Vision screening of older drivers for preventing road traffic injuries and fatalities
Notice bibliographique
Résumé
BACKGROUND: Demographic data in North America, Europe, Asia, Australia and New Zealand suggest a rapid growth in the number of persons over the age of 65 years as the baby boomer generation passes retirement age. As older adults make up an increasing proportion of the population, they are an important consideration when designing future evidence-based traffic safety policies, particularly those that lead to restrictions or cessation of driving. Research has shown that cessation of driving among older drivers can lead to negative emotional consequences such as loss of independence and depression. Those older adults who continue to drive tend to do so less frequently than other demographic groups and are more likely to be involved in a road traffic crash, probably due to what is termed the 'low mileage bias'. There is universal agreement among researchers that vision plays a significant role in driving performance, and that there are age-related visual changes. Vision testing of all drivers, and in particular of older drivers, is therefore an important road safety issue. The components of visual function essential for driving are acuity, field, depth perception and contrast sensitivity, which are currently not fully measured by licensing agencies. Furthermore, it is not known how effective vision screening tools are, and current vision screening regulations and cut-off values required to pass a licensing test vary from country to country. There is, therefore, a need to develop evidence-based tools for vision screening for driving, thereby increasing road safety. OBJECTIVES: To assess the effects of vision screening interventions for older drivers to prevent road traffic injuries and fatalities. SEARCH STRATEGY: We searched the Cochrane Injuries Group's Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2010, Issue 2), MEDLINE (Ovid), TRANSPORT (Ovid), IBSS (International Bibliography of Social Sciences), ASSIA: Applied Social Sciences Index and Abstracts, ISI Web of Science: Social Sciences Citation Index (SSCI), ISI Web of Science: Conference Proceedings Citation Index-Science (CPCI-S) and PubMed. We also searched the Internet and checked the reference lists of relevant papers to identify any further studies. The searches were conducted up to the first week of June 2010. SELECTION CRITERIA: Randomised controlled trials (RCTs) and controlled before and after studies comparing vision screening to non-screening of drivers aged 55 years and older, and which assessed the effect on road traffic crashes, injuries, fatalities and any involvement in traffic law violations, were included. DATA COLLECTION AND ANALYSIS: Two authors independently screened the reference lists for eligible articles and independently assessed the articles for inclusion against the criteria. Two authors independently extracted data using a standardised extraction form. MAIN RESULTS: No studies were found which met the inclusion criteria for this review. AUTHORS' CONCLUSIONS: Most countries require a vision screening test for the renewal of an individual's driver's license. There is, however insufficient evidence to assess the effects of vision screening tests on subsequent motor vehicle crash reduction. There is a need to develop valid and reliable tools of vision screening that can predict driving performance.
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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
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 ».