The effect of an occlusion-induced delay on braking behavior in critical situations: A driving simulator study.

OBJECTIVE: To share results of an experiment that used visual occlusion for a new purpose: inducing a waiting time. BACKGROUND: Senders was a leading figure in human factors. In his research on the visual demands of driving, he used occlusion techniques. METHODS: In a simulator experiment, we examined how drivers brake for different levels of urgency and different visual conditions. In three blocks (1 = brake lights, 2 = no brake lights, 3 = occlusion), drivers followed a vehicle at 13.4 or 33.4 m distance. At certain moments, the lead vehicle decelerated moderately (1.7 m/s2) or strongly (6.5 m/s2). In the occlusion condition, the screens blanked for 0.4 s (if 6.5 m/s2) or 2.0 s (if 1.7 m/s2) when the lead vehicle started to decelerate. Participants were instructed to brake only after the occlusion ended. RESULTS: The lack of brake lights caused a delayed response. In the occlusion condition, drivers adapted to the instructed late braking by braking harder. However, adaptation was not always possible: In the most urgent condition, most participants collided with the lead vehicle because the ego-vehicle's deceleration limits were reached. In non-urgent conditions, some drivers braked unnecessarily hard. Furthermore, while waiting until the occlusion cleared, some drivers lightly touched the brake pedal. CONCLUSION: This experimental design demonstrates how drivers (sometimes fail to) adjust their braking behavior to the criticality of the situation. APPLICATION: The phenomena of biomechanical readiness and (inappropriate) dosing of the brake pedal may be relevant to safety, traffic flow, and ADAS design.

Attribution Errors by People and Intelligent Machines.

OBJECTIVE: To explore the ramifications of attribution errors (AEs), initially in the context of vehicle collisions and then to extend this understanding into the broader and diverse realms of all forms of human-machine interaction. BACKGROUND: This work focuses upon a particular topic that John Senders was examining at the time of his death. He was using the lens of attribution, and its associated errors, to seek to further understand and explore dyadic forms of driver collision. METHOD: We evaluated the utility of the set of Senders' final observations on conjoint AE in two-vehicle collisions. We extended this evaluation to errors of attribution generally, as applicable to all human-human, human-technology, and prospectively technology-technology interactions. RESULTS: As with Senders and his many other contributions, we find evident value in this perspective on how humans react to each other and how they react to emerging forms of technology, such as autonomous systems. We illustrate this value through contemporary examples and prospective analyses. APPLICATIONS: The comprehension and mitigation of AEs can help improve all interactions between people, between intelligent machines and between humans and the machines they work with.

Listen carefully: the risk of error in spoken medication orders.

Clinicians and patients often confuse drug names that sound alike. We conducted auditory perception experiments in the United States to assess the impact of similarity, familiarity, background noise and other factors on clinicians' (physicians, family pharmacists, nurses) and laypersons' ability to identify spoken drug names. We found that accuracy increased significantly as the signal-to-noise (S/N) ratio increased, as subjective familiarity with the name increased and as the national prescribing frequency of the name increased. For clinicians only, similarity to other drug names reduced identification accuracy, especially when the neighboring names were frequently prescribed. When one name was substituted for another, the substituted name was almost always a more frequently prescribed drug. Objectively measurable properties of drug names can be used to predict confusability. The magnitude of the noise and familiarity effects suggests that they may be important targets for intervention. We conclude that the ability of clinicians and lay people to identify spoken drug names is influenced by signal-to-noise ratio, subjective familiarity, prescribing frequency, and the similarity neighborhoods of drug names.

Using nurses and office staff to report prescribing errors in primary care.

OBJECTIVE: To implement a prescribing-error reporting system in primary care offices and analyze the reports. DESIGN: Descriptive analysis of a voluntary prescribing-error-reporting system SETTING: Seven primary care offices in Vermont, USA. PARTICIPANTS: One hundred and three prescribers, managers, nurses and office staff. INTERVENTION: Nurses and office staff were asked to report all communications with community pharmacists regarding prescription problems. MAIN OUTCOME MEASURES: All reports were classified by severity category, setting, error mode, prescription domain and error-producing conditions. RESULTS: All practices submitted reports, although reporting decreased by 3.6 reports per month (95% CI, -2.7 to -4.4, P<0.001, by linear regression analysis). Two hundred and sixteen reports were submitted. Nearly 90% (142/165) of errors were severity Category B (errors that did not reach the patient) according to the National Coordinating Council for Medication Error Reporting and Prevention Index for Categorizing Medication Errors. Nineteen errors reached the patient without causing harm (Category C); and 4 errors caused temporary harm requiring intervention (Category E). Errors involving strength were found in 30% of reports, including 23 prescriptions written for strengths not commercially available. Antidepressants, narcotics and antihypertensives were the most frequent drug classes reported. Participants completed an exit survey with a response rate of 84.5% (87/103). Nearly 90% (77/87) of respondents were willing to continue reporting after the study ended, however none of the participants currently submit reports. CONCLUSIONS: Nurses and office staff are a valuable resource for reporting prescribing errors. However, without ongoing reminders, the reporting system is not sustainable.