The Influence of Liability Information, Severity of Injury, and Attitudes toward Vengeance on Damage Awards

2008 ◽  
Vol 102 (1) ◽  
pp. 239-258 ◽  
Author(s):  
William Douglas Woody
Keyword(s):  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Phase 1 ◽  
The Other ◽  
Punitive Damages ◽  
Damage Awards ◽  
Vehicle Accident ◽  
Descriptive Information ◽  
Severity Of Injury ◽  
Integral Role

This jury simulation study explored the effects of liability-related descriptive information, severity of injury, and attitudes toward vengeance on damage awards. 311 individual mock jurors read a trial summary describing a plaintiff injured in a motor vehicle accident. Half of the participants read liability-related descriptive information, theoretically unrelated to judgments concerning damages, and the other half did not. Half read about a mildly injured plaintiff, and the other half read about a severely injured plaintiff. In Phase 1 participants decided compensatory awards and in Phase 2 participants read punitive damages evidence and decided, if appropriate, punitive damages. The presence of liability-related description influenced neither compensatory nor punitive damages. Severity of the plaintiff's injuries affected compensatory awards and punitive awards. Although revenge has historically played an integral role in punitive damages, participants' attitudes toward vengeance were not associated with punitive damage awards.

Boots Are Not Made for Driving: A Cautionary Case Report About the Dangers of Driving in a CAM Walker Boot and Literature Review

2018 ◽  
Vol 11 (6) ◽  
pp. 559-562
Author(s):  
Michael J. Symes ◽  
Mario Escudero ◽  
Irfan Abdulla ◽  
Andrea Veljkovic ◽  
Scott Paquette ◽  
...  
Keyword(s):  
Case Report ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Experimental Studies ◽  
Real Life ◽  
Educational Tool ◽  
Ankle Motion ◽  
Vehicle Accident ◽  
Severity Of Injury ◽  
Lower Limb Surgery

This case report is the first documented case of a serious motor vehicle accident caused by a patient driving in a controlled ankle motion (CAM) walker boot. The real-life nature and severity of injury in this case supplements the existing experimental studies on the dangers of driving while immobilized in a CAM boot and is likely to resonate strongly with both patients and surgeons. With CAM boots used so commonly after lower limb surgery, this case not only has the potential to change practice as an educational tool for patients but also raises important medicolegal implications for orthopaedic surgeons. Levels of Evidence: Level V

Virtual reality and computer games in the treatment of driving phobia induced by a motor vehicle accident

2003 ◽  
Author(s):  
David Walshe ◽  
Elizabeth Lewis ◽  
Kathleen O'Sullivan ◽  
Brenda K. Wiederhold ◽  
Sun I. Kim
Keyword(s):  
Virtual Reality ◽  
Computer Games ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Vehicle Accident

Machine Learning of Motor Vehicle Accident Categories from Narrative Data

1996 ◽  
Vol 35 (04/05) ◽  
pp. 309-316 ◽  
Author(s):  
M. R. Lehto ◽  
G. S. Sorock
Keyword(s):  
Machine Learning ◽  
Bayesian Model ◽  
Keyword Search ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Computer Search ◽  
Vehicle Accident ◽  
Learning Technique ◽  
Expert Ratings ◽  
Keyword Searches

Abstract:Bayesian inferencing as a machine learning technique was evaluated for identifying pre-crash activity and crash type from accident narratives describing 3,686 motor vehicle crashes. It was hypothesized that a Bayesian model could learn from a computer search for 63 keywords related to accident categories. Learning was described in terms of the ability to accurately classify previously unclassifiable narratives not containing the original keywords. When narratives contained keywords, the results obtained using both the Bayesian model and keyword search corresponded closely to expert ratings (P(detection)≥0.9, and P(false positive)≤0.05). For narratives not containing keywords, when the threshold used by the Bayesian model was varied between p>0.5 and p>0.9, the overall probability of detecting a category assigned by the expert varied between 67% and 12%. False positives correspondingly varied between 32% and 3%. These latter results demonstrated that the Bayesian system learned from the results of the keyword searches.

Aspirated teeth - rigid or flexible bronchoscopy

2019 ◽  
pp. 1-2
Keyword(s):  
Clinical Practice ◽  
Foreign Bodies ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Flexible Bronchoscopy ◽  
Vehicle Accident

Tracheobronchial foreign bodies are a common problem in clinical practice. We present the case of a patient with three aspirated teeth following a motor vehicle accident.

Isolated second trimester uterine rupture following a motor vehicle accident

2021 ◽  
Vol 258 ◽  
pp. 461-463
Author(s):  
Tal Margaliot Kalifa ◽  
Misgav Rottenstreich ◽  
Eyal Mazaki ◽  
Hen Y. Sela ◽  
Schwartz Alon ◽  
...  
Keyword(s):  
Uterine Rupture ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Second Trimester ◽  
Vehicle Accident

scholarly journals Obstructive Sleep Apnea and Risk of Motor Vehicle Accident

2021 ◽  
Author(s):  
Gaia S. Pocobelli ◽  
Mary A. Akosile ◽  
Ryan N. Hansen ◽  
Joanna Eavey ◽  
Robert D. Wellman ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Vehicle Accident ◽  
Obstructive Sleep
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