The effect of conflicting public health guidance on smokers and vapers’ e-cigarette harm perceptions

Background: E-cigarettes are increasingly being viewed, incorrectly, as more harmful than cigarettes. This may discourage smokers from switching to e-cigarettes. One potential explanation for these increasingly harmful attitudes is conflicting information presented in the media, online and from public health bodies. Methods: In a prospectively registered online study, daily UK smokers who do not vape (n=334) and daily UK vapers (n=368) were randomised to receive either: 1) a consistent harm reduction statement from two different public health bodies (Harm Reduction); 2) a consistent negative statement about e-cigarette harms from two different public health bodies (Negative); 3) a harm reduction statement from one public health body and a negative statement from another (Conflict); 4) a statement of the risks of smoking followed by a harm reduction statement from one public health body and a negative statement from another (Smoking Risk + Conflict). Participants then answered questions regarding their e-cigarette harm perceptions. Results: The Negative condition had the highest e-cigarette harm perceptions, significantly higher than the Smoking Risk + Conflict condition (MD=5.4, SE=1.8, p<.016, d=0.3 [CI 0.73 to 10.04]), which did not differ from the Conflict condition (MD=1.5, SE=1.8, p=.836, d=0.1 [CI -3.14 to 6.17]). The Conflict condition differed from the Harm Reduction condition, where harm perceptions were lowest (MD=5.4, SE=1.8, p=.016, d=0.3 [CI 0.74 to 10.07]). Conclusions: These findings are the first to demonstrate that, compared to harm reduction information, conflicting information increases e-cigarette harm perceptions amongst vapers, and smokers who do not vape.

Risk Communication under Conflicting Information: The Role of Confidence in Subjective Risk Assessment

In this study, we develop a model of food consumption with a focus on the subjectively assessed risk of consumers and their degree of confidence in their risk assessment and use it to examine consumer behavior in the chaotic situation created by the Fukushima nuclear accident in 2011. The data were collected in March 2012 using a mail survey for 1300 Japanese women, the primary food purchasers. The respondents were asked to evaluate the cancer risk of eating agricultural products, which were assumed to be grown in the affected area, despite meeting national regulatory standards for radioactive materials, as a measure of their risk assessment and willingness to purchase Fukushima beef. The results show that the effect of confidence in a consumer’s risk assessment on their behavior depends on the stated risk level: when stated risk is below an estimated critical value, termed the switching point, the risk perceived by a consumer without confidence exceeds that of one with confidence. On the other hand, perceived risk is inversely related to confidence when the stated risk exceeds the switching point.

The time-course of distractor-based activation modulates effects of speed-accuracy tradeoffs in conflict tasks

The cognitive processes underlying the ability of human performers to trade speed for accuracy is often conceptualized within evidence accumulation models, but it is not yet clear whether and how these models can account for decision-making in the presence of various sources of conflicting information. In the present study, we provide evidence that speed-accuracy tradeoffs (SATs) can have opposing effects on performance across two different conflict tasks. Specifically, in a single preregistered experiment, the mean reaction time (RT) congruency effect in the Simon task increased, whereas the mean RT congruency effect in the Eriksen task decreased, when the focus was put on response speed versus accuracy. Critically, distributional RT analyses revealed distinct delta plot patterns across tasks, thus indicating that the unfolding of distractor-based response activation in time is sufficient to explain the opposing pattern of congruency effects. In addition, a recent evidence accumulation model with the notion of time-varying conflicting information was successfully fitted to the experimental data. These fits revealed task-specific time-courses of distractor-based activation and suggested that time pressure substantially decreases decision boundaries in addition to reducing the duration of non-decision processes and the rate of evidence accumulation. Overall, the present results suggest that time pressure can have multiple effects in decision-making under conflict, but that strategic adjustments of decision boundaries in conjunction with different time-courses of distractor-based activation can produce counteracting effects on task performance with different types of distracting sources of information.

Systems Barriers to Medication Management During Hospital to Home Transitions of Older Adults With Dementia

The hospital-to-home transition is a high-risk period for medication errors and adverse events for older adults living with dementia. Researchers conducted a qualitative study using semi-structured interviews and participant solicited diaries. Caregivers of adults ages 55 and older were recruited to understand barriers to medication management during hospital to skilled home health care transitions. We used a human factors engineering approach to guide our understanding of systems level barriers. At least two researchers independently coded each transcript using content analysis and the ATLAS.ti software. We interviewed 23 caregivers and identified five barrier types stemming from systems breakdowns related to: (1) knowledge and information, (2) access to and use of resources and tools, (3) caregiver burden, (4) pandemic concerns, and (5) health limitations. Caregivers grappled with receiving overwhelming, insufficient, incorrect, or conflicting information, and had difficulty managing information from different sources. Latinx caregivers encountered language barriers that impeded role and task clarity. Caregivers expressed mistrust in health systems elements and inability to access resources. Caregivers were in need of additional caregiving assistance, financial aid, and tools to manage medications. Balancing multiple medications and responsibilities left caregivers burdened. The health limitations of the older adult and COVID-19 concerns related to reduced access to resources and ability to deliver and receive in person care complicated task management. Altogether these barriers reflect systems level breakdowns impeding task understanding, execution, and overall management. These findings will inform the development of interdisciplinary strategies to ensure safer care transitions.

From Individual Cognitive Maps to a Collective Cognitive Map: Prescriptive Guidelines and Measurement of Factors that Could Distort the Mapping Process

In the collective navigation scenario of a trio exploring in a foreign city, we propose a theoretical piece, which is a prescriptive guideline describing rational ways that can enable the trio to form a collective cognitive map. The guidelines center around three stages of exploration: the initial gathering of information, coming together to plan a route in the new city, and executing the exploration plan. Depending on the desires and goals of the group, they might explore together for some or all of the time, splitting up only when their individual goals diverge. The guidelines suggest an optimal plan for these different possibilities. We propose that a collective cognitive map is formed and improved during the entire cognitive navigation process as demonstrated by the trio drawing sketch maps, creating place maps, and revising other people’s place maps. However, multiple factors could distort the navigation process at various points in the proposed prescriptive guidelines. These factors include individual differences (e.g., personal navigation ability, navigation anxiety, and sex), group dynamics (e.g., leaders and followers, group strategies), and the impact of the environment (e.g., language, culture, safety, and spatiality). We describe a thought experiment for testing collective navigation, including the measurement of these factors and the corresponding possible distortions in the collective map caused by these factors. Finally, we discuss future research directions, including using virtual environments and commercial applications. By utilizing our model, people can be flexible in resolving conflicting information during goal planning while still navigating efficiently.

Day length-dependent thermal COP1 dynamics integrate conflicting seasonal cues in the control of Arabidopsis elongation

As the summer approaches, plants experience enhanced light inputs and elevated temperatures, two environmental cues with an opposite morphogenic impact. How plants integrate this conflicting information throughout seasons remains unclear. Key components of the plant response to light and temperature include phytochrome B (phyB), PHYTOCROME INTERACTING FACTOR 4 (PIF4), EARLY FLOWERING 3 (ELF3) and CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1). Here, we used hypocotyl lengths of single and double mutant/over-expression lines to fit a mathematical model incorporating known interactions of these genes. The fitted model recapitulates day length-dependent thermoelongation of all lines studied, and correctly predicts temperature responsiveness of new genotypes. Whilst previous works pointed to a light-independent thermal function of COP1, simulations of our model suggested that COP1 has a role in temperature-signaling only during daytime. Based on by this prediction, we show that COP1 overexpression increases thermal response in continuous white light, while it has little effect in darkness. Defective thermal response of cop1-4 mutants is epistatic to phyB-9 and elf3-8, indicating that COP1 activity is essential to the transduction of phyB and ELF3 thermosensory function. Our model accurately captures phyB, ELF3 and PIF4 dynamics, providing an excellent toolbox for identification of best allelic combinations towards optimized crops resilience to climate change at different geographical latitudes.

Avoidance memory requires CaMKII activity to persist after recall

Avoidance memory is destabilized when recalled concurrently with conflicting information, and must undergo a hippocampus-dependent restabilization process called reconsolidation to persist. CaMKII is a serine/threonine protein kinase essential for memory processing; however, its possible involvement in avoidance memory reconsolidation has not yet been studied. Using pharmacological, electrophysiological and optogenetic tools, we found that in adult male Wistar rats hippocampal CaMKII is necessary to reconsolidate avoidance memory, but not to keep it stored while inactive, and that blocking reconsolidation via CaMKII inhibition erases learned avoidance responses.

Learning Feedback Molecular Network Models Using Integer Linear Programming

Analysis of intracellular molecular networks has many applications in understanding of the molecular bases of some complex diseases and finding the effective therapeutic targets for drug development. To perform such analyses, the molecular networks need to be converted into computational models. In general, network models constructed using literature and pathway databases may not accurately predict and reproduce experimental network data. This can be due to the incompleteness of literature on molecular pathways, the resources used to construct the networks, or some conflicting information in the resources. In this paper, we propose a network learning approach via an integer linear programming formulation that can efficiently incorporate biological dynamics and regulatory mechanisms of molecular networks in the learning process. Moreover, we present a method to properly take into account the feedback paths, while learning the network from data. Examples are also provided to show how one can apply the proposed learning approach to a network of interest. Overall, the proposed methods are useful for reducing the gap between the curated networks and experimental network data, and result in calibrated networks that are more reliable for making biologically meaningful predictions.