Human Behavior Research Articles

Using the Nudge Theory to Enhance Attending Anesthesiologist Breaks.

It is well understood that human behavior can be influenced, often by the most subtle of factors. Otherwise known as "nudging", these attempts to affect human decision making in a predictable manner are possible due to individual cognitive boundaries, biases, routines, and habits. This quality improvement study analyzes the impact of a norms nudge on compliance of attending anesthesiologists providing breaks to the providers they are working with under the care team model. The nudge displays the top performing attendings as well as the top performing hospital to all attendings. Each individual can also view where they fall in relation to the department average as well as their deidentified partners. Implementation of the norms nudge was associated with a significant increase in the percentage of breaks given in the accepted time frame. Morning break compliance increased from 75.0 to 78.1% (p = 0.0002), lunch breaks increased from 83.0% to 86.3 (p < 0.0001), and afternoon breaks increased from 61.8 to 65.3% (p < 0.0001). The present study suggests that norm nudges may be able modify intraoperative practices with regards to breaks without significant cost, education, or other investment.

How and When Ethics-oriented Human Resource Management Systems Promote Organizational Citizenship Behavior: The Moderated Mediation of Work-Family Balance and Moral Attentiveness

How and When Ethics-oriented Human Resource Management Systems Promote Organizational Citizenship Behavior: The Moderated Mediation of Work-Family Balance and Moral Attentiveness

Reconstruction of the paleoenvironmental context of Holocene human behavior at the Fenghuangzui site in the Nanyang Basin, Middle Yangtze River, China

Geomorphological research at archaeological sites reveals that environmental factors, such as geomorphology and hydrology, play a crucial role in understanding changes in site layout and cultural processes. However, due to the lack of reliable chronologies, there is limited understanding of environmental factors in relation to archaeological site. This study focuses on the sedimentary records from the southern moat of the Fenghuangzui (FHZ) site, a representative site in the middle Yangtze River region, integrating a chronological framework and climate proxies such as elemental geochemistry. It reconstructs the evolution of the regional sedimentary environment and the hydrogeomorphology during the mid-late Holocene at the FHZ site, elucidating its interplay with human activities. Key findings include: (1) From 5.6–4.5 ka BP, elevated chemical index of alteration (CIA), Rb/Sr, and Mn/Ti values indicate a warm and humid climate. The Qujialing culture unified the middle Yangtze River and established regional central settlements such as Shijiahe site, and then expanded to the north. The FHZ site was built in the Nanyang Basin at this time to prevent the invasion of northern culture. (2) During 4.5–4 ka BP, decreased CIA and Rb/Sr values alongside rising secondary aluminum factor (Saf) and dealkalization coefficient (Bc) values signify reduced weathering and a transition to cooler, drier conditions. A flood event of 4–3.9 ka BP caused the moat of the FHZ site to lose its defensive function. (3) During 4–2.7 ka BP, declining CIA and Rb/Sr values with slight increases in Saf and Bc suggest ongoing dry and cool environmental conditions. The FHZ site was abandoned at the end of the Meishan culture. (4) Between 2.7–1.6 ka BP, rising CIA and Rb/Sr values indicate a return to warmer and more humid conditions. The FHZ site was built to expand the influence of Qujialing culture and protect the Shijiahe settlement. Taking into account the location of the water system and farming area, the south-facing direction was chosen. In general, our findings suggest that changes in regional hydrology in the context of climate change can trigger upheaval and even collapse of prehistoric societies.

Affective‐Motivational States Link Threat Experience and Defensive Reactions During the Covid‐19 Pandemic

ABSTRACTThe pandemic changed people's lives and came with enormous restrictions on personal freedom, greatly restricting people's sense of agency. In response, people oscillated between fear and anger. We show (N = 2125) the ways in which people restored their perceived agency that was taken away by restrictions and that affective reactions to the pandemic may have guided people's pandemic behavior. In Study 1 (n = 276), psychological threat elicited by the pandemic predicted anxiety and was, in turn, related to reactance. While anxiety positively predicted reactions increasing the success of pandemic management, reactance was related to non‐facilitating reactions such as belief in conspiracies and vaccine distrust. In Study 2 (n = 354), reading about a conspiracy myth as one form of defense increased positive affect. In Study 3 (n = 213) and Study 4 (n = 1282), we replicated findings from Study 1, extending the focus to belief in conspiracies and fake news, anti‐vaccination attitudes, national trust, solidarity, and mainstream media mistrust. Interestingly, in Study 4, defensive reactions were associated with more perceived agency, indicating that defensive reactions may be tools to manage pandemic‐induced affect. This study series shows that a threat and defense perspective may be a useful angle to understand human behavior in times of crisis.

Uncomfortable Evidence: On the Challenge of Telling New Stories about Srebrenica

ABSTRACT The International Criminal Tribunal for the Former Yugoslavia (ICTY) has sculpted the story of July 1995 in Srebrenica. In working to hold accountable the perpetrators of the crime of genocide, among other crimes against humanity, the ICTY’s prosecutors gathered an immense amount of evidence, presented cases in the courtroom, and obtained numerous convictions. These legal proceedings have engendered bitter, ongoing disputes among various actors in Bosnia–Herzegovina over their validity. All these dynamics have affected how historians approach this history. In general, they have not posed questions that stray far from the objectives that are firmly tied to the ICTY’s genocide narrative, with its clear categories of perpetrators and victims, and objective of establishing the guilt of the former and the victimization of the latter. Nearly thirty years since July 1995, perhaps the time has come to ask: what can we learn from this approach that is new? Rather than retelling what we already know about these events, we might consider turning our analytical gaze toward what is called here, “uncomfortable evidence.” This is a shorthand for stories about July 1995 that resist our desire to domesticate them into binary categories of black and white, which are more relevant for legal proceedings, and those who seek to use history to affirm or deny their results. Instead, stories based on uncomfortable evidence – three of which are told and analysed here – invite us to enter a grey zone where we embrace the complexity of human behaviour and take up the challenge of accounting for it. In so doing, historians of Srebrenica can more effectively return to a primary challenge of their discipline: to explain this violent past, while resisting the urge to make sense of it with rigid categories based on their contemporary moral and political positions.

A Game of Risk: Human Activities Shape Roe Deer Spatial Behavior in Presence of Wolves in the Southwestern Alps

In human-dominated landscapes, human activities shape prey spatial behavior, creating complex landscapes of risks. We investigated habitat selection of roe deer using resource selection functions in a human-dominated mountain system located in the southwestern Alps, characterized by a high presence of wolves and human disturbance. Our study aimed to assess how the interplay of hunting, presence of infrastructures, and recreational activities in the presence of wolves influenced roe deer spatial responses inside and outside a protected area. We documented that during the hunting period, roe deer increased selection of high-wolf-density areas, with the strongest effect observed during wild boar drive hunts, supporting the risk enhancement hypothesis, where avoiding one predator increases exposure to another, and highlighting the temporary yet significant impact of hunting on predator–prey dynamics. During the period of the wild boar drive hunt, roe deer also showed stronger selection for proximity to buildings, supporting the human shield hypothesis. Protected areas had an increased effect on roe deer avoidance of trails, where hiking and recreational activities are more concentrated. Our findings revealed the complex trade-offs that roe deer face in navigating multiple risks within human-modified landscapes, important for the development of effective conservation and human sustainability strategies.

The effect of nature-based landscape design on human health and well-being: a thematic synthesis

Population growth, high-density living situations, and rapid urbanization lead to environmental change that affects ecosystems, human behavior, and well-being. To design health-promoting urban landscapes, it is necessary to conduct more detailed studies of landscape features. However, there is a lack of review articles discussing specific approaches and factors of landscape design for human well-being in evidence-based landscape research. Therefore, this review aims to explore the research trends and future studies’ direction by adopting a thematic analysis approach. Using ATLAS.ti 23 software, we analyzed 40 literature articles on landscape design and human well-being published between 2018 and 2022. The article attribute findings show the research trends on the topic. Six main themes emerged from the subsequent qualitative analysis: (1) Human-nature Interactions, (2) Health-promoting Design, (3) Integrative Strategies, (4) Landscape Intervention, (5) Perceptions and Restorativeness, and (6) Sustainability. The resulting framework serves to guide landscape designers, urban planners, and researchers to improve the effectiveness of public social, physical, and mental health with feasible measures and design approaches.

Great ape infants’ face touching and its role in social engagement

Touch has a key role in the social development of infant primates and in the regulation of social interactions, even so, there’s a rarity of studies on infants’ use of social touch. In this work, we document chimpanzee infants and human infants’ touching of other’s faces, a behavior already described in wild capuchin monkey infants, and investigate possible functions of infants’ social touch. A strength of this study is that we sampled chimpanzee and human infants from three different social ecologies each. Each infant was observed naturalistically, in their everyday environments. In 36 h of observation, we found 269 touch events, specifically 222 face touches and 47 head touches. We found significant differences between groups, within species. Face touching occurred preferentially with adult females in all groups, and preferentially in prosocial contexts, although the most preferred contexts differed across groups. A unifying concept was that almost all infant face touching occurred during joint attention events. We interpret this as the ability of 1-year-olds to use face touching as a behavioral marker of mutual engagement during bouts of triadic connectedness, that is when they engage together with a social partner about an object or an event. In this study, we document an understudied behavior of young chimpanzees and humans, one that is not only part of prosocial interactions, but one that may function to highlight infants’ active role in engagement with another, while they together engage in triadic connectedness.

Does increasing absolute conditioned reinforcement rate improve sensitivity to relative conditioned reinforcement rate?

Previous research has demonstrated several procedural modifications that improve the sensitivity of human behavior to relative rates of conditioned reinforcement or S+ production. Denser rates of reinforcement have proved useful in related human operant research, but the influence of denser rates of S+ production has yet to be evaluated. The purpose of the current study was to evaluate how the absolute S+ production rate influenced sensitivity to relative S+ production rate. Thirty undergraduate students were randomly assigned to three groups for which the absolute rate of S+ production varied but the programmed relative rate of S+ production was held constant across groups. Results similar to those of previous research were obtained with many participants; however, the absolute rate of S+ production exerted no systematic effect on sensitivity or the quality of fits of the generalized matching equation. Exploratory analyses suggest that methods ensuring steady-state responding and improving the predictive value of S+ are important directions for future research.

Empowering human-like walking with a bio-inspired gait controller for an under-actuated torque- driven human model.

Human gait simulation plays a crucial role in providing insights into various aspects of locomotion, such as diagnosing injuries and impairments, assessing abnormal gait patterns, and developing assistive and rehabilitation technologies. To achieve more realistic gait simulation results, it's essential to use a comprehensive model that accurately replicates the kinematics and kinetics of human movement. The human skeletal models in OpenSim software provide anatomically accurate and anthropomorphic structures, enabling users to create personalized models that accurately replicate individual human behavior. However, these torque-driven models encounter challenges in stabilizing unactuated degrees of freedom of pelvis tilt during forward dynamic simulations. Adopting a bio-inspired strategy that ensures human balance with a minimized energy expenditure during walking, this paper addresses a gait controller for a torque-deriven human skeletal model to achieve a stable walking. The proposed controller employs a nonlinear model-based approach to calculate a balance-equivalent control torque and utilizes the hip-ankle strategy to distribute this torque across the lower-limb joints during the stance phase. To optimize the parameters of the trajectory tracking controller and the balance distribution coefficients, we used a forward dynamic simulation interface established between MATLAB and OpenSim. The simulation results show that the torque-driven model achieves a natural gait, with joint torques closely aligning with the experimental data. The robustness of the bio-inspired gait controller is also assessed by applying a range of external forces on the skeletal model to investigate its response to disturbances. The robustness analysis demonstrates the quick and effective balance recovery mechanism of the proposed bio-inspired gait controller.

Human mobility is well described by closed-form gravity-like models learned automatically from data.

Modeling human mobility is critical to address questions in urban planning, sustainability, public health, and economic development. However, our understanding and ability to model flows between urban areas are still incomplete. At one end of the modeling spectrum we have gravity models, which are easy to interpret but provide modestly accurate predictions of flows. At the other end, we have machine learning models, with tens of features and thousands of parameters, which predict mobility more accurately than gravity models but do not provide clear insights on human behavior. Here, we show that simple machine-learned, closed-form models of mobility can predict mobility flows as accurately as complex machine learning models, and extrapolate better. Moreover, these models are simple and gravity-like, and can be interpreted similarly to standard gravity models. These models work for different datasets and at different scales, suggesting that they may capture the fundamental universal features of human mobility.

Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment

Algorithms are involved in decisions ranging from trivial to significant, but people often express distrust toward them. Research suggests that educational efforts to explain how algorithms work may help mitigate this distrust. In a study of 1,921 participants from 20 countries, we examined differences in algorithmic trust for low-stakes and high-stakes decisions. Our results suggest that statistical literacy is negatively associated with trust in algorithms for high-stakes situations, while it is positively associated with trust in low-stakes scenarios with high algorithm familiarity. However, explainability did not appear to influence trust in algorithms. We conclude that having statistical literacy enables individuals to critically evaluate the decisions made by algorithms, data and AI, and consider them alongside other factors before making significant life decisions. This ensures that individuals are not solely relying on algorithms that may not fully capture the complexity and nuances of human behavior and decision-making. Therefore, policymakers should consider promoting statistical/AI literacy to address some of the complexities associated with trust in algorithms. This work paves the way for further research, including the triangulation of data with direct observations of user interactions with algorithms or physiological measures to assess trust more accurately.

Plus Ça Change: The Politics of Alterity, and Italian and Maltese Responses to Recent Migration Challenges

This article analyzes the evolving refugee related policies of Italy and Malta in recent years by employing Hannah Arendt’s insights into the origins of refugee status and the power of alterity as an animating force of human behavior. We contend that both these countries have circumvented European Union and United Nations compacts and rules governing refugee treatment during this difficult historical era and that their behavior, and that of their populations, provides a powerful and salient reminder of the challenge of ensuring displaced people rights in the face of human willingness to ‘other.’ We argue too that the bases of those obstacles take multiple forms including deliberate appeals to hatreds, fears, and grievances, real and imagined, by political leaders for purposes of securing power, as well as via perversions of national memory and history. More deeply, the wellsprings of the behaviors to which Arendt pointed lie in individuals’ innate relative incapacity to tolerate difference, presenting a critical ongoing challenge for democratic governance amidst conditions of pluralism of whatever stripe. Keywords: refugees, Syrian Civil War, Hannah Arendt, Italy, Malta, alterity

Individualized models of social judgments and context-dependent representations.

How individuals view the world is critical to understanding human behavior. Yet, almost all research within perception and judgment has drawn inferences from group-level behavior, with little work focused on understanding how the individual perceives their world. However, for complex judgments (e.g., trustworthiness), most of the meaningful variance is due to factors specific to the individual. Here we showcase a data-driven reverse correlation method for visualizing any perceptually-derived stereotype at the individual level. We show that our method (1) produces photorealistic and reliable results related to a broad range of judgments, (2) produces valid, psychologically-aligned representations of what individuals are imagining "in their mind's eye", and (3) is capable of capturing visual representations sensitive enough to examine context-dependent categories (e.g., a trustworthy individual to babysit your children vs. to fix your car). Across all studies, we highlight the theoretical implications and utility of developing idiosyncratic models of visual perception.

An evolution model for the mobility of urban societal classes based on complex networks

Abstract Cities serve as the main platform for human socio-economic activities, where large crowds, products and information converge, forming complex societal interactions and the space for human to interact with each other. Like traditional geographical space, in cities, cyberspace and societal space also offer diverse channels for human interactions. While urban mobility in geographical space has been extensively studied across disciplines such as geography, economics, transportation and human behavior, mobility within societal space in cities has rarely been examined in depth. This paper focuses on the self-organized consolidation of mobility within urban societal spaces. Based on the rational actor assumption and Dunbar’s number, we construct a simple model to explain why urban societal classes spontaneously emerge in the evolution of societal space. We also find that the mobility within urban societal space decreases spontaneously over time and eventually outstanding individuals potentially can be trapped in lower classes, resulting in an inefficient matching of urban resources.

Development of Paving Block Structure Variation for Traffic Safety and Comfort

Urban traffic congestion worldwide leads to air pollution, increased vehicle noise, and longer travel times for both private and public transit. Congestion adversely affects the well-being of road users and urban residents, and traffic accidents are closely linked to congestion. Traffic composition, road infrastructure, environmental conditions, vehicle design, and human behavior can cause congestion. Concrete block pavement is a practical option for improving traffic safety and increasing driving comfort at intersections with traffic lights. Concrete block paving roads are a cost-effective engineering solution for residential, commercial, municipal, and industrial environments. The study uses the Autocad program to create a simulation of a paved surface and a research tool to analyze the model of the research subject. Results indicate that pavement types subjected to higher loads exhibit more deformation than those under lower loads. Pavements with higher weights are more likely to deform, with the Herringbone 90� pavement type able to withstand a maximum load of 2100 kg and exhibiting the highest load deformation rate of 0.21 cm/kg. The study investigates the load-bearing abilities of different pavement kinds and patterns. The Basketweave pavement type has the lowest load capacity at 2077.9 kg and the lowest load deformation rate of 0.41 cm/kg.

Human behavioral dynamics and stock return movements: Evidence from China

This paper develops an analysis framework based on the principle of human behavior dynamics and the jump-diffusion process. Based on empirical tests on Chinese stock markets, the paper reveals a negative correlation between jump levels in the previous month and stock returns in the following month. On average, an increase of each 1 unit in the value of the jump component results in a lower subsequent stock return of 58 basis points. Moreover, the long-short arbitrage portfolios based on jump levels perform better than the market portfolio; the Sharpe ratio is 4 times that of the market index, indicating that jump-based trading strategies have a great ability to pursue abnormal returns.

A review of accident models and incident analysis techniques.

This review article aims to provide an overview of accident models and incident analysis techniques in the context of radiation oncology. Accident models conceptualize the mechanisms through which accidents occur. Chain-of-event models and systemic models are two main categories of accident models and differ in how accident causation is portrayed. Chain-of-event models focus on the linear sequence of events leading up to an accident, whereas systemic models emphasize the nonlinear relationships between the components in a complex system. The article then introduces various incident analysis techniques, including root cause analysis (RCA), London Protocol, AcciMap, and Causal Analysis Based on Systems Theory (CAST), which are based on these accident models. The techniques based on the chain-of-event model can be effective in identifying causal factors, safety interventions, and improving safety. The other techniques based on the systemic models inherently facilitate an examination of how the influence of personal conditions, environmental conditions, and information exchange between different aspects of a system contributed to an accident. To improve incident analysis, it is essential to translate unsafe human behavior into decision-making flaws and the underlying contextual factors. Where resources allow, it is also crucial to systematically link frontline contributions to organizational and societal aspects of the system and incorporate expertise in safety science and human factors into the analysis team. The article also touches on related concepts such as Perrow's Normal Accident Theory (NAT), Functional Resonance Analysis Method (FRAM), and Bowtie Analysis, which are not based on specific accident models but have been used for safety improvement in radiation oncology. Overall, different incident analysis techniques have strengths and weaknesses. Taking a systems approach to incident analysis requires a shift from linear thinking to a more nuanced understanding of complex systems. However, the approach also brings unique value and can help improve safety as radiation oncology further gains complexity.

Analyzing disease control through testing game approach embedded with treatment and vaccination strategies

This research introduces an expanded SEIR (Susceptible-Exposed-Infected-Recovered) model that incorporates the components of testing, treatment, and vaccination. The study utilizes an evolutionary game theory (EGT) framework to investigate the impact of human behavior on the acceptance and implementation of these interventions. The choice to undergo testing and vaccination is considered a strategic decision influenced by perceived risks and benefits. Regarding disease dynamics, adherence to vaccination and testing protocols is seen as a behavioral factor. The present study employs a finite difference method to numerically examine the impact of proactive vaccination and retroactive treatment policies on human behavior. The investigation focuses on these policies’ individual and combined effects, considering various factors, including vaccination and testing costs, vaccine efficacy, awareness level, and infection rates. The findings indicate that the integration of heightened awareness and enhanced vaccination efficacy can successfully alleviate the transmission of diseases, even in situations where the expenses associated with testing and vaccination are substantial. Reducing infections in situations characterized by low or moderate awareness or vaccination effectiveness is contingent upon low testing costs. The final epidemic size (FES) negatively correlates with testing and vaccine costs, indicating that lower costs are linked to a lower FES. Optimal vaccine coverage (VC) occurs when vaccine costs are minimal and vaccine efficiency is efficient, whereas treatment coverage (TC) reaches its peak when testing costs are minimal. This research underscores the significance of considering human behavior and the intricate relationship between vaccination, testing, and treatment approaches in managing the transmission of contagious illnesses. It offers valuable perspectives for policymakers to mitigate the consequences of epidemics.

Perceptions of Students on Differentiated Learning of Video Content in Long Multiplication Mathematics Lessons

Currently, students often feel bored with the teaching and learning activities in the classroom, especially in Mathematics learning, for that a learning style approach is needed that is adjusted to the needs of each student. The purpose of studying content differentiation through videos for elementary school children is to provide a more meaningful learning experience and in accordance with the needs and learning styles of each student, facilitate diverse learning styles and provide an interactive learning experience. By using visual and auditory content videos, learning for grade 3 elementary school children greatly helps students understand the material to be studied; after watching the video, the teacher can interact directly with students through questions or quizzes based on the learning videos that have been watched by students. The method used in this study is qualitative, where this approach focuses on an in-depth understanding of socio-cultural phenomena and human behavior through non-numerical data. Qualitative research emphasizes the context of the process and quality rather than measurement. In this study, video content differentiation is a strategy where creators and content providers provide a variety of learning styles to students.