The influence of depression symptoms and antidepressant medications on cognition and driving performance
Notice bibliographique
Résumé
Research that has examined the influence of depression symptoms and antidepressant \nmedications on driving performance has revealed inconclusive findings (Brunnauer, Laux, \nGeiger, Soyka, & Moller, 2006; Bulmash et al., 2006; Ramaekers, 2003). The purpose of the present study was to elucidate the influence of depression symptoms and antidepressant medications on cognition and driving performances using self-report measures as well as an ecologically valid method measure, a driving simulator, and a clinical population. Two hundred and thirty-three drivers ranging in age from 18 to 35 years {M= 21.88; SD = 3.90 years) completed a screening measure that examined depressive and anxious symptoms, medication use, and self-reported driving behaviour on the Driving Behaviour Questionnaire (DBQ). Forty-three participants ranging in age from 18 to 35 {M= 24.24; SD = 5.05 years) also attended a laboratory session and completed a series of questionnaires designed to measure depression \ndriving habits, cognitive psychomotor functioning, and a diagnostic measure of MDD, two computerized tasks (one to measure attention and one to assess processing speed), and a 45 min simulated drive. In the overall sample, twenty-four (10.2%) participants were taking at least one antidepressant. Mean scores for depressive symptoms {M= 11.09; SD = 9.87) fell in the minimal range on the Beck Depression lnventory-11 (BDI-Il). A shortened version of the DBQ was created using this younger Canadian sample and correlation coefficients between the short and long version were excellent, ranging from .91 to .94. Overall, depressive symptoms and antidepressant use displayed little relationship to self-reported driving behaviour or driving performance on the driving simulator. However, our results do suggest that age (B= .12) and the cognitive/affective (B = .12) impairments on the BDI-II are statistically significantly related to increased self-reported absent-minded driving behaviour {p = .03). Overall depressive symptoms {B = -2.48) and cognitive/affective {B = 3.45) impairments were also related to inattention on a \ncomputerized task measuring attention {p < .05). The cognitive and affective impairments in depression were also positively related to visual perceptual ability {B = 2.02). The overall patterns of self-report data, neuropsychological data, and behavioural data suggest that although there is some consistency between self-report measures and neuropsychological data, this does not necessarily mean these impairments in attention translate into actual driving impairments on the simulator. Future studies could conduct a similar study using on-road performance as the behavioural measure of driving performance.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».