcomes — there is no denominator-matched crash count for the same population. The study is cited as the US exposure-prevalence anchor that demonstrates the behaviour is widespread, while explicitly not supplying a crash-risk number. No native or normalized probability is derived.\n"
    },
    {
      "url": "https://www.cdc.gov/mmwr/volumes/70/wr/mm7019a1.htm",
      "title": "Emergency Department Visits for Bicycle-Related Traumatic Brain Injuries Among Children and Adults — United States, 2009–2018",
      "publisher": "CDC Morbidity and Mortality Weekly Report (MMWR)",
      "source_type": "govt_report",
      "statistic": "An estimated 596,972 ED visits for bicycle-related TBIs occurred in the US during 2009–2018; the surveillance system does not record cyclist phone use, helmet use, or injury circumstances consistently",
      "excerpt": "\"An estimated 596,972 ED visits for bicycle-related TBIs occurred in the United States during this study period (2009–2018)… NEISS-AIP narrative descriptions do not provide detailed or consistent information about helmet use, injury circumstances (e.g., whether the injury occurred on a road or bicycle path), or about a person's level of exposure.\"\n",
      "source_date": "2021-05-14",
      "source_accessed": "2026-05-24",
      "archive_url": "http://web.archive.org/web/20260511084004/https://www.cdc.gov/mmwr/volumes/70/wr/mm7019a1.htm",
      "calculation_notes": "Sarmiento et al. 2021 (CDC MMWR) is the primary US bicycle-injury surveillance source. It documents that ED visits for bicycle-related TBI are common (≈60,000/year averaged over 2009–2018) but explicitly states that the surveillance instrument does not capture the circumstances that would let an analyst identify which crashes involved cyclist phone use. This source is cited as documentation of the data gap that prevents a US cyclist-phone-distraction injury rate from being estimated — the numerator data does not exist, regardless of what denominator one might assume.\n"
    },
    {
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC5685949/",
      "title": "Distracted Walking, Bicycling, and Driving: Systematic Review and Meta-Analysis of Mobile Technology and Youth Crash Risk",
      "publisher": "Child Development (Wiley), via PubMed Central",
      "source_type": "peer_reviewed",
      "statistic": "Of 41 peer-reviewed studies in a systematic review of mobile technology and youth road crash risk, only one cycling study met inclusion criteria and was excluded from the meta-analysis, so no aggregate effect size for phone-while-cycling crash risk could be computed",
      "excerpt": "\"A single study on bicycling met inclusion criteria, but was omitted from the meta-analysis.\"\n",
      "source_date": "2017-11-01",
      "source_accessed": "2026-05-24",
      "archive_url": "http://web.archive.org/web/20251017045210/https://pmc.ncbi.nlm.nih.gov/articles/PMC5685949/",
      "calculation_notes": "Stavrinos et al. 2017 is the closest available systematic review on mobile technology and crash risk that includes cycling as a category. The reviewers identified only one eligible cycling study (Kircher et al. 2015, an experimental study of behavioural compensation, not crash incidence), which they then excluded from quantitative synthesis. This is the strongest available evidence that no defensible pooled odds ratio exists for phone-while-cycling crash risk in the published literature. The source is cited as direct documentation of the evidence-base gap that justifies no_reliable_estimate=true.\n"
    }
  ],
  "comparison_anchors": [
    {
      "label": "Cyclist killed by a motor vehicle (lifetime, US regular cyclist)",
      "lifetime_us_adult": 0.0051
    },
    {
      "label": "Cycling helmetless serious head injury (lifetime, US frequent unhelmeted urban cyclist)",
      "lifetime_us_adult": 0.125
    },
    {
      "label": "Phone-distracted walking injury (lifetime, US adult)",
      "lifetime_us_adult": 0.0025
    }
  ],
  "personal_factor_multipliers": [
    {
      "factor": "occasional recreational cyclist on protected paths, phone in pocket, ear buds out",
      "multiplier": 0.3,
      "notes": "Lowest exposure profile — low cycling time, low device use, separated infrastructure. Multiplier is relative to a same-cohort cyclist with no phone use; absolute lifetime probability is not estimated for this entry."
    },
    {
      "factor": "regular urban commuter, occasional handheld phone glances at lights, single ear bud",
      "multiplier": 1,
      "notes": "Baseline reference profile in this entry — the relative risk floor against which the other multipliers are scaled. No absolute lifetime probability is implied."
    },
    {
      "factor": "every-trip handheld device user, teens or young adults (16–34)",
      "multiplier": 1.8,
      "notes": "Approximates the Goldenbeld et al. 2012 self-reported odds ratio for Dutch young-adult cyclists using devices on every trip vs never. Effect attenuates in middle-aged cyclists in the same study. Translation to US adults is not validated."
    },
    {
      "factor": "active texting or typing while moving, any age",
      "multiplier": 3,
      "notes": "de Waard et al. 2010 found texting had the largest negative effect on cycling performance — speed, lateral control, and peripheral vision all degraded substantially. The 3x is a qualitative direction estimate, not a measured crash odds ratio."
    },
    {
      "factor": "active texting on an arterial road or in unprotected mixed traffic",
      "multiplier": 6,
      "notes": "Compounds texting-degraded control with high-consequence environment (NHTSA: 65% of US cyclist fatalities occur on principal/minor arterials). Qualitative upper bound, not a measured number."
    }
  ],
  "short_label": "Phone-distracted cycling crash",
  "myth_framing": "underrated",
  "outcome_severity": "serious_harm",
  "exposure_pattern": "recurring",
  "outcome_type": "recoverable_injury",
  "valence": "negative",
  "caveats": "This entry uses `no_reliable_estimate: true` because the US literature does not contain the data required to compute a defensible lifetime probability of injury from cycling while distracted by a phone. The structural problem has three layers. First, the numerator: NHTSA's FARS records distracted *drivers* who strike cyclists but does not code the cyclist's own phone use, and the CDC's NEISS-AIP emergency department surveillance explicitly states that injury circumstances are not captured consistently. Second, the denominator: the US does not measure cyclist phone-use exposure-hours, and the closest available figure (Wolfe et al. 2016, 31% of Boston cyclists distracted, of which 13.5% visually/tactilely) is a single-city intersection snapshot, not a national exposure metric. Third, transfer bias: the best peer-reviewed crash-risk evidence is Dutch (Goldenbeld et al. 2012 odds ratio ~1.6–1.8 for every-trip vs never device use in young cyclists; effect absent in older cyclists), but Dutch cyclists ride on protected infrastructure at population trip-shares twenty to thirty times higher than US cyclists, and the Stavrinos et al. 2017 systematic review found only one cycling study globally that met inclusion criteria for mobile-technology crash-risk analysis — and excluded it from the meta- analysis. Even after the Netherlands banned handheld phone use while cycling in July 2019, the academic evaluation concluded \"there are no precise figures for how many accidents are caused by phone use while cycling\". What a US adult should take from this entry is qualitative: cyclist phone use measurably degrades peripheral vision, speed control, and reaction time, and is associated with elevated self-reported crash odds in young cyclists in the Netherlands; texting is worse than calling; and the elevated risk compounds with the road environment, especially on arterial roads where US cyclist fatalities are concentrated. The quantitative claim — what fraction of US adult cyclists will be injured in a phone-distraction crash over a lifetime — is not estimable from current evidence, and inventing a number to make the entry listable would misrepresent the state of the science.\n",
  "quality_score": {
    "d1": 3,
    "d2": 5,
    "d3": 5,
    "d4": 4,
    "d5": 4,
    "d6": 4,
    "d7": 3,
    "d8": 5,
    "avg": 4.125,
    "scored_by": "claude-code-8d",
    "scored_at": "2026-05-25",
    "methodology_version": "1.2"
  },
  "reviewer": "8d-eval-2026-05-24",
  "last_reviewed": "2026-05-24",
  "reviewed": true,
  "generated_at": "2026-05-24",
  "image": {
    "alt": "An empty bike lane viewed from above, with a faint phone-shaped outline drawn on the asphalt, flat vector illustration in muted tones."
  },
  "attribution": "Likelier — https://likelier.app",
  "license": "https://creativecommons.org/licenses/by-sa/4.0/",
  "support": "https://buymeacoffee.com/kgluszczyk?via=likelier&utm_content=api-fear-single",
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}