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Presentation Overview: Nuclear Weapon Medical Effects; Psychological Effects; Contamination; Lethal Dose; Acute Radiation Syndromes; Chronic Radiation Effects; Thermal Injuries; Blast Injuries
Technological innovations drive the evolution of human societies. The success of innovations depends not only on their actual benefits but also on how potential adopters perceive them and how their beliefs are affected by their social and cultural environment. To deepen our understanding of socio-psychological processes affecting the new technology spread, we model the joint dynamics of three interlinked processes: individual learning and mastering the new technology, changes in individual attitudes towards it, and changes in individual adoption decisions. We assume that the new technology can potentially lead to a higher benefit but achieving it requires learning. We posit that individual decision-making process as well as their attitudes are affected by cognitive dissonance and conformity with peers and an external authority. Individuals vary in different psychological characteristics and in their attitudes. We investigate both transient dynamics and long-term equilibria observed in our model. We show that early adopters are usually individuals who are characterized by low cognitive dissonance and low conformity with peers but are sensitive to the effort of an external authority promoting the innovation. We examine the effectiveness of five different intervention strategies aiming to promote the diffusion of a new technology: training individuals, providing subsidies for early adopters, increasing the visibility of peer actions, simplifying the exchange of opinions between people, and increasing the effort of an external authority. We also discuss the effects of culture on the spread of innovations. Finally, we demonstrate that neglecting the cognitive forces and the dynamic nature of individual attitudes can lead to wrong conclusions about adoption of innovations. Our results can be useful in developing more efficient policies aiming to promote the spread of new technologies in different societies, cultures and countries.
Abstract Aims The long-term physical health effects of the atomic bombings of Hiroshima and Nagasaki are well characterised, but the psychological effects remain unclear. Therefore, we sought to determine whether measures of exposure severity, as indirect measures of psychological trauma arising from exposure to the atomic bombings, are associated with suicide mortality among atomic bomb survivors. Methods The Life Span Study is a prospective cohort study of 93 741 Japanese atomic bomb survivors who were located within 10 km of the hypocentre in Hiroshima or Nagasaki at the time of the bombings in 1945, and 26 579 residents of Hiroshima and Nagasaki who were not in either city at the time of the bombings, matched to survivors on city, sex and age. Measures of exposure severity included: proximity to the hypocentre, type of shielding between the survivor and the blast and self-reported occurrence of acute radiation and thermal injuries. Date of death was obtained from the Japanese National Family Registry system. Cause of death was obtained from death certificates. Adjusted hazard ratios (HRs) were estimated from Cox regression models overall and stratified by sex and age. Results During the 60-year follow-up period (1950–2009), 1150 suicide deaths were recorded among 120 231 participants (23.6 per 100 000 person-years): 510 among 70 092 women (17.2 per 100 000 person-years) and 640 among 50 139 men (33.6 per 100 000 person-years). Overall, there was no association of proximity, type of shielding or the occurrence of acute injuries with suicide mortality. Among those <25 years of age at the time of the bombings, increased suicide risk was observed for survivors outside v . shielded inside any structure (HR: 1.24; 95% confidence interval (CI): 1.03, 1.48; interaction p = 0.054) and for those who reported flash burns (HR: 1.32; 95% CI: 1.00, 1.73; interaction p = 0.025). Sex-stratified analyses indicated that these associations were limited to men. Among women, closer proximity to the hypocentre was associated with a non-significant increase in suicide risk, with a positive association between proximity and suicide risk observed among women <15 years of age (HR: 1.09 per km; 95% CI: 1.00, 1.18; interaction p = 0.067). Conclusions Proximity to the hypocentre, shielding and acute injury presence do not generally appear to influence suicide mortality among atomic bomb survivors. However, heterogeneity may exist by age and sex, with younger survivors potentially more sensitive to psychological trauma. Coupled with other studies, our results suggest the importance of long-term monitoring of mental health among young populations exposed to catastrophic events or mass trauma.
Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals’ affected neighbors, such a spreading process becomes a “complex contagion”. This non-linearity does not typically appear with physically spreading infections, but instead can emerge when the concept that is spreading is subject to game theoretical considerations (e.g. for choices of strategy or behavior) or psychological effects such as social reinforcement and other forms of peer influence (e.g. for ideas, preferences, or opinions). Here we study how the stochastic dynamics of such complex contagions are affected by the underlying network structure. Motivated by simulations of complex contagions on real social networks, we present a framework for analyzing the statistics of contagions with arbitrary non-linear adoption probabilities based on the mathematical tools of population genetics. The central idea is to use an effective lower-dimensional diffusion process to approximate the statistics of the contagion. This leads to a tradeoff between the effects of ”selection” (microscopic tendencies for an idea to spread or die out), random drift, and network structure. Our framework illustrates intuitively several key properties of complex contagions: stronger community structure and network sparsity can significantly enhance the spread, while broad degree distributions dampen the effect of selection compared to random drift. Finally, we show that some structural features can exhibit critical values that demarcate regimes where global contagions become possible for networks of arbitrary size. Our results draw parallels between the competition of genes in a population and memes in a world of minds and ideas. Our tools provide insight into the spread of information, behaviors, and ideas via social influence, and highlight the role of macroscopic network structure in determining their fate.
Modern life is held together by a web of digital dependencies that enable and provide delivery of critical services and functions—think the provision of utilities such as electricity and water, as well as our dependency on digital services for social and economic services (internet, communication, etc.). As this dependency grows, the complexity related to the delivery of these critical services increases as well. As complexity increases, the understanding of the risk and impact associated with potential disruption, degradation, or destruction—due to either malicious or non-malicious events of those digitally enabled functions—decreases. One potential explanation for the difficulty to 1) understand the risks faced and 2) address them appropriately and effectively is the abstractness and psychological distance assigned to “digital threat.” The complexity of these digitally enabled services creates a perceived complicatedness; as a result, digital threats are treated differently than similarly devasting (but more easily understood) kinetic or physical threats. How we categorize these threats also matters. Acts of cyber-enabled sabotage to critical infrastructure need to be defined as irregular warfare. By inadequately defining the threat, we compound the problem. Acknowledging this digital-threat bias is foundational to improving the ability to protect critical infrastructure. Using construal-level theory and psychological-distance concepts provides an intriguing starting point to address these issues, to reframe the challenges faced, and pursue more effective critical infrastructure security and defense policy.
Perinatal depression (PD) is a highly prevalent psychological disorder that has a detrimental effect on infant and maternal physical and mental health, but effective and objective assessment of PD is still insufficient. In recent years, the functional near-infrared spectroscopy (fNIRS) has been acknowledged as an effective non-invasive tool for clinical assessment of depression. This study proposed a free association semantic task (FAST) paradigm for fNIRS-based assessment of PD. To better address the emotion characteristics of PD, the participants are required to generate a dynamic concept chain based on positive, negative or neutral seed words, while 48-channel fNIRS recordings over frontal and bilateral temporal regions. Results from twenty-two late-pregnant women revealed that, the oxyhemoglobin (oxy-Hb) changes during the FAST with the positive and negative seed words over the frontal region were correlated with PD severity, which was different from the correlation patterns in the FAST with neutral seed word and the classical verbal fluency test (VFT). Furthermore, distinct correlation patterns were also observed in the FAST with the positive and negative seed words, manifested in fNIRS channels corresponding to the right dorsolateral prefrontal cortex (DLPFC) and right inferior frontal gyrus (IFG), respectively. Moreover, regression analyses showed that the FAST with positive and negative seed words can well explain the severity of PD. Our findings suggest the proposed FAST paradigm as a promising approach for PD assessment.
Here, we propose a supervised learning approach using publicly available panel data to statistically quantify the specific manifestations of human impacts of an extreme event, such as changes number of suicides, substance abuse, excess mortality, and unemployment. This allows us to conceptually focus our framework on human impacts and how by attributing them to disaster events along widely accepted psychological, economic, and social dimensions. Our modified treatment-effect model allows counterfactual baseline conditions to be posited for each manifestation from which an aggregated quantitative multi-faceted measure of human impacts can be determined. The developed statistical methodology could be beneficial to policymakers who must allocate scarce resources to those communities in greater need. We illustrate the applicability of our approach using annual and monthly panel data from 2012 to 2018 encompassing the 2017 Hurricane Maria event across various municipalities in Puerto Rico. Our statistical modeling methodology stands apart since (i) it explicitly and more realistically captures the effect of different human-oriented manifestations of an actual event and (ii) it is flexible enough to accommodate individual preferences of various stakeholders in how they assign importance to multiple manifestations of human impacts.
In recent times, disinformation has spread rapidly through social media and news sites, biasing our (moral) judgements of other people and groups. “Deepfakes”, a new type of AI-generated media, represent a powerful new tool for spreading disinformation online. Although Deepfaked images, videos, and audio may appear genuine, they are actually hyper-realistic fabrications that enable one to digitally control what another person says or does. Given the recent emergence of this technology, we set out to examine the psychological impact of Deepfaked online content on viewers. Across seven preregistered studies (N = 2558) we exposed participants to either genuine or Deepfaked content, and then measured its impact on their explicit (self-reported) and implicit (unintentional) attitudes as well as behavioral intentions. Results indicated that Deepfaked videos and audio have a strong psychological impact on the viewer, and are just as effective in biasing their attitudes and intentions as genuine content. Many people are unaware that Deepfaking is possible; find it difficult to detect when they are being exposed to it; and most importantly, neither awareness nor detection serves to protect people from its influence. All preregistrations, data and code available at osf.io/f6ajb.
During spaceflight, astronauts are exposed to various physiological and psychological stressors that have been associated with adverse health effects. Therefore, there is an unmet need to develop novel diagnostic tools to predict early alterations in astronauts’ health. Small nucleolar RNA (snoRNA) is a type of short non-coding RNA (60–300 nucleotides) known to guide 2'-O-methylation (Nm) or pseudouridine (ψ) of ribosomal RNA (rRNA), small nuclear RNA (snRNA), or messenger RNA (mRNA). Emerging evidence suggests that dysregulated snoRNAs may be key players in regulating fundamental cellular mechanisms and in the pathogenesis of cancer, heart, and neurological disease. Therefore, we sought to determine whether the spaceflight-induced snoRNA changes in astronaut’s peripheral blood (PB) plasma extracellular vesicles (PB-EV) and peripheral blood mononuclear cells (PBMCs). Using unbiased small RNA sequencing (sRNAseq), we evaluated changes in PB-EV snoRNA content isolated from astronauts (n = 5/group) who underwent median 12-day long Shuttle missions between 1998 and 2001. Using stringent cutoff (fold change > 2 or log 2 -fold change >1, FDR < 0.05), we detected 21 down-and 9—up-regulated snoRNAs in PB-EVs 3 days after return (R + 3) compared to 10 days before launch (L-10). qPCR validation revealed that SNORA74A was significantly down-regulated at R + 3 compared to L-10. We next determined snoRNA expression levels in astronauts’ PBMCs at R + 3 and L-10 (n = 6/group). qPCR analysis further confirmed a significant increase in SNORA19 and SNORA47 in astronauts’ PBMCs at R + 3 compared to L-10. Notably, many downregulated snoRNA-guided rRNA modifications, including four Nms and five ψs. Our findings revealed that spaceflight induced changes in PB-EV and PBMCs snoRNA expression, thus suggesting snoRNAs may serve as potential novel biomarkers for monitoring astronauts’ health.
Background: Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging, is also important for minimizing long-term effects of an outbreak. Objective: We used social media data from Twitter to identify human behaviors relevant to COVID-19 transmission, as well as the perceived impacts of COVID-19 on individuals, as a first step toward real-time monitoring of public perceptions to inform public health communications. Methods: We developed a coding schema for 6 categories and 11 subcategories, which included both a wide number of behaviors as well codes focused on the impacts of the pandemic (eg, economic and mental health impacts). We used this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that performed adequately were applied to our remaining corpus, and temporal and geospatial trends were assessed. We compared the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. Results: We applied our labeling schema to approximately 7200 tweets. The worst-performing classifiers had F1 scores of only 0.18 to 0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, were much stronger, with F1 scores of 0.64 to 0.66. We applied the social distancing classifiers to over 228 million tweets. We showed temporal patterns consistent with real-world events, and we showed correlations of up to –0.5 between social distancing signals on Twitter and ground truth mobility throughout the United States. Conclusions: Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior, as well as for informing public health communication strategies by describing awareness of and compliance with suggested behaviors.
Anxiety and depression are common in the modern world, and there is growing demand for alternative therapies such as meditation. Meditation can decrease perceived stress and increase general well-being, although the physiological mechanism is not well-characterized. Endocannabinoids (eCBs), lipid mediators associated with enhanced mood and reduced anxiety/depression, have not been previously studied as biomarkers of meditation effects. Our aim was to assess biomarkers (eCBs and brain-derived neurotrophic factor [BDNF]) and psychological parameters after a meditation retreat. Methods. This was an observational pilot study of adults before and after the 4-day Isha Yoga Bhava Spandana Program retreat. Participants completed online surveys (before and after retreat, and 1 month later) to assess anxiety, depression, focus, well-being, and happiness through validated psychological scales. Voluntary blood sampling for biomarker studies was done before and within a day after the retreat. The biomarkers anandamide, 2-arachidonoylglycerol (2-AG), 1-arachidonoylglycerol (1-AG), docosatetraenoylethanolamide (DEA), oleoylethanolamide (OLA), and BDNF were evaluated. Primary outcomes were changes in psychological scales, as well as changes in eCBs and BDNF. Results. Depression and anxiety scores decreased while focus, happiness, and positive well-being scores increased immediately after retreat from their baseline values (P < 0.001). All improvements were sustained 1 month after BSP. All major eCBs including anandamide, 2-AG, 1-AG, DEA, and BDNF increased after meditation by > 70% (P < 0.001). Increases of ≥20% in anandamide, 2-AG, 1-AG, and total AG levels after meditation from the baseline had weak correlations with changes in happiness and well-being. Conclusions. A short meditation experience improved focus, happiness, and positive well-being and reduced depression and anxiety in participants for at least 1 month. Participants had increased blood eCBs and BDNF, suggesting a role for these biomarkers in the underlying mechanism of meditation. Meditation is a simple, organic, and effective way to improve well-being and reduce depression and anxiety.
Vaccination and the alternative behavior, vaccine refusal, are a classic example of manifesting behaviors driven by social norms and norm violations. Establishing how norms emerge, and under what circumstances people choose to violate them are key issues to understand in modeling epidemics. Interactions between individuals can lead to large-scale patterning of behavior (emergent phenomena). As norm violations are revealed through human behavior, drawing on psychological theory and principles to predict those violations is a viable approach for more human-constrained epidemiological models. As an example of the implications at scale, vaccine refusal is correlated with the spread of mis/disinformation about vaccine side-effects. Considering the complexities of network dynamics, the downstream effects means that if even a small group within a population are persuaded against vaccination, there is a reservoir from which disease and disease outbreaks can propagate. This work will attempt to identify those psychological indicators, to define circumstances that predict health behaviors, and identify potentially modifiable antecedents of health behavior, and factors that influence changes toward health protective behaviors.
This study presents the executive disruption model (EDM) of tinnitus distress and subsequently validates it statistically using two independent datasets (the Construction Dataset: n = 96 and the Validation Dataset: n = 200). The conceptual EDM was first operationalised as a structural causal model (construction phase). Then multiple regression was used to examine the effect of executive functioning on tinnitus-related distress (validation phase), adjusting for the additional contributions of hearing threshold and psychological distress. For both datasets, executive functioning negatively predicted tinnitus distress score by a similar amount (the Construction Dataset: β = −3.50, p = 0.13 and the Validation Dataset: β = −3.71, p = 0.02). Theoretical implications and applications of the EDM are subsequently discussed; these include the predictive nature of executive functioning in the development of distressing tinnitus, and the clinical utility of the EDM.
In previous studies, many travel-behavior-change strategies often relied on single behavior determinants or psychological theories, overlooking the incorporation of sociopsychological theories for guidance in their design. Integrating these theories could offer consistent guidance for program developers and enhance intervention effectiveness. This paper systematically reviews interventions targeting travel-behavior change, with a focus on self-determination theory and its principles of satisfying individuals’ competence, autonomy, and relatedness needs for enacting change. Additionally, experiment design methods, including randomized controlled trials and quasi-experimental designs, are reviewed and discussed. Key findings highlight the effectiveness of personalized interventions and integrating feedback with goal-setting strategies. Given the limited direct references to sociopsychological theories in existing studies, we explore relevant sociopsychological theories applicable to travel-behavior-change programs to provide examples of how strategies could be designed based on them. This review contributes valuable insights into the development of strategies for changing travel behavior, offering a theoretical framework for researchers and practitioners to guide intervention design, experimentation, and evaluation. In conclusion, leveraging these theories not only facilitates reproducibility but also provides a standardized approach for transportation demand management program developers.
The gut microbiota–brain axis allows for bidirectional communication between the microbes in our gastrointestinal (GI) tract and the central nervous system. Psychological stress has been known to disrupt the gut microbiome (dysbiosis) leading to anxiety-like behavior. Pathogens administered into the gut have been reported to cause anxiety. Whether commensal bacteria affect the gut–brain axis is not well understood. In this study, we examined the impact of a commensal sulfate-reducing bacteria (SRB) and its metabolite, hydrogen sulfide (H2S), on anxiety-like behavior. We found that mice gavaged with SRB had increased anxiety-like behavior as measured by the open field test. We also tested the effects of magnesium oxide (MgO) on SRB growth both in vitro and in vivo using a water avoidance stress (WAS) model. We found that MgO inhibited SRB growth and H2S production in a dose-dependent fashion. Mice that underwent psychological stress using the WAS model were observed to have an overgrowth (bloom) of SRB (Deferribacterota) and increased anxiety-like behavior. However, WAS-induced overgrowth of SRB and anxiety-like behavioral effects were attenuated in animals fed a MgO-enriched diet. These findings supported a potential MgO-reversible relationship between WAS-induced SRB blooms and anxiety-like behavior.
Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.
Abstract Historical assessment of radiation effects at low doses (below 0.2 Sv) are generally the result of back extrapolation from higher doses, which are known to have a linear relation between risk and dose. There are multiple counter-examples, and some literature argues that a threshold, nonlinear, or even a beneficial effect (hormeisis) can occur from radiation below these doses. The common theme found in all of these studies stems from the traditional approach of correlating disease rates to stimulus and then effectively curve-fitting the result toward zero dose. What has not been considered in general are the personal stress levels of the exposed individuals due to fear of cancer from low doses. The increased levels of cortisol due to the psychological stress from fear or depression has been shown in the literature to increase cancer probability. The extent to which low-dose exposed individuals were highly fearful or stressed from the radiation exposure would then give rise to elevated cancer based on stress rather than a fundamental radiogenic mechanism. If the population under epidemiological study is aware of a potential historical exposure (no matter how small) and has then lived under stress from fear or depression due to that exposure, the psychosomatic effects will bias the epidemiology accordingly and so should be quantified and accounted for as done with the effects of smoking. Health Phys. 129(0):000-000; 2025
Objective To evaluate neck muscle coactivation across different levels of mental workload during simulated flight tasks. Background Neck pain (NP) is highly prevalent among military aviators. Given the complex nature within the flight environment, mental workload may be a risk factor for NP. This may induce higher levels of neck muscle coactivity, which over time may accelerate fatigue, increase neck discomfort, and affect flight task performance. Method Three counterbalanced mental workload conditions represented by simulated flight tasks modulated by interstimulus frequency and complexity were investigated using the Modifiable Multitasking Environment (ModME). The primary measure was a neck coactivation index to describe the neuromuscular effort of the neck muscles as a system. Additional measures included perceived workload (NASA TLX), subjective discomfort, and task performance. Participants ( n = 60; 30M, 30F) performed three test conditions over 1 hr each while seated in a simulated seating environment. Results Neck coactivation indices (CoA) and subjective neck discomfort corresponded with increasing level of mental workload. Average CoAs for low, medium, and high workloads were: .0278(SD = .0232), .0286(SD = .0231), and .0295(SD = .0228), respectively. NASA TLX mental, temporal, effort, and overall scores also increased with the level of mental workload assigned. For ModME task performance, the overall performance score, monitoring accuracy, and resource management accuracy decreased while reaction times increased with the increasing level of mental workload. Communication accuracy was lowest with the low mental workload but had higher reaction times relative to increasing workload. Conclusion Mental workload affects neck muscle coactivation during combinations of simulated flight tasks within a simulated helicopter seating environment. Application The results of this study provide insights into the physical response to mental workload. With increasing multisensory modalities within the work environment, these insights may assist the consideration of physical effects from cognitive factors.