Little research has explored burnout and its causes in the American fire service. Data were collected from career firefighters in the southeastern United States (n = 208) to explore these relationships. A hierarchical regression model was tested to examine predictors of burnout including sociodemographic characteristics (model 1), work pressure (model 2), work stress and work–family conflict (model 3) and interaction terms (model 4). The main findings suggest that perceived work stress and work–family conflict emerged as the significant predictors of burnout (both p < .001). Interventions and programs aimed at these predictors could potentially curtail burnout among firefighters.

The rapid growth of autonomous vehicles is expected to improve roadway safety. However, certain levels of vehicle automation will still require drivers to ‘takeover’ during abnormal situations, which may lead to breakdowns in driver-vehicle interactions. To date, there is no agreement on how to best support drivers in accomplishing a takeover task. Therefore, the goal of this study was to investigate the effectiveness of multimodal alerts as a feasible approach. In particular, we examined the effects of uni-, bi-, and trimodal combinations of visual, auditory, and tactile cues on response times to takeover alerts. Sixteen participants were asked to detect 7 multimodal signals (i.e., visual, auditory, tactile, visual-auditory, visual-tactile, auditory-tactile, and visual-auditory-tactile) while driving under two conditions: with SAE Level 3 automation only or with SAE Level 3 automation in addition to performing a road sign detection task. Performance on the signal and road sign detection tasks, pupil size, and perceived workload were measured. Findings indicate that trimodal combinations result in the shortest response time. Also, response times were longer and perceived workload was higher when participants were engaged in a secondary task. Findings may contribute to the development of theory regarding the design of takeover request alert systems within (semi) autonomous vehicles.

Automated vehicles may occasionally require drivers to take over. The complexity of the takeover process warrants the design of effective human–machine interfaces that assist drivers in regaining control, especially when the visual and auditory sensory modalities are occupied. Vibrotactile displays, which can represent information about the status, direction, and position of driving environment elements, have been suggested as one promising approach, but their effectiveness to aid in takeover transitions has not been fully evaluated. This study investigated the effects of meaningful tactile signal patterns, used as takeover requests, on automated vehicle takeover performance. Forty participants rode in a simulated SAE Level 3 automated vehicle and completed a series of takeover tasks with two tactile pattern formats, i.e., informative (which displayed status information of surrounding vehicles) and instructional (that displayed the appropriate takeover maneuver), and three in-vehicle locations (seat back, seat pan, and a seat back and seat pan combination). Takeover response options included lane changes only or brake applications followed by changing lanes, depending on the locations of surrounding vehicles. Results indicate that only meaningful instructional tactile signals, in either the seat back or seat pan, were associated with worse takeover response time and maximum resulting acceleration compared to signals without any patterns. Additionally, tactile information presented on the seat back was perceived as the most useful and satisfying. Findings from this study can inform the development of next-generation human–machine interfaces that utilize tactile stimulation in a wide range of environments with automation.

Smart speech systems are becoming increasingly pervasive in society. At the same time, the number of older adults is rapidly growing. These simultaneous trends make it likely for older individuals to encounter and, in some cases, benefit from speech systems throughout later stages of life. To date, most research studies have examined older adult non-users’ opinions of speech systems, but not the sentiments of older users. To address this research gap, four focus groups were conducted to compare the perceptions and attitudes of seniors who voluntarily use and do not use speech systems across various devices. Findings suggest that older users and non-users are similar in their perception of the advantages provided this technology, factors that (could) motivate their use, common challenges faced while using these systems, and barriers to using particular features or speech systems altogether. The two groups differed in their preferences for learning how to use these systems, perception of system cost, and global perception of technology. In addition, older adult users exclusively believed speech systems to be easy to use, but also expressed concerns about information transparency and privacy. Older non-users explained that the absence of age-related declines was a barrier to use. These results may guide designers and researchers in developing, evaluating, and refining smart technologies to be used by various senior populations.