RE: “THE HIDDEN EPIDEMIC OF FIREARM INJURY: INCREASING FIREARM INJURY RATES DURING 2001–2013”
Notice bibliographique
Résumé
In a recent issue of the Journal, Kalesan et al. (1) made the case for a hidden epidemic of firearm injury in the United States during the period from 2001 to 2013. They concluded that “[t]he epidemic of firearm violence, driven largely by nonfatal injuries, is an important public health problem” and referred to the increase in nonfatal injuries as a “public health emergency” (1, p. 552). Over the course of their 12-year study period, there was a 2.5% increase in the crude rate of deaths from firearms (the net result of a large reduction in the firearm homicide rate coupled with an increase in the firearm suicide rate) and a supposed 20.4% increase in the nonfatal injury rate (due entirely to the trend in assault-related injury). It is this unexpected increase in the nonfatal injury rate that undergirds their principal conclusions. As it turns out, however, the surveillance data from which they computed the trends in nonfatal firearm injuries are flawed, and the apparent upward trend is an artifact of these flaws. Well-supported adjustments to the apparent trend in nonfatal injuries resulting from firearm assaults eliminate the upward trend, as we demonstrated in a recent article (2). Kalesan et al. estimated trends in nonfatal injuries that were primarily based on a nationally representative survey of hospital emergency departments. The National Electronic Injury Surveillance System–All Injury Program is managed by the Consumer Product Safety Commission (3). Annual estimates from 2001 onward are publically available on a website maintained by the Centers for Disease Control and Prevention (the Web-Based Injury Statistics Query and Reporting System, or WISQARS) (4). A closely related source of data on nonfatal firearm injuries is the Firearms Injury Surveillance System (NEISS-FISS), which is based on a somewhat expanded sample and includes more detail; in particular, it distinguishes between unintentional injuries and injuries of undetermined intent (5). We used the NEISS-FISS sample; because of data availability and other considerations, our analysis was focused on the period of 2003–2012. When examining the data as reported by Centers for Disease Control and Prevention, we found that the estimated trends in gunshot injuries from firearm assaults were very similar to those reported by Kalesan et al.; there was a 49% increase in the number of such nonfatal injuries during a time when there was essentially no change in the count of firearm homicides. However, we discovered that the “epidemic” increase was an artifact of problems with the NEISS-FISS data. There were 2 such problems. The first was a strong downward trend in coders’ use of “undetermined intent” during the decade, which implied that a larger share of the assault cases were concealed by this coding practice in 2003 than in 2012. Second, there were 15 instances during that decade in which one hospital was replaced by another to represent particular primary sampling units. Presumably by chance, the replacement hospitals had orders of magnitude more gunshot cases in 2 of the primary sampling units, and all of the apparent increase in the nonfatal cases came out of the replacements. (We cannot say whether the original or the replacement hospital was in some sense more representative, but we can say that the replacements distorted the estimated national trend.) Simple adjustments for these 2 problems eliminated the upward trend. Our conclusion is that there was no significant increase in nonfatal firearm assaults during this period. In particular, as the gun homicide rate dropped, the nonfatal assault rate dropped in proportion. An important implication is that there was no improvement in case fatality rates. We note that recently (beginning in 2015), there has been a sharp increase in the rates of gun homicides. That is indeed a serious problem for both public health and public safety. Conflict of interest: none declared.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,053 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,003 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,059 | 0,052 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,014 |
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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».