Stay SHARP (See, hear, attend, respond, perform) - sustaining and retraining visual-perception, motor and cognitive skills among older drivers : a feasibility project
Notice bibliographique
Résumé
The ability to drive an automobile is a central aspect of independent living for many older adults (Ragland, Satariano, & MacLeod, 2004). Much of the research in the field of driving and the elderly has focused on accident situations in which older drivers are over-involved, with little attention placed on developing and evaluating methods to enhance driving abilities. This thesis is comprised of two manuscripts, one examining the effectiveness of retraining programs for older drivers, and the other exploring older adults' perceptions of driving, concerns/difficulties associated with driving, and factors stimulating interest and participation in a driving program. The first manuscript presents a systematic review of the most recent literature on evidence regarding the effectiveness of retraining programs for older drivers. Reviewed articles were grouped according to the intervention studied: physical retraining, visual perception or education. Randomized controlled trials (RCTs) were appraised using the Physiotherapy Evidence Database (PEDro) Scale (PEDro, 2006) and interpreted following Foley's quality assessment (Foley, Teasell, Bhogal, & Speechley, 2003). Each intervention was then rated for effectiveness based on Sackett's levels of evidence (Sackett, Richardson, Rosenberg, & Haynes, 2000). Six RCTs, one pre- post-study design and one descriptive study met the inclusion criteria, one investigating physical retraining, one a visual perception intervention, five using an educational intervention and one examining a combination of all three, in addition to traffic engineering improvements. There is limited evidence that physical retraining (Level 2a) and visual perception retraining (Level 2a) improve driving related skills in older drivers. There is moderate evidence that educational interventions improve driving awareness and driving behavior (Level 1a), but do not reduce crashes (Level 1b) in older drivers. This suggests that while the evidence is limited, it is sufficiently encouraging to merit further research on interventions for healthy older drivers. In the second manuscript, the authors explore activities seniors use driving for, when and where they drive, importance of driving, perceived driving habits, behavioral changes as people age, and factors stimulating interest and participation in a driving program. Three focus groups (n=18), conducted using a structured format, were held with former and current drivers, 75 years and older, living in Montreal, Canada. Discussions were audiotaped, transcribed, and analyzed to identify themes/key points. Participants reported driving for short and long-distance trips, personal and leisure activities, or in situations where walking was not practical or possible. They indicated driving during days and evenings, on city streets and highways. Frequently reported changes and difficulties included reduced evening vision, slowing response times, and road signs not being clear or visible. The principle results indicated that participants were enthusiastic about a driving program and perceived a need for content such as: traffic law refreshers, retraining of driving-related skills, as well as an on-road driving component. An objective, comprehensive clinical assessment and on-road evaluation were also deemed important. Furthermore, participants expressed preference for a program offered sometime between 11am-to-5pm for one-to-two hours, once or twice weekly. This focus group research is the first step in a research agenda aimed at developing effective and practical driving interventions for healthy older drivers based on their desired needs and interests.
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 | 0,018 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».