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Enregistrement W2121451424 · doi:10.1016/j.gaceta.2013.09.003

The apparent ineffectiveness of bicycle helmets: A case of selective citation

2013· letter· en· W2121451424 sur OpenAlexaboutno aff
Jake Olivier

Notice bibliographique

RevueGaceta Sanitaria · 2013
Typeletter
Langueen
DomaineMedicine
ThématiqueInjury Epidemiology and Prevention
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCyclingOccupational safety and healthDemographyPoison controlInjury preventionSuicide preventionGeographyMedicineEnvironmental healthSociologyArchaeology

Résumé

récupéré en direct d'OpenAlex

A recent Gaceta Sanitaria letter concluded bicycle helmet use should not be mandated in urban areas.1 Mandatory helmet legislation (MHL) is controversial and a balanced presentation of all scientific evidence is therefore critical. This letter will briefly discuss relevant literature uncited by the authors. The authors note bicycle use declines with MHL. However, there is ample evidence the contrary is possible. South Australian household surveys found similar cycling rates prior to and after MHL regardless of gender, age or level of urbanisation.2 Adelaide cycling counts increased by 2.9% after MHL. Other surveys from Victoria, Australia3 and Ontario, Canada4 indicate either no change or an increase in cycling following MHL. New South Wales surveys were commissioned around the 1991 MHL to estimate changes in helmet wearing.5 These reports were designed to estimate helmet wearing and not cycling rates. No such surveys exist for NSW and conclusions using this data are therefore weak. However, this data forms the basis for the argument MHL leads to less cycling. Importantly, this data does not produce unequivocal results as Sydney adult cycling counts increased 22% following MHL. Regarding the effects of MHL on urban cycling, the cycling mode share in Australian cities changed little after MHL from 1.14% in 1986 to 1.13% in 1991 after most Australians were subjected to MHL. The above examples of non-decreasing cycling rates following MHL have important health implications. The de Jong paper, cited by Rojas-Rueda et al., assumes cycling rates only decline with MHL. However, as evidenced above, this does not hold uniformly. Importantly, for non-decreasing cycling rates, this model always estimates a benefit to MHL. A New Zealand evaluation by Clarke and cited by Rojas-Rueda et al. ignores critical analyses found in the original source material.6 This research demonstrates serious traumatic brain injury rates per million hours spent cycling declined significantly following MHL. Clarke only considered all cycling injuries and, since helmets are designed to protect the head only, his analysis could mask any positive impact of MHL. The manuscript mentions Australian research demonstrating a benefit of MHL, yet cites a rejoinder critical of this work. Missing from the letter was a full-length response to the rejoinder demonstrating the criticisms were unfounded and the original analysis was rigorous and robust.7 Briefly, the original study estimated a 29% decline in bicycle related head injury hospitalisations attributable to MHL compared with limb injuries. There was a concurrent helmet wearing increase from about 25% to 80%. Note the rejoinder self-cites a paper retracted due to numerous arithmetic errors.8 There is strong evidence helmet wearing, either voluntarily or compulsory, mitigates the risk of bicycle related head injury. Of note, head injury is the most common cause of cycling-related hospitalisation in Catalonia. Helmets, however, should not be viewed as a panacea and instead are an important part of any cycling safety strategy along with segregated cycling facilities and lower speed limits for motorised traffic. The benefits of each intervention are situational -- helmets will help a cyclist in an accident and segregated cycling infrastructure will help avoid accidents. I therefore believe the decision to mandate helmet use should be in conjunction with a comprehensive strategy and not in isolation. 1. Rojas-Rueda D, Cole-Hunter T, Nieuwenhuijsen M. Ley para el uso obligatorio de casco por ciclistas en zonas urbanas. ?Es bueno para la salud publica? Gac Sanit. 2013; 27: 282-285. 2. Marshall J, White M. Evaluation of the compulsory helmet wearing legislation for bicyclists in South Australia. Walkerville, SA: South Australian Department of Transport; 1994. Office of Road Safety Report Series 8/94 [consulted on 9/9/2013]. Available at: http://www.bicyclenetwork.com.au/media/vanilla/file/SA%20Helmet%20eval%201994%20S A%20Marshall.pdf 3. Finch C, Heiman L, Neiger D. Bicycle Use and Helmet Wearing Rates in Melbourne, 1987 to 1992: the influence of the helmet wearing law. Melbourne: Monash University Accident Research Centre; 1993 [consulted 9/9/2013]. Available at: http://www.monash.edu.au/miri/research/reports/muarc045.pdf 4. Macpherson AK, Parkin PC, To TM. Mandatory helmet legislation and children's exposure to cycling. Inj Prev. 2001; 7:228-230. 5. Smith NC, Milthorpe FW. An Observational Survey of Law Compliance and Helmet Wearing by Bicyclists in New South Wales - 1993. Rosebery, NSW: NSW Roads and Traffic Authority; 1993 [consulted on 9/9/2013]. Available at: http://bicycleinfo.nsw.gov.au/tools_and_resources/cycling_research.html. 6. Tin Tin S, Woodward A, Ameratunga S. Injuries to pedal cyclists on New Zealand roads, 1988- 2007. BMC Public Health. 2010; 10: 655. 7. Walter SR, Olivier J, Churches T, Grzebieta R. The impact of compulsory helmet legislation on cyclist head injuries in New South Wales, Australia: A response. Acc Anal Prev. 2013; 52: 204-209. 8. Grzebieta R. Retraction of the Voukelatos and Rissel paper on bicycle helmet legislation and injury. J Australas Coll Road Safety. 2011; 22: 39. Language: en

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,512
Score d'incertitude au seuil0,627

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,023
Tête enseignante GPT0,309
Écart entre enseignants0,286 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2013
Routes d'admission1
Résumé présentoui

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