Correlation between maternal and infant cortisol varies by breastfeeding status

ObjectiveThe objective of this study was to examine associations of mother and infant salivary cortisol, measured three times over the course of a day, and assess whether these varied by breastfeeding status.MethodsWe conducted a cross-sectional study of 54 mothers and their infants aged 4–11 months. Mothers collected their own saliva and that of their infants upon awakening, 30 min after waking and at bedtime. Breastfeeding status was reported by mothers and cortisol level was measured in saliva in μg/dl using standard techniques. We used generalized linear models to evaluate relationships between maternal and infant cortisol levels, and assessed whether the relationship differed by breastfeeding status: formula only compared to partial and full breastfeeding, adjusting for infant sex, race, age, maternal education, and family income.ResultsThirty-four infants received formula only and 20 were either partially or fully breastfed. Breastfeeding was associated with higher household income, higher maternal education, and white race. Cortisol levels were higher among breastfed infants at all three time points. After adjustment, maternal cortisol levels were related with infant cortisol at bedtime only (regression estimate 0.06; 95% CI: 0.10, 1.1; p = 0.02). The adjusted association between bedtime maternal and infant cortisol was stronger among breastfeeding dyads than among formula-feeding dyads (regression estimate 1.0; 95% CI: 0.1, 2.0; p = 0.04 vs. 0.6; CI: −0.1, 1.3; p = 0.10). In addition, we assessed the influence of maternal education and household income in our adjusted model; income strengthened the observed association, whereas maternal education did not change the estimate.ConclusionsBreastfeeding mothers and infants had significant correlations for cortisol at bedtime, while formula-feeding dyads did not. These data suggest that several factors may contribute to cortisol synchrony observed in mother/infant dyads, including the transfer of cortisol in human milk, physical interaction such as skin-to-skin contact, and shared environment. In addition, our findings support household income as a possible contributor.     

When motor congruency modulates immediate memory for objects

In line with the embodied cognition view, some researchers have suggested that our capacity to retain information relies on the perceptual and motor systems used to interact with our environment (Barsalou, 1999; Glenberg, 1997). For instance, the language production architecture would be responsible for the retention of verbal materials such as a list of words (Acheson & MacDonald, 2009). However, evidence for the role of the motor system in object memory is still limited. In the present experiments, participants were asked to retain lists of objects in memory. During encoding, participants had to pantomime an action to grasp (Experiments 1A & 1B) or to use the objects (Experiment 2) that was either congruent or incongruent with the objects to be retained. The results showed that performing an incongruent action impaired memory performance compared to a congruent action. This suggests that motor affordances play a role during object retention. The results are discussed in light of the embodied cognition view.     

The Need for a More Effective Science of Cultural Practices

Behavior analysis has produced a robust theoretical analysis of the contingencies involved in cultural evolution. Yet, thus far, the empirical yield of this work remains quite limited. With this paper, I attempt to provide specific examples of the ways to advance an experimental analysis of the contingencies involved in cultural evolution. I begin with a review of the theoretical analyses developed by behavior analysts and other contextually oriented scientists. Next, I submit that, if the goal of our science is both predicting and influencing cultural phenomena, we must produce experimental analyses of the impact of meta-contingencies on organizations’ practices. There is no more pressing reason for doing this than the threat of climate change posed by the continuing growth in human use of fossil fuels. Therefore, the paper provides an analysis of the contingencies influencing organizational practices now affecting continued use of fossil fuels and the contingencies for organizations seeking to prevent their use. One concrete step to advance a science of cultural change relevant to climate change would be to create a database of organizations that are promoting vs. working to prevent fossil fuel consumption and the consequences that seem to maintain their practices. I call for experimental analysis of the impact of altering consequences for these practices and for experimental analyses of interventions intended to change the norms, values, and behavior of organizational leaders who can influence fossil fuel consumption. I then discuss the role of prosocial behavior and values in affecting behavior relevant to reducing fossil fuel consumption because the empirical evidence shows that prosociality favors more “green” behavior. Recent advances in prevention research have identified interventions to promote prosociality, but we need experimental analyses of how advocacy organizations can be more effective in getting these interventions widely adopted.     

Effects of explanation-based knowledge regarding system functions and driver’s roles on driver takeover during conditionally automated driving: A test track study

The present study was designed to examine the influence of explanation-based knowledge regarding system functions and the driver’s role in conditionally automated driving (Level 3, as defined in SAE J3016). In particular, we studied how safely and successfully drivers assume control of the vehicle when encountering situations that exceed the automation parameters. This examination was conducted through a test-track experiment. Thirty-two younger drivers (mean age = 37.3 years) and 24 older drivers (mean age = 71.1 years) participated in Experiments 1 and 2, respectively. Adopting a between-participants design, in each experiment the participants were divided into two age- and sex-matched groups that were given differing levels of explanation-based knowledge concerning the system limitations of automated driving. The only information given to the less-informed groups was that, during automated driving, drivers may be required to occasionally assume control of the vehicle. The well-informed groups were given the same information, as well as details regarding the auditory-visual alerts produced by the human–machine interface (HMI) during requests to intervene (RtIs), and examples of situations where RtIs would be issued. Ten and nine RtI events were staged for each participant in Experiment 1 and 2, respectively; the participants performed a non-driving-related task while the automated driving system was functioning. For both experiments it was found that, for all RtI events, more participants in the well-informed groups than the less-informed groups successfully assumed control of the vehicle. These results suggest that, in addition to providing information regarding the possible occurrence of RtIs, explanations of HMI and RtI-related situations are effective for helping both younger and older drivers safely and successfully negotiate such events.     

The safety performance of connected vehicles on slippery horizontal curves through enhancing truck drivers’ situational awareness: A driving simulator experiment

Although drivers can adequately adjust their operating speed according to the road curvature, they show a lack of recognition regarding the pavement friction conditions. In this regard, inappropriate speed selection on Horizontal Curves (HCs) with reduced surface friction can lead to a remarkable rate of run-off-road, sideswipe, head-on, and rollover crashes, especially on rural highways. Aligned with the Connected Vehicle (CV) Pilot Program on Interstate-80 in Wyoming, this study scrutinizes how CV advisory/warning messages can enhance traffic safety on slippery HCs. To this aim, a roadway consists of two HCs with regular and slippery pavement conditions was designed in a high-fidelity driving simulator experiment. A total of 24 professional truck drivers were recruited to drive the simulated roadway under CV and non-CV environments. In the CV scenario, drivers were informed about the pavement conditions and the advisory speeds before entering HCs. In contrast, no messages were given to non-CV drivers. Truck drivers' behaviors in both scenarios were quantified using four Kinematic-based Surrogate Measures of Safety (K-SMoS), including deviation from the pathway, instantaneous acceleration, lateral speed, and steering angle. CVs’ trajectories were statistically compared to non-CVs in terms of the central tendency and dispersion using the Wilcoxon Signed-Rank Test (WSRT) and Median Absolute Deviation (MAD), respectively. The results of WSRT depicted, under the effect of CV advisory/warning messages and throughout the slippery HC, the central tendency of four K-SMoS could be shifted toward zero by 23% up to 99%. This shifting is associated with a significant safety enhancement that potentially can reduce the likelihood of curve-related crashes on slippery HCs. It was revealed that the variation in drivers’ behavior on the slippery HC could be minimized in the CV environment, where 54% up to 95% reduction in the dispersions of four K-SMoS were observed, leading to more certainty in drivers’ behavior.     

Impact of interface design on drivers’ behavior in partially automated cars: An on-road study

In partially automated vehicles, the driver and the automated system share control of the vehicle. Consequently, the driver may have to switch between driving and monitoring activities. This can critically impact the driver’s situational awareness. The human–machine interface (HMI) is responsible for efficient collaboration between driver and system. It must keep the driver informed about the status and capabilities of the automated system, so that he or she knows who or what is in charge of the driving. The present study was designed to compare the ability of two HMIs with different information displays to inform the driver about the system’s status and capabilities: a driving-centered HMI that displayed information in a multimodal way, with an exocentric representation of the road scene, and a vehicle-centered HMI that displayed information in a more traditional visual way. The impact of these HMIs on drivers was compared in an on-road study. Drivers’ eye movements and response times for questions asked while driving were measured. Their verbalizations during the test were also transcribed and coded. Results revealed shorter response times for questions on speed with the exocentric and multimodal HMI. The duration and number of fixations on the speedometer were also greater with the driving-centered HMI. The exocentric and multimodal HMI helped drivers understand the functioning of the system, but was more visually distracting than the traditional HMI. Both HMIs caused mode confusions. The use of a multimodal HMI can be beneficial and should be prioritized by designers. The use of auditory feedback to provide information about the level of automation needs to be explored in longitudinal studies.     

The power and sensitivity of four core driver workload measures for benchmarking the distraction potential of new driver vehicle interfaces

This study evaluated the power and sensitivity of several core driver workload measures in order to better understand their use as a component of future driver distraction potential evaluation procedures of the in-vehicle human machine interface (HMI). Driving is a task that requires visual, manual and cognitive resources to perform. Secondary tasks, such as mobile phone use and interaction with in-built navigation, which load onto any of these three processing resources increase driver workload and can lead to impaired driving. Because workload and distraction potential are interrelated, a comprehensive method to assess driver workload that produces valid and predictive results is needed to advance the science of distraction potential evaluation. It is also needed to incorporate into New Car Assessment Program (NCAP) testing regimes. Workload measures of cognitive (DRT [Detection Response Task] Reaction Time), visual (DRT Miss Rate), subjective (NASA-TLX [driver workload questionnaire]), and temporal demand (Task Interaction Time) were collected as participants drove one of 40 vehicles while completing a variety of secondary tasks with varying interaction requirements. Of the evaluated measures, variance and power analyses demonstrated that Task Interaction Time is the most sensitive in detecting differences in driver workload between different in-vehicle HMIs, followed by DRT Miss Rate, NASA-TLX and finally DRT Reaction Time. There were relatively weak correlations between each of the four measures. These results suggest that Task Interaction Time, coupled with a reliable visual demand metric such as DRT Miss Rate, eye glance coding, or visual occlusion, more efficiently detect differences in driver workload between different HMIs compared to DRT Reaction Time and the NASA-TLX questionnaire. These results can be used to improve the understanding of the utility of each of these core driver workload measures in assessing driver distraction potential.     

Should older people be considered a homogeneous group when interacting with level 3 automated vehicles?

Exploring the future mobility of older people is imperative for maintaining wellbeing and quality of life in an ageing society. The forthcoming level 3 automated vehicle may potentially benefit older people. In a level 3 automated vehicle, the driver can be completely disengaged from driving while, under some circumstances, being expected to take over the control occasionally. Existing research into older people and level 3 automated vehicles considers older people to be a homogeneous group, but it is not clear if different sub-groups of old people have different performance and perceptions when interacting with automated vehicles. To fill this research gap, a driving simulator investigation was conducted. We adopted a between-subjects experimental design with subgroup of old age as the independent variable. The differences in performance, behaviour, and perception towards level 3 automated vehicles between the younger old group (60–69 years old) and older old group (70 years old and over) was investigated. 15 subjects from the younger old group (mean age = 64.87 years, SD = 3.46 years) and 24 from the older old group (mean age = 75.13 years, SD = 3.35 years) participated in the study. The findings indicate that older people should not be regarded as a homogeneous group when interacting with automated vehicle. Compared to the younger old people, the older old people took over the control of the vehicle more slowly, and their takeover was less stable and more critical. However, both groups exhibited positive perceptions towards level 3 automation, and the of older old people’s perceptions were significantly more positive. This study demonstrated the importance of recognising older people as a heterogeneous group in terms of their performance, capabilities, needs and requirements when interacting with automated vehicles. This may have implications in the design of such systems and also understanding the market for autonomous mobility.     

The Power of a “Maverick” in Collaborative Problem Solving: An Experimental Investigation of Individual Perspective‐Taking Within a Group

Integrating different perspectives is a sophisticated strategy for developing constructive interactions in collaborative problem solving. However, cognitive aspects such as individuals’ knowledge and bias often obscure group consensus and produce conflict. This study investigated collaborative problem solving, focusing on a group member interacting with another member having a different perspective (a “maverick”). It was predicted that mavericks might mitigate disadvantages and facilitate perspective taking during problem solving. Thus, 344 university students participated in two laboratory‐based experiments by engaging in a simple rule‐discovery task that raised conflicts among perspectives. They interacted with virtual partners whose conversations were controlled by multiple conversational agents. Results show that when participants interacted with a maverick during the task, they were able to take others’ perspectives and integrate different perspectives to solve the problem. Moreover, when participants interacted in groups with a positive mood, groups with a maverick outperformed groups having several perspectives.     

Human machine interface design for continuous support of mode awareness during automated driving: An online simulation

In the transition towards higher levels of vehicle automation, one of the key concerns with regards to human factors is to avoid mode confusion, when drivers misinterpret the driving mode and therewith misjudge their own tasks and responsibility. To enhance mode awareness, a clear human centered Human Machine Interface (HMI) is essential. The HMI should support the driver tasks of both supervising the driving environment when needed and self-regulating their non-driving related activities (NDRAs). Such support may be provided by either presenting continuous information on automation reliability, from which the driver needs to infer what task is required, or by presenting continuous information on the currently required driving task and allowed NDRA directly. Additionally, it can be valuable to provide continuous information to support anticipation of upcoming changes in the automation mode and its associated reliability or required and allowed driver task(s). Information that could support anticipation includes the available time until a change in mode (i.e. time budget), information on the upcoming mode, and reasons for changing to the upcoming mode. The current work investigates the effects of communicating this potentially valuable information through HMI design. Participants received information from an HMI during simulated drives in a simulated car presented online (using Microsoft Teams) with an experimenter virtually accompanying and guiding each session. The HMI either communicated on automation reliability or on the driver task, and either included information supporting anticipation or did not include such information. Participants were thinking aloud during the simulated drives and reported on their experience and preferences afterwards. Anticipatory information supported understanding about upcoming changes without causing information overload or overreliance. Moreover, anticipatory information and information on automation reliability, and especially a combination of the two, best supported understandability and usability. Recommendations are provided for future work on facilitating supervision and NDRA self-regulation during automated driving through HMI design.