Notice bibliographique
Résumé
To the Editor: Young1 attempted to correct for a potential bias in early epidemiological studies of cell phone use and crash risk. Concerns with his analyses have been raised, including an incorrect assumption that people talk on phones only while driving. In response, Young2,3 conducted two reanalyses that substantially revise his original correction method by (1) refining the estimates of driving inconsistency and (2) adding a new correction ratio to account for the prevalence of phone use during periods of driving and nondriving. Based on these reanalyses, Young concludes there is no increase in crash risk with phone use (adjusted risk ratio = 1.292 and 1.13). However, his reanalyses are based on data that are not comparable with the epidemiological study samples, which greatly affect the validity of his corrected estimates. The new correction ratio of Young2,3 is based on data from several studies of US drivers and wireless subscribers. These studies provide reasonable estimates of cell phone use in the United States, but not necessarily the epidemiological study populations. Young’s data on US phone use are much more recent (2009–2010) than the epidemiological study data (1994–1995 and 2002–2004), even though cell phone use has changed over time. Moreover, handheld cell phone use was prohibited during the more recent epidemiological study, but not in the earlier Canadian study or in most US states. Evidence shows that handheld cell phone bans reduce use during driving. Even small inaccuracies in Young’s estimates can greatly affect conclusions drawn from the correction ratio. For example, Young estimates the average duration of cell phone conversations at 1.17 minutes using 2009–2010 US data,4 but the same data show that the average cell phone conversation during the more recent epidemiology study period was 2.95 minutes. When the latter value is used in Young’s correction ratio equation without other changes, the adjusted crash risk ratio increases from 1.29 to 2.5. Compounding possible problems with the precision of Young’s estimates is that some are inexplicably inconsistent in his two reanalyses. He uses different estimates of the prevalence of phone use while driving (11% and 6.7%), driving consistency (20% and 15%), and total hours in the day when a phone could be used (11 and 24 hours). In conclusion, Young is correct that estimates of crash risk associated with phone use from early epidemiological studies may not have accounted sufficiently for driving inconsistency. His original correction to these estimates was flawed, and his revised corrections exacerbate rather than remove these flaws. ACKNOWLEDGMENTS We thank our colleague David Zuby who contributed with helpful feedback. David G. Kidd Insurance Institute for Highway Safety Arlington, VA [email protected] Anne T. McCartt Insurance Institute for Highway Safety Arlington, VA
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,050 | 0,022 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».